WorldWideScience

Sample records for genome teacher networking

  1. Human Genome Teacher Networking Project, Final Report, April 1, 1992 - March 31, 1998

    Energy Technology Data Exchange (ETDEWEB)

    Collins, Debra

    1999-10-01

    Project to provide education regarding ethical legal and social implications of Human Genome Project to high school science teachers through two consecutive summer workshops, in class activities, and peer teaching workshops.

  2. Effective teacher professionalization in networks?

    NARCIS (Netherlands)

    Hofman, R.H.; Dijkstra, B.J.

    2010-01-01

    Teacher professionalization has been focused to strongly on external experts and a one-size-fits-all set of solutions that often fail to distinguish between the needs of different teachers. This article describes a research into teacher networks that might be more successful vehicles for professiona

  3. AcCNET (Accessory Genome Constellation Network): comparative genomics software for accessory genome analysis using bipartite networks.

    Science.gov (United States)

    Lanza, Val F; Baquero, Fernando; de la Cruz, Fernando; Coque, Teresa M

    2017-01-15

    AcCNET (Accessory genome Constellation Network) is a Perl application that aims to compare accessory genomes of a large number of genomic units, both at qualitative and quantitative levels. Using the proteomes extracted from the analysed genomes, AcCNET creates a bipartite network compatible with standard network analysis platforms. AcCNET allows merging phylogenetic and functional information about the concerned genomes, thus improving the capability of current methods of network analysis. The AcCNET bipartite network opens a new perspective to explore the pangenome of bacterial species, focusing on the accessory genome behind the idiosyncrasy of a particular strain and/or population.

  4. Genomic networks of hybrid sterility.

    Directory of Open Access Journals (Sweden)

    Leslie M Turner

    2014-02-01

    Full Text Available Hybrid dysfunction, a common feature of reproductive barriers between species, is often caused by negative epistasis between loci ("Dobzhansky-Muller incompatibilities". The nature and complexity of hybrid incompatibilities remain poorly understood because identifying interacting loci that affect complex phenotypes is difficult. With subspecies in the early stages of speciation, an array of genetic tools, and detailed knowledge of reproductive biology, house mice (Mus musculus provide a model system for dissecting hybrid incompatibilities. Male hybrids between M. musculus subspecies often show reduced fertility. Previous studies identified loci and several X chromosome-autosome interactions that contribute to sterility. To characterize the genetic basis of hybrid sterility in detail, we used a systems genetics approach, integrating mapping of gene expression traits with sterility phenotypes and QTL. We measured genome-wide testis expression in 305 male F2s from a cross between wild-derived inbred strains of M. musculus musculus and M. m. domesticus. We identified several thousand cis- and trans-acting QTL contributing to expression variation (eQTL. Many trans eQTL cluster into eleven 'hotspots,' seven of which co-localize with QTL for sterility phenotypes identified in the cross. The number and clustering of trans eQTL-but not cis eQTL-were substantially lower when mapping was restricted to a 'fertile' subset of mice, providing evidence that trans eQTL hotspots are related to sterility. Functional annotation of transcripts with eQTL provides insights into the biological processes disrupted by sterility loci and guides prioritization of candidate genes. Using a conditional mapping approach, we identified eQTL dependent on interactions between loci, revealing a complex system of epistasis. Our results illuminate established patterns, including the role of the X chromosome in hybrid sterility. The integrated mapping approach we employed is

  5. Genomic networks of hybrid sterility.

    Science.gov (United States)

    Turner, Leslie M; White, Michael A; Tautz, Diethard; Payseur, Bret A

    2014-02-01

    Hybrid dysfunction, a common feature of reproductive barriers between species, is often caused by negative epistasis between loci ("Dobzhansky-Muller incompatibilities"). The nature and complexity of hybrid incompatibilities remain poorly understood because identifying interacting loci that affect complex phenotypes is difficult. With subspecies in the early stages of speciation, an array of genetic tools, and detailed knowledge of reproductive biology, house mice (Mus musculus) provide a model system for dissecting hybrid incompatibilities. Male hybrids between M. musculus subspecies often show reduced fertility. Previous studies identified loci and several X chromosome-autosome interactions that contribute to sterility. To characterize the genetic basis of hybrid sterility in detail, we used a systems genetics approach, integrating mapping of gene expression traits with sterility phenotypes and QTL. We measured genome-wide testis expression in 305 male F2s from a cross between wild-derived inbred strains of M. musculus musculus and M. m. domesticus. We identified several thousand cis- and trans-acting QTL contributing to expression variation (eQTL). Many trans eQTL cluster into eleven 'hotspots,' seven of which co-localize with QTL for sterility phenotypes identified in the cross. The number and clustering of trans eQTL-but not cis eQTL-were substantially lower when mapping was restricted to a 'fertile' subset of mice, providing evidence that trans eQTL hotspots are related to sterility. Functional annotation of transcripts with eQTL provides insights into the biological processes disrupted by sterility loci and guides prioritization of candidate genes. Using a conditional mapping approach, we identified eQTL dependent on interactions between loci, revealing a complex system of epistasis. Our results illuminate established patterns, including the role of the X chromosome in hybrid sterility. The integrated mapping approach we employed is applicable in a broad

  6. Networking for Teacher Learning: Toward a Theory of Effective Design.

    Science.gov (United States)

    McDonald, Joseph P.; Klein, Emily J.

    2003-01-01

    Examines how teacher networks design for teacher learning, describing several dynamic tensions inherent in the designs of a sample of teacher networks and assessing the relationships of these tensions to teacher learning. The paper illustrates these design concepts with reference to the work of seven networks that aim to revamp teacher' knowledge…

  7. Predicting biological networks from genomic data

    DEFF Research Database (Denmark)

    Harrington, Eoghan D; Jensen, Lars J; Bork, Peer

    2008-01-01

    Continuing improvements in DNA sequencing technologies are providing us with vast amounts of genomic data from an ever-widening range of organisms. The resulting challenge for bioinformatics is to interpret this deluge of data and place it back into its biological context. Biological networks...... provide a conceptual framework with which we can describe part of this context, namely the different interactions that occur between the molecular components of a cell. Here, we review the computational methods available to predict biological networks from genomic sequence data and discuss how they relate...

  8. Integrative bayesian network analysis of genomic data.

    Science.gov (United States)

    Ni, Yang; Stingo, Francesco C; Baladandayuthapani, Veerabhadran

    2014-01-01

    Rapid development of genome-wide profiling technologies has made it possible to conduct integrative analysis on genomic data from multiple platforms. In this study, we develop a novel integrative Bayesian network approach to investigate the relationships between genetic and epigenetic alterations as well as how these mutations affect a patient's clinical outcome. We take a Bayesian network approach that admits a convenient decomposition of the joint distribution into local distributions. Exploiting the prior biological knowledge about regulatory mechanisms, we model each local distribution as linear regressions. This allows us to analyze multi-platform genome-wide data in a computationally efficient manner. We illustrate the performance of our approach through simulation studies. Our methods are motivated by and applied to a multi-platform glioblastoma dataset, from which we reveal several biologically relevant relationships that have been validated in the literature as well as new genes that could potentially be novel biomarkers for cancer progression.

  9. The Networked Teacher: How New Teachers Build Social Networks for Professional Support. Series on School Reform

    Science.gov (United States)

    Baker-Doyle, Kira J.

    2011-01-01

    New teachers need support from their peers and mentors to locate resources, information, new ideas, emotional support, and inspiration. This timely book explains the research and theory behind social networks (face-to-face and online), describes what effective social networking for educators looks like, reveals common obstacles that new teachers…

  10. Network Based Prediction Model for Genomics Data Analysis*

    OpenAIRE

    Huang, Ying; Wang, Pei

    2012-01-01

    Biological networks, such as genetic regulatory networks and protein interaction networks, provide important information for studying gene/protein activities. In this paper, we propose a new method, NetBoosting, for incorporating a priori biological network information in analyzing high dimensional genomics data. Specially, we are interested in constructing prediction models for disease phenotypes of interest based on genomics data, and at the same time identifying disease susceptible genes. ...

  11. Teachers Beware! The Dark Side of Social Networking

    Science.gov (United States)

    Belch, Harry Ess

    2012-01-01

    Think teachers can post what they want on their own time? Think again. Many have lost their jobs over social networking gaffes in recent years. In this article, the author shares what he has learned about how school districts cope with teachers and online social networking sites, and offers recommendations to teachers who want to have an online…

  12. First-Year Teachers' Support Networks: Intentional Professional Networks and Diverse Professional Allies

    Science.gov (United States)

    Baker-Doyle, Kira J.

    2012-01-01

    In this article the author describes a mixed-methods study of first-year urban teachers' social support networks. Social Network Analysis (SNA) data on the support networks of 24 first-year teachers provided a background context and framework for the case study analysis of 4 of the teachers. Findings of the analysis identified 2 important networks…

  13. International network of cancer genome projects

    NARCIS (Netherlands)

    Hudson, Thomas J.; Anderson, Warwick; Aretz, Axel; Barker, Anna D.; Bell, Cindy; Bernabe, Rosa R.; Bhan, M. K.; Calvo, Fabien; Eerola, Iiro; Gerhard, Daniela S.; Guttmacher, Alan; Guyer, Mark; Hemsley, Fiona M.; Jennings, Jennifer L.; Kerr, David; Klatt, Peter; Kolar, Patrik; Kusuda, Jun; Lane, David P.; Laplace, Frank; Lu, Youyong; Nettekoven, Gerd; Ozenberger, Brad; Peterson, Jane; Rao, T. S.; Remacle, Jacques; Schafer, Alan J.; Shibata, Tatsuhiro; Stratton, Michael R.; Vockley, Joseph G.; Watanabe, Koichi; Yang, Huanming; Yuen, Matthew M. F.; Knoppers, M.; Bobrow, Martin; Cambon-Thomsen, Anne; Dressler, Lynn G.; Dyke, Stephanie O. M.; Joly, Yann; Kato, Kazuto; Kennedy, Karen L.; Nicolas, Pilar; Parker, Michael J.; Rial-Sebbag, Emmanuelle; Romeo-Casabona, Carlos M.; Shaw, Kenna M.; Wallace, Susan; Wiesner, Georgia L.; Zeps, Nikolajs; Lichter, Peter; Biankin, Andrew V.; Chabannon, Christian; Chin, Lynda; Clement, Bruno; de Alava, Enrique; Degos, Francoise; Ferguson, Martin L.; Geary, Peter; Hayes, D. Neil; Johns, Amber L.; Nakagawa, Hidewaki; Penny, Robert; Piris, Miguel A.; Sarin, Rajiv; Scarpa, Aldo; Shibata, Tatsuhiro; van de Vijver, Marc; Futreal, P. Andrew; Aburatani, Hiroyuki; Bayes, Monica; Bowtell, David D. L.; Campbell, Peter J.; Estivill, Xavier; Grimmond, Sean M.; Gut, Ivo; Hirst, Martin; Lopez-Otin, Carlos; Majumder, Partha; Marra, Marco; Nakagawa, Hidewaki; Ning, Zemin; Puente, Xose S.; Ruan, Yijun; Shibata, Tatsuhiro; Stratton, Michael R.; Stunnenberg, Hendrik G.; Swerdlow, Harold; Velculescu, Victor E.; Wilson, Richard K.; Xue, Hong H.; Yang, Liu; Spellman, Paul T.; Bader, Gary D.; Boutros, Paul C.; Campbell, Peter J.; Flicek, Paul; Getz, Gad; Guigo, Roderic; Guo, Guangwu; Haussler, David; Heath, Simon; Hubbard, Tim J.; Jiang, Tao; Jones, Steven M.; Li, Qibin; Lopez-Bigas, Nuria; Luo, Ruibang; Pearson, John V.; Puente, Xose S.; Quesada, Victor; Raphael, Benjamin J.; Sander, Chris; Shibata, Tatsuhiro; Speed, Terence P.; Stuart, Joshua M.; Teague, Jon W.; Totoki, Yasushi; Tsunoda, Tatsuhiko; Valencia, Alfonso; Wheeler, David A.; Wu, Honglong; Zhao, Shancen; Zhou, Guangyu; Stein, Lincoln D.; Guigo, Roderic; Hubbard, Tim J.; Joly, Yann; Jones, Steven M.; Lathrop, Mark; Lopez-Bigas, Nuria; Ouellette, B. F. Francis; Spellman, Paul T.; Teague, Jon W.; Thomas, Gilles; Valencia, Alfonso; Yoshida, Teruhiko; Kennedy, Karen L.; Axton, Myles; Dyke, Stephanie O. M.; Futreal, P. Andrew; Gunter, Chris; Guyer, Mark; McPherson, John D.; Miller, Linda J.; Ozenberger, Brad; Kasprzyk, Arek; Zhang, Junjun; Haider, Syed A.; Wang, Jianxin; Yung, Christina K.; Cross, Anthony; Liang, Yong; Gnaneshan, Saravanamuttu; Guberman, Jonathan; Hsu, Jack; Bobrow, Martin; Chalmers, Don R. C.; Hasel, Karl W.; Joly, Yann; Kaan, Terry S. H.; Kennedy, Karen L.; Knoppers, Bartha M.; Lowrance, William W.; Masui, Tohru; Nicolas, Pilar; Rial-Sebbag, Emmanuelle; Rodriguez, Laura Lyman; Vergely, Catherine; Yoshida, Teruhiko; Grimmond, Sean M.; Biankin, Andrew V.; Bowtell, David D. L.; Cloonan, Nicole; Defazio, Anna; Eshleman, James R.; Etemadmoghadam, Dariush; Gardiner, Brooke A.; Kench, James G.; Scarpa, Aldo; Sutherland, Robert L.; Tempero, Margaret A.; Waddell, Nicola J.; Wilson, Peter J.; Gallinger, Steve; Tsao, Ming-Sound; Shaw, Patricia A.; Petersen, Gloria M.; Mukhopadhyay, Debabrata; Chin, Lynda; DePinho, Ronald A.; Thayer, Sarah; Muthuswamy, Lakshmi; Shazand, Kamran; Beck, Timothy; Sam, Michelle; Timms, Lee; Ballin, Vanessa; Lu, Youyong; Ji, Jiafu; Zhang, Xiuqing; Chen, Feng; Hu, Xueda; Zhou, Guangyu; Yang, Qi; Tian, Geng; Zhang, Lianhai; Xing, Xiaofang; Li, Xianghong; Zhu, Zhenggang; Yu, Yingyan; Yu, Jun; Yang, Huanming; Lathrop, Mark; Tost, Joerg; Brennan, Paul; Holcatova, Ivana; Zaridze, David; Brazma, Alvis; Egevad, Lars; Prokhortchouk, Egor; Banks, Rosamonde Elizabeth; Uhlen, Mathias; Cambon-Thomsen, Anne; Viksna, Juris; Ponten, Fredrik; Skryabin, Konstantin; Stratton, Michael R.; Futreal, P. Andrew; Birney, Ewan; Borg, Ake; Borresen-Dale, Anne-Lise; Caldas, Carlos; Foekens, John A.; Martin, Sancha; Reis-Filho, Jorge S.; Richardson, Andrea L.; Sotiriou, Christos; Stunnenberg, Hendrik G.; Thomas, Gilles; van de Vijver, Marc; van't Veer, Laura; Birnbaum, Daniel; Blanche, Helene; Boucher, Pascal; Boyault, Sandrine; Chabannon, Christian; Gut, Ivo; Masson-Jacquemier, Jocelyne D.; Lathrop, Mark; Pauporte, Iris; Pivot, Xavier; Vincent-Salomon, Anne; Tabone, Eric; Theillet, Charles; Thomas, Gilles; Tost, Joerg; Treilleux, Isabelle; Bioulac-Sage, Paulette; Clement, Bruno; Decaens, Thomas; Degos, Francoise; Franco, Dominique; Gut, Ivo; Gut, Marta; Heath, Simon; Lathrop, Mark; Samuel, Didier; Thomas, Gilles; Zucman-Rossi, Jessica; Lichter, Peter; Eils, Roland; Brors, Benedikt; Korbel, Jan O.; Korshunov, Andrey; Landgraf, Pablo; Lehrach, Hans; Pfister, Stefan; Radlwimmer, Bernhard; Reifenberger, Guido; Taylor, Michael D.; von Kalle, Christof; Majumder, Partha P.; Sarin, Rajiv; Scarpa, Aldo; Pederzoli, Paolo; Lawlor, Rita T.; Delledonne, Massimo; Bardelli, Alberto; Biankin, Andrew V.; Grimmond, Sean M.; Gress, Thomas; Klimstra, David; Zamboni, Giuseppe; Shibata, Tatsuhiro; Nakamura, Yusuke; Nakagawa, Hidewaki; Kusuda, Jun; Tsunoda, Tatsuhiko; Miyano, Satoru; Aburatani, Hiroyuki; Kato, Kazuto; Fujimoto, Akihiro; Yoshida, Teruhiko; Campo, Elias; Lopez-Otin, Carlos; Estivill, Xavier; Guigo, Roderic; de Sanjose, Silvia; Piris, Miguel A.; Montserrat, Emili; Gonzalez-Diaz, Marcos; Puente, Xose S.; Jares, Pedro; Valencia, Alfonso; Himmelbaue, Heinz; Quesada, Victor; Bea, Silvia; Stratton, Michael R.; Futreal, P. Andrew; Campbell, Peter J.; Vincent-Salomon, Anne; Richardson, Andrea L.; Reis-Filho, Jorge S.; van de Vijver, Marc; Thomas, Gilles; Masson-Jacquemier, Jocelyne D.; Aparicio, Samuel; Borg, Ake; Borresen-Dale, Anne-Lise; Caldas, Carlos; Foekens, John A.; Stunnenberg, Hendrik G.; van't Veer, Laura; Easton, Douglas F.; Spellman, Paul T.; Martin, Sancha; Chin, Lynda; Collins, Francis S.; Compton, Carolyn C.; Ferguson, Martin L.; Getz, Gad; Gunter, Chris; Guyer, Mark; Hayes, D. Neil; Lander, Eric S.; Ozenberger, Brad; Penny, Robert; Peterson, Jane; Sander, Chris; Speed, Terence P.; Spellman, Paul T.; Wheeler, David A.; Wilson, Richard K.; Chin, Lynda; Knoppers, Bartha M.; Lander, Eric S.; Lichter, Peter; Stratton, Michael R.; Bobrow, Martin; Burke, Wylie; Collins, Francis S.; DePinho, Ronald A.; Easton, Douglas F.; Futreal, P. Andrew; Green, Anthony R.; Guyer, Mark; Hamilton, Stanley R.; Hubbard, Tim J.; Kallioniemi, Olli P.; Kennedy, Karen L.; Ley, Timothy J.; Liu, Edison T.; Lu, Youyong; Majumder, Partha; Marra, Marco; Ozenberger, Brad; Peterson, Jane; Schafer, Alan J.; Spellman, Paul T.; Stunnenberg, Hendrik G.; Wainwright, Brandon J.; Wilson, Richard K.; Yang, Huanming

    2010-01-01

    The International Cancer Genome Consortium (ICGC) was launched to coordinate large-scale cancer genome studies in tumours from 50 different cancer types and/or subtypes that are of clinical and societal importance across the globe. Systematic studies of more than 25,000 cancer genomes at the genomic

  14. The network architecture of the Saccharomyces cerevisiae genome.

    Directory of Open Access Journals (Sweden)

    Stephen A Hoang

    Full Text Available We propose a network-based approach for surmising the spatial organization of genomes from high-throughput interaction data. Our strategy is based on methods for inferring architectural features of networks. Specifically, we employ a community detection algorithm to partition networks of genomic interactions. These community partitions represent an intuitive interpretation of genomic organization from interaction data. Furthermore, they are able to recapitulate known aspects of the spatial organization of the Saccharomyces cerevisiae genome, such as the rosette conformation of the genome, the clustering of centromeres, as well as tRNAs, and telomeres. We also demonstrate that simple architectural features of genomic interaction networks, such as cliques, can give meaningful insight into the functional role of the spatial organization of the genome. We show that there is a correlation between inter-chromosomal clique size and replication timing, as well as cohesin enrichment. Together, our network-based approach represents an effective and intuitive framework for interpreting high-throughput genomic interaction data. Importantly, there is a great potential for this strategy, given the rich literature and extensive set of existing tools in the field of network analysis.

  15. Impulsive Neural Networks Algorithm Based on the Artificial Genome Model

    Directory of Open Access Journals (Sweden)

    Yuan Gao

    2014-05-01

    Full Text Available To describe gene regulatory networks, this article takes the framework of the artificial genome model and proposes impulsive neural networks algorithm based on the artificial genome model. Firstly, the gene expression and the cell division tree are applied to generate spiking neurons with specific attributes, neural network structure, connection weights and specific learning rules of each neuron. Next, the gene segment duplications and divergence model are applied to design the evolutionary algorithm of impulsive neural networks at the level of the artificial genome. The dynamic changes of developmental gene regulatory networks are controlled during the whole evolutionary process. Finally, the behavior of collecting food for autonomous intelligent agent is simulated, which is driven by nerves. Experimental results demonstrate that the algorithm in this article has the evolutionary ability on large-scale impulsive neural networks

  16. National Geographic Society Kids Network: Report on 1994 teacher participants

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1995-03-01

    In 1994, National Geographic Society Kids Network, a computer/telecommunications-based science curriculum, was presented to elementary and middle school teachers through summer programs sponsored by NGS and US DOE. The network program assists teachers in understanding the process of doing science; understanding the role of computers and telecommunications in the study of science, math, and engineering; and utilizing computers and telecommunications appropriately in the classroom. The program enables teacher to integrate science, math, and technology with other subjects with the ultimate goal of encouraging students of all abilities to pursue careers in science/math/engineering. This report assesses the impact of the network program on participating teachers.

  17. Genome-scale reconstruction of the Saccharomyces cerevisiae metabolic network

    DEFF Research Database (Denmark)

    Förster, Jochen; Famili, I.; Fu, P.

    2003-01-01

    and the environment were included. A total of 708 structural open reading frames (ORFs) were accounted for in the reconstructed network, corresponding to 1035 metabolic reactions. Further, 140 reactions were included on the basis of biochemical evidence resulting in a genome-scale reconstructed metabolic network...... with Escherichia coli. The reconstructed metabolic network is the first comprehensive network for a eukaryotic organism, and it may be used as the basis for in silico analysis of phenotypic functions....

  18. Modeling protein network evolution under genome duplication and domain shuffling

    Directory of Open Access Journals (Sweden)

    Isambert Hervé

    2007-11-01

    Full Text Available Abstract Background Successive whole genome duplications have recently been firmly established in all major eukaryote kingdoms. Such exponential evolutionary processes must have largely contributed to shape the topology of protein-protein interaction (PPI networks by outweighing, in particular, all time-linear network growths modeled so far. Results We propose and solve a mathematical model of PPI network evolution under successive genome duplications. This demonstrates, from first principles, that evolutionary conservation and scale-free topology are intrinsically linked properties of PPI networks and emerge from i prevailing exponential network dynamics under duplication and ii asymmetric divergence of gene duplicates. While required, we argue that this asymmetric divergence arises, in fact, spontaneously at the level of protein-binding sites. This supports a refined model of PPI network evolution in terms of protein domains under exponential and asymmetric duplication/divergence dynamics, with multidomain proteins underlying the combinatorial formation of protein complexes. Genome duplication then provides a powerful source of PPI network innovation by promoting local rearrangements of multidomain proteins on a genome wide scale. Yet, we show that the overall conservation and topology of PPI networks are robust to extensive domain shuffling of multidomain proteins as well as to finer details of protein interaction and evolution. Finally, large scale features of direct and indirect PPI networks of S. cerevisiae are well reproduced numerically with only two adjusted parameters of clear biological significance (i.e. network effective growth rate and average number of protein-binding domains per protein. Conclusion This study demonstrates the statistical consequences of genome duplication and domain shuffling on the conservation and topology of PPI networks over a broad evolutionary scale across eukaryote kingdoms. In particular, scale

  19. A genome wide dosage suppressor network reveals genomic robustness

    Science.gov (United States)

    Patra, Biranchi; Kon, Yoshiko; Yadav, Gitanjali; Sevold, Anthony W.; Frumkin, Jesse P.; Vallabhajosyula, Ravishankar R.; Hintze, Arend; Østman, Bjørn; Schossau, Jory; Bhan, Ashish; Marzolf, Bruz; Tamashiro, Jenna K.; Kaur, Amardeep; Baliga, Nitin S.; Grayhack, Elizabeth J.; Adami, Christoph; Galas, David J.; Raval, Alpan; Phizicky, Eric M.; Ray, Animesh

    2017-01-01

    Genomic robustness is the extent to which an organism has evolved to withstand the effects of deleterious mutations. We explored the extent of genomic robustness in budding yeast by genome wide dosage suppressor analysis of 53 conditional lethal mutations in cell division cycle and RNA synthesis related genes, revealing 660 suppressor interactions of which 642 are novel. This collection has several distinctive features, including high co-occurrence of mutant-suppressor pairs within protein modules, highly correlated functions between the pairs and higher diversity of functions among the co-suppressors than previously observed. Dosage suppression of essential genes encoding RNA polymerase subunits and chromosome cohesion complex suggests a surprising degree of functional plasticity of macromolecular complexes, and the existence of numerous degenerate pathways for circumventing the effects of potentially lethal mutations. These results imply that organisms and cancer are likely able to exploit the genomic robustness properties, due the persistence of cryptic gene and pathway functions, to generate variation and adapt to selective pressures. PMID:27899637

  20. Pathway and network analysis of cancer genomes

    DEFF Research Database (Denmark)

    Creixell, Pau; Reimand, Jueri; Haider, Syed

    2015-01-01

    Genomic information on tumors from 50 cancer types cataloged by the International Cancer Genome Consortium (ICGC) shows that only a few well-studied driver genes are frequently mutated, in contrast to many infrequently mutated genes that may also contribute to tumor biology. Hence there has been...

  1. Teacher Professionalization in the Age of Social Networking Sites

    Science.gov (United States)

    Kimmons, Royce; Veletsianos, George

    2015-01-01

    As teacher education students become professionals, they face a number of tensions related to identity, social participation, and work-life balance, which may be further complicated by social networking sites (SNS). This qualitative study sought to articulate tensions that arose between professionalization influences and teacher education student…

  2. Teacher Professionalization in the Age of Social Networking Sites

    Science.gov (United States)

    Kimmons, Royce; Veletsianos, George

    2015-01-01

    As teacher education students become professionals, they face a number of tensions related to identity, social participation, and work-life balance, which may be further complicated by social networking sites (SNS). This qualitative study sought to articulate tensions that arose between professionalization influences and teacher education student…

  3. Genome-wide inference of regulatory networks in Streptomyces coelicolor

    Directory of Open Access Journals (Sweden)

    Takano Eriko

    2010-10-01

    Full Text Available Abstract Background The onset of antibiotics production in Streptomyces species is co-ordinated with differentiation events. An understanding of the genetic circuits that regulate these coupled biological phenomena is essential to discover and engineer the pharmacologically important natural products made by these species. The availability of genomic tools and access to a large warehouse of transcriptome data for the model organism, Streptomyces coelicolor, provides incentive to decipher the intricacies of the regulatory cascades and develop biologically meaningful hypotheses. Results In this study, more than 500 samples of genome-wide temporal transcriptome data, comprising wild-type and more than 25 regulatory gene mutants of Streptomyces coelicolor probed across multiple stress and medium conditions, were investigated. Information based on transcript and functional similarity was used to update a previously-predicted whole-genome operon map and further applied to predict transcriptional networks constituting modules enriched in diverse functions such as secondary metabolism, and sigma factor. The predicted network displays a scale-free architecture with a small-world property observed in many biological networks. The networks were further investigated to identify functionally-relevant modules that exhibit functional coherence and a consensus motif in the promoter elements indicative of DNA-binding elements. Conclusions Despite the enormous experimental as well as computational challenges, a systems approach for integrating diverse genome-scale datasets to elucidate complex regulatory networks is beginning to emerge. We present an integrated analysis of transcriptome data and genomic features to refine a whole-genome operon map and to construct regulatory networks at the cistron level in Streptomyces coelicolor. The functionally-relevant modules identified in this study pose as potential targets for further studies and verification.

  4. A mixture copula Bayesian network model for multimodal genomic data

    Directory of Open Access Journals (Sweden)

    Qingyang Zhang

    2017-04-01

    Full Text Available Gaussian Bayesian networks have become a widely used framework to estimate directed associations between joint Gaussian variables, where the network structure encodes the decomposition of multivariate normal density into local terms. However, the resulting estimates can be inaccurate when the normality assumption is moderately or severely violated, making it unsuitable for dealing with recent genomic data such as the Cancer Genome Atlas data. In the present paper, we propose a mixture copula Bayesian network model which provides great flexibility in modeling non-Gaussian and multimodal data for causal inference. The parameters in mixture copula functions can be efficiently estimated by a routine expectation–maximization algorithm. A heuristic search algorithm based on Bayesian information criterion is developed to estimate the network structure, and prediction can be further improved by the best-scoring network out of multiple predictions from random initial values. Our method outperforms Gaussian Bayesian networks and regular copula Bayesian networks in terms of modeling flexibility and prediction accuracy, as demonstrated using a cell signaling data set. We apply the proposed methods to the Cancer Genome Atlas data to study the genetic and epigenetic pathways that underlie serous ovarian cancer.

  5. Exploring Networks at the genome scale

    NARCIS (Netherlands)

    Lam, M.C.; Puchalka, J.; Diez, M.S.; Martins Dos Santos, V.A.P.

    2010-01-01

    Systems biology is aimed at achieving a holistic understanding of living organisms, while synthetic biology seeks to design and construct new living organisms with targeted functionalities. Genome sequencing and the fields of ‘omics’ technology have proven a goldmine of information for scientists

  6. Power Laws, Scale-Free Networks and Genome Biology

    CERN Document Server

    Koonin, Eugene V; Karev, Georgy P

    2006-01-01

    Power Laws, Scale-free Networks and Genome Biology deals with crucial aspects of the theoretical foundations of systems biology, namely power law distributions and scale-free networks which have emerged as the hallmarks of biological organization in the post-genomic era. The chapters in the book not only describe the interesting mathematical properties of biological networks but moves beyond phenomenology, toward models of evolution capable of explaining the emergence of these features. The collection of chapters, contributed by both physicists and biologists, strives to address the problems in this field in a rigorous but not excessively mathematical manner and to represent different viewpoints, which is crucial in this emerging discipline. Each chapter includes, in addition to technical descriptions of properties of biological networks and evolutionary models, a more general and accessible introduction to the respective problems. Most chapters emphasize the potential of theoretical systems biology for disco...

  7. Unethical Behaviours Preservice Teachers Encounter on Social Networks

    Science.gov (United States)

    Deveci Topal, Arzu; Kolburan Gecer, Aynur

    2015-01-01

    The development of web 2.0 technology has resulted in an increase in internet sharing. The scope of this study is social networking, which is one of the web 2.0 tools most heavily used by internet users. In this paper, the unethical behaviours that preservice teachers encounter on social networks and the ways to deal with these problems are…

  8. The Embeddedness of Teachers' Social Networks: Evidence from a Study of Mathematics Reform

    Science.gov (United States)

    Coburn, Cynthia E.; Mata, Willow S.; Choi, Linda

    2013-01-01

    Teachers' social networks can play an important role in teacher learning and organizational change. But what influences teachers' networks? Why do some teachers have networks that are likely to support individual and organizational change, while others do not? This study is a first step in answering this question. We focus on how district policy…

  9. Inference of self-regulated transcriptional networks by comparative genomics.

    Science.gov (United States)

    Cornish, Joseph P; Matthews, Fialelei; Thomas, Julien R; Erill, Ivan

    2012-01-01

    The assumption of basic properties, like self-regulation, in simple transcriptional regulatory networks can be exploited to infer regulatory motifs from the growing amounts of genomic and meta-genomic data. These motifs can in principle be used to elucidate the nature and scope of transcriptional networks through comparative genomics. Here we assess the feasibility of this approach using the SOS regulatory network of Gram-positive bacteria as a test case. Using experimentally validated data, we show that the known regulatory motif can be inferred through the assumption of self-regulation. Furthermore, the inferred motif provides a more robust search pattern for comparative genomics than the experimental motifs defined in reference organisms. We take advantage of this robustness to generate a functional map of the SOS response in Gram-positive bacteria. Our results reveal definite differences in the composition of the LexA regulon between Firmicutes and Actinobacteria, and confirm that regulation of cell-division inhibition is a widespread characteristic of this network among Gram-positive bacteria.

  10. MIRAGE: a functional genomics-based approach for metabolic network model reconstruction and its application to cyanobacteria networks.

    Science.gov (United States)

    Vitkin, Edward; Shlomi, Tomer

    2012-11-29

    Genome-scale metabolic network reconstructions are considered a key step in quantifying the genotype-phenotype relationship. We present a novel gap-filling approach, MetabolIc Reconstruction via functionAl GEnomics (MIRAGE), which identifies missing network reactions by integrating metabolic flux analysis and functional genomics data. MIRAGE's performance is demonstrated on the reconstruction of metabolic network models of E. coli and Synechocystis sp. and validated via existing networks for these species. Then, it is applied to reconstruct genome-scale metabolic network models for 36 sequenced cyanobacteria amenable for constraint-based modeling analysis and specifically for metabolic engineering. The reconstructed network models are supplied via standard SBML files.

  11. Assessment of a national network: the case of the French teacher training colleges' health education network.

    Science.gov (United States)

    Guével, Marie-Renée; Jourdan, Didier

    2009-06-01

    The French teacher training colleges' health education (HE) network was set up in 2005 to encourage the inclusion of HE in courses for primary and secondary school teachers. A systematic process of monitoring the activity and the impact of this initiative was implemented. This analysis was systematically compared with the perceptions of teaching staff involved in the network. This paper assesses the network after 2 years using documents produced and interviews with 24 coordinators. Twenty-nine teacher training colleges out of a total of 31 are involved in the network. The network has helped to create links between teacher training colleges, extend HE training and encourage partnerships with other public health organizations. By 2007, HE was included in courses offered by 19 teacher training colleges as opposed to only 3 in 2005. This study not only showed the positive impact of the network but also revealed issues in its management and presented new challenges to ensure the effectiveness of the network. The network has succeeded in attracting and training trainers who were already providing or were interested in HE. Reaching other trainers who are not familiar with HE remains a challenge for the future.

  12. Evolution after whole-genome duplication: a network perspective.

    Science.gov (United States)

    Zhu, Yun; Lin, Zhenguo; Nakhleh, Luay

    2013-11-06

    Gene duplication plays an important role in the evolution of genomes and interactomes. Elucidating how evolution after gene duplication interplays at the sequence and network level is of great interest. In this work, we analyze a data set of gene pairs that arose through whole-genome duplication (WGD) in yeast. All these pairs have the same duplication time, making them ideal for evolutionary investigation. We investigated the interplay between evolution after WGD at the sequence and network levels and correlated these two levels of divergence with gene expression and fitness data. We find that molecular interactions involving WGD genes evolve at rates that are three orders of magnitude slower than the rates of evolution of the corresponding sequences. Furthermore, we find that divergence of WGD pairs correlates strongly with gene expression and fitness data. Because of the role of gene duplication in determining redundancy in biological systems and particularly at the network level, we investigated the role of interaction networks in elucidating the evolutionary fate of duplicated genes. We find that gene neighborhoods in interaction networks provide a mechanism for inferring these fates, and we developed an algorithm for achieving this task. Further epistasis analysis of WGD pairs categorized by their inferred evolutionary fates demonstrated the utility of these techniques. Finally, we find that WGD pairs and other pairs of paralogous genes of small-scale duplication origin share similar properties, giving good support for generalizing our results from WGD pairs to evolution after gene duplication in general.

  13. Chemical and genomic evolution of enzyme-catalyzed reaction networks.

    Science.gov (United States)

    Kanehisa, Minoru

    2013-09-02

    There is a tendency that a unit of enzyme genes in an operon-like structure in the prokaryotic genome encodes enzymes that catalyze a series of consecutive reactions in a metabolic pathway. Our recent analysis shows that this and other genomic units correspond to chemical units reflecting chemical logic of organic reactions. From all known metabolic pathways in the KEGG database we identified chemical units, called reaction modules, as the conserved sequences of chemical structure transformation patterns of small molecules. The extracted patterns suggest co-evolution of genomic units and chemical units. While the core of the metabolic network may have evolved with mechanisms involving individual enzymes and reactions, its extension may have been driven by modular units of enzymes and reactions.

  14. The Global Genome Biodiversity Network (GGBN) Data Portal.

    Science.gov (United States)

    Droege, Gabriele; Barker, Katharine; Astrin, Jonas J; Bartels, Paul; Butler, Carol; Cantrill, David; Coddington, Jonathan; Forest, Félix; Gemeinholzer, Birgit; Hobern, Donald; Mackenzie-Dodds, Jacqueline; Ó Tuama, Éamonn; Petersen, Gitte; Sanjur, Oris; Schindel, David; Seberg, Ole

    2014-01-01

    The Global Genome Biodiversity Network (GGBN) was formed in 2011 with the principal aim of making high-quality well-documented and vouchered collections that store DNA or tissue samples of biodiversity, discoverable for research through a networked community of biodiversity repositories. This is achieved through the GGBN Data Portal (http://data.ggbn.org), which links globally distributed databases and bridges the gap between biodiversity repositories, sequence databases and research results. Advances in DNA extraction techniques combined with next-generation sequencing technologies provide new tools for genome sequencing. Many ambitious genome sequencing projects with the potential to revolutionize biodiversity research consider access to adequate samples to be a major bottleneck in their workflow. This is linked not only to accelerating biodiversity loss and demands to improve conservation efforts but also to a lack of standardized methods for providing access to genomic samples. Biodiversity biobank-holding institutions urgently need to set a standard of collaboration towards excellence in collections stewardship, information access and sharing and responsible and ethical use of such collections. GGBN meets these needs by enabling and supporting accessibility and the efficient coordinated expansion of biodiversity biobanks worldwide.

  15. Untangling statistical and biological models to understand network inference: the need for a genomics network ontology.

    Science.gov (United States)

    Emmert-Streib, Frank; Dehmer, Matthias; Haibe-Kains, Benjamin

    2014-01-01

    In this paper, we shed light on approaches that are currently used to infer networks from gene expression data with respect to their biological meaning. As we will show, the biological interpretation of these networks depends on the chosen theoretical perspective. For this reason, we distinguish a statistical perspective from a mathematical modeling perspective and elaborate their differences and implications. Our results indicate the imperative need for a genomic network ontology in order to avoid increasing confusion about the biological interpretation of inferred networks, which can be even enhanced by approaches that integrate multiple data sets, respectively, data types.

  16. The Role of Social Networks in the Teacher Job Search Process

    Science.gov (United States)

    Cannata, Marisa

    2011-01-01

    This article highlights the role of social networks in the elementary teacher job search. Using interviews with 27 teacher applicants, it explores how prospective elementary teachers used their social networks to identify job opportunities, obtain jobs, and gather information about schools. The findings suggest that teacher applicants assumed that…

  17. Social Networking Tools and Teacher Education Learning Communities: A Case Study

    Science.gov (United States)

    Poulin, Michael T.

    2014-01-01

    Social networking tools have become an integral part of a pre-service teacher's educational experience. As a result, the educational value of social networking tools in teacher preparation programs must be examined. The specific problem addressed in this study is that the role of social networking tools in teacher education learning communities…

  18. Social Networking Tools and Teacher Education Learning Communities: A Case Study

    Science.gov (United States)

    Poulin, Michael T.

    2014-01-01

    Social networking tools have become an integral part of a pre-service teacher's educational experience. As a result, the educational value of social networking tools in teacher preparation programs must be examined. The specific problem addressed in this study is that the role of social networking tools in teacher education learning communities…

  19. Follicular cell thyroid neoplasia: insights from genomics and The Cancer Genome Atlas research network.

    Science.gov (United States)

    Giordano, Thomas J

    2016-01-01

    The present review is focused on the recently published study on the genomics of papillary thyroid carcinoma performed by The Cancer Genome Atlas Research Network and its implications for the follicular variant of papillary carcinoma. The Cancer Genome Atlas study of papillary thyroid carcinoma comprehensively examined the cancer genome of nearly 500 primary tumors. Using a highly integrated bioinformatic analysis, papillary carcinoma was shown at the genomic level to consist of two highly distinct classes that reflected both tumor histology and underlying genotype. Tumors with true papillary architecture were dominated by BRAF(V600E) mutations and RET kinase fusions and were designated as BRAF(V600E)-like. Tumors with follicular architecture were conversely dominated by RAS mutations and were designated as RAS-like. Given the strong genotype:phenotype correlation known to be present in thyroid cancer, the separation of BRAF(V600E)-like and RAS-like tumors has profound implications for its classification, especially the follicular variant of papillary carcinoma. The recent genomic characterization of papillary thyroid carcinoma is challenging the established pathological classification of thyroid cancer with significance for the care of patients.

  20. The Global Genome Biodiversity Network (GGBN) Data Standard specification

    Science.gov (United States)

    Droege, G.; Barker, K.; Seberg, O.; Coddington, J.; Benson, E.; Berendsohn, W. G.; Bunk, B.; Butler, C.; Cawsey, E. M.; Deck, J.; Döring, M.; Flemons, P.; Gemeinholzer, B.; Güntsch, A.; Hollowell, T.; Kelbert, P.; Kostadinov, I.; Kottmann, R.; Lawlor, R. T.; Lyal, C.; Mackenzie-Dodds, J.; Meyer, C.; Mulcahy, D.; Nussbeck, S. Y.; O'Tuama, É.; Orrell, T.; Petersen, G.; Robertson, T.; Söhngen, C.; Whitacre, J.; Wieczorek, J.; Yilmaz, P.; Zetzsche, H.; Zhang, Y.; Zhou, X.

    2016-01-01

    Genomic samples of non-model organisms are becoming increasingly important in a broad range of studies from developmental biology, biodiversity analyses, to conservation. Genomic sample definition, description, quality, voucher information and metadata all need to be digitized and disseminated across scientific communities. This information needs to be concise and consistent in today’s ever-increasing bioinformatic era, for complementary data aggregators to easily map databases to one another. In order to facilitate exchange of information on genomic samples and their derived data, the Global Genome Biodiversity Network (GGBN) Data Standard is intended to provide a platform based on a documented agreement to promote the efficient sharing and usage of genomic sample material and associated specimen information in a consistent way. The new data standard presented here build upon existing standards commonly used within the community extending them with the capability to exchange data on tissue, environmental and DNA sample as well as sequences. The GGBN Data Standard will reveal and democratize the hidden contents of biodiversity biobanks, for the convenience of everyone in the wider biobanking community. Technical tools exist for data providers to easily map their databases to the standard. Database URL: http://terms.tdwg.org/wiki/GGBN_Data_Standard

  1. Teacher Agency in Educational Reform: Lessons from Social Networks Research

    Science.gov (United States)

    Datnow, Amanda

    2012-01-01

    This article provides a context for understanding how social networks among teachers support or constrain school improvement in terms of instructional practice, professional development, and educational reform. It comments on the articles in this special issue, summarizing their contributions to the field. This analysis reveals several important…

  2. Teacher Agency in Educational Reform: Lessons from Social Networks Research

    Science.gov (United States)

    Datnow, Amanda

    2012-01-01

    This article provides a context for understanding how social networks among teachers support or constrain school improvement in terms of instructional practice, professional development, and educational reform. It comments on the articles in this special issue, summarizing their contributions to the field. This analysis reveals several important…

  3. Symbolic flux analysis for genome-scale metabolic networks

    Directory of Open Access Journals (Sweden)

    Peterson Pearu

    2011-05-01

    Full Text Available Abstract Background With the advent of genomic technology, the size of metabolic networks that are subject to analysis is growing. A common task when analyzing metabolic networks is to find all possible steady state regimes. There are several technical issues that have to be addressed when analyzing large metabolic networks including accumulation of numerical errors and presentation of the solution to the researcher. One way to resolve those technical issues is to analyze the network using symbolic methods. The aim of this paper is to develop a routine that symbolically finds the steady state solutions of large metabolic networks. Results A symbolic Gauss-Jordan elimination routine was developed for analyzing large metabolic networks. This routine was tested by finding the steady state solutions for a number of curated stoichiometric matrices with the largest having about 4000 reactions. The routine was able to find the solution with a computational time similar to the time used by a numerical singular value decomposition routine. As an advantage of symbolic solution, a set of independent fluxes can be suggested by the researcher leading to the formation of a desired flux basis describing the steady state solution of the network. These independent fluxes can be constrained using experimental data. We demonstrate the application of constraints by calculating a flux distribution for the central metabolic and amino acid biosynthesis pathways of yeast. Conclusions We were able to find symbolic solutions for the steady state flux distribution of large metabolic networks. The ability to choose a flux basis was found to be useful in the constraint process and provides a strong argument for using symbolic Gauss-Jordan elimination in place of singular value decomposition.

  4. Symbolic flux analysis for genome-scale metabolic networks.

    Science.gov (United States)

    Schryer, David W; Vendelin, Marko; Peterson, Pearu

    2011-05-23

    With the advent of genomic technology, the size of metabolic networks that are subject to analysis is growing. A common task when analyzing metabolic networks is to find all possible steady state regimes. There are several technical issues that have to be addressed when analyzing large metabolic networks including accumulation of numerical errors and presentation of the solution to the researcher. One way to resolve those technical issues is to analyze the network using symbolic methods. The aim of this paper is to develop a routine that symbolically finds the steady state solutions of large metabolic networks. A symbolic Gauss-Jordan elimination routine was developed for analyzing large metabolic networks. This routine was tested by finding the steady state solutions for a number of curated stoichiometric matrices with the largest having about 4000 reactions. The routine was able to find the solution with a computational time similar to the time used by a numerical singular value decomposition routine. As an advantage of symbolic solution, a set of independent fluxes can be suggested by the researcher leading to the formation of a desired flux basis describing the steady state solution of the network. These independent fluxes can be constrained using experimental data. We demonstrate the application of constraints by calculating a flux distribution for the central metabolic and amino acid biosynthesis pathways of yeast. We were able to find symbolic solutions for the steady state flux distribution of large metabolic networks. The ability to choose a flux basis was found to be useful in the constraint process and provides a strong argument for using symbolic Gauss-Jordan elimination in place of singular value decomposition.

  5. Assembling networks of microbial genomes using linear programming

    Directory of Open Access Journals (Sweden)

    Holloway Catherine

    2010-11-01

    Full Text Available Abstract Background Microbial genomes exhibit complex sets of genetic affinities due to lateral genetic transfer. Assessing the relative contributions of parent-to-offspring inheritance and gene sharing is a vital step in understanding the evolutionary origins and modern-day function of an organism, but recovering and showing these relationships is a challenging problem. Results We have developed a new approach that uses linear programming to find between-genome relationships, by treating tables of genetic affinities (here, represented by transformed BLAST e-values as an optimization problem. Validation trials on simulated data demonstrate the effectiveness of the approach in recovering and representing vertical and lateral relationships among genomes. Application of the technique to a set comprising Aquifex aeolicus and 75 other thermophiles showed an important role for large genomes as 'hubs' in the gene sharing network, and suggested that genes are preferentially shared between organisms with similar optimal growth temperatures. We were also able to discover distinct and common genetic contributors to each sequenced representative of genus Pseudomonas. Conclusions The linear programming approach we have developed can serve as an effective inference tool in its own right, and can be an efficient first step in a more-intensive phylogenomic analysis.

  6. The Media Awareness Network: Online for Teachers.

    Science.gov (United States)

    Taylor, Anne

    1996-01-01

    Discusses the Media Awareness Network, a Web site established by the National Film Board of Canada and designed to provide the latest media-related news; information about media education workshops and other media Web sites; subject specific teaching units; and updates on government policy related to violence, pornography, copyright, and hate…

  7. Developing networks to support science teachers work

    DEFF Research Database (Denmark)

    Sillasen, Martin Krabbe; Valero, Paola

    2012-01-01

    In educational research literature constructing networks among practitioners has been suggested as a strategy to support teachers’ professional development (Huberman, 1995; Jackson & Temperley, 2007; Van Driel, Beijaard, & Verloop, 2001). The purpose of this paper is to report on a study about ho...

  8. Layers of epistasis: genome-wide regulatory networks and network approaches to genome-wide association studies

    Science.gov (United States)

    Cowper-Sal·lari, Richard; Cole, Michael D.; Karagas, Margaret R.; Lupien, Mathieu; Moore, Jason H.

    2010-01-01

    The conceptual foundation of the genome-wide association study (GWAS) has advanced unchecked since its conception. A revision might seem premature as the potential of GWAS has not been fully realized. Multiple technical and practical limitations need to be overcome before GWAS can be fairly criticized. But with the completion of hundreds of studies and a deeper understanding of the genetic architecture of disease, warnings are being raised. The results compiled to date indicate that risk-associated variants lie predominantly in non-coding regions of the genome. Additionally, alternative methodologies are uncovering large and heterogeneous sets of rare variants underlying disease. The fear is that, even in its fulfilment, the current GWAS paradigm might be incapable of dissecting all kinds of phenotypes. In the following text we review several initiatives that aim to overcome these limitations. The overarching theme of these studies is the inclusion of biological knowledge to both the analysis and interpretation of genotyping data. GWAS is uninformed of biology by design and although there is some virtue in its simplicity it is also its most conspicuous deficiency. We propose a framework in which to integrate these novel approaches, both empirical and theoretical, in the form of a genome-wide regulatory network (GWRN). By processing experimental data into networks, emerging data types based on chromatin-immunoprecipitation are made computationally tractable. This will give GWAS re-analysis efforts the most current and relevant substrates, and root them firmly on our knowledge of human disease. PMID:21197657

  9. Public Health Genomics European Network: Report from the 2nd Network Meeting in Rome

    Directory of Open Access Journals (Sweden)

    Nicole Rosenkötter

    2007-03-01

    Full Text Available

    Dear Sirs,

    The Public Health Genomics European Network (PHGEN is a mapping exercise for the responsible and effective integration of genome-based knowledge and technologies into public policy and health services for the benefit of population health. In 2005, the European Commission called for a “networking exercise…to lead to an inventory report on genetic determinants relevant for public health”[1], this lead to the funding of a PHGEN three year project (EC project 2005313.This project started in early 2006 with a kick-off meeting in Bielefeld / Germany.The project work is comprised of, according to the public health trias, three one year periods of assessment, policy development and assurance.At the end of the assessment phase a network meeting was held in Rome from January, 31st to February 2nd 2007 with over 90 network members and network observers in attendance. The participants represented different organisations throughout the European Union with expertise in areas such as human genetics and other medical disciplines,epidemiology,public health, law, ethics, political and social sciences. The aim of the meeting was to wrap up the last year’s assessment period and to herald the policy development phase.The assessment period of PHGEN was characterised by several activities: - Contact and cooperation with other European and internationally funded networks and projects on public health genomics or related issues (e.g. EuroGenetest, EUnetHTA, Orphanet, IPTS, PHOEBE, GRaPHInt, P3G - Identification of key experts in public health genomics in the European members states, applicant countries and EFTA/EEA countries from different disciplines (e.g. human genetics and other medical disciplines, public health, law, philosophy, epidemiology, political and social sciences - Building up national task forces on public health genomics in the above mentioned countries - Establishing and work in three working groups: public health genomics

  10. What Is the Role of Constructivist Teachers within Faculty Communication Networks?

    Science.gov (United States)

    Judson, Eugene; Lawson, Anton E.

    2007-01-01

    Using the biology faculty of one high school (n = 9) and the mathematics faculty of another (n = 16), this study tested the hypothesis that constructivist teachers play an active role within teacher communication networks (the constructivist-teacher hypothesis). This hypothesis contrasts with the view that constructivist teachers operate alone and…

  11. Properties of Teacher Networks in Twitter: Are They Related to Community-Based Peer Production?

    Science.gov (United States)

    Macià, Maria; Garcia, Iolanda

    2017-01-01

    Teachers participate in social networking sites to share knowledge and collaborate with other teachers to create education-related content. In this study we selected several communities in order to better understand the networks that these participants establish in Twitter and the role that the social network plays in their activity within the…

  12. A scored human protein-protein interaction network to catalyze genomic interpretation

    DEFF Research Database (Denmark)

    Li, Taibo; Wernersson, Rasmus; Hansen, Rasmus B;

    2017-01-01

    Genome-scale human protein-protein interaction networks are critical to understanding cell biology and interpreting genomic data, but challenging to produce experimentally. Through data integration and quality control, we provide a scored human protein-protein interaction network (In...

  13. Integrated Genomic and Network-Based Analyses of Complex Diseases and Human Disease Network.

    Science.gov (United States)

    Al-Harazi, Olfat; Al Insaif, Sadiq; Al-Ajlan, Monirah A; Kaya, Namik; Dzimiri, Nduna; Colak, Dilek

    2016-06-20

    A disease phenotype generally reflects various pathobiological processes that interact in a complex network. The highly interconnected nature of the human protein interaction network (interactome) indicates that, at the molecular level, it is difficult to consider diseases as being independent of one another. Recently, genome-wide molecular measurements, data mining and bioinformatics approaches have provided the means to explore human diseases from a molecular basis. The exploration of diseases and a system of disease relationships based on the integration of genome-wide molecular data with the human interactome could offer a powerful perspective for understanding the molecular architecture of diseases. Recently, subnetwork markers have proven to be more robust and reliable than individual biomarker genes selected based on gene expression profiles alone, and achieve higher accuracy in disease classification. We have applied one of these methodologies to idiopathic dilated cardiomyopathy (IDCM) data that we have generated using a microarray and identified significant subnetworks associated with the disease. In this paper, we review the recent endeavours in this direction, and summarize the existing methodologies and computational tools for network-based analysis of complex diseases and molecular relationships among apparently different disorders and human disease network. We also discuss the future research trends and topics of this promising field.

  14. CMIP: a software package capable of reconstructing genome-wide regulatory networks using gene expression data.

    Science.gov (United States)

    Zheng, Guangyong; Xu, Yaochen; Zhang, Xiujun; Liu, Zhi-Ping; Wang, Zhuo; Chen, Luonan; Zhu, Xin-Guang

    2016-12-23

    A gene regulatory network (GRN) represents interactions of genes inside a cell or tissue, in which vertexes and edges stand for genes and their regulatory interactions respectively. Reconstruction of gene regulatory networks, in particular, genome-scale networks, is essential for comparative exploration of different species and mechanistic investigation of biological processes. Currently, most of network inference methods are computationally intensive, which are usually effective for small-scale tasks (e.g., networks with a few hundred genes), but are difficult to construct GRNs at genome-scale. Here, we present a software package for gene regulatory network reconstruction at a genomic level, in which gene interaction is measured by the conditional mutual information measurement using a parallel computing framework (so the package is named CMIP). The package is a greatly improved implementation of our previous PCA-CMI algorithm. In CMIP, we provide not only an automatic threshold determination method but also an effective parallel computing framework for network inference. Performance tests on benchmark datasets show that the accuracy of CMIP is comparable to most current network inference methods. Moreover, running tests on synthetic datasets demonstrate that CMIP can handle large datasets especially genome-wide datasets within an acceptable time period. In addition, successful application on a real genomic dataset confirms its practical applicability of the package. This new software package provides a powerful tool for genomic network reconstruction to biological community. The software can be accessed at http://www.picb.ac.cn/CMIP/ .

  15. Stories in Networks and Networks in Stories: A Tri-Modal Model for Mixed-Methods Social Network Research on Teachers

    Science.gov (United States)

    Baker-Doyle, Kira J.

    2015-01-01

    Social network research on teachers and schools has risen exponentially in recent years as an innovative method to reveal the role of social networks in education. However, scholars are still exploring ways to incorporate traditional quantitative methods of Social Network Analysis (SNA) with qualitative approaches to social network research. This…

  16. Stories in Networks and Networks in Stories: A Tri-Modal Model for Mixed-Methods Social Network Research on Teachers

    Science.gov (United States)

    Baker-Doyle, Kira J.

    2015-01-01

    Social network research on teachers and schools has risen exponentially in recent years as an innovative method to reveal the role of social networks in education. However, scholars are still exploring ways to incorporate traditional quantitative methods of Social Network Analysis (SNA) with qualitative approaches to social network research. This…

  17. Uncovering changes in university teachers' professional networks during an instructional development program

    NARCIS (Netherlands)

    Van Waes, Sara; Van den Bossche, Piet; Moolenaar, Nienke M.; Stes, Ann; Van Petegem, Peter

    2015-01-01

    This study examined (1) the extent to which university teachers' networks changed while they participated in an instructional development program, (2) which mechanisms supported or constrained network change, and (3) the extent to which value was created through networks. Longitudinal social network

  18. "Newbies" and "Celebrities": Detecting Social Roles in an Online Network of Teachers via Participation Patterns

    Science.gov (United States)

    Smith Risser, H.; Bottoms, SueAnn

    2014-01-01

    The advent of social networking tools allows teachers to create online networks and share information. While some virtual networks have a formal structure and defined boundaries, many do not. These unstructured virtual networks are difficult to study because they lack defined boundaries and a formal structure governing leadership roles and the…

  19. Connected to Learn: Teachers' Experiences with Networked Technologies in the Classroom

    Science.gov (United States)

    Johnson, Matthew; Riel, Richard; Germain-Froese, Bernie

    2016-01-01

    To get a better understanding of how networked technologies are impacting teachers and their teaching practices, in 2015 MediaSmarts partnered with the Canadian Teachers' Federation to survey 4,043 K-12 teachers and school administrators who were teaching in classroom settings across the country. The survey explored the extent to which networked…

  20. Riding the Wave of Social Networking in the Context of Preservice Teacher Education

    Science.gov (United States)

    Highfield, Kate; Papic, Marina

    2015-01-01

    This study examined the use of one online social networking tool, NING™, in teacher education, highlighting preservice teachers' engagement and perceptions of the tool. Data obtained from 91 preservice teachers suggest that they found the multimodal platform useful as a tool to build pedagogic and content knowledge. Responses to surveys and online…

  1. Measuring Teacher Knowledge of Classroom Social Networks: Convergent and Predictive Validity in Elementary School Classrooms

    Science.gov (United States)

    Madill, Rebecca A.; Gest, Scott D.; Rodkin, Philip C.

    2012-01-01

    This study contributes to a growing body of literature focused on the role of the teacher's "invisible hand" in managing students social relationships. The authors focus on one specific aspect of attunement, teachers' social network knowledge, which they conceptualize as the completeness and accuracy of the teacher's social network…

  2. The Effectiveness of Using Social Communications Networks in Mathematics Teachers' Professional Development

    Science.gov (United States)

    Hussein, Hisham Barakat

    2013-01-01

    The study aims to determine the effectiveness of using social communications networks in mathematics teachers' professional development. The main research questions was: what is the effectiveness of using social communications networks in mathematics teachers' professional development. The sub questions were: (1) what are the standards of…

  3. Handbook of Graphs and Networks From the Genome to the Internet

    CERN Document Server

    Bornholdt, Stefan

    2002-01-01

    Complex interacting networks are observed in systems from such diverse areas as physics, biology, economics, ecology, and computer science. For example, economic or social interactions often organize themselves in complex network structures. Similar phenomena are observed in traffic flow and in communication networks as the internet. In current problems of the Biosciences, prominent examples are protein networks in the living cell, as well as molecular networks in the genome. On larger scales one finds networks of cells as in neural networks, up to the scale of organisms in ecological food web

  4. The NASA Galileo Educator Network: Using Astronomy to Engage Teachers in Science Practices

    Science.gov (United States)

    Kruse, B.; Bass, K. M.; Schultz, G.

    2015-11-01

    With funding from a NASA EPOESS grant, the Astronomical Society of the Pacific developed the NASA Galileo Educator Network (GEN), a train-the-trainer teacher professional development program based in part on the Galileo Teacher Training Program. Formal evaluation of the program demonstrates that both teacher trainers and teacher participants grew in their ability to utilize astronomy investigations focusing on science practices as described in the Next Generation Science Standards.

  5. Network Structure and Dynamics, and Emergence of Robustness by Stabilizing Selection in an Artificial Genome

    CERN Document Server

    Rohlf, Thimo

    2008-01-01

    Genetic regulation is a key component in development, but a clear understanding of the structure and dynamics of genetic networks is not yet at hand. In this work we investigate these properties within an artificial genome model originally introduced by Reil. We analyze statistical properties of randomly generated genomes both on the sequence- and network level, and show that this model correctly predicts the frequency of genes in genomes as found in experimental data. Using an evolutionary algorithm based on stabilizing selection for a phenotype, we show that robustness against single base mutations, as well as against random changes in initial network states that mimic stochastic fluctuations in environmental conditions, can emerge in parallel. Evolved genomes exhibit characteristic patterns on both sequence and network level.

  6. Genome-wide identification of specific oligonucleotides using artificial neural network and computational genomic analysis

    Directory of Open Access Journals (Sweden)

    Chen Jiun-Ching

    2007-05-01

    Full Text Available Abstract Background Genome-wide identification of specific oligonucleotides (oligos is a computationally-intensive task and is a requirement for designing microarray probes, primers, and siRNAs. An artificial neural network (ANN is a machine learning technique that can effectively process complex and high noise data. Here, ANNs are applied to process the unique subsequence distribution for prediction of specific oligos. Results We present a novel and efficient algorithm, named the integration of ANN and BLAST (IAB algorithm, to identify specific oligos. We establish the unique marker database for human and rat gene index databases using the hash table algorithm. We then create the input vectors, via the unique marker database, to train and test the ANN. The trained ANN predicted the specific oligos with high efficiency, and these oligos were subsequently verified by BLAST. To improve the prediction performance, the ANN over-fitting issue was avoided by early stopping with the best observed error and a k-fold validation was also applied. The performance of the IAB algorithm was about 5.2, 7.1, and 6.7 times faster than the BLAST search without ANN for experimental results of 70-mer, 50-mer, and 25-mer specific oligos, respectively. In addition, the results of polymerase chain reactions showed that the primers predicted by the IAB algorithm could specifically amplify the corresponding genes. The IAB algorithm has been integrated into a previously published comprehensive web server to support microarray analysis and genome-wide iterative enrichment analysis, through which users can identify a group of desired genes and then discover the specific oligos of these genes. Conclusion The IAB algorithm has been developed to construct SpecificDB, a web server that provides a specific and valid oligo database of the probe, siRNA, and primer design for the human genome. We also demonstrate the ability of the IAB algorithm to predict specific oligos through

  7. Comparative analysis of Salmonella genomes identifies a metabolic network for escalating growth in the inflamed gut.

    Science.gov (United States)

    Nuccio, Sean-Paul; Bäumler, Andreas J

    2014-03-18

    The Salmonella genus comprises a group of pathogens associated with illnesses ranging from gastroenteritis to typhoid fever. We performed an in silico analysis of comparatively reannotated Salmonella genomes to identify genomic signatures indicative of disease potential. By removing numerous annotation inconsistencies and inaccuracies, the process of reannotation identified a network of 469 genes involved in central anaerobic metabolism, which was intact in genomes of gastrointestinal pathogens but degrading in genomes of extraintestinal pathogens. This large network contained pathways that enable gastrointestinal pathogens to utilize inflammation-derived nutrients as well as many of the biochemical reactions used for the enrichment and biochemical discrimination of Salmonella serovars. Thus, comparative genome analysis identifies a metabolic network that provides clues about the strategies for nutrient acquisition and utilization that are characteristic of gastrointestinal pathogens. IMPORTANCE While some Salmonella serovars cause infections that remain localized to the gut, others disseminate throughout the body. Here, we compared Salmonella genomes to identify characteristics that distinguish gastrointestinal from extraintestinal pathogens. We identified a large metabolic network that is functional in gastrointestinal pathogens but decaying in extraintestinal pathogens. While taxonomists have used traits from this network empirically for many decades for the enrichment and biochemical discrimination of Salmonella serovars, our findings suggest that it is part of a "business plan" for growth in the inflamed gastrointestinal tract. By identifying a large metabolic network characteristic of Salmonella serovars associated with gastroenteritis, our in silico analysis provides a blueprint for potential strategies to utilize inflammation-derived nutrients and edge out competing gut microbes.

  8. Toward the automated generation of genome-scale metabolic networks in the SEED

    Directory of Open Access Journals (Sweden)

    Gould John

    2007-04-01

    Full Text Available Abstract Background Current methods for the automated generation of genome-scale metabolic networks focus on genome annotation and preliminary biochemical reaction network assembly, but do not adequately address the process of identifying and filling gaps in the reaction network, and verifying that the network is suitable for systems level analysis. Thus, current methods are only sufficient for generating draft-quality networks, and refinement of the reaction network is still largely a manual, labor-intensive process. Results We have developed a method for generating genome-scale metabolic networks that produces substantially complete reaction networks, suitable for systems level analysis. Our method partitions the reaction space of central and intermediary metabolism into discrete, interconnected components that can be assembled and verified in isolation from each other, and then integrated and verified at the level of their interconnectivity. We have developed a database of components that are common across organisms, and have created tools for automatically assembling appropriate components for a particular organism based on the metabolic pathways encoded in the organism's genome. This focuses manual efforts on that portion of an organism's metabolism that is not yet represented in the database. We have demonstrated the efficacy of our method by reverse-engineering and automatically regenerating the reaction network from a published genome-scale metabolic model for Staphylococcus aureus. Additionally, we have verified that our method capitalizes on the database of common reaction network components created for S. aureus, by using these components to generate substantially complete reconstructions of the reaction networks from three other published metabolic models (Escherichia coli, Helicobacter pylori, and Lactococcus lactis. We have implemented our tools and database within the SEED, an open-source software environment for comparative

  9. A Social Network Analysis of Teaching and Research Collaboration in a Teachers' Virtual Learning Community

    Science.gov (United States)

    Lin, Xiaofan; Hu, Xiaoyong; Hu, Qintai; Liu, Zhichun

    2016-01-01

    Analysing the structure of a social network can help us understand the key factors influencing interaction and collaboration in a virtual learning community (VLC). Here, we describe the mechanisms used in social network analysis (SNA) to analyse the social network structure of a VLC for teachers and discuss the relationship between face-to-face…

  10. The MI bundle: enabling network and structural biology in genome visualization tools.

    Science.gov (United States)

    Céol, Arnaud; Müller, Heiko

    2015-11-15

    Prioritization of candidate genes emanating from large-scale screens requires integrated analyses at the genomics, molecular, network and structural biology levels. We have extended the Integrated Genome Browser (IGB) to facilitate these tasks. The graphical user interface greatly simplifies building disease networks and zooming in at atomic resolution to identify variations in molecular complexes that may affect molecular interactions in the context of genomic data. All results are summarized in genome tracks and can be visualized and analyzed at the transcript level. The MI Bundle is a plugin for the IGB. The plugin, help, video and tutorial are available at http://cru.genomics.iit.it/igbmibundle/ and https://github.com/CRUiit/igb-mi-bundle/wiki. The source code is released under the Apache License, Version 2. arnaud.ceol@iit.it Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

  11. Googling your genes: personal genomics and the discourse of citizen bioscience in the network age

    Directory of Open Access Journals (Sweden)

    Marina Levina

    2010-03-01

    Full Text Available In this essay, I argue that the rise of personal genomics is technologically, economically, and most importantly, discursively tied to the rise of network subjectivity, an imperative of which is an understanding of self as always already a subject in the network. I illustrate how personal genomics takes full advantage of social media technology and network subjectivity to advertise a new way of doing research that emphasizes collaboration between researchers and its members. Sharing one’s genetic information is considered to be an act of citizenship, precisely because it is good for the network. Here members are encouraged to think of themselves as dividuals, or nodes, in the network and their actions acquire value based on that imperative. Therefore, citizen bioscience is intricately tied, both in discourse and practices, to the growth of the network in the age of new media.

  12. Comparative genomic reconstruction of transcriptional networks controlling central metabolism in the Shewanella genus

    Directory of Open Access Journals (Sweden)

    Kovaleva Galina

    2011-06-01

    Full Text Available Abstract Background Genome-scale prediction of gene regulation and reconstruction of transcriptional regulatory networks in bacteria is one of the critical tasks of modern genomics. The Shewanella genus is comprised of metabolically versatile gamma-proteobacteria, whose lifestyles and natural environments are substantially different from Escherichia coli and other model bacterial species. The comparative genomics approaches and computational identification of regulatory sites are useful for the in silico reconstruction of transcriptional regulatory networks in bacteria. Results To explore conservation and variations in the Shewanella transcriptional networks we analyzed the repertoire of transcription factors and performed genomics-based reconstruction and comparative analysis of regulons in 16 Shewanella genomes. The inferred regulatory network includes 82 transcription factors and their DNA binding sites, 8 riboswitches and 6 translational attenuators. Forty five regulons were newly inferred from the genome context analysis, whereas others were propagated from previously characterized regulons in the Enterobacteria and Pseudomonas spp.. Multiple variations in regulatory strategies between the Shewanella spp. and E. coli include regulon contraction and expansion (as in the case of PdhR, HexR, FadR, numerous cases of recruiting non-orthologous regulators to control equivalent pathways (e.g. PsrA for fatty acid degradation and, conversely, orthologous regulators to control distinct pathways (e.g. TyrR, ArgR, Crp. Conclusions We tentatively defined the first reference collection of ~100 transcriptional regulons in 16 Shewanella genomes. The resulting regulatory network contains ~600 regulated genes per genome that are mostly involved in metabolism of carbohydrates, amino acids, fatty acids, vitamins, metals, and stress responses. Several reconstructed regulons including NagR for N-acetylglucosamine catabolism were experimentally validated in S

  13. A call for an international network of genomic observatories (GOs).

    Science.gov (United States)

    Davies, Neil; Meyer, Chris; Gilbert, Jack A; Amaral-Zettler, Linda; Deck, John; Bicak, Mesude; Rocca-Serra, Philippe; Assunta-Sansone, Susanna; Willis, Kathy; Field, Dawn

    2012-07-12

    We are entering a new era in genomics-that of large-scale, place-based, highly contextualized genomic research. Here we review this emerging paradigm shift and suggest that sites of utmost scientific importance be expanded into 'Genomic Observatories' (GOs). Investment in GOs should focus on the digital characterization of whole ecosystems, from all-taxa biotic inventories to time-series 'omics studies. The foundational layer of biodiversity-genetic variation-would thus be mainstreamed into Earth Observation systems enabling predictive modelling of biodiversity dynamics and resultant impacts on ecosystem services.

  14. Comparing Two Versions of Professional Development for Teachers Using Formative Assessment in Networked Mathematics Classrooms

    Science.gov (United States)

    Yin, Yue; Olson, Judith; Olson, Melfried; Solvin, Hannah; Brandon, Paul R.

    2015-01-01

    This study compared two versions of professional development (PD) designed for teachers using formative assessment (FA) in mathematics classrooms that were networked with Texas Instruments Navigator (NAV) technology. Thirty-two middle school mathematics teachers were randomly assigned to one of the two groups: FA-then-NAV group and FA-and-NAV…

  15. Perceptions of Teacher Candidates about Social Network Usage Levels in Turkey

    Science.gov (United States)

    Koçoglu, Erol

    2017-01-01

    This study was conducted to determine the perceptions of the teacher candidates in educational faculties in Turkey about social network usage levels in today's globalizing world. The study was performed with 4 separate study groups. The first study group consisted of 657 teacher candidates, the second study group consisted of 364 teacher…

  16. Pursuing Excellence in Teacher Preparation: Evidence of Institutional Change from TNE Learning Network Universities

    Science.gov (United States)

    Rogers Poliakoff, Anne; Dailey, Caitlin Rose; White, Robin

    2011-01-01

    The purpose of this report is to document evidence of institutional change in teacher preparation among universities participating in the Teachers for a New Era (TNE) Learning Network. The report is based upon a cross-case analysis of individual case studies of nine universities, conducted by Academy for Educational Development (AED) researchers.…

  17. Why Should They Stay? A Social Network Analysis of Teacher Retention

    Science.gov (United States)

    Hodgson, Kevin W.

    2013-01-01

    Decades of research have established that there is a significant issue retaining teachers in America's schools. In fact, upwards of 50% of all teachers do not last more than five years (Ingersoll, 2001). Despite a tremendous amount of research, very little in the form of social network analysis has been utilized to study the problem. This…

  18. "I Gave up MySpace for Lent": New Teachers and Social Networking Sites

    Science.gov (United States)

    Kist, William

    2008-01-01

    This Digital Literacies column describes the dilemma many new teachers feel as their uses of social networking sites pose conflicts with institutional cautions regarding educators' participation in these kinds of online activities. Pre-service teachers discuss the challenges of marrying their own out-of-school literacies to mandated professional…

  19. CONCERNING THE NETWORKING INTERACTION EXPERIENCE OF TEACHERS AND STUDENTS OF PEDAGOGICAL UNIVERSITY

    Directory of Open Access Journals (Sweden)

    E. A. Dmitrieva

    2015-01-01

    Full Text Available The purpose of the research is to identify the possibilities for the formation knowledge and practical skills related to the use of the professional activity of software and network resource of teaching communities in the pedagogical sphere.Methods. The methods involve the analysis of the literary sources, regulatory documents, Internet resources within the researched problem; an analysis of the practical experience of teachers of secondary schools, work of high school teachers and establishment of training teachers on the research problem; the experimental work and monitoring the learning process.Results. The process of teachers’ training inYaroslavl, in particular preparation of students-biologists at theYaroslavlStatePedagogicalUniversityis reflected. Activity of network pedagogical community of Yaroslavl is considered as a platform for network interaction; the analysis of such platform, use of its resources, and also conversations with subject teachers and students have shown that the given electronic and communication resources cause a great interest for practicing teachers and future experts, however, they not always possess necessary knowledge and abilities concerning its operation.Scientific novelty. The author describes in detail the process of forming a competence of networking of professional interaction in terms of its methodological support that is relevant to the educational process, both in the high school, and post-graduate education.Practical significance. The research implementations can be useful while developing specific guidelines to explain the content and methodology of the training network of professional interaction with examples of practicing teachers and students ofPedagogicalUniversity– future teachers of biology.The article is addressed to researchers, dealing with networking, specialists of teaching service centers (institutions of educational development, the practicing subject teachers and teachers of high

  20. Genome-scale reconstruction of the sigma factor network in Escherichia coli: topology and functional states

    DEFF Research Database (Denmark)

    Cho, Byung-Kwan; Kim, Donghyuk; Knight, Eric M.

    2014-01-01

    to transcription units (TUs), representing an increase of more than 300% over what has been previously reported. The reconstructed network was used to investigate competition between alternative sigma-factors (the sigma(70) and sigma(38) regulons), confirming the competition model of sigma substitution......Background: At the beginning of the transcription process, the RNA polymerase (RNAP) core enzyme requires a sigma-factor to recognize the genomic location at which the process initiates. Although the crucial role of sigma-factors has long been appreciated and characterized for many individual...... promoters, we do not yet have a genome-scale assessment of their function. Results: Using multiple genome-scale measurements, we elucidated the network of s-factor and promoter interactions in Escherichia coli. The reconstructed network includes 4,724 sigma-factor-specific promoters corresponding...

  1. Learning causal networks with latent variables from multivariate information in genomic data.

    Science.gov (United States)

    Verny, Louis; Sella, Nadir; Affeldt, Séverine; Singh, Param Priya; Isambert, Hervé

    2017-10-02

    Learning causal networks from large-scale genomic data remains challenging in absence of time series or controlled perturbation experiments. We report an information- theoretic method which learns a large class of causal or non-causal graphical models from purely observational data, while including the effects of unobserved latent variables, commonly found in many genomic datasets. Starting from a complete graph, the method iteratively removes dispensable edges, by uncovering significant information contributions from indirect paths, and assesses edge-specific confidences from randomization of available data. The remaining edges are then oriented based on the signature of causality in observational data. The approach and associated algorithm, miic, outperform earlier methods on a broad range of benchmark networks. Causal network reconstructions are presented at different biological size and time scales, from gene regulation in single cells to whole genome duplication in tumor development as well as long term evolution of vertebrates. Miic is publicly available at https://github.com/miicTeam/MIIC.

  2. Comparative genomic reconstruction of transcriptional networks controlling central metabolism in the Shewanella genus

    Energy Technology Data Exchange (ETDEWEB)

    Rodionov, Dmitry A.; Novichkov, Pavel; Stavrovskaya, Elena D.; Rodionova, Irina A.; Li, Xiaoqing; Kazanov, Marat D.; Ravcheev, Dmitry A.; Gerasimova, Anna V.; Kazakov, Alexey E.; Kovaleva, Galina Y.; Permina, Elizabeth A.; Laikova, Olga N.; Overbeek, Ross; Romine, Margaret F.; Fredrickson, Jim K.; Arkin, Adam P.; Dubchak, Inna; Osterman, Andrei L.; Gelfand, Mikhail S.

    2011-06-15

    Genome-scale prediction of gene regulation and reconstruction of transcriptional regulatory networks in bacteria is one of the critical tasks of modern genomics. Despite the growing number of genome-scale gene expression studies, our abilities to convert the results of these studies into accurate regulatory annotations and to project them from model to other organisms are extremely limited. The comparative genomics approaches and computational identification of regulatory sites are useful for the in silico reconstruction of transcriptional regulatory networks in bacteria. The Shewanella genus is comprised of metabolically versatile gamma-proteobacteria, whose lifestyles and natural environments are substantially different from Escherichia coli and other model bacterial species. To explore conservation and variations in the Shewanella transcriptional networks we analyzed the repertoire of transcription factors and performed genomics-based reconstruction and comparative analysis of regulons in 16 Shewanella genomes. The inferred regulatory network includes 82 transcription factors and their DNA binding sites, 8 riboswitches and 6 translational attenuators. Forty five regulons were newly inferred from the genome context analysis, whereas others were propagated from previously characterized regulons in the Enterobacteria and Pseudomonas spp.. However, even orthologous regulators with conserved DNA-binding motifs may control substantially different gene sets, revealing striking differences in regulatory strategies between the Shewanella spp. and E. coli. Multiple examples of regulatory network rewiring include regulon contraction and expansion (as in the case of PdhR, HexR, FadR), and numerous cases of recruiting non-orthologous regulators to control equivalent pathways (e.g. NagR for N-acetylglucosamine catabolism and PsrA for fatty acid degradation) and, conversely, orthologous regulators to control distinct pathways (e.g. TyrR, ArgR, Crp).

  3. In Silico Genome-Scale Reconstruction and Validation of the Corynebacterium glutamicum Metabolic Network

    DEFF Research Database (Denmark)

    Kjeldsen, Kjeld Raunkjær; Nielsen, J.

    2009-01-01

    A genome-scale metabolic model of the Gram-positive bacteria Corynebacterium glutamicum ATCC 13032 was constructed comprising 446 reactions and 411 metabolite, based on the annotated genome and available biochemical information. The network was analyzed using constraint based methods. The model...... and lactate. Comparable flux values between in silico model and experimental values were seen, although some differences in the phenotypic behavior between the model and the experimental data were observed,...

  4. A call for an international network of genomic observatories (GOs

    Directory of Open Access Journals (Sweden)

    Davies Neil

    2012-07-01

    Full Text Available Abstract We are entering a new era in genomics–that of large-scale, place-based, highly contextualized genomic research. Here we review this emerging paradigm shift and suggest that sites of utmost scientific importance be expanded into ‘Genomic Observatories’ (GOs. Investment in GOs should focus on the digital characterization of whole ecosystems, from all-taxa biotic inventories to time-series ’omics studies. The foundational layer of biodiversity–genetic variation–would thus be mainstreamed into Earth Observation systems enabling predictive modelling of biodiversity dynamics and resultant impacts on ecosystem services.

  5. Evolution of Intra-specific Regulatory Networks in a Multipartite Bacterial Genome.

    Directory of Open Access Journals (Sweden)

    Marco Galardini

    2015-09-01

    Full Text Available Reconstruction of the regulatory network is an important step in understanding how organisms control the expression of gene products and therefore phenotypes. Recent studies have pointed out the importance of regulatory network plasticity in bacterial adaptation and evolution. The evolution of such networks within and outside the species boundary is however still obscure. Sinorhizobium meliloti is an ideal species for such study, having three large replicons, many genomes available and a significant knowledge of its transcription factors (TF. Each replicon has a specific functional and evolutionary mark; which might also emerge from the analysis of their regulatory signatures. Here we have studied the plasticity of the regulatory network within and outside the S. meliloti species, looking for the presence of 41 TFs binding motifs in 51 strains and 5 related rhizobial species. We have detected a preference of several TFs for one of the three replicons, and the function of regulated genes was found to be in accordance with the overall replicon functional signature: house-keeping functions for the chromosome, metabolism for the chromid, symbiosis for the megaplasmid. This therefore suggests a replicon-specific wiring of the regulatory network in the S. meliloti species. At the same time a significant part of the predicted regulatory network is shared between the chromosome and the chromid, thus adding an additional layer by which the chromid integrates itself in the core genome. Furthermore, the regulatory network distance was found to be correlated with both promoter regions and accessory genome evolution inside the species, indicating that both pangenome compartments are involved in the regulatory network evolution. We also observed that genes which are not included in the species regulatory network are more likely to belong to the accessory genome, indicating that regulatory interactions should also be considered to predict gene conservation in

  6. Evolution of Intra-specific Regulatory Networks in a Multipartite Bacterial Genome.

    Science.gov (United States)

    Galardini, Marco; Brilli, Matteo; Spini, Giulia; Rossi, Matteo; Roncaglia, Bianca; Bani, Alessia; Chiancianesi, Manuela; Moretto, Marco; Engelen, Kristof; Bacci, Giovanni; Pini, Francesco; Biondi, Emanuele G; Bazzicalupo, Marco; Mengoni, Alessio

    2015-09-01

    Reconstruction of the regulatory network is an important step in understanding how organisms control the expression of gene products and therefore phenotypes. Recent studies have pointed out the importance of regulatory network plasticity in bacterial adaptation and evolution. The evolution of such networks within and outside the species boundary is however still obscure. Sinorhizobium meliloti is an ideal species for such study, having three large replicons, many genomes available and a significant knowledge of its transcription factors (TF). Each replicon has a specific functional and evolutionary mark; which might also emerge from the analysis of their regulatory signatures. Here we have studied the plasticity of the regulatory network within and outside the S. meliloti species, looking for the presence of 41 TFs binding motifs in 51 strains and 5 related rhizobial species. We have detected a preference of several TFs for one of the three replicons, and the function of regulated genes was found to be in accordance with the overall replicon functional signature: house-keeping functions for the chromosome, metabolism for the chromid, symbiosis for the megaplasmid. This therefore suggests a replicon-specific wiring of the regulatory network in the S. meliloti species. At the same time a significant part of the predicted regulatory network is shared between the chromosome and the chromid, thus adding an additional layer by which the chromid integrates itself in the core genome. Furthermore, the regulatory network distance was found to be correlated with both promoter regions and accessory genome evolution inside the species, indicating that both pangenome compartments are involved in the regulatory network evolution. We also observed that genes which are not included in the species regulatory network are more likely to belong to the accessory genome, indicating that regulatory interactions should also be considered to predict gene conservation in bacterial

  7. University-School Collaborative Networks: A Strategy to Improve the Professional Skills of Future Teachers

    Directory of Open Access Journals (Sweden)

    Rosario Mérida Serrano

    2012-01-01

    Full Text Available This paper presents an experiment in teaching innovation developed at the University of Cordoba's Faculty of Education (Spain, in the second year of the Infant Education Teacher Training course, within the subject of general didactics. The innovative approach taken focused on setting up a collaborative network between infants' schools and the university. Taking Project Work as the central axis, a learning network has been built with the participation of sixteen Infant Education teachers, three hundred twenty children from this stage, seven university teachers, eighty-five trainee teachers, and two Infant Education advisers from a continuing professional development centre for teachers. The theoretical foundations that support this experiment are described along with their different stages, evaluating the benefits of each of them in facilitating the acquisition of professional competences among university students.

  8. A System for Predicting Subcellular Localization of Yeast Genome Using Neural Network

    CERN Document Server

    Thampi, Sabu M

    2007-01-01

    The subcellular location of a protein can provide valuable information about its function. With the rapid increase of sequenced genomic data, the need for an automated and accurate tool to predict subcellular localization becomes increasingly important. Many efforts have been made to predict protein subcellular localization. This paper aims to merge the artificial neural networks and bioinformatics to predict the location of protein in yeast genome. We introduce a new subcellular prediction method based on a backpropagation neural network. The results show that the prediction within an error limit of 5 to 10 percentage can be achieved with the system.

  9. The Social Fabric of Elementary Schools: A Network Typology of Social Interaction among Teachers

    Science.gov (United States)

    Moolenaar, Nienke M.; Sleegers, Peter J. C.; Karsten, Sjoerd; Daly, Alan J.

    2012-01-01

    While researchers are currently studying various forms of social network interaction among teachers for their impact on educational policy implementation and practice, knowledge on how various types of networks are interrelated is limited. The goal of this study is to understand the dimensionality that may underlie various types of social networks…

  10. Investigation of Social Studies Teachers' Intended Uses of Social Networks in Terms of Various Variables

    Science.gov (United States)

    Akgün, Ismail Hakan

    2016-01-01

    The aim of this research is to determine Social Studies teacher candidates' intended uses of social networks in terms of various variables. The research was carried out by using screening model of quantitative research methods. In the study, "The Social Network Intended Use Scale" was used as a data collection tool. As a result of the…

  11. A Social Network Perspective on Teacher Collaboration in Schools: Theory, Methodology, and Applications

    Science.gov (United States)

    Moolenaar, Nienke M.

    2012-01-01

    An emerging trend in educational research is the use of social network theory and methodology to understand how teacher collaboration can support or constrain teaching, learning, and educational change. This article provides a critical synthesis of educational literature on school social networks among educators to advance our understanding of the…

  12. The Sol Genomics Network (SGN)—from genotype to phenotype to breeding

    Science.gov (United States)

    Fernandez-Pozo, Noe; Menda, Naama; Edwards, Jeremy D.; Saha, Surya; Tecle, Isaak Y.; Strickler, Susan R.; Bombarely, Aureliano; Fisher-York, Thomas; Pujar, Anuradha; Foerster, Hartmut; Yan, Aimin; Mueller, Lukas A.

    2015-01-01

    The Sol Genomics Network (SGN, http://solgenomics.net) is a web portal with genomic and phenotypic data, and analysis tools for the Solanaceae family and close relatives. SGN hosts whole genome data for an increasing number of Solanaceae family members including tomato, potato, pepper, eggplant, tobacco and Nicotiana benthamiana. The database also stores loci and phenotype data, which researchers can upload and edit with user-friendly web interfaces. Tools such as BLAST, GBrowse and JBrowse for browsing genomes, expression and map data viewers, a locus community annotation system and a QTL analysis tools are available. A new tool was recently implemented to improve Virus-Induced Gene Silencing (VIGS) constructs called the SGN VIGS tool. With the growing genomic and phenotypic data in the database, SGN is now advancing to develop new web-based breeding tools and implement the code and database structure for other species or clade-specific databases. PMID:25428362

  13. Cycling Transcriptional Networks Optimize Energy Utilization on a Genome Scale.

    Science.gov (United States)

    Wang, Guang-Zhong; Hickey, Stephanie L; Shi, Lei; Huang, Hung-Chung; Nakashe, Prachi; Koike, Nobuya; Tu, Benjamin P; Takahashi, Joseph S; Konopka, Genevieve

    2015-12-01

    Genes expressing circadian RNA rhythms are enriched for metabolic pathways, but the adaptive significance of cyclic gene expression remains unclear. We estimated the genome-wide synthetic and degradative cost of transcription and translation in three organisms and found that the cost of cycling genes is strikingly higher compared to non-cycling genes. Cycling genes are expressed at high levels and constitute the most costly proteins to synthesize in the genome. We demonstrate that metabolic cycling is accelerated in yeast grown under higher nutrient flux and the number of cycling genes increases ∼40%, which are achieved by increasing the amplitude and not the mean level of gene expression. These results suggest that rhythmic gene expression optimizes the metabolic cost of global gene expression and that highly expressed genes have been selected to be downregulated in a cyclic manner for energy conservation.

  14. CCor: A whole genome network-based similarity measure between two genes.

    Science.gov (United States)

    Hu, Yiming; Zhao, Hongyu

    2016-12-01

    Measuring the similarity between genes is often the starting point for building gene regulatory networks. Most similarity measures used in practice only consider pairwise information with a few also consider network structure. Although theoretical properties of pairwise measures are well understood in the statistics literature, little is known about their statistical properties of those similarity measures based on network structure. In this article, we consider a new whole genome network-based similarity measure, called CCor, that makes use of information of all the genes in the network. We derive a concentration inequality of CCor and compare it with the commonly used Pearson correlation coefficient for inferring network modules. Both theoretical analysis and real data example demonstrate the advantages of CCor over existing measures for inferring gene modules.

  15. A mixed-integer linear programming approach to the reduction of genome-scale metabolic networks.

    Science.gov (United States)

    Röhl, Annika; Bockmayr, Alexander

    2017-01-03

    Constraint-based analysis has become a widely used method to study metabolic networks. While some of the associated algorithms can be applied to genome-scale network reconstructions with several thousands of reactions, others are limited to small or medium-sized models. In 2015, Erdrich et al. introduced a method called NetworkReducer, which reduces large metabolic networks to smaller subnetworks, while preserving a set of biological requirements that can be specified by the user. Already in 2001, Burgard et al. developed a mixed-integer linear programming (MILP) approach for computing minimal reaction sets under a given growth requirement. Here we present an MILP approach for computing minimum subnetworks with the given properties. The minimality (with respect to the number of active reactions) is not guaranteed by NetworkReducer, while the method by Burgard et al. does not allow specifying the different biological requirements. Our procedure is about 5-10 times faster than NetworkReducer and can enumerate all minimum subnetworks in case there exist several ones. This allows identifying common reactions that are present in all subnetworks, and reactions appearing in alternative pathways. Applying complex analysis methods to genome-scale metabolic networks is often not possible in practice. Thus it may become necessary to reduce the size of the network while keeping important functionalities. We propose a MILP solution to this problem. Compared to previous work, our approach is more efficient and allows computing not only one, but even all minimum subnetworks satisfying the required properties.

  16. Genome-wide system analysis reveals stable yet flexible network dynamics in yeast.

    Science.gov (United States)

    Gustafsson, M; Hörnquist, M; Björkegren, J; Tegnér, J

    2009-07-01

    Recently, important insights into static network topology for biological systems have been obtained, but still global dynamical network properties determining stability and system responsiveness have not been accessible for analysis. Herein, we explore a genome-wide gene-to-gene regulatory network based on expression data from the cell cycle in Saccharomyces cerevisae (budding yeast). We recover static properties like hubs (genes having several out-going connections), network motifs and modules, which have previously been derived from multiple data sources such as whole-genome expression measurements, literature mining, protein-protein and transcription factor binding data. Further, our analysis uncovers some novel dynamical design principles; hubs are both repressed and repressors, and the intra-modular dynamics are either strongly activating or repressing whereas inter-modular couplings are weak. Finally, taking advantage of the inferred strength and direction of all interactions, we perform a global dynamical systems analysis of the network. Our inferred dynamics of hubs, motifs and modules produce a more stable network than what is expected given randomised versions. The main contribution of the repressed hubs is to increase system stability, while higher order dynamic effects (e.g. module dynamics) mainly increase system flexibility. Altogether, the presence of hubs, motifs and modules induce few flexible modes, to which the network is extra sensitive to an external signal. We believe that our approach, and the inferred biological mode of strong flexibility and stability, will also apply to other cellular networks and adaptive systems.

  17. Novice ESOL Teachers' Perceptions of Social Support Networks

    Science.gov (United States)

    Brannan, Debi; Bleistein, Tasha

    2012-01-01

    As new teachers navigate the challenging first years of work, they need positive support providers (Villani, 2002). The impact of support providers on novice educators' beliefs about teaching efficacy previously went unexplored. This study examined novice English to speakers of other languages (ESOL) teachers' perceptions of social support and…

  18. Bread Loaf Rural Teacher Network: A Portable Community.

    Science.gov (United States)

    Active Learner: A Foxfire Journal for Teachers, 1998

    1998-01-01

    The experiences of two teachers describe how BreadNet, an online professional-development and educational conference, enables teachers with similar interests to work together and maintain a sense of community. BreadNet allowed their rural schools to participate in projects with distant schools, leading to improvements in the quantity and quality…

  19. Preferential duplication of intermodular hub genes: an evolutionary signature in eukaryotes genome networks.

    Directory of Open Access Journals (Sweden)

    Ricardo M Ferreira

    Full Text Available Whole genome protein-protein association networks are not random and their topological properties stem from genome evolution mechanisms. In fact, more connected, but less clustered proteins are related to genes that, in general, present more paralogs as compared to other genes, indicating frequent previous gene duplication episodes. On the other hand, genes related to conserved biological functions present few or no paralogs and yield proteins that are highly connected and clustered. These general network characteristics must have an evolutionary explanation. Considering data from STRING database, we present here experimental evidence that, more than not being scale free, protein degree distributions of organisms present an increased probability for high degree nodes. Furthermore, based on this experimental evidence, we propose a simulation model for genome evolution, where genes in a network are either acquired de novo using a preferential attachment rule, or duplicated with a probability that linearly grows with gene degree and decreases with its clustering coefficient. For the first time a model yields results that simultaneously describe different topological distributions. Also, this model correctly predicts that, to produce protein-protein association networks with number of links and number of nodes in the observed range for Eukaryotes, it is necessary 90% of gene duplication and 10% of de novo gene acquisition. This scenario implies a universal mechanism for genome evolution.

  20. Regulatory Network Construction in Arabidopsis using genome-wide gene expression QTLs

    NARCIS (Netherlands)

    Keurentjes, J.J.B.; Fu, J.J.; Terpstra, I.R.; Garcia, J.M.; van den Ackerveken, G.; Snoek, L.B.; Peeters, A.J.M.; Vreugdenhil, D.; Koornreef, M.; Jansen, R.C.

    2007-01-01

    Regulatory network construction in Arabidopsis by using genome-wide gene expression quantitative trait loci.Keurentjes JJ, Fu J, Terpstra IR, Garcia JM, van den Ackerveken G, Snoek LB, Peeters AJ, Vreugdenhil D, Koornneef M, Jansen RC. Laboratory of Genetics, Wageningen University, Arboretumlaan 4,

  1. Genomic analysis of the hierarchical structure of regulatory networks

    Science.gov (United States)

    Yu, Haiyuan; Gerstein, Mark

    2006-01-01

    A fundamental question in biology is how the cell uses transcription factors (TFs) to coordinate the expression of thousands of genes in response to various stimuli. The relationships between TFs and their target genes can be modeled in terms of directed regulatory networks. These relationships, in turn, can be readily compared with commonplace “chain-of-command” structures in social networks, which have characteristic hierarchical layouts. Here, we develop algorithms for identifying generalized hierarchies (allowing for various loop structures) and use these approaches to illuminate extensive pyramid-shaped hierarchical structures existing in the regulatory networks of representative prokaryotes (Escherichia coli) and eukaryotes (Saccharomyces cerevisiae), with most TFs at the bottom levels and only a few master TFs on top. These masters are situated near the center of the protein–protein interaction network, a different type of network from the regulatory one, and they receive most of the input for the whole regulatory hierarchy through protein interactions. Moreover, they have maximal influence over other genes, in terms of affecting expression-level changes. Surprisingly, however, TFs at the bottom of the regulatory hierarchy are more essential to the viability of the cell. Finally, one might think master TFs achieve their wide influence through directly regulating many targets, but TFs with most direct targets are in the middle of the hierarchy. We find, in fact, that these midlevel TFs are “control bottlenecks” in the hierarchy, and this great degree of control for “middle managers” has parallels in efficient social structures in various corporate and governmental settings. PMID:17003135

  2. Collaborating on Facebook: Teachers Exchanging Experiences Through Social Networking Sites

    Directory of Open Access Journals (Sweden)

    da Cunha Júnior F.,

    2016-12-01

    Full Text Available This study explores the use of Facebook for educational purposes, as a collaborative online space for enabling communication among teachers from different schools. The article describes how a group of 43 teachers on Facebook, from various schools in the southeast region of Brazil used a group on Facebook as a collaborative space for communicating among each other. On the group, these teachers shared experiences about the use of digital technologies in their secondary education classes. This study is based on Cultural Historical Activity Theory, considering the group on Facebook as a tool for mediating communication . The objective of this study is to explore why and how teachers collaborated with each other on Facebook, and to study how communication among them evolved in the process. We examined the posts on that group from 2012 to 2014, and two questionnaires responded online by the teachers in June 2012 and in December 2013. Our findings suggest that teachers tend to critically collaborate in smaller groups and that further online communication evolved outside the group of teachers, with the creation of smaller groups on Facebook inside their schools.

  3. Mapping the structure and dynamics of genomics-related MeSH terms complex networks.

    Science.gov (United States)

    Siqueiros-García, Jesús M; Hernández-Lemus, Enrique; García-Herrera, Rodrigo; Robina-Galatas, Andrea

    2014-01-01

    It has been proposed that the history and evolution of scientific ideas may reflect certain aspects of the underlying socio-cognitive frameworks in which science itself is developing. Systematic analyses of the development of scientific knowledge may help us to construct models of the collective dynamics of science. Aiming at scientific rigor, these models should be built upon solid empirical evidence, analyzed with formal tools leading to ever-improving results that support the related conclusions. Along these lines we studied the dynamics and structure of the development of research in genomics as represented by the entire collection of genomics-related scientific papers contained in the PubMed database. The analyzed corpus consisted in more than 49,000 articles published in the years 1987 (first appearance of the term Genomics) to 2011, categorized by means of the Medical Subheadings (MeSH) content-descriptors. Complex networks were built where two MeSH terms were connected if they are descriptors of the same article(s). The analysis of such networks revealed a complex structure and dynamics that to certain extent resembled small-world networks. The evolution of such networks in time reflected interesting phenomena in the historical development of genomic research, including what seems to be a phase-transition in a period marked by the completion of the first draft of the Human Genome Project. We also found that different disciplinary areas have different dynamic evolution patterns in their MeSH connectivity networks. In the case of areas related to science, changes in topology were somewhat fast while retaining a certain core-structure, whereas in the humanities, the evolution was pretty slow and the structure resulted highly redundant and in the case of technology related issues, the evolution was very fast and the structure remained tree-like with almost no overlapping terms.

  4. Mapping the structure and dynamics of genomics-related MeSH terms complex networks.

    Directory of Open Access Journals (Sweden)

    Jesús M Siqueiros-García

    Full Text Available It has been proposed that the history and evolution of scientific ideas may reflect certain aspects of the underlying socio-cognitive frameworks in which science itself is developing. Systematic analyses of the development of scientific knowledge may help us to construct models of the collective dynamics of science. Aiming at scientific rigor, these models should be built upon solid empirical evidence, analyzed with formal tools leading to ever-improving results that support the related conclusions. Along these lines we studied the dynamics and structure of the development of research in genomics as represented by the entire collection of genomics-related scientific papers contained in the PubMed database. The analyzed corpus consisted in more than 49,000 articles published in the years 1987 (first appearance of the term Genomics to 2011, categorized by means of the Medical Subheadings (MeSH content-descriptors. Complex networks were built where two MeSH terms were connected if they are descriptors of the same article(s. The analysis of such networks revealed a complex structure and dynamics that to certain extent resembled small-world networks. The evolution of such networks in time reflected interesting phenomena in the historical development of genomic research, including what seems to be a phase-transition in a period marked by the completion of the first draft of the Human Genome Project. We also found that different disciplinary areas have different dynamic evolution patterns in their MeSH connectivity networks. In the case of areas related to science, changes in topology were somewhat fast while retaining a certain core-structure, whereas in the humanities, the evolution was pretty slow and the structure resulted highly redundant and in the case of technology related issues, the evolution was very fast and the structure remained tree-like with almost no overlapping terms.

  5. Genome Neighborhood Network Reveals Insights into Enediyne Biosynthesis and Facilitates Prediction and Prioritization for Discovery

    Science.gov (United States)

    Rudolf, Jeffrey D.; Yan, Xiaohui; Shen, Ben

    2015-01-01

    The enediynes are one of the most fascinating families of bacterial natural products given their unprecedented molecular architecture and extraordinary cytotoxicity. Enediynes are rare with only 11 structurally characterized members and four additional members isolated in their cycloaromatized form. Recent advances in DNA sequencing have resulted in an explosion of microbial genomes. A virtual survey of the GenBank and JGI genome databases revealed 87 enediyne biosynthetic gene clusters from 78 bacteria strains, implying enediynes are more common than previously thought. Here we report the construction and analysis of an enediyne genome neighborhood network (GNN) as a high-throughput approach to analyze secondary metabolite gene clusters. Analysis of the enediyne GNN facilitated rapid gene cluster annotation, revealed genetic trends in enediyne biosynthetic gene clusters resulting in a simple prediction scheme to determine 9- vs 10-membered enediyne gene clusters, and supported a genomic-based strain prioritization method for enediyne discovery. PMID:26318027

  6. Genome-wide analyses for dissecting gene regulatory networks in the shoot apical meristem.

    Science.gov (United States)

    Bustamante, Mariana; Matus, José Tomás; Riechmann, José Luis

    2016-03-01

    Shoot apical meristem activity is controlled by complex regulatory networks in which components such as transcription factors, miRNAs, small peptides, hormones, enzymes and epigenetic marks all participate. Many key genes that determine the inherent characteristics of the shoot apical meristem have been identified through genetic approaches. Recent advances in genome-wide studies generating extensive transcriptomic and DNA-binding datasets have increased our understanding of the interactions within the regulatory networks that control the activity of the meristem, identifying new regulators and uncovering connections between previously unlinked network components. In this review, we focus on recent studies that illustrate the contribution of whole genome analyses to understand meristem function. © The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

  7. Deciphering primordial cyanobacterial genome functions from protein network analysis.

    Science.gov (United States)

    Harel, Arye; Karkar, Slim; Cheng, Shu; Falkowski, Paul G; Bhattacharya, Debashish

    2015-03-02

    The Great Oxidation Event (GOE) ∼2.4 billion years ago resulted from the accumulation of oxygen by the ancestors of cyanobacteria [1-3]. Cyanobacteria continue to play a significant role in primary production [4] and in regulating the global marine and limnic nitrogen cycles [5, 6]. Relatively little is known, however, about the evolutionary history and gene content of primordial cyanobacteria [7, 8]. To address these issues, we used protein similarity networks [9], containing proteomes from 48 cyanobacteria as the test group, and reference proteomes from 84 microbes representing four distinct metabolic groups from most reducing to most oxidizing: methanogens, obligate anaerobes (nonmethanogenic), facultative aerobes, and obligate aerobes. These four metabolic groups represent extant bioinformatic proxies for ancient redox chemistries, extending from an anoxic origin through the GOE and ultimately to obligate aerobes [10-13]. Analysis of the network metric degree showed a strong relationship between cyanobacteria and obligate anaerobes, from which cyanobacteria presumably arose, for core functions that include translation, photosynthesis, energy conservation, and environmental interactions. These data were used to reconstruct primordial functions in cyanobacteria that included nine gene families involved in photosynthesis, hydrogenases, and proteins involved in defense from environmental stress. The presence of 60% of these genes in both reaction center I (RC-I) and RC-II-type bacteria may be explained by selective loss of either RC in the evolutionary history of some photosynthetic lineages. Finally, the network reveals that cyanobacteria occupy a unique position among prokaryotes as a hub between anaerobes and obligate aerobes.

  8. Genome network medicine: innovation to overcome huge challenges in cancer therapy.

    Science.gov (United States)

    Roukos, Dimitrios H

    2014-01-01

    The post-ENCODE era shapes now a new biomedical research direction for understanding transcriptional and signaling networks driving gene expression and core cellular processes such as cell fate, survival, and apoptosis. Over the past half century, the Francis Crick 'central dogma' of single n gene/protein-phenotype (trait/disease) has defined biology, human physiology, disease, diagnostics, and drugs discovery. However, the ENCODE project and several other genomic studies using high-throughput sequencing technologies, computational strategies, and imaging techniques to visualize regulatory networks, provide evidence that transcriptional process and gene expression are regulated by highly complex dynamic molecular and signaling networks. This Focus article describes the linear experimentation-based limitations of diagnostics and therapeutics to cure advanced cancer and the need to move on from reductionist to network-based approaches. With evident a wide genomic heterogeneity, the power and challenges of next-generation sequencing (NGS) technologies to identify a patient's personal mutational landscape for tailoring the best target drugs in the individual patient are discussed. However, the available drugs are not capable of targeting aberrant signaling networks and research on functional transcriptional heterogeneity and functional genome organization is poorly understood. Therefore, the future clinical genome network medicine aiming at overcoming multiple problems in the new fields of regulatory DNA mapping, noncoding RNA, enhancer RNAs, and dynamic complexity of transcriptional circuitry are also discussed expecting in new innovation technology and strong appreciation of clinical data and evidence-based medicine. The problematic and potential solutions in the discovery of next-generation, molecular, and signaling circuitry-based biomarkers and drugs are explored.

  9. TIGER: Toolbox for integrating genome-scale metabolic models, expression data, and transcriptional regulatory networks

    Directory of Open Access Journals (Sweden)

    Jensen Paul A

    2011-09-01

    Full Text Available Abstract Background Several methods have been developed for analyzing genome-scale models of metabolism and transcriptional regulation. Many of these methods, such as Flux Balance Analysis, use constrained optimization to predict relationships between metabolic flux and the genes that encode and regulate enzyme activity. Recently, mixed integer programming has been used to encode these gene-protein-reaction (GPR relationships into a single optimization problem, but these techniques are often of limited generality and lack a tool for automating the conversion of rules to a coupled regulatory/metabolic model. Results We present TIGER, a Toolbox for Integrating Genome-scale Metabolism, Expression, and Regulation. TIGER converts a series of generalized, Boolean or multilevel rules into a set of mixed integer inequalities. The package also includes implementations of existing algorithms to integrate high-throughput expression data with genome-scale models of metabolism and transcriptional regulation. We demonstrate how TIGER automates the coupling of a genome-scale metabolic model with GPR logic and models of transcriptional regulation, thereby serving as a platform for algorithm development and large-scale metabolic analysis. Additionally, we demonstrate how TIGER's algorithms can be used to identify inconsistencies and improve existing models of transcriptional regulation with examples from the reconstructed transcriptional regulatory network of Saccharomyces cerevisiae. Conclusion The TIGER package provides a consistent platform for algorithm development and extending existing genome-scale metabolic models with regulatory networks and high-throughput data.

  10. New approach for phylogenetic tree recovery based on genome-scale metabolic networks.

    Science.gov (United States)

    Gamermann, Daniel; Montagud, Arnaud; Conejero, J Alberto; Urchueguía, Javier F; de Córdoba, Pedro Fernández

    2014-07-01

    A wide range of applications and research has been done with genome-scale metabolic models. In this work, we describe an innovative methodology for comparing metabolic networks constructed from genome-scale metabolic models and how to apply this comparison in order to infer evolutionary distances between different organisms. Our methodology allows a quantification of the metabolic differences between different species from a broad range of families and even kingdoms. This quantification is then applied in order to reconstruct phylogenetic trees for sets of various organisms.

  11. Dissecting the brown adipogenic regulatory network using integrative genomics

    Science.gov (United States)

    Pradhan, Rachana N.; Bues, Johannes J.; Gardeux, Vincent; Schwalie, Petra C.; Alpern, Daniel; Chen, Wanze; Russeil, Julie; Raghav, Sunil K.; Deplancke, Bart

    2017-01-01

    Brown adipocytes regulate energy expenditure via mitochondrial uncoupling, which makes them attractive therapeutic targets to tackle obesity. However, the regulatory mechanisms underlying brown adipogenesis are still poorly understood. To address this, we profiled the transcriptome and chromatin state during mouse brown fat cell differentiation, revealing extensive gene expression changes and chromatin remodeling, especially during the first day post-differentiation. To identify putatively causal regulators, we performed transcription factor binding site overrepresentation analyses in active chromatin regions and prioritized factors based on their expression correlation with the bona-fide brown adipogenic marker Ucp1 across multiple mouse and human datasets. Using loss-of-function assays, we evaluated both the phenotypic effect as well as the transcriptomic impact of several putative regulators on the differentiation process, uncovering ZFP467, HOXA4 and Nuclear Factor I A (NFIA) as novel transcriptional regulators. Of these, NFIA emerged as the regulator yielding the strongest molecular and cellular phenotypes. To examine its regulatory function, we profiled the genomic localization of NFIA, identifying it as a key early regulator of terminal brown fat cell differentiation. PMID:28181539

  12. Developing a workable teacher identity: Building and negotiating identity within a professional network

    Science.gov (United States)

    Rostock, Roseanne

    The challenge of attracting and retaining the next generation of teachers who are skilled and committed to meeting the growing demands of the profession is of increasing concern to researchers and policy makers, particularly since 45--50% of beginning teachers leave the profession within five years (Ingersoll & Smith, 2003). Reasons for such attrition include compensation, status and working conditions; however, there is growing evidence that a critical factor in new teacher retention hinges on teachers' ability to accomplish the difficult task of forming a workable professional identity in the midst of competing discourses about teaching (Alsup, 2006; Britzman, 2003). There is little research on professional identity development among those beginning teachers at highest risk for attrition (secondary math and science teachers, and those with strong academic backgrounds). This study explores the professional identity development of early-career math and science teachers who are part of the Knowles Science Teaching Foundation's (KSTF) teaching fellowship program, an external support network that aims to address many of the issues leading to high attrition among this particular population of teachers. Using narrative research methods, I examine three case studies of beginning teachers, exploring how they construct professional identity in relation to various discourse communities and negotiate tensions across multiple discourses. The cases identify both dominant discourses and counter-discourses that the teachers draw upon for important identity development resources. They also demonstrate that the way a teacher manages tensions across competing discourses is important to how well one can negotiate a workable professional identity. In particular, they emphasize the importance of engaging in borderland discourses (Gee, 1996) as a way of taking agency in one's own identity development as well as in transforming one's discourse communities. These cases shed light on how

  13. A New Addiction for Teacher Candidates: Social Networks

    Science.gov (United States)

    Cam, Emre; Isbulan, Onur

    2012-01-01

    With the transition to being a knowledge-based society, the internet usage has become an irreplaceable part of life. As socials networks have come into our lives, the internet usage has taken a different dimension. People can affiliate to social networks in order to make friends, exchange information, find partners, and to play games. The process…

  14. Lukasiewicz-Topos Models of Neural Networks, Cell Genome and Interactome Nonlinear Dynamic Models

    CERN Document Server

    Baianu, I C

    2004-01-01

    A categorical and Lukasiewicz-Topos framework for Lukasiewicz Algebraic Logic models of nonlinear dynamics in complex functional systems such as neural networks, genomes and cell interactomes is proposed. Lukasiewicz Algebraic Logic models of genetic networks and signaling pathways in cells are formulated in terms of nonlinear dynamic systems with n-state components that allow for the generalization of previous logical models of both genetic activities and neural networks. An algebraic formulation of variable 'next-state functions' is extended to a Lukasiewicz Topos with an n-valued Lukasiewicz Algebraic Logic subobject classifier description that represents non-random and nonlinear network activities as well as their transformations in developmental processes and carcinogenesis.

  15. Genomic connectivity networks based on the BrainSpan atlas of the developing human brain

    Science.gov (United States)

    Mahfouz, Ahmed; Ziats, Mark N.; Rennert, Owen M.; Lelieveldt, Boudewijn P. F.; Reinders, Marcel J. T.

    2014-03-01

    The human brain comprises systems of networks that span the molecular, cellular, anatomic and functional levels. Molecular studies of the developing brain have focused on elucidating networks among gene products that may drive cellular brain development by functioning together in biological pathways. On the other hand, studies of the brain connectome attempt to determine how anatomically distinct brain regions are connected to each other, either anatomically (diffusion tensor imaging) or functionally (functional MRI and EEG), and how they change over development. A global examination of the relationship between gene expression and connectivity in the developing human brain is necessary to understand how the genetic signature of different brain regions instructs connections to other regions. Furthermore, analyzing the development of connectivity networks based on the spatio-temporal dynamics of gene expression provides a new insight into the effect of neurodevelopmental disease genes on brain networks. In this work, we construct connectivity networks between brain regions based on the similarity of their gene expression signature, termed "Genomic Connectivity Networks" (GCNs). Genomic connectivity networks were constructed using data from the BrainSpan Transcriptional Atlas of the Developing Human Brain. Our goal was to understand how the genetic signatures of anatomically distinct brain regions relate to each other across development. We assessed the neurodevelopmental changes in connectivity patterns of brain regions when networks were constructed with genes implicated in the neurodevelopmental disorder autism (autism spectrum disorder; ASD). Using graph theory metrics to characterize the GCNs, we show that ASD-GCNs are relatively less connected later in development with the cerebellum showing a very distinct expression of ASD-associated genes compared to other brain regions.

  16. Teachers' Self-Initiated Professional Learning through Personal Learning Networks

    Science.gov (United States)

    Tour, Ekaterina

    2017-01-01

    It is widely acknowledged that to be able to teach language and literacy with digital technologies, teachers need to engage in relevant professional learning. Existing formal models of professional learning are often criticised for being ineffective. In contrast, informal and self-initiated forms of learning have been recently recognised as…

  17. Brokering Knowledge Mobilization Networks: Policy Reforms, Partnerships, and Teacher Education

    Science.gov (United States)

    Ng-A-Fook, Nicholas; Kane, Ruth G.; Butler, Jesse K.; Glithero, Lisa; Forte, Rita

    2015-01-01

    Educational researchers and policy-makers are now expected by funding agencies and their institutions to innovate the multi-directional ways in which our production of knowledge can impact the classrooms of teachers (practitioners), while also integrating their experiential knowledge into the landscape of our research. In this article, we draw on…

  18. Integration of expression data in genome-scale metabolic network reconstructions

    Directory of Open Access Journals (Sweden)

    Anna S. Blazier

    2012-08-01

    Full Text Available With the advent of high-throughput technologies, the field of systems biology has amassed an abundance of omics data, quantifying thousands of cellular components across a variety of scales, ranging from mRNA transcript levels to metabolite quantities. Methods are needed to not only integrate this omics data but to also use this data to heighten the predictive capabilities of computational models. Several recent studies have successfully demonstrated how flux balance analysis (FBA, a constraint-based modeling approach, can be used to integrate transcriptomic data into genome-scale metabolic network reconstructions to generate predictive computational models. In this review, we summarize such FBA-based methods for integrating expression data into genome-scale metabolic network reconstructions, highlighting their advantages as well as their limitations.

  19. Leveraging the Potential of Personal Learning Networks for Teacher Professional Development

    Science.gov (United States)

    Maloney, Katherine J.

    2016-01-01

    In times of exponential change, high quality, cost-effective teacher professional development is an urgent need that personal learning networks (PLNs) promise to address. The purpose of the qualitative case study was to (a) explore, understand, and describe how PreK-12 educators, who are members of The Educator's PLN and Classroom 2.0 communities,…

  20. An Interactive Communication Network's Potential as a Communication and Student Teacher Supervision Tool in Agricultural Education.

    Science.gov (United States)

    Miller, Greg; Miller, Wade; Kessell, John

    2002-01-01

    Eight student teachers received two onsite supervisory visits and one via the Iowa Communications Network (ICN); 11 received three onsite visits. ICN-facilitated supervision was thought to be equally effective and was viewed favorably. Prior experience with ICN influenced perceptions. ICN-facilitated supervision offered substantial cost savings.…

  1. An Implementation of a Twitter-Supported Personal Learning Network to Individualize Teacher Professional Development

    Science.gov (United States)

    Deyamport, W. H., III.

    2013-01-01

    In this action research study, eight teachers at an elementary school were trained in the use of Twitter to support the development of a personal learning network as a strategy to address non-differentiated professional development at the school. The main research question for this study was: In what ways, if any, can the use of a…

  2. The genome-scale metabolic extreme pathway structure in Haemophilus influenzae shows significant network redundancy.

    Science.gov (United States)

    Papin, Jason A; Price, Nathan D; Edwards, Jeremy S; Palsson B, Bernhard Ø

    2002-03-07

    Genome-scale metabolic networks can be characterized by a set of systemically independent and unique extreme pathways. These extreme pathways span a convex, high-dimensional space that circumscribes all potential steady-state flux distributions achievable by the defined metabolic network. Genome-scale extreme pathways associated with the production of non-essential amino acids in Haemophilus influenzae were computed. They offer valuable insight into the functioning of its metabolic network. Three key results were obtained. First, there were multiple internal flux maps corresponding to externally indistinguishable states. It was shown that there was an average of 37 internal states per unique exchange flux vector in H. influenzae when the network was used to produce a single amino acid while allowing carbon dioxide and acetate as carbon sinks. With the inclusion of succinate as an additional output, this ratio increased to 52, a 40% increase. Second, an analysis of the carbon fates illustrated that the extreme pathways were non-uniformly distributed across the carbon fate spectrum. In the detailed case study, 45% of the distinct carbon fate values associated with lysine production represented 85% of the extreme pathways. Third, this distribution fell between distinct systemic constraints. For lysine production, the carbon fate values that represented 85% of the pathways described above corresponded to only 2 distinct ratios of 1:1 and 4:1 between carbon dioxide and acetate. The present study analysed single outputs from one organism, and provides a start to genome-scale extreme pathways studies. These emergent system-level characterizations show the significance of metabolic extreme pathway analysis at the genome-scale.

  3. Comparative Genome-Scale Reconstruction of Gapless Metabolic Networks for Present and Ancestral Species

    Science.gov (United States)

    Pitkänen, Esa; Jouhten, Paula; Hou, Jian; Syed, Muhammad Fahad; Blomberg, Peter; Kludas, Jana; Oja, Merja; Holm, Liisa; Penttilä, Merja; Rousu, Juho; Arvas, Mikko

    2014-01-01

    We introduce a novel computational approach, CoReCo, for comparative metabolic reconstruction and provide genome-scale metabolic network models for 49 important fungal species. Leveraging on the exponential growth in sequenced genome availability, our method reconstructs genome-scale gapless metabolic networks simultaneously for a large number of species by integrating sequence data in a probabilistic framework. High reconstruction accuracy is demonstrated by comparisons to the well-curated Saccharomyces cerevisiae consensus model and large-scale knock-out experiments. Our comparative approach is particularly useful in scenarios where the quality of available sequence data is lacking, and when reconstructing evolutionary distant species. Moreover, the reconstructed networks are fully carbon mapped, allowing their use in 13C flux analysis. We demonstrate the functionality and usability of the reconstructed fungal models with computational steady-state biomass production experiment, as these fungi include some of the most important production organisms in industrial biotechnology. In contrast to many existing reconstruction techniques, only minimal manual effort is required before the reconstructed models are usable in flux balance experiments. CoReCo is available at http://esaskar.github.io/CoReCo/. PMID:24516375

  4. Comparative genome-scale reconstruction of gapless metabolic networks for present and ancestral species.

    Directory of Open Access Journals (Sweden)

    Esa Pitkänen

    2014-02-01

    Full Text Available We introduce a novel computational approach, CoReCo, for comparative metabolic reconstruction and provide genome-scale metabolic network models for 49 important fungal species. Leveraging on the exponential growth in sequenced genome availability, our method reconstructs genome-scale gapless metabolic networks simultaneously for a large number of species by integrating sequence data in a probabilistic framework. High reconstruction accuracy is demonstrated by comparisons to the well-curated Saccharomyces cerevisiae consensus model and large-scale knock-out experiments. Our comparative approach is particularly useful in scenarios where the quality of available sequence data is lacking, and when reconstructing evolutionary distant species. Moreover, the reconstructed networks are fully carbon mapped, allowing their use in 13C flux analysis. We demonstrate the functionality and usability of the reconstructed fungal models with computational steady-state biomass production experiment, as these fungi include some of the most important production organisms in industrial biotechnology. In contrast to many existing reconstruction techniques, only minimal manual effort is required before the reconstructed models are usable in flux balance experiments. CoReCo is available at http://esaskar.github.io/CoReCo/.

  5. Head teacher professional networks in Italy: preliminary results of a national survey

    Directory of Open Access Journals (Sweden)

    Maurissens Isabel de

    2016-06-01

    Full Text Available In this article, we present the preliminary results of a national survey conducted by INDIRE on head teachers communities and professional networks. About one-fourth of the total population of Italian public school leaders participated in the survey. One of the main intents of this research is to contribute to understanding of the phenomenon of professional networks frequented by school leaders and to pave the way for a further reflection on how to use such networks for head teachers’ training so as to support their daily professional practice conducted too often in isolation.

  6. Networks of Learning : Professional Association and the Continuing Education of Teachers of Mathematics in Pakistan

    DEFF Research Database (Denmark)

    Baber, Sikunder Ali

    . The formation and growth of this network can be viewed as developing insights into the improvement of mathematics education in the developing world. The contributions of the association may also add value to the learning of teacher colleagues in other parts of the world. This sharing of the experience may...... and policy makers have been recently receiving attention an innovative and flexible professional development forum for creating ownership among these stakeholders' regarding implementing change and reforms in educational landscape in different countries. The paper draws on the notion of "networking...... further support in opening up possibilities for creating other networks of learning to assist reform efforts in education throughout the world....

  7. Genome-scale reconstruction of the Streptococcus pyogenes M49 metabolic network reveals growth requirements and indicates potential drug targets

    NARCIS (Netherlands)

    Levering, J.; Fiedler, T.; Sieg, A.; van Grinsven, K.W.A.; Hering, S.; Veith, N.; Olivier, B.G.; Klett, L.; Hugenholtz, J.; Teusink, B.; Kreikemeyer, B.; Kummer, U.

    2016-01-01

    Genome-scale metabolic models comprise stoichiometric relations between metabolites, as well as associations between genes and metabolic reactions and facilitate the analysis of metabolism. We computationally reconstructed the metabolic network of the lactic acid bacterium Streptococcus pyogenes M49

  8. Basset: learning the regulatory code of the accessible genome with deep convolutional neural networks

    Science.gov (United States)

    Kelley, David R.; Snoek, Jasper; Rinn, John L.

    2016-01-01

    The complex language of eukaryotic gene expression remains incompletely understood. Despite the importance suggested by many noncoding variants statistically associated with human disease, nearly all such variants have unknown mechanisms. Here, we address this challenge using an approach based on a recent machine learning advance—deep convolutional neural networks (CNNs). We introduce the open source package Basset to apply CNNs to learn the functional activity of DNA sequences from genomics data. We trained Basset on a compendium of accessible genomic sites mapped in 164 cell types by DNase-seq, and demonstrate greater predictive accuracy than previous methods. Basset predictions for the change in accessibility between variant alleles were far greater for Genome-wide association study (GWAS) SNPs that are likely to be causal relative to nearby SNPs in linkage disequilibrium with them. With Basset, a researcher can perform a single sequencing assay in their cell type of interest and simultaneously learn that cell's chromatin accessibility code and annotate every mutation in the genome with its influence on present accessibility and latent potential for accessibility. Thus, Basset offers a powerful computational approach to annotate and interpret the noncoding genome. PMID:27197224

  9. Prediction of maize phenotype based on whole-genome single nucleotide polymorphisms using deep belief networks

    Science.gov (United States)

    Rachmatia, H.; Kusuma, W. A.; Hasibuan, L. S.

    2017-05-01

    Selection in plant breeding could be more effective and more efficient if it is based on genomic data. Genomic selection (GS) is a new approach for plant-breeding selection that exploits genomic data through a mechanism called genomic prediction (GP). Most of GP models used linear methods that ignore effects of interaction among genes and effects of higher order nonlinearities. Deep belief network (DBN), one of the architectural in deep learning methods, is able to model data in high level of abstraction that involves nonlinearities effects of the data. This study implemented DBN for developing a GP model utilizing whole-genome Single Nucleotide Polymorphisms (SNPs) as data for training and testing. The case study was a set of traits in maize. The maize dataset was acquisitioned from CIMMYT’s (International Maize and Wheat Improvement Center) Global Maize program. Based on Pearson correlation, DBN is outperformed than other methods, kernel Hilbert space (RKHS) regression, Bayesian LASSO (BL), best linear unbiased predictor (BLUP), in case allegedly non-additive traits. DBN achieves correlation of 0.579 within -1 to 1 range.

  10. Basset: learning the regulatory code of the accessible genome with deep convolutional neural networks.

    Science.gov (United States)

    Kelley, David R; Snoek, Jasper; Rinn, John L

    2016-07-01

    The complex language of eukaryotic gene expression remains incompletely understood. Despite the importance suggested by many noncoding variants statistically associated with human disease, nearly all such variants have unknown mechanisms. Here, we address this challenge using an approach based on a recent machine learning advance-deep convolutional neural networks (CNNs). We introduce the open source package Basset to apply CNNs to learn the functional activity of DNA sequences from genomics data. We trained Basset on a compendium of accessible genomic sites mapped in 164 cell types by DNase-seq, and demonstrate greater predictive accuracy than previous methods. Basset predictions for the change in accessibility between variant alleles were far greater for Genome-wide association study (GWAS) SNPs that are likely to be causal relative to nearby SNPs in linkage disequilibrium with them. With Basset, a researcher can perform a single sequencing assay in their cell type of interest and simultaneously learn that cell's chromatin accessibility code and annotate every mutation in the genome with its influence on present accessibility and latent potential for accessibility. Thus, Basset offers a powerful computational approach to annotate and interpret the noncoding genome.

  11. Generating a Networked Improvement Community to Improve Secondary Mathematics Teacher Preparation: Network Leadership, Organization, and Operation

    Science.gov (United States)

    Martin, W. Gary; Gobstein, Howard

    2015-01-01

    The Mathematics Teacher Education Partnership (MTE-Partnership) was formed to address the undersupply of new secondary mathematics teachers who are well prepared to help their students attain the goals of the Common Core State Standards and other college- and career-ready standards. This national consortium of more than 90 universities and 100…

  12. Metabolism and evolution: A comparative study of reconstructed genome-level metabolic networks

    Science.gov (United States)

    Almaas, Eivind

    2008-03-01

    The availability of high-quality annotations of sequenced genomes has made it possible to generate organism-specific comprehensive maps of cellular metabolism. Currently, more than twenty such metabolic reconstructions are publicly available, with the majority focused on bacteria. A typical metabolic reconstruction for a bacterium results in a complex network containing hundreds of metabolites (nodes) and reactions (links), while some even contain more than a thousand. The constrain-based optimization approach of flux-balance analysis (FBA) is used to investigate the functional characteristics of such large-scale metabolic networks, making it possible to estimate an organism's growth behavior in a wide variety of nutrient environments, as well as its robustness to gene loss. We have recently completed the genome-level metabolic reconstruction of Yersinia pseudotuberculosis, as well as the three Yersinia pestis biovars Antiqua, Mediaevalis, and Orientalis. While Y. pseudotuberculosis typically only causes fever and abdominal pain that can mimic appendicitis, the evolutionary closely related Y. pestis strains are the aetiological agents of the bubonic plague. In this presentation, I will discuss our results and conclusions from a comparative study on the evolution of metabolic function in the four Yersiniae networks using FBA and related techniques, and I will give particular focus to the interplay between metabolic network topology and evolutionary flexibility.

  13. A network-based approach to prioritize results from genome-wide association studies.

    Directory of Open Access Journals (Sweden)

    Nirmala Akula

    Full Text Available Genome-wide association studies (GWAS are a valuable approach to understanding the genetic basis of complex traits. One of the challenges of GWAS is the translation of genetic association results into biological hypotheses suitable for further investigation in the laboratory. To address this challenge, we introduce Network Interface Miner for Multigenic Interactions (NIMMI, a network-based method that combines GWAS data with human protein-protein interaction data (PPI. NIMMI builds biological networks weighted by connectivity, which is estimated by use of a modification of the Google PageRank algorithm. These weights are then combined with genetic association p-values derived from GWAS, producing what we call 'trait prioritized sub-networks.' As a proof of principle, NIMMI was tested on three GWAS datasets previously analyzed for height, a classical polygenic trait. Despite differences in sample size and ancestry, NIMMI captured 95% of the known height associated genes within the top 20% of ranked sub-networks, far better than what could be achieved by a single-locus approach. The top 2% of NIMMI height-prioritized sub-networks were significantly enriched for genes involved in transcription, signal transduction, transport, and gene expression, as well as nucleic acid, phosphate, protein, and zinc metabolism. All of these sub-networks were ranked near the top across all three height GWAS datasets we tested. We also tested NIMMI on a categorical phenotype, Crohn's disease. NIMMI prioritized sub-networks involved in B- and T-cell receptor, chemokine, interleukin, and other pathways consistent with the known autoimmune nature of Crohn's disease. NIMMI is a simple, user-friendly, open-source software tool that efficiently combines genetic association data with biological networks, translating GWAS findings into biological hypotheses.

  14. The properties of genome conformation and spatial gene interaction and regulation networks of normal and malignant human cell types.

    Directory of Open Access Journals (Sweden)

    Zheng Wang

    Full Text Available The spatial conformation of a genome plays an important role in the long-range regulation of genome-wide gene expression and methylation, but has not been extensively studied due to lack of genome conformation data. The recently developed chromosome conformation capturing techniques such as the Hi-C method empowered by next generation sequencing can generate unbiased, large-scale, high-resolution chromosomal interaction (contact data, providing an unprecedented opportunity to investigate the spatial structure of a genome and its applications in gene regulation, genomics, epigenetics, and cell biology. In this work, we conducted a comprehensive, large-scale computational analysis of this new stream of genome conformation data generated for three different human leukemia cells or cell lines by the Hi-C technique. We developed and applied a set of bioinformatics methods to reliably generate spatial chromosomal contacts from high-throughput sequencing data and to effectively use them to study the properties of the genome structures in one-dimension (1D and two-dimension (2D. Our analysis demonstrates that Hi-C data can be effectively applied to study tissue-specific genome conformation, chromosome-chromosome interaction, chromosomal translocations, and spatial gene-gene interaction and regulation in a three-dimensional genome of primary tumor cells. Particularly, for the first time, we constructed genome-scale spatial gene-gene interaction network, transcription factor binding site (TFBS - TFBS interaction network, and TFBS-gene interaction network from chromosomal contact information. Remarkably, all these networks possess the properties of scale-free modular networks.

  15. Network properties of complex human disease genes identified through genome-wide association studies.

    Directory of Open Access Journals (Sweden)

    Fredrik Barrenas

    Full Text Available BACKGROUND: Previous studies of network properties of human disease genes have mainly focused on monogenic diseases or cancers and have suffered from discovery bias. Here we investigated the network properties of complex disease genes identified by genome-wide association studies (GWAs, thereby eliminating discovery bias. PRINCIPAL FINDINGS: We derived a network of complex diseases (n = 54 and complex disease genes (n = 349 to explore the shared genetic architecture of complex diseases. We evaluated the centrality measures of complex disease genes in comparison with essential and monogenic disease genes in the human interactome. The complex disease network showed that diseases belonging to the same disease class do not always share common disease genes. A possible explanation could be that the variants with higher minor allele frequency and larger effect size identified using GWAs constitute disjoint parts of the allelic spectra of similar complex diseases. The complex disease gene network showed high modularity with the size of the largest component being smaller than expected from a randomized null-model. This is consistent with limited sharing of genes between diseases. Complex disease genes are less central than the essential and monogenic disease genes in the human interactome. Genes associated with the same disease, compared to genes associated with different diseases, more often tend to share a protein-protein interaction and a Gene Ontology Biological Process. CONCLUSIONS: This indicates that network neighbors of known disease genes form an important class of candidates for identifying novel genes for the same disease.

  16. Network properties of complex human disease genes identified through genome-wide association studies.

    Science.gov (United States)

    Barrenas, Fredrik; Chavali, Sreenivas; Holme, Petter; Mobini, Reza; Benson, Mikael

    2009-11-30

    Previous studies of network properties of human disease genes have mainly focused on monogenic diseases or cancers and have suffered from discovery bias. Here we investigated the network properties of complex disease genes identified by genome-wide association studies (GWAs), thereby eliminating discovery bias. We derived a network of complex diseases (n = 54) and complex disease genes (n = 349) to explore the shared genetic architecture of complex diseases. We evaluated the centrality measures of complex disease genes in comparison with essential and monogenic disease genes in the human interactome. The complex disease network showed that diseases belonging to the same disease class do not always share common disease genes. A possible explanation could be that the variants with higher minor allele frequency and larger effect size identified using GWAs constitute disjoint parts of the allelic spectra of similar complex diseases. The complex disease gene network showed high modularity with the size of the largest component being smaller than expected from a randomized null-model. This is consistent with limited sharing of genes between diseases. Complex disease genes are less central than the essential and monogenic disease genes in the human interactome. Genes associated with the same disease, compared to genes associated with different diseases, more often tend to share a protein-protein interaction and a Gene Ontology Biological Process. This indicates that network neighbors of known disease genes form an important class of candidates for identifying novel genes for the same disease.

  17. Relationships in reform: the role of teachers' social networks

    NARCIS (Netherlands)

    Daly, A.J.; Moolenaar, N.M.; Bolivar, J.M.; Burke, P.

    2010-01-01

    Purpose - Scholars have focused their attention on systemic reform as a way to support instructional coherence. These efforts are often layered on to existing social relationships between school staff that are rarely taken into account when enacting reform. Social network theory posits that the stru

  18. Polysaccharides utilization in human gut bacterium Bacteroides thetaiotaomicron: comparative genomics reconstruction of metabolic and regulatory networks.

    Science.gov (United States)

    Ravcheev, Dmitry A; Godzik, Adam; Osterman, Andrei L; Rodionov, Dmitry A

    2013-12-12

    Bacteroides thetaiotaomicron, a predominant member of the human gut microbiota, is characterized by its ability to utilize a wide variety of polysaccharides using the extensive saccharolytic machinery that is controlled by an expanded repertoire of transcription factors (TFs). The availability of genomic sequences for multiple Bacteroides species opens an opportunity for their comparative analysis to enable characterization of their metabolic and regulatory networks. A comparative genomics approach was applied for the reconstruction and functional annotation of the carbohydrate utilization regulatory networks in 11 Bacteroides genomes. Bioinformatics analysis of promoter regions revealed putative DNA-binding motifs and regulons for 31 orthologous TFs in the Bacteroides. Among the analyzed TFs there are 4 SusR-like regulators, 16 AraC-like hybrid two-component systems (HTCSs), and 11 regulators from other families. Novel DNA motifs of HTCSs and SusR-like regulators in the Bacteroides have the common structure of direct repeats with a long spacer between two conserved sites. The inferred regulatory network in B. thetaiotaomicron contains 308 genes encoding polysaccharide and sugar catabolic enzymes, carbohydrate-binding and transport systems, and TFs. The analyzed TFs control pathways for utilization of host and dietary glycans to monosaccharides and their further interconversions to intermediates of the central metabolism. The reconstructed regulatory network allowed us to suggest and refine specific functional assignments for sugar catabolic enzymes and transporters, providing a substantial improvement to the existing metabolic models for B. thetaiotaomicron. The obtained collection of reconstructed TF regulons is available in the RegPrecise database (http://regprecise.lbl.gov).

  19. Genome-scale reconstruction of metabolic networks of Lactobacillus casei ATCC 334 and 12A.

    Directory of Open Access Journals (Sweden)

    Elena Vinay-Lara

    Full Text Available Lactobacillus casei strains are widely used in industry and the utility of this organism in these industrial applications is strain dependent. Hence, tools capable of predicting strain specific phenotypes would have utility in the selection of strains for specific industrial processes. Genome-scale metabolic models can be utilized to better understand genotype-phenotype relationships and to compare different organisms. To assist in the selection and development of strains with enhanced industrial utility, genome-scale models for L. casei ATCC 334, a well characterized strain, and strain 12A, a corn silage isolate, were constructed. Draft models were generated from RAST genome annotations using the Model SEED database and refined by evaluating ATP generating cycles, mass-and-charge-balances of reactions, and growth phenotypes. After the validation process was finished, we compared the metabolic networks of these two strains to identify metabolic, genetic and ortholog differences that may lead to different phenotypic behaviors. We conclude that the metabolic capabilities of the two networks are highly similar. The L. casei ATCC 334 model accounts for 1,040 reactions, 959 metabolites and 548 genes, while the L. casei 12A model accounts for 1,076 reactions, 979 metabolites and 640 genes. The developed L. casei ATCC 334 and 12A metabolic models will enable better understanding of the physiology of these organisms and be valuable tools in the development and selection of strains with enhanced utility in a variety of industrial applications.

  20. Genome –Scale Reconstruction of Metabolic Networks of Lactobacillus casei ATCC 334 and 12A

    Science.gov (United States)

    Vinay-Lara, Elena; Hamilton, Joshua J.; Stahl, Buffy; Broadbent, Jeff R.; Reed, Jennifer L.; Steele, James L.

    2014-01-01

    Lactobacillus casei strains are widely used in industry and the utility of this organism in these industrial applications is strain dependent. Hence, tools capable of predicting strain specific phenotypes would have utility in the selection of strains for specific industrial processes. Genome-scale metabolic models can be utilized to better understand genotype-phenotype relationships and to compare different organisms. To assist in the selection and development of strains with enhanced industrial utility, genome-scale models for L. casei ATCC 334, a well characterized strain, and strain 12A, a corn silage isolate, were constructed. Draft models were generated from RAST genome annotations using the Model SEED database and refined by evaluating ATP generating cycles, mass-and-charge-balances of reactions, and growth phenotypes. After the validation process was finished, we compared the metabolic networks of these two strains to identify metabolic, genetic and ortholog differences that may lead to different phenotypic behaviors. We conclude that the metabolic capabilities of the two networks are highly similar. The L. casei ATCC 334 model accounts for 1,040 reactions, 959 metabolites and 548 genes, while the L. casei 12A model accounts for 1,076 reactions, 979 metabolites and 640 genes. The developed L. casei ATCC 334 and 12A metabolic models will enable better understanding of the physiology of these organisms and be valuable tools in the development and selection of strains with enhanced utility in a variety of industrial applications. PMID:25365062

  1. A Network of Multi-Tasking Proteins at the DNA Replication Fork Preserves Genome Stability.

    Directory of Open Access Journals (Sweden)

    2005-12-01

    Full Text Available To elucidate the network that maintains high fidelity genome replication, we have introduced two conditional mutant alleles of DNA2, an essential DNA replication gene, into each of the approximately 4,700 viable yeast deletion mutants and determined the fitness of the double mutants. Fifty-six DNA2-interacting genes were identified. Clustering analysis of genomic synthetic lethality profiles of each of 43 of the DNA2-interacting genes defines a network (consisting of 322 genes and 876 interactions whose topology provides clues as to how replication proteins coordinate regulation and repair to protect genome integrity. The results also shed new light on the functions of the query gene DNA2, which, despite many years of study, remain controversial, especially its proposed role in Okazaki fragment processing and the nature of its in vivo substrates. Because of the multifunctional nature of virtually all proteins at the replication fork, the meaning of any single genetic interaction is inherently ambiguous. The multiplexing nature of the current studies, however, combined with follow-up supporting experiments, reveals most if not all of the unique pathways requiring Dna2p. These include not only Okazaki fragment processing and DNA repair but also chromatin dynamics.

  2. A network of multi-tasking proteins at the DNA replication fork preserves genome stability.

    Directory of Open Access Journals (Sweden)

    Martin E Budd

    2005-12-01

    Full Text Available To elucidate the network that maintains high fidelity genome replication, we have introduced two conditional mutant alleles of DNA2, an essential DNA replication gene, into each of the approximately 4,700 viable yeast deletion mutants and determined the fitness of the double mutants. Fifty-six DNA2-interacting genes were identified. Clustering analysis of genomic synthetic lethality profiles of each of 43 of the DNA2-interacting genes defines a network (consisting of 322 genes and 876 interactions whose topology provides clues as to how replication proteins coordinate regulation and repair to protect genome integrity. The results also shed new light on the functions of the query gene DNA2, which, despite many years of study, remain controversial, especially its proposed role in Okazaki fragment processing and the nature of its in vivo substrates. Because of the multifunctional nature of virtually all proteins at the replication fork, the meaning of any single genetic interaction is inherently ambiguous. The multiplexing nature of the current studies, however, combined with follow-up supporting experiments, reveals most if not all of the unique pathways requiring Dna2p. These include not only Okazaki fragment processing and DNA repair but also chromatin dynamics.

  3. Investigating host-pathogen behavior and their interaction using genome-scale metabolic network models.

    Science.gov (United States)

    Sadhukhan, Priyanka P; Raghunathan, Anu

    2014-01-01

    Genome Scale Metabolic Modeling methods represent one way to compute whole cell function starting from the genome sequence of an organism and contribute towards understanding and predicting the genotype-phenotype relationship. About 80 models spanning all the kingdoms of life from archaea to eukaryotes have been built till date and used to interrogate cell phenotype under varying conditions. These models have been used to not only understand the flux distribution in evolutionary conserved pathways like glycolysis and the Krebs cycle but also in applications ranging from value added product formation in Escherichia coli to predicting inborn errors of Homo sapiens metabolism. This chapter describes a protocol that delineates the process of genome scale metabolic modeling for analysing host-pathogen behavior and interaction using flux balance analysis (FBA). The steps discussed in the process include (1) reconstruction of a metabolic network from the genome sequence, (2) its representation in a precise mathematical framework, (3) its translation to a model, and (4) the analysis using linear algebra and optimization. The methods for biological interpretations of computed cell phenotypes in the context of individual host and pathogen models and their integration are also discussed.

  4. The SOL Genomics Network. A Comparative Resource for Solanaceae Biology and Beyond1

    Science.gov (United States)

    Mueller, Lukas A.; Solow, Teri H.; Taylor, Nicolas; Skwarecki, Beth; Buels, Robert; Binns, John; Lin, Chenwei; Wright, Mark H.; Ahrens, Robert; Wang, Ying; Herbst, Evan V.; Keyder, Emil R.; Menda, Naama; Zamir, Dani; Tanksley, Steven D.

    2005-01-01

    The SOL Genomics Network (SGN; http://sgn.cornell.edu) is a rapidly evolving comparative resource for the plants of the Solanaceae family, which includes important crop and model plants such as potato (Solanum tuberosum), eggplant (Solanum melongena), pepper (Capsicum annuum), and tomato (Solanum lycopersicum). The aim of SGN is to relate these species to one another using a comparative genomics approach and to tie them to the other dicots through the fully sequenced genome of Arabidopsis (Arabidopsis thaliana). SGN currently houses map and marker data for Solanaceae species, a large expressed sequence tag collection with computationally derived unigene sets, an extensive database of phenotypic information for a mutagenized tomato population, and associated tools such as real-time quantitative trait loci. Recently, the International Solanaceae Project (SOL) was formed as an umbrella organization for Solanaceae research in over 30 countries to address important questions in plant biology. The first cornerstone of the SOL project is the sequencing of the entire euchromatic portion of the tomato genome. SGN is collaborating with other bioinformatics centers in building the bioinformatics infrastructure for the tomato sequencing project and implementing the bioinformatics strategy of the larger SOL project. The overarching goal of SGN is to make information available in an intuitive comparative format, thereby facilitating a systems approach to investigations into the basis of adaptation and phenotypic diversity in the Solanaceae family, other species in the Asterid clade such as coffee (Coffea arabica), Rubiaciae, and beyond. PMID:16010005

  5. Predicting DNA Methylation State of CpG Dinucleotide Using Genome Topological Features and Deep Networks.

    Science.gov (United States)

    Wang, Yiheng; Liu, Tong; Xu, Dong; Shi, Huidong; Zhang, Chaoyang; Mo, Yin-Yuan; Wang, Zheng

    2016-01-22

    The hypo- or hyper-methylation of the human genome is one of the epigenetic features of leukemia. However, experimental approaches have only determined the methylation state of a small portion of the human genome. We developed deep learning based (stacked denoising autoencoders, or SdAs) software named "DeepMethyl" to predict the methylation state of DNA CpG dinucleotides using features inferred from three-dimensional genome topology (based on Hi-C) and DNA sequence patterns. We used the experimental data from immortalised myelogenous leukemia (K562) and healthy lymphoblastoid (GM12878) cell lines to train the learning models and assess prediction performance. We have tested various SdA architectures with different configurations of hidden layer(s) and amount of pre-training data and compared the performance of deep networks relative to support vector machines (SVMs). Using the methylation states of sequentially neighboring regions as one of the learning features, an SdA achieved a blind test accuracy of 89.7% for GM12878 and 88.6% for K562. When the methylation states of sequentially neighboring regions are unknown, the accuracies are 84.82% for GM12878 and 72.01% for K562. We also analyzed the contribution of genome topological features inferred from Hi-C. DeepMethyl can be accessed at http://dna.cs.usm.edu/deepmethyl/.

  6. The Sol Genomics Network (solgenomics.net): growing tomatoes using Perl

    Science.gov (United States)

    Bombarely, Aureliano; Menda, Naama; Tecle, Isaak Y.; Buels, Robert M.; Strickler, Susan; Fischer-York, Thomas; Pujar, Anuradha; Leto, Jonathan; Gosselin, Joseph; Mueller, Lukas A.

    2011-01-01

    The Sol Genomics Network (SGN; http://solgenomics.net/) is a clade-oriented database (COD) containing biological data for species in the Solanaceae and their close relatives, with data types ranging from chromosomes and genes to phenotypes and accessions. SGN hosts several genome maps and sequences, including a pre-release of the tomato (Solanum lycopersicum cv Heinz 1706) reference genome. A new transcriptome component has been added to store RNA-seq and microarray data. SGN is also an open source software project, continuously developing and improving a complex system for storing, integrating and analyzing data. All code and development work is publicly visible on GitHub (http://github.com). The database architecture combines SGN-specific schemas and the community-developed Chado schema (http://gmod.org/wiki/Chado) for compatibility with other genome databases. The SGN curation model is community-driven, allowing researchers to add and edit information using simple web tools. Currently, over a hundred community annotators help curate the database. SGN can be accessed at http://solgenomics.net/. PMID:20935049

  7. Emergence and evolutionary analysis of the human DDR network: implications in comparative genomics and downstream analyses.

    Science.gov (United States)

    Arcas, Aida; Fernández-Capetillo, Oscar; Cases, Ildefonso; Rojas, Ana M

    2014-04-01

    The DNA damage response (DDR) is a crucial signaling network that preserves the integrity of the genome. This network is an ensemble of distinct but often overlapping subnetworks, where different components fulfill distinct functions in precise spatial and temporal scenarios. To understand how these elements have been assembled together in humans, we performed comparative genomic analyses in 47 selected species to trace back their emergence using systematic phylogenetic analyses and estimated gene ages. The emergence of the contribution of posttranslational modifications to the complex regulation of DDR was also investigated. This is the first time a systematic analysis has focused on the evolution of DDR subnetworks as a whole. Our results indicate that a DDR core, mostly constructed around metabolic activities, appeared soon after the emergence of eukaryotes, and that additional regulatory capacities appeared later through complex evolutionary process. Potential key posttranslational modifications were also in place then, with interacting pairs preferentially appearing at the same evolutionary time, although modifications often led to the subsequent acquisition of new targets afterwards. We also found extensive gene loss in essential modules of the regulatory network in fungi, plants, and arthropods, important for their validation as model organisms for DDR studies.

  8. Network thermodynamic curation of human and yeast genome-scale metabolic models.

    Science.gov (United States)

    Martínez, Verónica S; Quek, Lake-Ee; Nielsen, Lars K

    2014-07-15

    Genome-scale models are used for an ever-widening range of applications. Although there has been much focus on specifying the stoichiometric matrix, the predictive power of genome-scale models equally depends on reaction directions. Two-thirds of reactions in the two eukaryotic reconstructions Homo sapiens Recon 1 and Yeast 5 are specified as irreversible. However, these specifications are mainly based on biochemical textbooks or on their similarity to other organisms and are rarely underpinned by detailed thermodynamic analysis. In this study, a to our knowledge new workflow combining network-embedded thermodynamic and flux variability analysis was used to evaluate existing irreversibility constraints in Recon 1 and Yeast 5 and to identify new ones. A total of 27 and 16 new irreversible reactions were identified in Recon 1 and Yeast 5, respectively, whereas only four reactions were found with directions incorrectly specified against thermodynamics (three in Yeast 5 and one in Recon 1). The workflow further identified for both models several isolated internal loops that require further curation. The framework also highlighted the need for substrate channeling (in human) and ATP hydrolysis (in yeast) for the essential reaction catalyzed by phosphoribosylaminoimidazole carboxylase in purine metabolism. Finally, the framework highlighted differences in proline metabolism between yeast (cytosolic anabolism and mitochondrial catabolism) and humans (exclusively mitochondrial metabolism). We conclude that network-embedded thermodynamics facilitates the specification and validation of irreversibility constraints in compartmentalized metabolic models, at the same time providing further insight into network properties.

  9. Extending pathways and processes using molecular interaction networks to analyse cancer genome data

    Directory of Open Access Journals (Sweden)

    Krasnogor Natalio

    2010-12-01

    Full Text Available Abstract Background Cellular processes and pathways, whose deregulation may contribute to the development of cancers, are often represented as cascades of proteins transmitting a signal from the cell surface to the nucleus. However, recent functional genomic experiments have identified thousands of interactions for the signalling canonical proteins, challenging the traditional view of pathways as independent functional entities. Combining information from pathway databases and interaction networks obtained from functional genomic experiments is therefore a promising strategy to obtain more robust pathway and process representations, facilitating the study of cancer-related pathways. Results We present a methodology for extending pre-defined protein sets representing cellular pathways and processes by mapping them onto a protein-protein interaction network, and extending them to include densely interconnected interaction partners. The added proteins display distinctive network topological features and molecular function annotations, and can be proposed as putative new components, and/or as regulators of the communication between the different cellular processes. Finally, these extended pathways and processes are used to analyse their enrichment in pancreatic mutated genes. Significant associations between mutated genes and certain processes are identified, enabling an analysis of the influence of previously non-annotated cancer mutated genes. Conclusions The proposed method for extending cellular pathways helps to explain the functions of cancer mutated genes by exploiting the synergies of canonical knowledge and large-scale interaction data.

  10. EGN: a wizard for construction of gene and genome similarity networks.

    Science.gov (United States)

    Halary, Sébastien; McInerney, James O; Lopez, Philippe; Bapteste, Eric

    2013-07-11

    Increasingly, similarity networks are being used for evolutionary analyses of molecular datasets. These networks are very useful, in particular for the analysis of gene sharing, lateral gene transfer and for the detection of distant homologs. Currently, such analyses require some computer programming skills due to the limited availability of user-friendly freely distributed software. Consequently, although appealing, the construction and analyses of these networks remain less familiar to biologists than do phylogenetic approaches. In order to ease the use of similarity networks in the community of evolutionary biologists, we introduce a software program, EGN, that runs under Linux or MacOSX. EGN automates the reconstruction of gene and genome networks from nucleic and proteic sequences. EGN also implements statistics describing genetic diversity in these samples, for various user-defined thresholds of similarities. In the interest of studying the complexity of evolutionary processes affecting microbial evolution, we applied EGN to a dataset of 571,044 proteic sequences from the three domains of life and from mobile elements. We observed that, in Borrelia, plasmids play a different role than in most other eubacteria. Rather than being genetic couriers involved in lateral gene transfer, Borrelia's plasmids and their genes act as private genetic goods, that contribute to the creation of genetic diversity within their parasitic hosts. EGN can be used for constructing, analyzing, and mining molecular datasets in evolutionary studies. The program can help increase our knowledge of the processes through which genes from distinct sources and/or from multiple genomes co-evolve in lineages of cellular organisms.

  11. Assessing computational genomics skills: Our experience in the H3ABioNet African bioinformatics network.

    Directory of Open Access Journals (Sweden)

    C Victor Jongeneel

    2017-06-01

    Full Text Available The H3ABioNet pan-African bioinformatics network, which is funded to support the Human Heredity and Health in Africa (H3Africa program, has developed node-assessment exercises to gauge the ability of its participating research and service groups to analyze typical genome-wide datasets being generated by H3Africa research groups. We describe a framework for the assessment of computational genomics analysis skills, which includes standard operating procedures, training and test datasets, and a process for administering the exercise. We present the experiences of 3 research groups that have taken the exercise and the impact on their ability to manage complex projects. Finally, we discuss the reasons why many H3ABioNet nodes have declined so far to participate and potential strategies to encourage them to do so.

  12. A hybrid neural network system for prediction and recognition of promoter regions in human genome

    Institute of Scientific and Technical Information of China (English)

    CHEN Chuan-bo; LI Tao

    2005-01-01

    This paper proposes a high specificity and sensitivity algorithm called PromPredictor for recognizing promoter regions in the human genome. PromPredictor extracts compositional features and CpG islands information from genomic sequence,feeding these features as input for a hybrid neural network system (HNN) and then applies the HNN for prediction. It combines a novel promoter recognition model, coding theory, feature selection and dimensionality reduction with machine learning algorithm.Evaluation on Human chromosome 22 was ~66% in sensitivity and ~48% in specificity. Comparison with two other systems revealed that our method had superior sensitivity and specificity in predicting promoter regions. PromPredictor is written in MATLAB and requires Matlab to run. PromPredictor is freely available at http://www.whtelecom.com/Prompredictor.htm.

  13. Basic and applied uses of genome-scale metabolic network reconstructions of Escherichia coli

    DEFF Research Database (Denmark)

    McCloskey, Douglas; Palsson, Bernhard; Feist, Adam

    2013-01-01

    The genome-scale model (GEM) of metabolism in the bacterium Escherichia coli K-12 has been in development for over a decade and is now in wide use. GEM-enabled studies of E. coli have been primarily focused on six applications: (1) metabolic engineering, (2) model-driven discovery, (3) prediction...... of cellular phenotypes, (4) analysis of biological network properties, (5) studies of evolutionary processes, and (6) models of interspecies interactions. In this review, we provide an overview of these applications along with a critical assessment of their successes and limitations, and a perspective...... on likely future developments in the field. Taken together, the studies performed over the past decade have established a genome-scale mechanistic understanding of genotype-phenotype relationships in E. coli metabolism that forms the basis for similar efforts for other microbial species. Future challenges...

  14. Acute Genome-wide effects of Rosiglitazone on PPARγ transcriptional networks in Adipocytes

    DEFF Research Database (Denmark)

    Haakonsson, Anders Kristian; Madsen, Maria Stahl; Nielsen, Ronni

    2013-01-01

    Peroxisome proliferator-activated receptor γ (PPARγ) is a master regulator of adipocyte differentiation, and genome-wide studies indicate that it is involved in the induction of most adipocyte genes. Here we report, for the first time, the acute effects of the synthetic PPARγ agonist rosiglitazone...... on the transcriptional network of PPARγ in adipocytes. Treatment with rosiglitazone for 1 hour leads to acute transcriptional activation as well as repression of a number of genes as determined by genome-wide RNA polymerase II occupancy. Unlike what has been shown for many other nuclear receptors, agonist treatment does...... not lead to major changes in the occurrence of PPARγ binding sites. However, rosiglitazone promotes PPARγ occupancy at many preexisting sites, and this is paralleled by increased occupancy of the mediator subunit MED1. The increase in PPARγ and MED1 binding is correlated with an increase in transcription...

  15. Attitudes towards Social Networking and Sharing Behaviors among Consumers of Direct-to-Consumer Personal Genomics.

    Science.gov (United States)

    Lee, Sandra Soo-Jin; Vernez, Simone L; Ormond, K E; Granovetter, Mark

    2013-10-14

    Little is known about how consumers of direct-to-consumer personal genetic services share personal genetic risk information. In an age of ubiquitous online networking and rapid development of social networking tools, understanding how consumers share personal genetic risk assessments is critical in the development of appropriate and effective policies. This exploratory study investigates how consumers share personal genetic information and attitudes towards social networking behaviors. Adult participants aged 23 to 72 years old who purchased direct-to-consumer genetic testing from a personal genomics company were administered a web-based survey regarding their sharing activities and social networking behaviors related to their personal genetic test results. 80 participants completed the survey; of those, 45% shared results on Facebook and 50.9% reported meeting or reconnecting with more than 10 other individuals through the sharing of their personal genetic information. For help interpreting test results, 70.4% turned to Internet websites and online sources, compared to 22.7% who consulted their healthcare providers. Amongst participants, 51.8% reported that they believe the privacy of their personal genetic information would be breached in the future. Consumers actively utilize online social networking tools to help them share and interpret their personal genetic information. These findings suggest a need for careful consideration of policy recommendations in light of the current ambiguity of regulation and oversight of consumer initiated sharing activities.

  16. Functional Genomics Assistant (FUGA: a toolbox for the analysis of complex biological networks

    Directory of Open Access Journals (Sweden)

    Ouzounis Christos A

    2011-10-01

    Full Text Available Abstract Background Cellular constituents such as proteins, DNA, and RNA form a complex web of interactions that regulate biochemical homeostasis and determine the dynamic cellular response to external stimuli. It follows that detailed understanding of these patterns is critical for the assessment of fundamental processes in cell biology and pathology. Representation and analysis of cellular constituents through network principles is a promising and popular analytical avenue towards a deeper understanding of molecular mechanisms in a system-wide context. Findings We present Functional Genomics Assistant (FUGA - an extensible and portable MATLAB toolbox for the inference of biological relationships, graph topology analysis, random network simulation, network clustering, and functional enrichment statistics. In contrast to conventional differential expression analysis of individual genes, FUGA offers a framework for the study of system-wide properties of biological networks and highlights putative molecular targets using concepts of systems biology. Conclusion FUGA offers a simple and customizable framework for network analysis in a variety of systems biology applications. It is freely available for individual or academic use at http://code.google.com/p/fuga.

  17. Attitudes towards Social Networking and Sharing Behaviors among Consumers of Direct-to-Consumer Personal Genomics

    Directory of Open Access Journals (Sweden)

    Mark Granovetter

    2013-10-01

    Full Text Available Little is known about how consumers of direct-to-consumer personal genetic services share personal genetic risk information. In an age of ubiquitous online networking and rapid development of social networking tools, understanding how consumers share personal genetic risk assessments is critical in the development of appropriate and effective policies. This exploratory study investigates how consumers share personal genetic information and attitudes towards social networking behaviors. Methods: Adult participants aged 23 to 72 years old who purchased direct-to-consumer genetic testing from a personal genomics company were administered a web-based survey regarding their sharing activities and social networking behaviors related to their personal genetic test results. Results: 80 participants completed the survey; of those, 45% shared results on Facebook and 50.9% reported meeting or reconnecting with more than 10 other individuals through the sharing of their personal genetic information. For help interpreting test results, 70.4% turned to Internet websites and online sources, compared to 22.7% who consulted their healthcare providers. Amongst participants, 51.8% reported that they believe the privacy of their personal genetic information would be breached in the future. Conclusion: Consumers actively utilize online social networking tools to help them share and interpret their personal genetic information. These findings suggest a need for careful consideration of policy recommendations in light of the current ambiguity of regulation and oversight of consumer initiated sharing activities.

  18. On the Connectivity of Wireless Network Systems and an Application in Teacher-Student Interactive Platforms

    Directory of Open Access Journals (Sweden)

    Xun Ge

    2014-01-01

    Full Text Available A wireless network system is a pair (U;B, where B is a family of some base stations and U is a set of their users. To investigate the connectivity of wireless network systems, this paper takes covering approximation spaces as mathematical models of wireless network systems. With the help of covering approximation operators, this paper characterizes the connectivity of covering approximation spaces by their definable subsets. Furthermore, it is obtained that a wireless network system is connected if and only if the relevant covering approximation space has no nonempty definable proper subset. As an application of this result, the connectivity of a teacher-student interactive platform is discussed, which is established in the School of Mathematical Sciences of Soochow University. This application further demonstrates the usefulness of rough set theory in pedagogy and makes it possible to research education by logical methods and mathematical methods.

  19. CTD² Dashboard: a searchable web interface to connect validated results from the Cancer Target Discovery and Development Network | Office of Cancer Genomics

    Science.gov (United States)

    The Cancer Target Discovery and Development (CTD2) Network aims to use functional genomics to accelerate the translation of high-throughput and high-content genomic and small-molecule data towards use in precision oncology.

  20. Global Genome Biodiversity Network: saving a blueprint of the Tree of Life – a botanical perspective

    Science.gov (United States)

    Seberg, O.; Droege, G.; Barker, K.; Coddington, J. A.; Funk, V.; Gostel, M.; Petersen, G.; Smith, P. P.

    2016-01-01

    Background Genomic research depends upon access to DNA or tissue collected and preserved according to high-quality standards. At present, the collections in most natural history museums do not sufficiently address these standards, making them often hard or impossible to use for whole-genome sequencing or transcriptomics. In response to these challenges, natural history museums, herbaria, botanical gardens and other stakeholders have started to build high-quality biodiversity biobanks. Unfortunately, information about these collections remains fragmented, scattered and largely inaccessible. Without a central registry or even an overview of relevant institutions, it is difficult and time-consuming to locate the needed samples. Scope The Global Genome Biodiversity Network (GGBN) was created to fill this vacuum by establishing a one-stop access point for locating samples meeting quality standards for genome-scale applications, while complying with national and international legislations and conventions. Increased accessibility to genomic samples will further genomic research and development, conserve genetic resources, help train the next generation of genome researchers and raise the visibility of biodiversity collections. Additionally, the availability of a data-sharing platform will facilitate identification of gaps in the collections, thereby empowering targeted sampling efforts, increasing the breadth and depth of preservation of genetic diversity. The GGBN is rapidly growing and currently has 41 members. The GGBN covers all branches of the Tree of Life, except humans, but here the focus is on a pilot project with emphasis on ‘harvesting’ the Tree of Life for vascular plant taxa to enable genome-level studies. Conclusion While current efforts are centred on getting the existing samples of all GGBN members online, a pilot project, GGI-Gardens, has been launched as proof of concept. Over the next 6 years GGI-Gardens aims to add to the GGBN high-quality genetic

  1. EduCamp Colombia: Social Networked Learning for Teacher Training

    Directory of Open Access Journals (Sweden)

    Diego Ernesto Leal Fonseca

    2011-03-01

    Full Text Available This paper describes a learning experience called EduCamp, which was launched by the Ministry of Education of Colombia in 2007, based on emerging concepts such as e-Learning 2.0, connectivism, and personal learning environments. An EduCamp proposes an unstructured collective learning experience, which intends to make palpable the possibilities of social software tools in learning and interaction processes while demonstrating face-to-face organizational forms that reflect social networked learning ideas. The experience opens new perspectives for the design of technology training workshops and for the development of lifelong learning experiences.

  2. Funding Opportunity: Genomic Data Centers

    Science.gov (United States)

    Funding Opportunity CCG, Funding Opportunity Center for Cancer Genomics, CCG, Center for Cancer Genomics, CCG RFA, Center for cancer genomics rfa, genomic data analysis network, genomic data analysis network centers,

  3. Documentation and Evaluation Study of the Texas Teacher Corps Network Program '78 Community Council Developmental Training Conference.

    Science.gov (United States)

    Leos, Robert; Olivarez, Ruben Dario

    This document describes a training conference sponsored by the Teacher Corps Network. Informational and skill development sessions for Community Council members from the Teacher Corps projects are included. A special planning session, held prior to the conference is described. A description is given of the conference planning and events. The…

  4. The future of genome-scale modeling of yeast through integration of a transcriptional regulatory network

    DEFF Research Database (Denmark)

    Liu, Guodong; Marras, Antonio; Nielsen, Jens

    2014-01-01

    regulatory information is necessary to improve the accuracy and predictive ability of metabolic models. Here we review the strategies for the reconstruction of a transcriptional regulatory network (TRN) for yeast and the integration of such a reconstruction into a flux balance analysis-based metabolic model......Metabolism is regulated at multiple levels in response to the changes of internal or external conditions. Transcriptional regulation plays an important role in regulating many metabolic reactions by altering the concentrations of metabolic enzymes. Thus, integration of the transcriptional...... transcriptional regulatory interactions to genome-scale metabolic models in a quantitative manner....

  5. Identification of TSS in the Human Genome Based on a RBF Neural Network

    Institute of Scientific and Technical Information of China (English)

    Zhi-Hong Peng; Jie Chen; Li-Jun Cao; Ting-Ting Gao

    2006-01-01

    The identification of functional motifs in a DNA sequence is fundamentally a statistical pattern recognition problem. This paper introduces a new algorithm for the recognition of functional transcription start sites (TSSs) in human genome sequences, in which a RBF neural network is adopted, and an improved heuristic method for a 5-tuple feature viable construction, is proposed and implemented in two RBFPromoter and ImpRBFPromoter packages developed in Visual C++6.0. The algorithm is evaluated on several different test sequence sets. Compared with several other promoter recognition programs, this algorithm is proved to be more flexible, with stronger learning ability and higher accuracy.

  6. Genome-scale cold stress response regulatory networks in ten Arabidopsis thaliana ecotypes

    DEFF Research Database (Denmark)

    Barah, Pankaj; Jayavelu, Naresh Doni; Rasmussen, Simon

    2013-01-01

    BACKGROUND: Low temperature leads to major crop losses every year. Although several studies have been conducted focusing on diversity of cold tolerance level in multiple phenotypically divergent Arabidopsis thaliana (A. thaliana) ecotypes, genome-scale molecular understanding is still lacking...... using Arabidopsis NimbleGen ATH6 microarrays. In total 6061 transcripts were significantly cold regulated (p ... be crucial for their local geographic adaptation to cold temperature. Additionally, since the approach presented here is general, it could be adapted to study networks regulating biological process in any biological systems....

  7. Pre-service teachers opinions on cloud supported social network

    Directory of Open Access Journals (Sweden)

    Seher Ozcan

    2015-07-01

    Full Text Available Pre-service\tteachers\tare\texpected\tto\tuse\tnew\ttechnologies\tsuch\tas\tGoogle+\twhich\tfacilitates\tcontacting,\tsharing\tin\tcertain\tenvironments\tand\tworking\tcollaboratively\twith\tthe\thelp\tof\tcloud\tsupport\tin\ttheir\tlessons\teffectively.\tThis study aims to examine pre-service teachers’ opinions regarding the use of Google+ to support lesson activities.\tIn\tthis\tstudy\tthe\tdata\twas\tcollected\tusing\tsemi-structured\tinterview\ttechniques\tcarried\tout\twith\tpreservice teachers (n=15\tchosen\tby\tpurposeful sampling.\tThe\tpurposes\tof\tusing\tGoogle+\twere sharing,\tchatting\tand\tcommunication,\twhereas\tGoogle\tDocs\twas\tmostly\tused\tfor\tits\tefficiency,\tinteraction,\tthe\tprudential\tpurpose\tof\tuse\tand\tto\tsupport\tteaching.\tWhen\tthe\tviews\tof\tthe\tpre-service\tteachers\tregarding\tthe\tuse\tof\tGoogle+\twere examined\tit\twas\tfound\tthat\tinterface\tbeing\tthought\tto\tbe\tmore\tcomplex\tthan\tother\tsocial\tnetworks\taffected\tthe teachers’\tfirst\timpressions\tnegatively.\tAs\tthe\tnegative\tfirst\timpression\ttowards\tGoogle+\tchanged\tin\ttime,\tit\twas\tstated to have provided a number of teaching opportunities. Some suggestions regarding the opportunities Google+\toffers\twere\talso\tmade.

  8. Influence of the Kansas Collaborative Research Network on teacher beliefs, instructional practices and technology integration

    Science.gov (United States)

    Andersen, Gary G.

    Student-centered inquiry has been advocated for a lengthy period of time, through various waves of reform, and in 1996 was included in the vision of the National Science Education Standards. In 1997, the United States Department of Education awarded Kansas City, Kansas Public Schools a Technology Innovation Challenge Grant to support the Kansas Collaborative Research Network (KanCRN), which was an attempt to fulfill this vision by engaging teachers and students in scientific inquiry. KanCRN supported inquiry by providing teachers of various disciplines with project-based professional development, on-line curriculum and research tools, mentors, materials and equipment. This study examines the influences of KanCRN interventions on teachers' beliefs, classroom practices, technology skill-efficacies, and the integration of technology into classroom practices. Background characteristics of teachers and the influence of contemporary school-based professional development also were included in the research in order to evaluate and compare their impact on participation in KanCRN and the teacher outcome variables. Survey data collected on participation in professional development, beliefs and teaching practices were analyzed using a process that included: (a) factor analysis to assure reliability of constructs, (b) generation of theoretical models, and (c) analysis of those models using structural equation analysis. Longitudinal data concerning teacher beliefs and practices also were examined with a paired-comparison t-test. Analysis of the structural models revealed that KanCRN had significant and positive influences on teachers': (a) beliefs about student inquiry abilities, (b) beliefs about authentic and engaging work, (c) self-efficacy in support of inquiry, (d) self-reported content expertise, (e) frequency of use of authentic/engaging classwork, (f) frequency of use of the research process, (g) frequency of use of project/problem-based learning, (h) technology self

  9. Genome-scale metabolic network of Cordyceps militaris useful for comparative analysis of entomopathogenic fungi.

    Science.gov (United States)

    Vongsangnak, Wanwipa; Raethong, Nachon; Mujchariyakul, Warasinee; Nguyen, Nam Ninh; Leong, Hon Wai; Laoteng, Kobkul

    2017-08-30

    The first genome-scale metabolic network of Cordyceps militaris (iWV1170) was constructed representing its whole metabolisms, which consisted of 894 metabolites and 1,267 metabolic reactions across five compartments, including the plasma membrane, cytoplasm, mitochondria, peroxisome and extracellular space. The iWV1170 could be exploited to explain its phenotypes of growth ability, cordycepin and other metabolites production on various substrates. A high number of genes encoding extracellular enzymes for degradation of complex carbohydrates, lipids and proteins were existed in C. militaris genome. By comparative genome-scale analysis, the adenine metabolic pathway towards putative cordycepin biosynthesis was reconstructed, indicating their evolutionary relationships across eleven species of entomopathogenic fungi. The overall metabolic routes involved in the putative cordycepin biosynthesis were also identified in C. militaris, including central carbon metabolism, amino acid metabolism (glycine, l-glutamine and l-aspartate) and nucleotide metabolism (adenosine and adenine). Interestingly, a lack of the sequence coding for ribonucleotide reductase inhibitor was observed in C. militaris that might contribute to its over-production of cordycepin. Copyright © 2017. Published by Elsevier B.V.

  10. In Search of Practitioner-Based Social Capital: A Social Network Analysis Tool for Understanding and Facilitating Teacher Collaboration in a US-Based STEM Professional Development Program

    Science.gov (United States)

    Baker-Doyle, Kira J.; Yoon, Susan A.

    2011-01-01

    This paper presents the first in a series of studies on the informal advice networks of a community of teachers in an in-service professional development program. The aim of the research was to use Social Network Analysis as a methodological tool to reveal the social networks developed by the teachers, and to examine whether these networks…

  11. Genome-scale reconstruction and analysis of the metabolic network in the hyperthermophilic archaeon Sulfolobus solfataricus.

    Directory of Open Access Journals (Sweden)

    Thomas Ulas

    Full Text Available We describe the reconstruction of a genome-scale metabolic model of the crenarchaeon Sulfolobus solfataricus, a hyperthermoacidophilic microorganism. It grows in terrestrial volcanic hot springs with growth occurring at pH 2-4 (optimum 3.5 and a temperature of 75-80°C (optimum 80°C. The genome of Sulfolobus solfataricus P2 contains 2,992,245 bp on a single circular chromosome and encodes 2,977 proteins and a number of RNAs. The network comprises 718 metabolic and 58 transport/exchange reactions and 705 unique metabolites, based on the annotated genome and available biochemical data. Using the model in conjunction with constraint-based methods, we simulated the metabolic fluxes induced by different environmental and genetic conditions. The predictions were compared to experimental measurements and phenotypes of S. solfataricus. Furthermore, the performance of the network for 35 different carbon sources known for S. solfataricus from the literature was simulated. Comparing the growth on different carbon sources revealed that glycerol is the carbon source with the highest biomass flux per imported carbon atom (75% higher than glucose. Experimental data was also used to fit the model to phenotypic observations. In addition to the commonly known heterotrophic growth of S. solfataricus, the crenarchaeon is also able to grow autotrophically using the hydroxypropionate-hydroxybutyrate cycle for bicarbonate fixation. We integrated this pathway into our model and compared bicarbonate fixation with growth on glucose as sole carbon source. Finally, we tested the robustness of the metabolism with respect to gene deletions using the method of Minimization of Metabolic Adjustment (MOMA, which predicted that 18% of all possible single gene deletions would be lethal for the organism.

  12. Prediction of Prospective Mathematics Teachers' Academic Success in Entering Graduate Education by Using Back-Propagation Neural Network

    Science.gov (United States)

    Bahadir, Elif

    2016-01-01

    The purpose of this study is to examine a neural network based approach to predict achievement in graduate education for Elementary Mathematics prospective teachers. With the help of this study, it can be possible to make an effective prediction regarding the students' achievement in graduate education with Artificial Neural Networks (ANN). Two…

  13. Incorporating Collaborative, Interactive Experiences into a Technology-Facilitated Professional Learning Network for Pre-Service Science Teachers

    Science.gov (United States)

    Delaney, Seamus; Redman, Christine

    2014-01-01

    This paper describes the utilisation of a technology-facilitated professional learning network (PLN) for pre-service teachers, centred on chemical demonstrations. The network provided direct experiences designed to extend their pedagogical content knowledge on demonstrations in Chemistry teaching. It provided scaffolded opportunities to…

  14. Reconstructing Genome-Wide Protein–Protein Interaction Networks Using Multiple Strategies with Homologous Mapping

    Science.gov (United States)

    Lo, Yu-Shu; Huang, Sing-Han; Luo, Yong-Chun; Lin, Chun-Yu; Yang, Jinn-Moon

    2015-01-01

    PPIs share similar biological processes and cellular components, and the reconstructed genome-wide PPI network can reflect network topology and modularity. We believe that our method is useful for inferring reliable PPIs and reconstructing a comprehensive PPI network of an interesting organism. PMID:25602759

  15. Coevolution analysis of Hepatitis C virus genome to identify the structural and functional dependency network of viral proteins

    Science.gov (United States)

    Champeimont, Raphaël; Laine, Elodie; Hu, Shuang-Wei; Penin, Francois; Carbone, Alessandra

    2016-05-01

    A novel computational approach of coevolution analysis allowed us to reconstruct the protein-protein interaction network of the Hepatitis C Virus (HCV) at the residue resolution. For the first time, coevolution analysis of an entire viral genome was realized, based on a limited set of protein sequences with high sequence identity within genotypes. The identified coevolving residues constitute highly relevant predictions of protein-protein interactions for further experimental identification of HCV protein complexes. The method can be used to analyse other viral genomes and to predict the associated protein interaction networks.

  16. Analyzing and interpreting genome data at the network level with ConsensusPathDB.

    Science.gov (United States)

    Herwig, Ralf; Hardt, Christopher; Lienhard, Matthias; Kamburov, Atanas

    2016-10-01

    ConsensusPathDB consists of a comprehensive collection of human (as well as mouse and yeast) molecular interaction data integrated from 32 different public repositories and a web interface featuring a set of computational methods and visualization tools to explore these data. This protocol describes the use of ConsensusPathDB (http://consensuspathdb.org) with respect to the functional and network-based characterization of biomolecules (genes, proteins and metabolites) that are submitted to the system either as a priority list or together with associated experimental data such as RNA-seq. The tool reports interaction network modules, biochemical pathways and functional information that are significantly enriched by the user's input, applying computational methods for statistical over-representation, enrichment and graph analysis. The results of this protocol can be observed within a few minutes, even with genome-wide data. The resulting network associations can be used to interpret high-throughput data mechanistically, to characterize and prioritize biomarkers, to integrate different omics levels, to design follow-up functional assay experiments and to generate topology for kinetic models at different scales.

  17. Challenges and strategies for implementing genomic services in diverse settings: experiences from the Implementing GeNomics In pracTicE (IGNITE) network.

    Science.gov (United States)

    Sperber, Nina R; Carpenter, Janet S; Cavallari, Larisa H; J Damschroder, Laura; Cooper-DeHoff, Rhonda M; Denny, Joshua C; Ginsburg, Geoffrey S; Guan, Yue; Horowitz, Carol R; Levy, Kenneth D; Levy, Mia A; Madden, Ebony B; Matheny, Michael E; Pollin, Toni I; Pratt, Victoria M; Rosenman, Marc; Voils, Corrine I; W Weitzel, Kristen; Wilke, Russell A; Ryanne Wu, R; Orlando, Lori A

    2017-05-22

    To realize potential public health benefits from genetic and genomic innovations, understanding how best to implement the innovations into clinical care is important. The objective of this study was to synthesize data on challenges identified by six diverse projects that are part of a National Human Genome Research Institute (NHGRI)-funded network focused on implementing genomics into practice and strategies to overcome these challenges. We used a multiple-case study approach with each project considered as a case and qualitative methods to elicit and describe themes related to implementation challenges and strategies. We describe challenges and strategies in an implementation framework and typology to enable consistent definitions and cross-case comparisons. Strategies were linked to challenges based on expert review and shared themes. Three challenges were identified by all six projects, and strategies to address these challenges varied across the projects. One common challenge was to increase the relative priority of integrating genomics within the health system electronic health record (EHR). Four projects used data warehousing techniques to accomplish the integration. The second common challenge was to strengthen clinicians' knowledge and beliefs about genomic medicine. To overcome this challenge, all projects developed educational materials and conducted meetings and outreach focused on genomic education for clinicians. The third challenge was engaging patients in the genomic medicine projects. Strategies to overcome this challenge included use of mass media to spread the word, actively involving patients in implementation (e.g., a patient advisory board), and preparing patients to be active participants in their healthcare decisions. This is the first collaborative evaluation focusing on the description of genomic medicine innovations implemented in multiple real-world clinical settings. Findings suggest that strategies to facilitate integration of genomic

  18. Neural Network Prediction of Translation Initiation Sites in Eukaryotes: Perspectives for EST and Genome analysis

    DEFF Research Database (Denmark)

    Pedersen, Anders Gorm; Nielsen, Henrik

    1997-01-01

    Translation in eukaryotes does not always start at the first AUG in an mRNA, implying that context information also plays a role.This makes prediction of translation initiation sites a non-trivial task, especially when analysing EST and genome data where the entire mature mRNA sequence is not known...... and global sequence information. Furthermore, analysis of false predictions shows that AUGs in frame with the actual start codon are more frequently selected than out-of-frame AUGs, suggesting that our nteworks use reading frame detection. A number of conflicts between neural network predictions and database...... annotations are analysed in detail, leading to identification of possible database errors....

  19. Networks of lexical borrowing and lateral gene transfer in language and genome evolution.

    Science.gov (United States)

    List, Johann-Mattis; Nelson-Sathi, Shijulal; Geisler, Hans; Martin, William

    2014-02-01

    Like biological species, languages change over time. As noted by Darwin, there are many parallels between language evolution and biological evolution. Insights into these parallels have also undergone change in the past 150 years. Just like genes, words change over time, and language evolution can be likened to genome evolution accordingly, but what kind of evolution? There are fundamental differences between eukaryotic and prokaryotic evolution. In the former, natural variation entails the gradual accumulation of minor mutations in alleles. In the latter, lateral gene transfer is an integral mechanism of natural variation. The study of language evolution using biological methods has attracted much interest of late, most approaches focusing on language tree construction. These approaches may underestimate the important role that borrowing plays in language evolution. Network approaches that were originally designed to study lateral gene transfer may provide more realistic insights into the complexities of language evolution.

  20. GDTN: Genome-Based Delay Tolerant Network Formation in Heterogeneous 5G Using Inter-UA Collaboration.

    Science.gov (United States)

    You, Ilsun; Sharma, Vishal; Atiquzzaman, Mohammed; Choo, Kim-Kwang Raymond

    2016-01-01

    With a more Internet-savvy and sophisticated user base, there are more demands for interactive applications and services. However, it is a challenge for existing radio access networks (e.g. 3G and 4G) to cope with the increasingly demanding requirements such as higher data rates and wider coverage area. One potential solution is the inter-collaborative deployment of multiple radio devices in a 5G setting designed to meet exacting user demands, and facilitate the high data rate requirements in the underlying networks. These heterogeneous 5G networks can readily resolve the data rate and coverage challenges. Networks established using the hybridization of existing networks have diverse military and civilian applications. However, there are inherent limitations in such networks such as irregular breakdown, node failures, and halts during speed transmissions. In recent years, there have been attempts to integrate heterogeneous 5G networks with existing ad hoc networks to provide a robust solution for delay-tolerant transmissions in the form of packet switched networks. However, continuous connectivity is still required in these networks, in order to efficiently regulate the flow to allow the formation of a robust network. Therefore, in this paper, we present a novel network formation consisting of nodes from different network maneuvered by Unmanned Aircraft (UA). The proposed model utilizes the features of a biological aspect of genomes and forms a delay tolerant network with existing network models. This allows us to provide continuous and robust connectivity. We then demonstrate that the proposed network model has an efficient data delivery, lower overheads and lesser delays with high convergence rate in comparison to existing approaches, based on evaluations in both real-time testbed and simulation environment.

  1. Multiple horizontal gene transfer events and domain fusions have created novel regulatory and metabolic networks in the oomycete genome.

    Directory of Open Access Journals (Sweden)

    Paul Francis Morris

    Full Text Available Complex enzymes with multiple catalytic activities are hypothesized to have evolved from more primitive precursors. Global analysis of the Phytophthora sojae genome using conservative criteria for evaluation of complex proteins identified 273 novel multifunctional proteins that were also conserved in P. ramorum. Each of these proteins contains combinations of protein motifs that are not present in bacterial, plant, animal, or fungal genomes. A subset of these proteins were also identified in the two diatom genomes, but the majority of these proteins have formed after the split between diatoms and oomycetes. Documentation of multiple cases of domain fusions that are common to both oomycetes and diatom genomes lends additional support for the hypothesis that oomycetes and diatoms are monophyletic. Bifunctional proteins that catalyze two steps in a metabolic pathway can be used to infer the interaction of orthologous proteins that exist as separate entities in other genomes. We postulated that the novel multifunctional proteins of oomycetes could function as potential Rosetta Stones to identify interacting proteins of conserved metabolic and regulatory networks in other eukaryotic genomes. However ortholog analysis of each domain within our set of 273 multifunctional proteins against 39 sequenced bacterial and eukaryotic genomes, identified only 18 candidate Rosetta Stone proteins. Thus the majority of multifunctional proteins are not Rosetta Stones, but they may nonetheless be useful in identifying novel metabolic and regulatory networks in oomycetes. Phylogenetic analysis of all the enzymes in three pathways with one or more novel multifunctional proteins was conducted to determine the probable origins of individual enzymes. These analyses revealed multiple examples of horizontal transfer from both bacterial genomes and the photosynthetic endosymbiont in the ancestral genome of Stramenopiles. The complexity of the phylogenetic origins of these

  2. Cancer systems biology in the genome sequencing era: part 1, dissecting and modeling of tumor clones and their networks.

    Science.gov (United States)

    Wang, Edwin; Zou, Jinfeng; Zaman, Naif; Beitel, Lenore K; Trifiro, Mark; Paliouras, Miltiadis

    2013-08-01

    Recent tumor genome sequencing confirmed that one tumor often consists of multiple cell subpopulations (clones) which bear different, but related, genetic profiles such as mutation and copy number variation profiles. Thus far, one tumor has been viewed as a whole entity in cancer functional studies. With the advances of genome sequencing and computational analysis, we are able to quantify and computationally dissect clones from tumors, and then conduct clone-based analysis. Emerging technologies such as single-cell genome sequencing and RNA-Seq could profile tumor clones. Thus, we should reconsider how to conduct cancer systems biology studies in the genome sequencing era. We will outline new directions for conducting cancer systems biology by considering that genome sequencing technology can be used for dissecting, quantifying and genetically characterizing clones from tumors. Topics discussed in Part 1 of this review include computationally quantifying of tumor subpopulations; clone-based network modeling, cancer hallmark-based networks and their high-order rewiring principles and the principles of cell survival networks of fast-growing clones. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

  3. Genome-scale reconstruction of metabolic network for a halophilic extremophile, Chromohalobacter salexigens DSM 3043

    Directory of Open Access Journals (Sweden)

    Oner Ebru

    2011-01-01

    Full Text Available Abstract Background Chromohalobacter salexigens (formerly Halomonas elongata DSM 3043 is a halophilic extremophile with a very broad salinity range and is used as a model organism to elucidate prokaryotic osmoadaptation due to its strong euryhaline phenotype. Results C. salexigens DSM 3043's metabolism was reconstructed based on genomic, biochemical and physiological information via a non-automated but iterative process. This manually-curated reconstruction accounts for 584 genes, 1386 reactions, and 1411 metabolites. By using flux balance analysis, the model was extensively validated against literature data on the C. salexigens phenotypic features, the transport and use of different substrates for growth as well as against experimental observations on the uptake and accumulation of industrially important organic osmolytes, ectoine, betaine, and its precursor choline, which play important roles in the adaptive response to osmotic stress. Conclusions This work presents the first comprehensive genome-scale metabolic model of a halophilic bacterium. Being a useful guide for identification and filling of knowledge gaps, the reconstructed metabolic network iOA584 will accelerate the research on halophilic bacteria towards application of systems biology approaches and design of metabolic engineering strategies.

  4. Genome-wide analysis of a Wnt1-regulated transcriptional network implicates neurodegenerative pathways.

    Science.gov (United States)

    Wexler, Eric M; Rosen, Ezra; Lu, Daning; Osborn, Gregory E; Martin, Elizabeth; Raybould, Helen; Geschwind, Daniel H

    2011-10-04

    Wnt proteins are critical to mammalian brain development and function. The canonical Wnt signaling pathway involves the stabilization and nuclear translocation of β-catenin; however, Wnt also signals through alternative, noncanonical pathways. To gain a systems-level, genome-wide view of Wnt signaling, we analyzed Wnt1-stimulated changes in gene expression by transcriptional microarray analysis in cultured human neural progenitor (hNP) cells at multiple time points over a 72-hour time course. We observed a widespread oscillatory-like pattern of changes in gene expression, involving components of both the canonical and the noncanonical Wnt signaling pathways. A higher-order, systems-level analysis that combined independent component analysis, waveform analysis, and mutual information-based network construction revealed effects on pathways related to cell death and neurodegenerative disease. Wnt effectors were tightly clustered with presenilin1 (PSEN1) and granulin (GRN), which cause dominantly inherited forms of Alzheimer's disease and frontotemporal dementia (FTD), respectively. We further explored a potential link between Wnt1 and GRN and found that Wnt1 decreased GRN expression by hNPs. Conversely, GRN knockdown increased WNT1 expression, demonstrating that Wnt and GRN reciprocally regulate each other. Finally, we provided in vivo validation of the in vitro findings by analyzing gene expression data from individuals with FTD. These unbiased and genome-wide analyses provide evidence for a connection between Wnt signaling and the transcriptional regulation of neurodegenerative disease genes.

  5. Genome-wide analysis of LXRα activation reveals new transcriptional networks in human atherosclerotic foam cells.

    Science.gov (United States)

    Feldmann, Radmila; Fischer, Cornelius; Kodelja, Vitam; Behrens, Sarah; Haas, Stefan; Vingron, Martin; Timmermann, Bernd; Geikowski, Anne; Sauer, Sascha

    2013-04-01

    Increased physiological levels of oxysterols are major risk factors for developing atherosclerosis and cardiovascular disease. Lipid-loaded macrophages, termed foam cells, are important during the early development of atherosclerotic plaques. To pursue the hypothesis that ligand-based modulation of the nuclear receptor LXRα is crucial for cell homeostasis during atherosclerotic processes, we analysed genome-wide the action of LXRα in foam cells and macrophages. By integrating chromatin immunoprecipitation-sequencing (ChIP-seq) and gene expression profile analyses, we generated a highly stringent set of 186 LXRα target genes. Treatment with the nanomolar-binding ligand T0901317 and subsequent auto-regulatory LXRα activation resulted in sequence-dependent sharpening of the genome-binding patterns of LXRα. LXRα-binding loci that correlated with differential gene expression revealed 32 novel target genes with potential beneficial effects, which in part explained the implications of disease-associated genetic variation data. These observations identified highly integrated LXRα ligand-dependent transcriptional networks, including the APOE/C1/C4/C2-gene cluster, which contribute to the reversal of cholesterol efflux and the dampening of inflammation processes in foam cells to prevent atherogenesis.

  6. Weighted Interaction SNP Hub (WISH) network method for building genetic networks for complex diseases and traits using whole genome genotype data.

    Science.gov (United States)

    Kogelman, Lisette J A; Kadarmideen, Haja N

    2014-01-01

    High-throughput genotype (HTG) data has been used primarily in genome-wide association (GWA) studies; however, GWA results explain only a limited part of the complete genetic variation of traits. In systems genetics, network approaches have been shown to be able to identify pathways and their underlying causal genes to unravel the biological and genetic background of complex diseases and traits, e.g., the Weighted Gene Co-expression Network Analysis (WGCNA) method based on microarray gene expression data. The main objective of this study was to develop a scale-free weighted genetic interaction network method using whole genome HTG data in order to detect biologically relevant pathways and potential genetic biomarkers for complex diseases and traits. We developed the Weighted Interaction SNP Hub (WISH) network method that uses HTG data to detect genome-wide interactions between single nucleotide polymorphism (SNPs) and its relationship with complex traits. Data dimensionality reduction was achieved by selecting SNPs based on its: 1) degree of genome-wide significance and 2) degree of genetic variation in a population. Network construction was based on pairwise Pearson's correlation between SNP genotypes or the epistatic interaction effect between SNP pairs. To identify modules the Topological Overlap Measure (TOM) was calculated, reflecting the degree of overlap in shared neighbours between SNP pairs. Modules, clusters of highly interconnected SNPs, were defined using a tree-cutting algorithm on the SNP dendrogram created from the dissimilarity TOM (1-TOM). Modules were selected for functional annotation based on their association with the trait of interest, defined by the Genome-wide Module Association Test (GMAT). We successfully tested the established WISH network method using simulated and real SNP interaction data and GWA study results for carcass weight in a pig resource population; this resulted in detecting modules and key functional and biological pathways

  7. A genome scale metabolic network for rice and accompanying analysis of tryptophan, auxin and serotonin biosynthesis regulation under biotic stress

    Science.gov (United States)

    Functional annotations of large plant genome projects mostly provide information on gene function and gene families based on the presence of protein domains and gene homology, but not necessarily in association with gene expression or metabolic and regulatory networks. These additional annotations a...

  8. Genomic and network patterns of schizophrenia genetic variation in human evolutionary accelerated regions.

    Science.gov (United States)

    Xu, Ke; Schadt, Eric E; Pollard, Katherine S; Roussos, Panos; Dudley, Joel T

    2015-05-01

    The population persistence of schizophrenia despite associated reductions in fitness and fecundity suggests that the genetic basis of schizophrenia has a complex evolutionary history. A recent meta-analysis of schizophrenia genome-wide association studies offers novel opportunities for assessment of the evolutionary trajectories of schizophrenia-associated loci. In this study, we hypothesize that components of the genetic architecture of schizophrenia are attributable to human lineage-specific evolution. Our results suggest that schizophrenia-associated loci enrich in genes near previously identified human accelerated regions (HARs). Specifically, we find that genes near HARs conserved in nonhuman primates (pHARs) are enriched for schizophrenia-associated loci, and that pHAR-associated schizophrenia genes are under stronger selective pressure than other schizophrenia genes and other pHAR-associated genes. We further evaluate pHAR-associated schizophrenia genes in regulatory network contexts to investigate associated molecular functions and mechanisms. We find that pHAR-associated schizophrenia genes significantly enrich in a GABA-related coexpression module that was previously found to be differentially regulated in schizophrenia affected individuals versus healthy controls. In another two independent networks constructed from gene expression profiles from prefrontal cortex samples, we find that pHAR-associated schizophrenia genes are located in more central positions and their average path lengths to the other nodes are significantly shorter than those of other schizophrenia genes. Together, our results suggest that HARs are associated with potentially important functional roles in the genetic architecture of schizophrenia.

  9. Identification of the minimal connected network of transcription factors by transcriptomic and genomic data integration.

    Science.gov (United States)

    Essaghir, Ahmed

    2014-01-01

    Thanks to high-throughput experiments, biological conditions can be investigated at both the entire genomic and transcriptomic levels. In addition, protein-protein interaction (PPI) data are widely available for well-studied organisms, such as human. In this chapter, we will present an integrative approach that makes use of these data to find the PPI module involving the key regulated transcription factors shared by a number of given conditions. These conditions could be for instance different cancer types. Briefly, for the studied conditions, we need to identify commonly affected chromosomal regions subjected to copy number alterations together with the identification of differentially expressed list of genes in each condition. Transcription factor activity will be inferred from these regulated gene lists. Then, we will define TFs, for which the activity could be explained by an associative effect of both loci copy number alteration and gene expression levels of their coding genes. PPI networks could be mined, afterwards, using appropriate algorithms to find the significant module that connect those TFs together. This module could be viewed as the minimal connected network of TFs, the regulation of which is shared between the investigated conditions.

  10. FunCoup 3.0: database of genome-wide functional coupling networks.

    Science.gov (United States)

    Schmitt, Thomas; Ogris, Christoph; Sonnhammer, Erik L L

    2014-01-01

    We present an update of the FunCoup database (http://FunCoup.sbc.su.se) of functional couplings, or functional associations, between genes and gene products. Identifying these functional couplings is an important step in the understanding of higher level mechanisms performed by complex cellular processes. FunCoup distinguishes between four classes of couplings: participation in the same signaling cascade, participation in the same metabolic process, co-membership in a protein complex and physical interaction. For each of these four classes, several types of experimental and statistical evidence are combined by Bayesian integration to predict genome-wide functional coupling networks. The FunCoup framework has been completely re-implemented to allow for more frequent future updates. It contains many improvements, such as a regularization procedure to automatically downweight redundant evidences and a novel method to incorporate phylogenetic profile similarity. Several datasets have been updated and new data have been added in FunCoup 3.0. Furthermore, we have developed a new Web site, which provides powerful tools to explore the predicted networks and to retrieve detailed information about the data underlying each prediction.

  11. Integrated genome-scale prediction of detrimental mutations in transcription networks.

    Directory of Open Access Journals (Sweden)

    Mirko Francesconi

    2011-05-01

    Full Text Available A central challenge in genetics is to understand when and why mutations alter the phenotype of an organism. The consequences of gene inhibition have been systematically studied and can be predicted reasonably well across a genome. However, many sequence variants important for disease and evolution may alter gene regulation rather than gene function. The consequences of altering a regulatory interaction (or "edge" rather than a gene (or "node" in a network have not been as extensively studied. Here we use an integrative analysis and evolutionary conservation to identify features that predict when the loss of a regulatory interaction is detrimental in the extensively mapped transcription network of budding yeast. Properties such as the strength of an interaction, location and context in a promoter, regulator and target gene importance, and the potential for compensation (redundancy associate to some extent with interaction importance. Combined, however, these features predict quite well whether the loss of a regulatory interaction is detrimental across many promoters and for many different transcription factors. Thus, despite the potential for regulatory diversity, common principles can be used to understand and predict when changes in regulation are most harmful to an organism.

  12. Parallel Mutual Information Based Construction of Genome-Scale Networks on the Intel® Xeon Phi™ Coprocessor.

    Science.gov (United States)

    Misra, Sanchit; Pamnany, Kiran; Aluru, Srinivas

    2015-01-01

    Construction of whole-genome networks from large-scale gene expression data is an important problem in systems biology. While several techniques have been developed, most cannot handle network reconstruction at the whole-genome scale, and the few that can, require large clusters. In this paper, we present a solution on the Intel Xeon Phi coprocessor, taking advantage of its multi-level parallelism including many x86-based cores, multiple threads per core, and vector processing units. We also present a solution on the Intel® Xeon® processor. Our solution is based on TINGe, a fast parallel network reconstruction technique that uses mutual information and permutation testing for assessing statistical significance. We demonstrate the first ever inference of a plant whole genome regulatory network on a single chip by constructing a 15,575 gene network of the plant Arabidopsis thaliana from 3,137 microarray experiments in only 22 minutes. In addition, our optimization for parallelizing mutual information computation on the Intel Xeon Phi coprocessor holds out lessons that are applicable to other domains.

  13. In times of war, adolescents do not fall silent: Teacher-student social network communication in wartime.

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    Ophir, Yaakov; Rosenberg, Hananel; Asterhan, Christa S C; Schwarz, Baruch B

    2016-01-01

    Exposure to war is associated with psychological disturbances, but ongoing communication between adolescents and teachers may contribute to adolescents' resilience. This study examined the extent and nature of teacher-student communication on Social Network Sites (SNS) during the 2014 Israel-Gaza war. Israeli adolescents (N = 208, 13-18 yrs) completed information about SNS communication. A subset of these (N = 145) completed questionnaires on social rejection and distress sharing on SNS. More than a half (56%) of the respondents communicated with teachers via SNS. The main content category was 'emotional support'. Adolescents' perceived benefits from SNS communication with teachers were associated with distress sharing. Social rejection was negatively associated with emotional support and perceived benefits from SNS communication. We conclude that SNS communication between teachers and students may provide students with easy access to human connections and emotional support, which is likely to contribute to adolescents' resilience in times of war.

  14. The Genome-Wide Interaction Network of Nutrient Stress Genes in Escherichia coli

    Directory of Open Access Journals (Sweden)

    Jean-Philippe Côtôé

    2016-11-01

    Full Text Available Conventional efforts to describe essential genes in bacteria have typically emphasized nutrient-rich growth conditions. Of note, however, are the set of genes that become essential when bacteria are grown under nutrient stress. For example, more than 100 genes become indispensable when the model bacterium Escherichia coli is grown on nutrient-limited media, and many of these nutrient stress genes have also been shown to be important for the growth of various bacterial pathogens in vivo. To better understand the genetic network that underpins nutrient stress in E. coli, we performed a genome-scale cross of strains harboring deletions in some 82 nutrient stress genes with the entire E. coli gene deletion collection (Keio to create 315,400 double deletion mutants. An analysis of the growth of the resulting strains on rich microbiological media revealed an average of 23 synthetic sick or lethal genetic interactions for each nutrient stress gene, suggesting that the network defining nutrient stress is surprisingly complex. A vast majority of these interactions involved genes of unknown function or genes of unrelated pathways. The most profound synthetic lethal interactions were between nutrient acquisition and biosynthesis. Further, the interaction map reveals remarkable metabolic robustness in E. coli through pathway redundancies. In all, the genetic interaction network provides a powerful tool to mine and identify missing links in nutrient synthesis and to further characterize genes of unknown function in E. coli. Moreover, understanding of bacterial growth under nutrient stress could aid in the development of novel antibiotic discovery platforms.

  15. A genome-wide MeSH-based literature mining system predicts implicit gene-to-gene relationships and networks.

    Science.gov (United States)

    Xiang, Zuoshuang; Qin, Tingting; Qin, Zhaohui S; He, Yongqun

    2013-10-16

    The large amount of literature in the post-genomics era enables the study of gene interactions and networks using all available articles published for a specific organism. MeSH is a controlled vocabulary of medical and scientific terms that is used by biomedical scientists to manually index articles in the PubMed literature database. We hypothesized that genome-wide gene-MeSH term associations from the PubMed literature database could be used to predict implicit gene-to-gene relationships and networks. While the gene-MeSH associations have been used to detect gene-gene interactions in some studies, different methods have not been well compared, and such a strategy has not been evaluated for a genome-wide literature analysis. Genome-wide literature mining of gene-to-gene interactions allows ranking of the best gene interactions and investigation of comprehensive biological networks at a genome level. The genome-wide GenoMesh literature mining algorithm was developed by sequentially generating a gene-article matrix, a normalized gene-MeSH term matrix, and a gene-gene matrix. The gene-gene matrix relies on the calculation of pairwise gene dissimilarities based on gene-MeSH relationships. An optimized dissimilarity score was identified from six well-studied functions based on a receiver operating characteristic (ROC) analysis. Based on the studies with well-studied Escherichia coli and less-studied Brucella spp., GenoMesh was found to accurately identify gene functions using weighted MeSH terms, predict gene-gene interactions not reported in the literature, and cluster all the genes studied from an organism using the MeSH-based gene-gene matrix. A web-based GenoMesh literature mining program is also available at: http://genomesh.hegroup.org. GenoMesh also predicts gene interactions and networks among genes associated with specific MeSH terms or user-selected gene lists. The GenoMesh algorithm and web program provide the first genome-wide, MeSH-based literature mining

  16. Analyzing the relationship between social networking addiction, interaction anxiousness and levels of loneliness of pre-service teachers

    Directory of Open Access Journals (Sweden)

    Hasan Özgür

    2013-10-01

    Full Text Available In this research, it was aimed to analyze the social networking addiction of pre-service teachers in terms of various variables and evaluate the relationship between social networking addiction and loneliness and interaction anxiousness. The research was designed according to the relational screening model. The study sample included 349 pre-service teachers studying at Trakya University Faculty of Education in 2012-2013 academic year fall term. The data were obtained using Facebook Addiction Scale, Interaction Anxiousness Scale, the UCLA-Loneliness Scale III and personal information form. In analysis of data, descriptive statistics, Mann Whitney U-Test, Kruskal-Wallis H and correlation tests were benefited. The research findings revealed that social networking addiction of pre-service teachers was at a low level, the relationship between interaction anxiousness and social networking addiction was high, and the relationship between the level of loneliness and social networking addiction was at a mid-level. Moreover, in the research a statistically significant difference was obtained between the variables of social networking addiction and frequency of using social networking, gender and the level of grade they study.

  17. Teachers' professional development in a community: A study of the central actors, their networks and web-based learning

    Directory of Open Access Journals (Sweden)

    Jiri Lallimo

    2008-07-01

    Full Text Available The goal of this article was to study teachers' professional development related to web-based learning in the context of the teacher community. The object was to learn in what kind of networks teachers share the knowledge of web-based learning and what are the factors in the community that support or challenge teachers professional development of web-based learning. The findings of the study revealed that there are teachers who are especially active, called the central actors in this study, in the teacher community who collaborate and share knowledge of web-based learning. These central actors share both technical and pedagogical knowledge of web-based learning in networks that include both internal and external relations in the community and involve people, artefacts and a variety of media. Furthermore, the central actors appear to bridge different fields of teaching expertise in their community.According to the central actors' experiences the important factors that support teachers' professional development of web-based learning in the community are; the possibility to learn from colleagues and from everyday working practices, an emotionally safe atmosphere, the leader's personal support and community-level commitment. Also, the flexibility in work planning, challenging pupils, shared lessons with colleagues, training events in an authentic work environment and colleagues' professionalism are considered meaningful for professional development. As challenges, the knowledge sharing of web-based learning in the community needs mutual interests, transactive memory, time and facilities, peer support, a safe atmosphere and meaningful pedagogical practices.On the basis of the findings of the study it is suggested that by intensive collaboration related to web-based learning it may be possible to break the boundaries of individual teachership and create such sociocultural activities which support collaborative professional development in the teacher

  18. Comparing genomes to computer operating systems in terms of the topology and evolution of their regulatory control networks.

    Science.gov (United States)

    Yan, Koon-Kiu; Fang, Gang; Bhardwaj, Nitin; Alexander, Roger P; Gerstein, Mark

    2010-05-18

    The genome has often been called the operating system (OS) for a living organism. A computer OS is described by a regulatory control network termed the call graph, which is analogous to the transcriptional regulatory network in a cell. To apply our firsthand knowledge of the architecture of software systems to understand cellular design principles, we present a comparison between the transcriptional regulatory network of a well-studied bacterium (Escherichia coli) and the call graph of a canonical OS (Linux) in terms of topology and evolution. We show that both networks have a fundamentally hierarchical layout, but there is a key difference: The transcriptional regulatory network possesses a few global regulators at the top and many targets at the bottom; conversely, the call graph has many regulators controlling a small set of generic functions. This top-heavy organization leads to highly overlapping functional modules in the call graph, in contrast to the relatively independent modules in the regulatory network. We further develop a way to measure evolutionary rates comparably between the two networks and explain this difference in terms of network evolution. The process of biological evolution via random mutation and subsequent selection tightly constrains the evolution of regulatory network hubs. The call graph, however, exhibits rapid evolution of its highly connected generic components, made possible by designers' continual fine-tuning. These findings stem from the design principles of the two systems: robustness for biological systems and cost effectiveness (reuse) for software systems.

  19. Acute genome-wide effects of rosiglitazone on PPARγ transcriptional networks in adipocytes.

    Science.gov (United States)

    Haakonsson, Anders Kristian; Stahl Madsen, Maria; Nielsen, Ronni; Sandelin, Albin; Mandrup, Susanne

    2013-09-01

    Peroxisome proliferator-activated receptor γ (PPARγ) is a master regulator of adipocyte differentiation, and genome-wide studies indicate that it is involved in the induction of most adipocyte genes. Here we report, for the first time, the acute effects of the synthetic PPARγ agonist rosiglitazone on the transcriptional network of PPARγ in adipocytes. Treatment with rosiglitazone for 1 hour leads to acute transcriptional activation as well as repression of a number of genes as determined by genome-wide RNA polymerase II occupancy. Unlike what has been shown for many other nuclear receptors, agonist treatment does not lead to major changes in the occurrence of PPARγ binding sites. However, rosiglitazone promotes PPARγ occupancy at many preexisting sites, and this is paralleled by increased occupancy of the mediator subunit MED1. The increase in PPARγ and MED1 binding is correlated with an increase in transcription of nearby genes, indicating that rosiglitazone, in addition to activating the receptor, also promotes its association with DNA, and that this is causally linked to recruitment of mediator and activation of genes. Notably, both rosiglitazone-activated and -repressed genes are induced during adipogenesis. However, rosiglitazone-activated genes are markedly more associated with PPARγ than repressed genes and are highly dependent on PPARγ for expression in adipocytes. By contrast, repressed genes are associated with the other key adipocyte transcription factor CCAAT-enhancer binding proteinα (C/EBPα), and their expression is more dependent on C/EBPα. This suggests that the relative occupancies of PPARγ and C/EBPα are critical for whether genes will be induced or repressed by PPARγ agonist.

  20. Network-assisted investigation of combined causal signals from genome-wide association studies in schizophrenia.

    Science.gov (United States)

    Jia, Peilin; Wang, Lily; Fanous, Ayman H; Pato, Carlos N; Edwards, Todd L; Zhao, Zhongming

    2012-01-01

    With the recent success of genome-wide association studies (GWAS), a wealth of association data has been accomplished for more than 200 complex diseases/traits, proposing a strong demand for data integration and interpretation. A combinatory analysis of multiple GWAS datasets, or an integrative analysis of GWAS data and other high-throughput data, has been particularly promising. In this study, we proposed an integrative analysis framework of multiple GWAS datasets by overlaying association signals onto the protein-protein interaction network, and demonstrated it using schizophrenia datasets. Building on a dense module search algorithm, we first searched for significantly enriched subnetworks for schizophrenia in each single GWAS dataset and then implemented a discovery-evaluation strategy to identify module genes with consistent association signals. We validated the module genes in an independent dataset, and also examined them through meta-analysis of the related SNPs using multiple GWAS datasets. As a result, we identified 205 module genes with a joint effect significantly associated with schizophrenia; these module genes included a number of well-studied candidate genes such as DISC1, GNA12, GNA13, GNAI1, GPR17, and GRIN2B. Further functional analysis suggested these genes are involved in neuronal related processes. Additionally, meta-analysis found that 18 SNPs in 9 module genes had P(meta)<1 × 10⁻⁴, including the gene HLA-DQA1 located in the MHC region on chromosome 6, which was reported in previous studies using the largest cohort of schizophrenia patients to date. These results demonstrated our bi-directional network-based strategy is efficient for identifying disease-associated genes with modest signals in GWAS datasets. This approach can be applied to any other complex diseases/traits where multiple GWAS datasets are available.

  1. Network-assisted investigation of combined causal signals from genome-wide association studies in schizophrenia.

    Directory of Open Access Journals (Sweden)

    Peilin Jia

    Full Text Available With the recent success of genome-wide association studies (GWAS, a wealth of association data has been accomplished for more than 200 complex diseases/traits, proposing a strong demand for data integration and interpretation. A combinatory analysis of multiple GWAS datasets, or an integrative analysis of GWAS data and other high-throughput data, has been particularly promising. In this study, we proposed an integrative analysis framework of multiple GWAS datasets by overlaying association signals onto the protein-protein interaction network, and demonstrated it using schizophrenia datasets. Building on a dense module search algorithm, we first searched for significantly enriched subnetworks for schizophrenia in each single GWAS dataset and then implemented a discovery-evaluation strategy to identify module genes with consistent association signals. We validated the module genes in an independent dataset, and also examined them through meta-analysis of the related SNPs using multiple GWAS datasets. As a result, we identified 205 module genes with a joint effect significantly associated with schizophrenia; these module genes included a number of well-studied candidate genes such as DISC1, GNA12, GNA13, GNAI1, GPR17, and GRIN2B. Further functional analysis suggested these genes are involved in neuronal related processes. Additionally, meta-analysis found that 18 SNPs in 9 module genes had P(meta<1 × 10⁻⁴, including the gene HLA-DQA1 located in the MHC region on chromosome 6, which was reported in previous studies using the largest cohort of schizophrenia patients to date. These results demonstrated our bi-directional network-based strategy is efficient for identifying disease-associated genes with modest signals in GWAS datasets. This approach can be applied to any other complex diseases/traits where multiple GWAS datasets are available.

  2. Statistical estimation of correlated genome associations to a quantitative trait network.

    Directory of Open Access Journals (Sweden)

    Seyoung Kim

    2009-08-01

    Full Text Available Many complex disease syndromes, such as asthma, consist of a large number of highly related, rather than independent, clinical or molecular phenotypes. This raises a new technical challenge in identifying genetic variations associated simultaneously with correlated traits. In this study, we propose a new statistical framework called graph-guided fused lasso (GFlasso to directly and effectively incorporate the correlation structure of multiple quantitative traits such as clinical metrics and gene expressions in association analysis. Our approach represents correlation information explicitly among the quantitative traits as a quantitative trait network (QTN and then leverages this network to encode structured regularization functions in a multivariate regression model over the genotypes and traits. The result is that the genetic markers that jointly influence subgroups of highly correlated traits can be detected jointly with high sensitivity and specificity. While most of the traditional methods examined each phenotype independently and combined the results afterwards, our approach analyzes all of the traits jointly in a single statistical framework. This allows our method to borrow information across correlated phenotypes to discover the genetic markers that perturb a subset of the correlated traits synergistically. Using simulated datasets based on the HapMap consortium and an asthma dataset, we compared the performance of our method with other methods based on single-marker analysis and regression-based methods that do not use any of the relational information in the traits. We found that our method showed an increased power in detecting causal variants affecting correlated traits. Our results showed that, when correlation patterns among traits in a QTN are considered explicitly and directly during a structured multivariate genome association analysis using our proposed methods, the power of detecting true causal SNPs with possibly pleiotropic

  3. Supporting Teachers in Designing CSCL Activities: A Case Study of Principle-Based Pedagogical Patterns in Networked Second Language Classrooms

    Science.gov (United States)

    Wen, Yun; Looi, Chee-Kit; Chen, Wenli

    2012-01-01

    This paper proposes the identification and use of principle-based pedagogical patterns to help teachers to translate design principles into actionable teaching activities, and to scaffold student learning with sufficient flexibility and creativity. A set of pedagogical patterns for networked Second language (L2) learning, categorized and…

  4. Teachers and Coaches in Adolescent Social Networks Are Associated with Healthier Self-Concept and Decreased Substance Use

    Science.gov (United States)

    Dudovitz, Rebecca N.; Chung, Paul J.; Wong, Mitchell D.

    2017-01-01

    Background: Poor academic (eg, "I am a bad student") and behavioral (eg, "I am a troublemaker") self-concepts are strongly linked to adolescent substance use. Social networks likely influence self-concept. However, little is understood about the role teachers and athletic coaches play in shaping both academic and behavioral…

  5. Meneco, a Topology-Based Gap-Filling Tool Applicable to Degraded Genome-Wide Metabolic Networks

    Science.gov (United States)

    Prigent, Sylvain; Frioux, Clémence; Dittami, Simon M.; Larhlimi, Abdelhalim; Collet, Guillaume; Gutknecht, Fabien; Got, Jeanne; Eveillard, Damien; Bourdon, Jérémie; Plewniak, Frédéric; Tonon, Thierry; Siegel, Anne

    2017-01-01

    Increasing amounts of sequence data are becoming available for a wide range of non-model organisms. Investigating and modelling the metabolic behaviour of those organisms is highly relevant to understand their biology and ecology. As sequences are often incomplete and poorly annotated, draft networks of their metabolism largely suffer from incompleteness. Appropriate gap-filling methods to identify and add missing reactions are therefore required to address this issue. However, current tools rely on phenotypic or taxonomic information, or are very sensitive to the stoichiometric balance of metabolic reactions, especially concerning the co-factors. This type of information is often not available or at least prone to errors for newly-explored organisms. Here we introduce Meneco, a tool dedicated to the topological gap-filling of genome-scale draft metabolic networks. Meneco reformulates gap-filling as a qualitative combinatorial optimization problem, omitting constraints raised by the stoichiometry of a metabolic network considered in other methods, and solves this problem using Answer Set Programming. Run on several artificial test sets gathering 10,800 degraded Escherichia coli networks Meneco was able to efficiently identify essential reactions missing in networks at high degradation rates, outperforming the stoichiometry-based tools in scalability. To demonstrate the utility of Meneco we applied it to two case studies. Its application to recent metabolic networks reconstructed for the brown algal model Ectocarpus siliculosus and an associated bacterium Candidatus Phaeomarinobacter ectocarpi revealed several candidate metabolic pathways for algal-bacterial interactions. Then Meneco was used to reconstruct, from transcriptomic and metabolomic data, the first metabolic network for the microalga Euglena mutabilis. These two case studies show that Meneco is a versatile tool to complete draft genome-scale metabolic networks produced from heterogeneous data, and to

  6. Meneco, a Topology-Based Gap-Filling Tool Applicable to Degraded Genome-Wide Metabolic Networks.

    Science.gov (United States)

    Prigent, Sylvain; Frioux, Clémence; Dittami, Simon M; Thiele, Sven; Larhlimi, Abdelhalim; Collet, Guillaume; Gutknecht, Fabien; Got, Jeanne; Eveillard, Damien; Bourdon, Jérémie; Plewniak, Frédéric; Tonon, Thierry; Siegel, Anne

    2017-01-01

    Increasing amounts of sequence data are becoming available for a wide range of non-model organisms. Investigating and modelling the metabolic behaviour of those organisms is highly relevant to understand their biology and ecology. As sequences are often incomplete and poorly annotated, draft networks of their metabolism largely suffer from incompleteness. Appropriate gap-filling methods to identify and add missing reactions are therefore required to address this issue. However, current tools rely on phenotypic or taxonomic information, or are very sensitive to the stoichiometric balance of metabolic reactions, especially concerning the co-factors. This type of information is often not available or at least prone to errors for newly-explored organisms. Here we introduce Meneco, a tool dedicated to the topological gap-filling of genome-scale draft metabolic networks. Meneco reformulates gap-filling as a qualitative combinatorial optimization problem, omitting constraints raised by the stoichiometry of a metabolic network considered in other methods, and solves this problem using Answer Set Programming. Run on several artificial test sets gathering 10,800 degraded Escherichia coli networks Meneco was able to efficiently identify essential reactions missing in networks at high degradation rates, outperforming the stoichiometry-based tools in scalability. To demonstrate the utility of Meneco we applied it to two case studies. Its application to recent metabolic networks reconstructed for the brown algal model Ectocarpus siliculosus and an associated bacterium Candidatus Phaeomarinobacter ectocarpi revealed several candidate metabolic pathways for algal-bacterial interactions. Then Meneco was used to reconstruct, from transcriptomic and metabolomic data, the first metabolic network for the microalga Euglena mutabilis. These two case studies show that Meneco is a versatile tool to complete draft genome-scale metabolic networks produced from heterogeneous data, and to

  7. An evolutionary network of genes present in the eukaryote common ancestor polls genomes on eukaryotic and mitochondrial origin.

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    Thiergart, Thorsten; Landan, Giddy; Schenk, Marc; Dagan, Tal; Martin, William F

    2012-01-01

    To test the predictions of competing and mutually exclusive hypotheses for the origin of eukaryotes, we identified from a sample of 27 sequenced eukaryotic and 994 sequenced prokaryotic genomes 571 genes that were present in the eukaryote common ancestor and that have homologues among eubacterial and archaebacterial genomes. Maximum-likelihood trees identified the prokaryotic genomes that most frequently contained genes branching as the sister to the eukaryotic nuclear homologues. Among the archaebacteria, euryarchaeote genomes most frequently harbored the sister to the eukaryotic nuclear gene, whereas among eubacteria, the α-proteobacteria were most frequently represented within the sister group. Only 3 genes out of 571 gave a 3-domain tree. Homologues from α-proteobacterial genomes that branched as the sister to nuclear genes were found more frequently in genomes of facultatively anaerobic members of the rhiozobiales and rhodospirilliales than in obligate intracellular ricketttsial parasites. Following α-proteobacteria, the most frequent eubacterial sister lineages were γ-proteobacteria, δ-proteobacteria, and firmicutes, which were also the prokaryote genomes least frequently found as monophyletic groups in our trees. Although all 22 higher prokaryotic taxa sampled (crenarchaeotes, γ-proteobacteria, spirochaetes, chlamydias, etc.) harbor genes that branch as the sister to homologues present in the eukaryotic common ancestor, that is not evidence of 22 different prokaryotic cells participating at eukaryote origins because prokaryotic "lineages" have laterally acquired genes for more than 1.5 billion years since eukaryote origins. The data underscore the archaebacterial (host) nature of the eukaryotic informational genes and the eubacterial (mitochondrial) nature of eukaryotic energy metabolism. The network linking genes of the eukaryote ancestor to contemporary homologues distributed across prokaryotic genomes elucidates eukaryote gene origins in a dialect

  8. Functional genomics of the brain: uncovering networks in the CNS using a systems approach.

    Science.gov (United States)

    Konopka, Genevieve

    2011-01-01

    The central nervous system (CNS) is undoubtedly the most complex human organ system in terms of its diverse functions, cellular composition, and connections. Attempts to capture this diversity experimentally were the foundation on which the field of neurobiology was built. Until now though, techniques were either painstakingly slow or insufficient in capturing this heterogeneity. In addition, the combination of multiple layers of information needed for a complete picture of neuronal diversity from the epigenome to the proteome requires an even more complex compilation of data. In this era of high-throughput genomics though, the ability to isolate and profile neurons and brain tissue has increased tremendously and now requires less effort. Both microarrays and next-generation sequencing have identified neuronal transcriptomes and signaling networks involved in normal brain development, as well as in disease. However, the expertise needed to organize and prioritize the resultant data remains substantial. A combination of supervised organization and unsupervised analyses are needed to fully appreciate the underlying structure in these datasets. When utilized effectively, these analyses have yielded striking insights into a number of fundamental questions in neuroscience on topics ranging from the evolution of the human brain to neuropsychiatric and neurodegenerative disorders. Future studies will incorporate these analyses with behavioral and physiological data from patients to more efficiently move toward personalized therapeutics.

  9. Core and region-enriched networks of behaviorally regulated genes and the singing genome

    Science.gov (United States)

    Whitney, Osceola; Pfenning, Andreas R.; Howard, Jason T.; Blatti, Charles A; Liu, Fang; Ward, James M.; Wang, Rui; Audet, Jean-Nicolas; Kellis, Manolis; Mukherjee, Sayan; Sinha, Saurabh; Hartemink, Alexander J.; West, Anne E.; Jarvis, Erich D.

    2015-01-01

    Songbirds represent an important model organism for elucidating molecular mechanisms that link genes with complex behaviors, in part because they have discrete vocal learning circuits that have parallels with those that mediate human speech. We found that ~10% of the genes in the avian genome were regulated by singing, and we found a striking regional diversity of both basal and singing-induced programs in the four key song nuclei of the zebra finch, a vocal learning songbird. The region-enriched patterns were a result of distinct combinations of region-enriched transcription factors (TFs), their binding motifs, and presinging acetylation of histone 3 at lysine 27 (H3K27ac) enhancer activity in the regulatory regions of the associated genes. RNA interference manipulations validated the role of the calcium-response transcription factor (CaRF) in regulating genes preferentially expressed in specific song nuclei in response to singing. Thus, differential combinatorial binding of a small group of activity-regulated TFs and predefined epigenetic enhancer activity influences the anatomical diversity of behaviorally regulated gene networks. PMID:25504732

  10. Genome-wide analysis of the p53 gene regulatory network in the developing mouse kidney.

    Science.gov (United States)

    Li, Yuwen; Liu, Jiao; McLaughlin, Nathan; Bachvarov, Dimcho; Saifudeen, Zubaida; El-Dahr, Samir S

    2013-10-16

    Despite mounting evidence that p53 senses and responds to physiological cues in vivo, existing knowledge regarding p53 function and target genes is largely derived from studies in cancer or stressed cells. Herein we utilize p53 transcriptome and ChIP-Seq (chromatin immunoprecipitation-high throughput sequencing) analyses to identify p53 regulated pathways in the embryonic kidney, an organ that develops via mesenchymal-epithelial interactions. This integrated approach allowed identification of novel genes that are possible direct p53 targets during kidney development. We find the p53-regulated transcriptome in the embryonic kidney is largely composed of genes regulating developmental, morphogenesis, and metabolic pathways. Surprisingly, genes in cell cycle and apoptosis pathways account for kidney lie within proximal promoters of annotated genes compared with 7% in a representative cancer cell line; 25% of the differentially expressed p53-bound genes are present in nephron progenitors and nascent nephrons, including key transcriptional regulators, components of Fgf, Wnt, Bmp, and Notch pathways, and ciliogenesis genes. The results indicate widespread p53 binding to the genome in vivo and context-dependent differences in the p53 regulon between cancer, stress, and development. To our knowledge, this is the first comprehensive analysis of the p53 transcriptome and cistrome in a developing mammalian organ, substantiating the role of p53 as a bona fide developmental regulator. We conclude p53 targets transcriptional networks regulating nephrogenesis and cellular metabolism during kidney development.

  11. Genome-Wide Analysis Revealed the Complex Regulatory Network of Brassinosteroid Effects in Photomorphogenesis

    Institute of Scientific and Technical Information of China (English)

    Li Song; Xiao-Yi Zhou; Li Li; Liang-Jiao Xue; Xi Yang; Hong-Wei Xue

    2009-01-01

    Light and brassinosteroids (BRs) have been proved to be crucial in regulating plant growth and development;however,the mechanism of how they synergistically function is still largely unknown.To explore the underlying mechanisms in photomorphogenesis,genome-wide analyses were carried out through examining the gene expressions of the dark-grown WT or BR biosynthesis-defective mutant det2 seedlings in the presence of light stimuli or exogenous Brassinolide (BL).Results showed that BR deficiency stimulates,while BL treatment suppresses,the expressions of lightresponsive genes and photomorphogenesis,confirming the negative effects of BR in photomorphogenesis.This is consistent with the specific effects of BR on the expression of genes involved in cell wall modification,cellular metabolism and energy utilization during dark-light transition.Further analysis revealed that hormone biosynthesis and signaling-related genes,especially those of auxin,were altered under BL treatment or light stimuli,indicating that BR may modulate photomorphogenesis through synergetic regulation with other hormones.Additionally,suppressed ubiquitin-cycle pathway during light-dark transition hinted the presence of a complicated network among light,hormone,and protein degradation.The study provides the direct evidence of BR effects in photomorphogenesis and identified the genes involved in BR and light signaling pathway,which will help to elucidate the molecular mechanism of plant photomorphogenesis.

  12. Network-Assisted Investigation of Combined Causal Signals from Genome-Wide Association Studies in Schizophrenia

    Science.gov (United States)

    Jia, Peilin; Wang, Lily; Fanous, Ayman H.; Pato, Carlos N.; Edwards, Todd L.; Zhao, Zhongming

    2012-01-01

    With the recent success of genome-wide association studies (GWAS), a wealth of association data has been accomplished for more than 200 complex diseases/traits, proposing a strong demand for data integration and interpretation. A combinatory analysis of multiple GWAS datasets, or an integrative analysis of GWAS data and other high-throughput data, has been particularly promising. In this study, we proposed an integrative analysis framework of multiple GWAS datasets by overlaying association signals onto the protein-protein interaction network, and demonstrated it using schizophrenia datasets. Building on a dense module search algorithm, we first searched for significantly enriched subnetworks for schizophrenia in each single GWAS dataset and then implemented a discovery-evaluation strategy to identify module genes with consistent association signals. We validated the module genes in an independent dataset, and also examined them through meta-analysis of the related SNPs using multiple GWAS datasets. As a result, we identified 205 module genes with a joint effect significantly associated with schizophrenia; these module genes included a number of well-studied candidate genes such as DISC1, GNA12, GNA13, GNAI1, GPR17, and GRIN2B. Further functional analysis suggested these genes are involved in neuronal related processes. Additionally, meta-analysis found that 18 SNPs in 9 module genes had P metadatasets. This approach can be applied to any other complex diseases/traits where multiple GWAS datasets are available. PMID:22792057

  13. Combining Genomics, Metabolome Analysis, and Biochemical Modelling to Understand Metabolic Networks

    Directory of Open Access Journals (Sweden)

    Oliver Fiehn

    2006-04-01

    Full Text Available Now that complete genome sequences are available for a variety of organisms, the elucidation of gene functions involved in metabolism necessarily includes a better understanding of cellular responses upon mutations on all levels of gene products, mRNA, proteins, and metabolites. Such progress is essential since the observable properties of organisms – the phenotypes – are produced by the genotype in juxtaposition with the environment. Whereas much has been done to make mRNA and protein profiling possible, considerably less effort has been put into profiling the end products of gene expression, metabolites. To date, analytical approaches have been aimed primarily at the accurate quantification of a number of pre-defined target metabolites, or at producing fingerprints of metabolic changes without individually determining metabolite identities. Neither of these approaches allows the formation of an in-depth understanding of the biochemical behaviour within metabolic networks. Yet, by carefully choosing protocols for sample preparation and analytical techniques, a number of chemically different classes of compounds can be quantified simultaneously to enable such understanding. In this review, the terms describing various metabolite-oriented approaches are given, and the differences among these approaches are outlined. Metabolite target analysis, metabolite profiling, metabolomics, and metabolic fingerprinting are considered. For each approach, a number of examples are given, and potential applications are discussed.

  14. ALK evaluation in the world of multiplex testing: Network Genomic Medicine (NGM): the Cologne model for implementing personalised oncology.

    Science.gov (United States)

    Heydt, C; Kostenko, A; Merkelbach-Bruse, S; Wolf, J; Büttner, R

    2016-09-01

    Comprehensive molecular genotyping of lung cancers has become a key requirement for guiding therapeutic decisions. As a paradigm model of implementing next-generation comprehensive diagnostics, Network Genomic Medicine (NGM) has established central diagnostic and clinical trial platforms for centralised testing and decentralised personalised treatment in clinical practice. Here, we describe the structures of the NGM network and give a summary of technologies to identify patients with anaplastic lymphoma kinase (ALK) fusion-positive lung adenocarcinomas. As unifying test platforms will become increasingly important for delivering reliable, quick and affordable tests, the NGM diagnostic platform is currently implementing a comprehensive hybrid capture-based parallel sequencing pan-cancer assay.

  15. Establishing a Social Media Presence and Network for the Pennsylvania Earth Science Teachers Association (PAESTA)

    Science.gov (United States)

    Guertin, L. A.; Merkel, C.

    2011-12-01

    In Spring 2011, the Pennsylvania Earth Science Teachers Association (PAESTA) became an official state chapter of the National Earth Science Teachers Association (NESTA). Established with funds from the National Science Foundation, PAESTA is focused on advancing, extending, improving, and coordinating all levels of Earth Science education in Pennsylvania. Our goal is to reach earth science educators across Pennsylvania and beyond who are not physically co-located. An early priority of this new organization was to establish a web presence (http://www.paesta.psu.edu/) and to build an online community to support PAESTA activities and members. PAESTA exists as a distributed group made up of educators across Pennsylvania. Many initial members were participants in summer Earth and space science workshops held at Penn State University, which has allowed for face-to-face connections and network building. PAESTA will hold sessions and a reception at the Pennsylvania Science Teachers Association annual conference. The work of the group also takes place virtually via the PAESTA organizational website, providing professional development opportunities and Earth Science related teaching resources and links. As PAESTA is still in the very early days of its formation, we are utilizing a variety of social media tools to disseminate information and to promote asynchronous discussions around Earth and space science topics and pedagogy. The site features discussion boards for members and non-members to post comments along a specific topic or theme. For example, each month the PAESTA site features an article from one of the National Science Teacher's Association (NSTA)'s journals and encourages teachers to discuss and apply the pedagogical approach or strategy from the article to their classroom situation. We send email blasts so that members learn about organizational news and professional development opportunities. We also leverage in-person training sessions and conference sessions

  16. Integration of structural dynamics and molecular evolution via protein interaction networks: a new era in genomic medicine.

    Science.gov (United States)

    Kumar, Avishek; Butler, Brandon M; Kumar, Sudhir; Ozkan, S Banu

    2015-12-01

    Sequencing technologies are revealing many new non-synonymous single nucleotide variants (nsSNVs) in each personal exome. To assess their functional impacts, comparative genomics is frequently employed to predict if they are benign or not. However, evolutionary analysis alone is insufficient, because it misdiagnoses many disease-associated nsSNVs, such as those at positions involved in protein interfaces, and because evolutionary predictions do not provide mechanistic insights into functional change or loss. Structural analyses can aid in overcoming both of these problems by incorporating conformational dynamics and allostery in nSNV diagnosis. Finally, protein-protein interaction networks using systems-level methodologies shed light onto disease etiology and pathogenesis. Bridging these network approaches with structurally resolved protein interactions and dynamics will advance genomic medicine. Copyright © 2015 Elsevier Ltd. All rights reserved.

  17. Use of online social networking sites among pre-service information technology teachers

    Directory of Open Access Journals (Sweden)

    Elif Buğra Kuzu

    2013-12-01

    Full Text Available The current study aimed to investigate the current status and perceptions of pre-service information technology (IT teachers regarding the use of online social networking sites (SNSs. The investigation was further supported through participant feedback regarding the design and implementation of a blended learning environment to embrace online SNSs in instructional settings. The study had a qualitative nature and employed a focus group interview to collect data. Participants were ten fourth graders who were randomly selected from voluntary undergraduate students enrolled at an IT education department of a Turkish state university. Researchers resorted to content analysis through an inductive coding process, provided themes addressing student perceptions and needs, and proposed implications and suggestions for further instructional practices.

  18. Exploring the metabolic network of the epidemic pathogen Burkholderia cenocepacia J2315 via genome-scale reconstruction

    Directory of Open Access Journals (Sweden)

    Panda Gurudutta

    2011-05-01

    Full Text Available Abstract Background Burkholderia cenocepacia is a threatening nosocomial epidemic pathogen in patients with cystic fibrosis (CF or a compromised immune system. Its high level of antibiotic resistance is an increasing concern in treatments against its infection. Strain B. cenocepacia J2315 is the most infectious isolate from CF patients. There is a strong demand to reconstruct a genome-scale metabolic network of B. cenocepacia J2315 to systematically analyze its metabolic capabilities and its virulence traits, and to search for potential clinical therapy targets. Results We reconstructed the genome-scale metabolic network of B. cenocepacia J2315. An iterative reconstruction process led to the establishment of a robust model, iKF1028, which accounts for 1,028 genes, 859 internal reactions, and 834 metabolites. The model iKF1028 captures important metabolic capabilities of B. cenocepacia J2315 with a particular focus on the biosyntheses of key metabolic virulence factors to assist in understanding the mechanism of disease infection and identifying potential drug targets. The model was tested through BIOLOG assays. Based on the model, the genome annotation of B. cenocepacia J2315 was refined and 24 genes were properly re-annotated. Gene and enzyme essentiality were analyzed to provide further insights into the genome function and architecture. A total of 45 essential enzymes were identified as potential therapeutic targets. Conclusions As the first genome-scale metabolic network of B. cenocepacia J2315, iKF1028 allows a systematic study of the metabolic properties of B. cenocepacia and its key metabolic virulence factors affecting the CF community. The model can be used as a discovery tool to design novel drugs against diseases caused by this notorious pathogen.

  19. The role of genome and gene regulatory network canalization in the evolution of multi-trait polymorphisms and sympatric speciation

    Directory of Open Access Journals (Sweden)

    Hogeweg Paulien

    2009-07-01

    Full Text Available Abstract Background Sexual reproduction has classically been considered as a barrier to the buildup of discrete phenotypic differentiation. This notion has been confirmed by models of sympatric speciation in which a fixed genetic architecture and a linear genotype phenotype mapping were assumed. In this paper we study the influence of a flexible genetic architecture and non-linear genotype phenotype map on differentiation under sexual reproduction. We use an individual based model in which organisms have a genome containing genes and transcription factor binding sites. Mutations involve single genes or binding sites or stretches of genome. The genome codes for a regulatory network that determines the gene expression pattern and hence the phenotype of the organism, resulting in a non-linear genotype phenotype map. The organisms compete in a multi-niche environment, imposing selection for phenotypic differentiation. Results We find as a generic outcome the evolution of discrete clusters of organisms adapted to different niches, despite random mating. Organisms from different clusters are distinct on the genotypic, the network and the phenotypic level. However, the genome and network differences are constrained to a subset of the genome locations, a process we call genotypic canalization. We demonstrate how this canalization leads to an increased robustness to recombination and increasing hybrid fitness. Finally, in case of assortative mating, we explain how this canalization increases the effectiveness of assortativeness. Conclusion We conclude that in case of a flexible genetic architecture and a non-linear genotype phenotype mapping, sexual reproduction does not constrain phenotypic differentiation, but instead constrains the genotypic differences underlying it. We hypothesize that, as genotypic canalization enables differentiation despite random mating and increases the effectiveness of assortative mating, sympatric speciation is more likely

  20. A multi-tissue type genome-scale metabolic network for analysis of whole-body systems physiology

    OpenAIRE

    Feist Adam M; Bordbar Aarash; Usaite-Black Renata; Woodcock Joseph; Palsson Bernhard O; Famili Iman

    2011-01-01

    Abstract Background Genome-scale metabolic reconstructions provide a biologically meaningful mechanistic basis for the genotype-phenotype relationship. The global human metabolic network, termed Recon 1, has recently been reconstructed allowing the systems analysis of human metabolic physiology and pathology. Utilizing high-throughput data, Recon 1 has recently been tailored to different cells and tissues, including the liver, kidney, brain, and alveolar macrophage. These models have shown ut...

  1. Traumatic Brain Injury Induces Genome-Wide Transcriptomic, Methylomic, and Network Perturbations in Brain and Blood Predicting Neurological Disorders

    Directory of Open Access Journals (Sweden)

    Qingying Meng

    2017-02-01

    Full Text Available The complexity of the traumatic brain injury (TBI pathology, particularly concussive injury, is a serious obstacle for diagnosis, treatment, and long-term prognosis. Here we utilize modern systems biology in a rodent model of concussive injury to gain a thorough view of the impact of TBI on fundamental aspects of gene regulation, which have the potential to drive or alter the course of the TBI pathology. TBI perturbed epigenomic programming, transcriptional activities (expression level and alternative splicing, and the organization of genes in networks centered around genes such as Anax2, Ogn, and Fmod. Transcriptomic signatures in the hippocampus are involved in neuronal signaling, metabolism, inflammation, and blood function, and they overlap with those in leukocytes from peripheral blood. The homology between genomic signatures from blood and brain elicited by TBI provides proof of concept information for development of biomarkers of TBI based on composite genomic patterns. By intersecting with human genome-wide association studies, many TBI signature genes and network regulators identified in our rodent model were causally associated with brain disorders with relevant link to TBI. The overall results show that concussive brain injury reprograms genes which could lead to predisposition to neurological and psychiatric disorders, and that genomic information from peripheral leukocytes has the potential to predict TBI pathogenesis in the brain.

  2. Traumatic Brain Injury Induces Genome-Wide Transcriptomic, Methylomic, and Network Perturbations in Brain and Blood Predicting Neurological Disorders.

    Science.gov (United States)

    Meng, Qingying; Zhuang, Yumei; Ying, Zhe; Agrawal, Rahul; Yang, Xia; Gomez-Pinilla, Fernando

    2017-02-01

    The complexity of the traumatic brain injury (TBI) pathology, particularly concussive injury, is a serious obstacle for diagnosis, treatment, and long-term prognosis. Here we utilize modern systems biology in a rodent model of concussive injury to gain a thorough view of the impact of TBI on fundamental aspects of gene regulation, which have the potential to drive or alter the course of the TBI pathology. TBI perturbed epigenomic programming, transcriptional activities (expression level and alternative splicing), and the organization of genes in networks centered around genes such as Anax2, Ogn, and Fmod. Transcriptomic signatures in the hippocampus are involved in neuronal signaling, metabolism, inflammation, and blood function, and they overlap with those in leukocytes from peripheral blood. The homology between genomic signatures from blood and brain elicited by TBI provides proof of concept information for development of biomarkers of TBI based on composite genomic patterns. By intersecting with human genome-wide association studies, many TBI signature genes and network regulators identified in our rodent model were causally associated with brain disorders with relevant link to TBI. The overall results show that concussive brain injury reprograms genes which could lead to predisposition to neurological and psychiatric disorders, and that genomic information from peripheral leukocytes has the potential to predict TBI pathogenesis in the brain.

  3. Metabolic stasis in an ancient symbiosis: genome-scale metabolic networks from two Blattabacterium cuenoti strains, primary endosymbionts of cockroaches.

    Science.gov (United States)

    González-Domenech, Carmen Maria; Belda, Eugeni; Patiño-Navarrete, Rafael; Moya, Andrés; Peretó, Juli; Latorre, Amparo

    2012-01-18

    Cockroaches are terrestrial insects that strikingly eliminate waste nitrogen as ammonia instead of uric acid. Blattabacterium cuenoti (Mercier 1906) strains Bge and Pam are the obligate primary endosymbionts of the cockroaches Blattella germanica and Periplaneta americana, respectively. The genomes of both bacterial endosymbionts have recently been sequenced, making possible a genome-scale constraint-based reconstruction of their metabolic networks. The mathematical expression of a metabolic network and the subsequent quantitative studies of phenotypic features by Flux Balance Analysis (FBA) represent an efficient functional approach to these uncultivable bacteria. We report the metabolic models of Blattabacterium strains Bge (iCG238) and Pam (iCG230), comprising 296 and 289 biochemical reactions, associated with 238 and 230 genes, and 364 and 358 metabolites, respectively. Both models reflect both the striking similarities and the singularities of these microorganisms. FBA was used to analyze the properties, potential and limits of the models, assuming some environmental constraints such as aerobic conditions and the net production of ammonia from these bacterial systems, as has been experimentally observed. In addition, in silico simulations with the iCG238 model have enabled a set of carbon and nitrogen sources to be defined, which would also support a viable phenotype in terms of biomass production in the strain Pam, which lacks the first three steps of the tricarboxylic acid cycle. FBA reveals a metabolic condition that renders these enzymatic steps dispensable, thus offering a possible evolutionary explanation for their elimination. We also confirm, by computational simulations, the fragility of the metabolic networks and their host dependence. The minimized Blattabacterium metabolic networks are surprisingly similar in strains Bge and Pam, after 140 million years of evolution of these endosymbionts in separate cockroach lineages. FBA performed on the

  4. Learning in networks: individual teacher learning versus organizational learning in a regional health-promoting schools network

    National Research Council Canada - National Science Library

    Flaschberger, Edith; Gugglberger, Lisa; Dietscher, Christina

    2013-01-01

    ... (steering group, network coordinator and representatives of the network schools; n = 26). Through thematic analysis and deep-structure analyses, the following three forms of learning in the network were identified...

  5. Sequential computation of elementary modes and minimal cut sets in genome-scale metabolic networks using alternate integer linear programming

    Energy Technology Data Exchange (ETDEWEB)

    Song, Hyun-Seob; Goldberg, Noam; Mahajan, Ashutosh; Ramkrishna, Doraiswami

    2017-03-27

    Elementary (flux) modes (EMs) have served as a valuable tool for investigating structural and functional properties of metabolic networks. Identification of the full set of EMs in genome-scale networks remains challenging due to combinatorial explosion of EMs in complex networks. It is often, however, that only a small subset of relevant EMs needs to be known, for which optimization-based sequential computation is a useful alternative. Most of the currently available methods along this line are based on the iterative use of mixed integer linear programming (MILP), the effectiveness of which significantly deteriorates as the number of iterations builds up. To alleviate the computational burden associated with the MILP implementation, we here present a novel optimization algorithm termed alternate integer linear programming (AILP). Results: Our algorithm was designed to iteratively solve a pair of integer programming (IP) and linear programming (LP) to compute EMs in a sequential manner. In each step, the IP identifies a minimal subset of reactions, the deletion of which disables all previously identified EMs. Thus, a subsequent LP solution subject to this reaction deletion constraint becomes a distinct EM. In cases where no feasible LP solution is available, IP-derived reaction deletion sets represent minimal cut sets (MCSs). Despite the additional computation of MCSs, AILP achieved significant time reduction in computing EMs by orders of magnitude. The proposed AILP algorithm not only offers a computational advantage in the EM analysis of genome-scale networks, but also improves the understanding of the linkage between EMs and MCSs.

  6. Buoyed on All Sides: A Network of Support Guides Teacher Leaders in High-Needs Schools

    Science.gov (United States)

    Suescun, Marisa; Romer, Toby; MacDonald, Elisa

    2012-01-01

    The idea of teacher leadership holds an immense and intuitive appeal. Most educators agree that teacher leaders are essential to fostering a climate of authentic and robust leadership and learning across a school. Teacher leadership is peer leading at its most authentic, demanding, and empowering. While the value of teacher leadership may be…

  7. Strain Dependent Genetic Networks for Antibiotic-Sensitivity in a Bacterial Pathogen with a Large Pan-Genome.

    Directory of Open Access Journals (Sweden)

    Tim van Opijnen

    2016-09-01

    Full Text Available The interaction between an antibiotic and bacterium is not merely restricted to the drug and its direct target, rather antibiotic induced stress seems to resonate through the bacterium, creating selective pressures that drive the emergence of adaptive mutations not only in the direct target, but in genes involved in many different fundamental processes as well. Surprisingly, it has been shown that adaptive mutations do not necessarily have the same effect in all species, indicating that the genetic background influences how phenotypes are manifested. However, to what extent the genetic background affects the manner in which a bacterium experiences antibiotic stress, and how this stress is processed is unclear. Here we employ the genome-wide tool Tn-Seq to construct daptomycin-sensitivity profiles for two strains of the bacterial pathogen Streptococcus pneumoniae. Remarkably, over half of the genes that are important for dealing with antibiotic-induced stress in one strain are dispensable in another. By confirming over 100 genotype-phenotype relationships, probing potassium-loss, employing genetic interaction mapping as well as temporal gene-expression experiments we reveal genome-wide conditionally important/essential genes, we discover roles for genes with unknown function, and uncover parts of the antibiotic's mode-of-action. Moreover, by mapping the underlying genomic network for two query genes we encounter little conservation in network connectivity between strains as well as profound differences in regulatory relationships. Our approach uniquely enables genome-wide fitness comparisons across strains, facilitating the discovery that antibiotic responses are complex events that can vary widely between strains, which suggests that in some cases the emergence of resistance could be strain specific and at least for species with a large pan-genome less predictable.

  8. Strain Dependent Genetic Networks for Antibiotic-Sensitivity in a Bacterial Pathogen with a Large Pan-Genome.

    Science.gov (United States)

    van Opijnen, Tim; Dedrick, Sandra; Bento, José

    2016-09-01

    The interaction between an antibiotic and bacterium is not merely restricted to the drug and its direct target, rather antibiotic induced stress seems to resonate through the bacterium, creating selective pressures that drive the emergence of adaptive mutations not only in the direct target, but in genes involved in many different fundamental processes as well. Surprisingly, it has been shown that adaptive mutations do not necessarily have the same effect in all species, indicating that the genetic background influences how phenotypes are manifested. However, to what extent the genetic background affects the manner in which a bacterium experiences antibiotic stress, and how this stress is processed is unclear. Here we employ the genome-wide tool Tn-Seq to construct daptomycin-sensitivity profiles for two strains of the bacterial pathogen Streptococcus pneumoniae. Remarkably, over half of the genes that are important for dealing with antibiotic-induced stress in one strain are dispensable in another. By confirming over 100 genotype-phenotype relationships, probing potassium-loss, employing genetic interaction mapping as well as temporal gene-expression experiments we reveal genome-wide conditionally important/essential genes, we discover roles for genes with unknown function, and uncover parts of the antibiotic's mode-of-action. Moreover, by mapping the underlying genomic network for two query genes we encounter little conservation in network connectivity between strains as well as profound differences in regulatory relationships. Our approach uniquely enables genome-wide fitness comparisons across strains, facilitating the discovery that antibiotic responses are complex events that can vary widely between strains, which suggests that in some cases the emergence of resistance could be strain specific and at least for species with a large pan-genome less predictable.

  9. WormBase: network access to the genome and biology of Caenorhabditis elegans.

    Science.gov (United States)

    Stein, L; Sternberg, P; Durbin, R; Thierry-Mieg, J; Spieth, J

    2001-01-01

    WormBase (http://www.wormbase.org) is a web-based resource for the Caenorhabditis elegans genome and its biology. It builds upon the existing ACeDB database of the C.elegans genome by providing data curation services, a significantly expanded range of subject areas and a user-friendly front end.

  10. Teacher Directed Design: Content Knowledge, Pedagogy and Assessment under the Nevada K-12 Real-Time Seismic Network

    Science.gov (United States)

    Cantrell, P.; Ewing-Taylor, J.; Crippen, K. J.; Smith, K. D.; Snelson, C. M.

    2004-12-01

    Education professionals and seismologists under the emerging SUN (Shaking Up Nevada) program are leveraging the existing infrastructure of the real-time Nevada K-12 Seismic Network to provide a unique inquiry based science experience for teachers. The concept and effort are driven by teacher needs and emphasize rigorous content knowledge acquisition coupled with the translation of that knowledge into an integrated seismology based earth sciences curriculum development process. We are developing a pedagogical framework, graduate level coursework, and materials to initiate the SUN model for teacher professional development in an effort to integrate the research benefits of real-time seismic data with science education needs in Nevada. A component of SUN is to evaluate teacher acquisition of qualified seismological and earth science information and pedagogy both in workshops and in the classroom and to assess the impact on student achievement. SUN's mission is to positively impact earth science education practices. With the upcoming EarthScope initiative, the program is timely and will incorporate EarthScope real-time seismic data (USArray) and educational materials in graduate course materials and teacher development programs. A number of schools in Nevada are contributing real-time data from both inexpensive and high-quality seismographs that are integrated with Nevada regional seismic network operations as well as the IRIS DMC. A powerful and unique component of the Nevada technology model is that schools can receive "stable" continuous live data feeds from 100's seismograph stations in Nevada, California and world (including live data from Earthworm systems and the IRIS DMC BUD - Buffer of Uniform Data). Students and teachers see their own networked seismograph station within a global context, as participants in regional and global monitoring. The robust real-time Internet communications protocols invoked in the Nevada network provide for local data acquisition

  11. Large-scale reduction of the Bacillus subtilis genome: consequences for the transcriptional network, resource allocation, and metabolism.

    Science.gov (United States)

    Reuß, Daniel R; Altenbuchner, Josef; Mäder, Ulrike; Rath, Hermann; Ischebeck, Till; Sappa, Praveen Kumar; Thürmer, Andrea; Guérin, Cyprien; Nicolas, Pierre; Steil, Leif; Zhu, Bingyao; Feussner, Ivo; Klumpp, Stefan; Daniel, Rolf; Commichau, Fabian M; Völker, Uwe; Stülke, Jörg

    2017-02-01

    Understanding cellular life requires a comprehensive knowledge of the essential cellular functions, the components involved, and their interactions. Minimized genomes are an important tool to gain this knowledge. We have constructed strains of the model bacterium, Bacillus subtilis, whose genomes have been reduced by ∼36%. These strains are fully viable, and their growth rates in complex medium are comparable to those of wild type strains. An in-depth multi-omics analysis of the genome reduced strains revealed how the deletions affect the transcription regulatory network of the cell, translation resource allocation, and metabolism. A comparison of gene counts and resource allocation demonstrates drastic differences in the two parameters, with 50% of the genes using as little as 10% of translation capacity, whereas the 6% essential genes require 57% of the translation resources. Taken together, the results are a valuable resource on gene dispensability in B. subtilis, and they suggest the roads to further genome reduction to approach the final aim of a minimal cell in which all functions are understood.

  12. CONTINUING EDUCATION TEACHER OF INDIGENOUS AND NON-INDIGENOUS MEDIATED SOCIAL NETWORK ON THE INTERNET: A PERSPECTIVE INTERCULTURAL

    Directory of Open Access Journals (Sweden)

    Maria Cristina Lima Paniago Lopes

    2013-04-01

    Full Text Available This research aims to analyze continuous training of teachers indigenous and non-indigenous, mediated by a social network on Ning called Internet under an intercultural perspective. This social network has come up as a virtual community as they have been established emotional ties, webs of connections and relationships between its participants. This is a qualitative research and collaborative in the sense that the experiences of researchers and teachers are valued and shared within a social context. The results show that participants in the group continuing of education, despite their difficulties using the technology itself and with little technological infrastructure, they see these virtual spaces as a possibility for new discoveries, creations and knowledge production, not forsaking the customs, traditions and their own culture.

  13. A genomic approach to identify regulatory nodes in the transcriptional network of systemic acquired resistance in plants.

    Directory of Open Access Journals (Sweden)

    Dong Wang

    2006-11-01

    Full Text Available Many biological processes are controlled by intricate networks of transcriptional regulators. With the development of microarray technology, transcriptional changes can be examined at the whole-genome level. However, such analysis often lacks information on the hierarchical relationship between components of a given system. Systemic acquired resistance (SAR is an inducible plant defense response involving a cascade of transcriptional events induced by salicylic acid through the transcription cofactor NPR1. To identify additional regulatory nodes in the SAR network, we performed microarray analysis on Arabidopsis plants expressing the NPR1-GR (glucocorticoid receptor fusion protein. Since nuclear translocation of NPR1-GR requires dexamethasone, we were able to control NPR1-dependent transcription and identify direct transcriptional targets of NPR1. We show that NPR1 directly upregulates the expression of eight WRKY transcription factor genes. This large family of 74 transcription factors has been implicated in various defense responses, but no specific WRKY factor has been placed in the SAR network. Identification of NPR1-regulated WRKY factors allowed us to perform in-depth genetic analysis on a small number of WRKY factors and test well-defined phenotypes of single and double mutants associated with NPR1. Among these WRKY factors we found both positive and negative regulators of SAR. This genomics-directed approach unambiguously positioned five WRKY factors in the complex transcriptional regulatory network of SAR. Our work not only discovered new transcription regulatory components in the signaling network of SAR but also demonstrated that functional studies of large gene families have to take into consideration sequence similarity as well as the expression patterns of the candidates.

  14. Counselling Implications of Teachers' Digital Competencies in the Use of Social Networking Sites (SNSs) in the Teaching-Learning Process in Calabar, Nigeria

    Science.gov (United States)

    Eyo, Mfon

    2016-01-01

    The study investigated teachers' digital competencies in the use of Social Networking Sites (SNSs) in the teaching-learning process. It had five research questions and two hypotheses. Adopting a survey design, it used a sample of 250 teachers from 10 out of 16 secondary schools in Calabar Municipal Local Government. A researcher-developed…

  15. Systems genetics of obesity in an F2 pig model by genome-wide association, genetic network and pathway analyses

    Directory of Open Access Journals (Sweden)

    Lisette J. A. Kogelman

    2014-07-01

    Full Text Available Obesity is a complex condition with world-wide exponentially rising prevalence rates, linked with severe diseases like Type 2 Diabetes. Economic and welfare consequences have led to a raised interest in a better understanding of the biological and genetic background. To date, whole genome investigations focusing on single genetic variants have achieved limited success, and the importance of including genetic interactions is becoming evident. Here, the aim was to perform an integrative genomic analysis in an F2 pig resource population that was constructed with an aim to maximize genetic variation of obesity-related phenotypes and genotyped using the 60K SNP chip. Firstly, Genome Wide Association (GWA analysis was performed on the Obesity Index to locate candidate genomic regions that were further validated using combined Linkage Disequilibrium Linkage Analysis and investigated by evaluation of haplotype blocks. We built Weighted Interaction SNP Hub (WISH and differentially wired (DW networks using genotypic correlations amongst obesity-associated SNPs resulting from GWA analysis. GWA results and SNP modules detected by WISH and DW analyses were further investigated by functional enrichment analyses. The functional annotation of SNPs revealed several genes associated with obesity, e.g. NPC2 and OR4D10. Moreover, gene enrichment analyses identified several significantly associated pathways, over and above the GWA study results, that may influence obesity and obesity related diseases, e.g. metabolic processes. WISH networks based on genotypic correlations allowed further identification of various gene ontology terms and pathways related to obesity and related traits, which were not identified by the GWA study. In conclusion, this is the first study to develop a (genetic obesity index and employ systems genetics in a porcine model to provide important insights into the complex genetic architecture associated with obesity and many biological pathways

  16. Systems genetics of obesity in an F2 pig model by genome-wide association, genetic network, and pathway analyses.

    Science.gov (United States)

    Kogelman, Lisette J A; Pant, Sameer D; Fredholm, Merete; Kadarmideen, Haja N

    2014-01-01

    Obesity is a complex condition with world-wide exponentially rising prevalence rates, linked with severe diseases like Type 2 Diabetes. Economic and welfare consequences have led to a raised interest in a better understanding of the biological and genetic background. To date, whole genome investigations focusing on single genetic variants have achieved limited success, and the importance of including genetic interactions is becoming evident. Here, the aim was to perform an integrative genomic analysis in an F2 pig resource population that was constructed with an aim to maximize genetic variation of obesity-related phenotypes and genotyped using the 60K SNP chip. Firstly, Genome Wide Association (GWA) analysis was performed on the Obesity Index to locate candidate genomic regions that were further validated using combined Linkage Disequilibrium Linkage Analysis and investigated by evaluation of haplotype blocks. We built Weighted Interaction SNP Hub (WISH) and differentially wired (DW) networks using genotypic correlations amongst obesity-associated SNPs resulting from GWA analysis. GWA results and SNP modules detected by WISH and DW analyses were further investigated by functional enrichment analyses. The functional annotation of SNPs revealed several genes associated with obesity, e.g., NPC2 and OR4D10. Moreover, gene enrichment analyses identified several significantly associated pathways, over and above the GWA study results, that may influence obesity and obesity related diseases, e.g., metabolic processes. WISH networks based on genotypic correlations allowed further identification of various gene ontology terms and pathways related to obesity and related traits, which were not identified by the GWA study. In conclusion, this is the first study to develop a (genetic) obesity index and employ systems genetics in a porcine model to provide important insights into the complex genetic architecture associated with obesity and many biological pathways that underlie

  17. Observing and Providing Feedback to Teachers of Adults Learning English. CAELA Network Brief

    Science.gov (United States)

    Marshall, Brigitte; Young, Sarah

    2009-01-01

    Effective and collaborative supervision of language teachers involves understanding teacher and learner characteristics and needs, approaching supervision from a developmental rather than an evaluative perspective, and engaging in reflective communication. Teacher observation is an important component of supervision, and there are various ways…

  18. Using a Genome-Scale Metabolic Network Model to Elucidate the Mechanism of Chloroquine Action in Plasmodium falciparum

    Science.gov (United States)

    2017-03-22

    Parasitology: Drugs and Drug Resistance journal homepage: www.elsevier .com/locate/ i jpddrUsing a genome-scale metabolic network model to elucidate...the mechanism of chloroquine action in Plasmodium falciparum Shivendra G. Tewari a , *, Sean T. Prigge b, Jaques Reifman a , Anders Wallqvist a , * a ...authors. E-mail addresses: stewari@bhsai.org (S.G. (S.T. Prigge), jaques.reifman.civ@mail.mil (J. Reifma mil ( A . Wallqvist). http://dx.doi.org/10.1016

  19. Sequential computation of elementary modes and minimal cut sets in genome-scale metabolic networks using alternate integer linear programming.

    Science.gov (United States)

    Song, Hyun-Seob; Goldberg, Noam; Mahajan, Ashutosh; Ramkrishna, Doraiswami

    2017-08-01

    Elementary (flux) modes (EMs) have served as a valuable tool for investigating structural and functional properties of metabolic networks. Identification of the full set of EMs in genome-scale networks remains challenging due to combinatorial explosion of EMs in complex networks. It is often, however, that only a small subset of relevant EMs needs to be known, for which optimization-based sequential computation is a useful alternative. Most of the currently available methods along this line are based on the iterative use of mixed integer linear programming (MILP), the effectiveness of which significantly deteriorates as the number of iterations builds up. To alleviate the computational burden associated with the MILP implementation, we here present a novel optimization algorithm termed alternate integer linear programming (AILP). Our algorithm was designed to iteratively solve a pair of integer programming (IP) and linear programming (LP) to compute EMs in a sequential manner. In each step, the IP identifies a minimal subset of reactions, the deletion of which disables all previously identified EMs. Thus, a subsequent LP solution subject to this reaction deletion constraint becomes a distinct EM. In cases where no feasible LP solution is available, IP-derived reaction deletion sets represent minimal cut sets (MCSs). Despite the additional computation of MCSs, AILP achieved significant time reduction in computing EMs by orders of magnitude. The proposed AILP algorithm not only offers a computational advantage in the EM analysis of genome-scale networks, but also improves the understanding of the linkage between EMs and MCSs. The software is implemented in Matlab, and is provided as supplementary information . hyunseob.song@pnnl.gov. Supplementary data are available at Bioinformatics online.

  20. Non-essential genes form the hubs of genome scale protein function and environmental gene expression networks in Salmonella enterica serovar Typhimurium

    DEFF Research Database (Denmark)

    Rosenkrantz, Jesper T.; Aarts, Henk; Abee, Tjakko

    2013-01-01

    Background: Salmonella Typhimurium is an important pathogen of human and animals. It shows a broad growth range and survives in harsh conditions. The aim of this study was to analyze transcriptional responses to a number of growth and stress conditions as well as the relationship of metabolic...... pathways and/or cell functions at the genome-scale-level by network analysis, and further to explore whether highly connected genes ( hubs) in these networks were essential for growth, stress adaptation and virulence. Results: De novo generated as well as published transcriptional data for 425 selected...... genes under a number of growth and stress conditions were used to construct a bipartite network connecting culture conditions and significantly regulated genes (transcriptional network). Also, a genome scale network was constructed for strain LT2. The latter connected genes with metabolic pathways...

  1. Integrating large-scale functional genomics data to dissect metabolic networks for hydrogen production

    Energy Technology Data Exchange (ETDEWEB)

    Harwood, Caroline S

    2012-12-17

    The goal of this project is to identify gene networks that are critical for efficient biohydrogen production by leveraging variation in gene content and gene expression in independently isolated Rhodopseudomonas palustris strains. Coexpression methods were applied to large data sets that we have collected to define probabilistic causal gene networks. To our knowledge this a first systems level approach that takes advantage of strain-to strain variability to computationally define networks critical for a particular bacterial phenotypic trait.

  2. Open source tool for prediction of genome wide protein-protein interaction network based on ortholog information

    Directory of Open Access Journals (Sweden)

    Pedamallu Chandra Sekhar

    2010-08-01

    Full Text Available Abstract Background Protein-protein interactions are crucially important for cellular processes. Knowledge of these interactions improves the understanding of cell cycle, metabolism, signaling, transport, and secretion. Information about interactions can hint at molecular causes of diseases, and can provide clues for new therapeutic approaches. Several (usually expensive and time consuming experimental methods can probe protein - protein interactions. Data sets, derived from such experiments make the development of prediction methods feasible, and make the creation of protein-protein interaction network predicting tools possible. Methods Here we report the development of a simple open source program module (OpenPPI_predictor that can generate a putative protein-protein interaction network for target genomes. This tool uses the orthologous interactome network data from a related, experimentally studied organism. Results Results from our predictions can be visualized using the Cytoscape visualization software, and can be piped to downstream processing algorithms. We have employed our program to predict protein-protein interaction network for the human parasite roundworm Brugia malayi, using interactome data from the free living nematode Caenorhabditis elegans. Availability The OpenPPI_predictor source code is available from http://tools.neb.com/~posfai/.

  3. Bacterial molecular networks: bridging the gap between functional genomics and dynamical modelling.

    Science.gov (United States)

    van Helden, Jacques; Toussaint, Ariane; Thieffry, Denis

    2012-01-01

    This introductory review synthesizes the contents of the volume Bacterial Molecular Networks of the series Methods in Molecular Biology. This volume gathers 9 reviews and 16 method chapters describing computational protocols for the analysis of metabolic pathways, protein interaction networks, and regulatory networks. Each protocol is documented by concrete case studies dedicated to model bacteria or interacting populations. Altogether, the chapters provide a representative overview of state-of-the-art methods for data integration and retrieval, network visualization, graph analysis, and dynamical modelling.

  4. Identification of Gene Networks for Residual Feed Intake in Angus Cattle Using Genomic Prediction and RNA-seq.

    Directory of Open Access Journals (Sweden)

    Kristina L Weber

    Full Text Available Improvement in feed conversion efficiency can improve the sustainability of beef cattle production, but genomic selection for feed efficiency affects many underlying molecular networks and physiological traits. This study describes the differences between steer progeny of two influential Angus bulls with divergent genomic predictions for residual feed intake (RFI. Eight steer progeny of each sire were phenotyped for growth and feed intake from 8 mo. of age (average BW 254 kg, with a mean difference between sire groups of 4.8 kg until slaughter at 14-16 mo. of age (average BW 534 kg, sire group difference of 28.8 kg. Terminal samples from pituitary gland, skeletal muscle, liver, adipose, and duodenum were collected from each steer for transcriptome sequencing. Gene expression networks were derived using partial correlation and information theory (PCIT, including differentially expressed (DE genes, tissue specific (TS genes, transcription factors (TF, and genes associated with RFI from a genome-wide association study (GWAS. Relative to progeny of the high RFI sire, progeny of the low RFI sire had -0.56 kg/d finishing period RFI (P = 0.05, -1.08 finishing period feed conversion ratio (P = 0.01, +3.3 kg^0.75 finishing period metabolic mid-weight (MMW; P = 0.04, +28.8 kg final body weight (P = 0.01, -12.9 feed bunk visits per day (P = 0.02 with +0.60 min/visit duration (P = 0.01, and +0.0045 carcass specific gravity (weight in air/weight in air-weight in water, a predictor of carcass fat content; P = 0.03. RNA-seq identified 633 DE genes between sire groups among 17,016 expressed genes. PCIT analysis identified >115,000 significant co-expression correlations between genes and 25 TF hubs, i.e. controllers of clusters of DE, TS, and GWAS SNP genes. Pathway analysis suggests low RFI bull progeny possess heightened gut inflammation and reduced fat deposition. This multi-omics analysis shows how differences in RFI genomic breeding values can impact other

  5. Identification of Gene Networks for Residual Feed Intake in Angus Cattle Using Genomic Prediction and RNA-seq.

    Science.gov (United States)

    Weber, Kristina L; Welly, Bryan T; Van Eenennaam, Alison L; Young, Amy E; Porto-Neto, Laercio R; Reverter, Antonio; Rincon, Gonzalo

    2016-01-01

    Improvement in feed conversion efficiency can improve the sustainability of beef cattle production, but genomic selection for feed efficiency affects many underlying molecular networks and physiological traits. This study describes the differences between steer progeny of two influential Angus bulls with divergent genomic predictions for residual feed intake (RFI). Eight steer progeny of each sire were phenotyped for growth and feed intake from 8 mo. of age (average BW 254 kg, with a mean difference between sire groups of 4.8 kg) until slaughter at 14-16 mo. of age (average BW 534 kg, sire group difference of 28.8 kg). Terminal samples from pituitary gland, skeletal muscle, liver, adipose, and duodenum were collected from each steer for transcriptome sequencing. Gene expression networks were derived using partial correlation and information theory (PCIT), including differentially expressed (DE) genes, tissue specific (TS) genes, transcription factors (TF), and genes associated with RFI from a genome-wide association study (GWAS). Relative to progeny of the high RFI sire, progeny of the low RFI sire had -0.56 kg/d finishing period RFI (P = 0.05), -1.08 finishing period feed conversion ratio (P = 0.01), +3.3 kg^0.75 finishing period metabolic mid-weight (MMW; P = 0.04), +28.8 kg final body weight (P = 0.01), -12.9 feed bunk visits per day (P = 0.02) with +0.60 min/visit duration (P = 0.01), and +0.0045 carcass specific gravity (weight in air/weight in air-weight in water, a predictor of carcass fat content; P = 0.03). RNA-seq identified 633 DE genes between sire groups among 17,016 expressed genes. PCIT analysis identified >115,000 significant co-expression correlations between genes and 25 TF hubs, i.e. controllers of clusters of DE, TS, and GWAS SNP genes. Pathway analysis suggests low RFI bull progeny possess heightened gut inflammation and reduced fat deposition. This multi-omics analysis shows how differences in RFI genomic breeding values can impact other

  6. Cancer systems biology in the genome sequencing era: part 2, evolutionary dynamics of tumor clonal networks and drug resistance.

    Science.gov (United States)

    Wang, Edwin; Zou, Jinfeng; Zaman, Naif; Beitel, Lenore K; Trifiro, Mark; Paliouras, Miltiadis

    2013-08-01

    A tumor often consists of multiple cell subpopulations (clones). Current chemo-treatments often target one clone of a tumor. Although the drug kills that clone, other clones overtake it and the tumor recurs. Genome sequencing and computational analysis allows to computational dissection of clones from tumors, while singe-cell genome sequencing including RNA-Seq allows profiling of these clones. This opens a new window for treating a tumor as a system in which clones are evolving. Future cancer systems biology studies should consider a tumor as an evolving system with multiple clones. Therefore, topics discussed in Part 2 of this review include evolutionary dynamics of clonal networks, early-warning signals (e.g., genome duplication events) for formation of fast-growing clones, dissecting tumor heterogeneity, and modeling of clone-clone-stroma interactions for drug resistance. The ultimate goal of the future systems biology analysis is to obtain a 'whole-system' understanding of a tumor and therefore provides a more efficient and personalized management strategies for cancer patients. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

  7. Tapping into Salmonella typhimurium LT2 genome in a quest to explore its therapeutic arsenal: A metabolic network modeling approach.

    Science.gov (United States)

    Mehla, Kusum; Ramana, Jayashree

    2017-02-01

    S. typhimurium, the classical broad-host-range serovar is a widely distributed cause of food-borne illness. Escalating antibiotic resistance and potential of conjugal transmission to other pathogens attributable to its broad spectrum host specificities have aided S. typhimurium to emerge as a global health threat. To keep pace with ever evolving bacterial defenses, there is dire need to restock the antibiotic pipeline. Genome scale metabolic reconstructions present immense possibilities to decipher physiological properties of an organism using constraint-based methods The systems-level approaches of genome scale metabolic networks interrogation open up new avenues of drug target identification against deadly infectious diseases. We performed flux balance analysis and minimization of metabolic adjustment studies of genome scale reconstruction model of S. typhimurium targeted at identifying large number of metabolites with a potential to be utilized as therapeutic drug targets. These constraint based approaches initially predict a set of genes indispensable to bacterial survival by performing gene knockout studies which are then prioritized through a multistep process. Metabolites involved in l-rhamnose biosynthesis, peptidoglycan biosynthesis, fatty acid biosynthesis, and folate biosynthesis pathways were prioritized as candidate drug targets. This study provides a general therapeutic approach which can be effectively applied to other pathogens as well.

  8. Multi-OMICs and Genome Editing Perspectives on Liver Cancer Signaling Networks

    Directory of Open Access Journals (Sweden)

    Shengda Lin

    2016-01-01

    Full Text Available The advent of the human genome sequence and the resulting ~20,000 genes provide a crucial framework for a transition from traditional biology to an integrative “OMICs” arena (Lander et al., 2001; Venter et al., 2001; Kitano, 2002. This brings in a revolution for cancer research, which now enters a big data era. In the past decade, with the facilitation by next-generation sequencing, there have been a huge number of large-scale sequencing efforts, such as The Cancer Genome Atlas (TCGA, the HapMap, and the 1000 genomes project. As a result, a deluge of genomic information becomes available from patients stricken by a variety of cancer types. The list of cancer-associated genes is ever expanding. New discoveries are made on how frequent and highly penetrant mutations, such as those in the telomerase reverse transcriptase (TERT and TP53, function in cancer initiation, progression, and metastasis. Most genes with relatively frequent but weakly penetrant cancer mutations still remain to be characterized. In addition, genes that harbor rare but highly penetrant cancer-associated mutations continue to emerge. Here, we review recent advances related to cancer genomics, proteomics, and systems biology and suggest new perspectives in targeted therapy and precision medicine.

  9. Multi-OMICs and Genome Editing Perspectives on Liver Cancer Signaling Networks

    Science.gov (United States)

    Lin, Shengda; Yin, Yi A.; Jiang, Xiaoqian; Sahni, Nidhi; Yi, Song

    2016-01-01

    The advent of the human genome sequence and the resulting ~20,000 genes provide a crucial framework for a transition from traditional biology to an integrative “OMICs” arena (Lander et al., 2001; Venter et al., 2001; Kitano, 2002). This brings in a revolution for cancer research, which now enters a big data era. In the past decade, with the facilitation by next-generation sequencing, there have been a huge number of large-scale sequencing efforts, such as The Cancer Genome Atlas (TCGA), the HapMap, and the 1000 genomes project. As a result, a deluge of genomic information becomes available from patients stricken by a variety of cancer types. The list of cancer-associated genes is ever expanding. New discoveries are made on how frequent and highly penetrant mutations, such as those in the telomerase reverse transcriptase (TERT) and TP53, function in cancer initiation, progression, and metastasis. Most genes with relatively frequent but weakly penetrant cancer mutations still remain to be characterized. In addition, genes that harbor rare but highly penetrant cancer-associated mutations continue to emerge. Here, we review recent advances related to cancer genomics, proteomics, and systems biology and suggest new perspectives in targeted therapy and precision medicine. PMID:27403431

  10. Generation and Evaluation of a Genome-Scale Metabolic Network Model of Synechococcus elongatus PCC7942

    Directory of Open Access Journals (Sweden)

    Julián Triana

    2014-08-01

    Full Text Available The reconstruction of genome-scale metabolic models and their applications represent a great advantage of systems biology. Through their use as metabolic flux simulation models, production of industrially-interesting metabolites can be predicted. Due to the growing number of studies of metabolic models driven by the increasing genomic sequencing projects, it is important to conceptualize steps of reconstruction and analysis. We have focused our work in the cyanobacterium Synechococcus elongatus PCC7942, for which several analyses and insights are unveiled. A comprehensive approach has been used, which can be of interest to lead the process of manual curation and genome-scale metabolic analysis. The final model, iSyf715 includes 851 reactions and 838 metabolites. A biomass equation, which encompasses elementary building blocks to allow cell growth, is also included. The applicability of the model is finally demonstrated by simulating autotrophic growth conditions of Synechococcus elongatus PCC7942.

  11. Generation and Evaluation of a Genome-Scale Metabolic Network Model of Synechococcus elongatus PCC7942

    Science.gov (United States)

    Triana, Julián; Montagud†, Arnau; Siurana, Maria; Fuente, David; Urchueguía, Arantxa; Gamermann, Daniel; Torres, Javier; Tena, Jose; de Córdoba, Pedro Fernández; Urchueguía, Javier F.

    2014-01-01

    The reconstruction of genome-scale metabolic models and their applications represent a great advantage of systems biology. Through their use as metabolic flux simulation models, production of industrially-interesting metabolites can be predicted. Due to the growing number of studies of metabolic models driven by the increasing genomic sequencing projects, it is important to conceptualize steps of reconstruction and analysis. We have focused our work in the cyanobacterium Synechococcus elongatus PCC7942, for which several analyses and insights are unveiled. A comprehensive approach has been used, which can be of interest to lead the process of manual curation and genome-scale metabolic analysis. The final model, iSyf715 includes 851 reactions and 838 metabolites. A biomass equation, which encompasses elementary building blocks to allow cell growth, is also included. The applicability of the model is finally demonstrated by simulating autotrophic growth conditions of Synechococcus elongatus PCC7942. PMID:25141288

  12. Genomic structure and marker-derived gene networks for growth and meat quality traits of Brazilian Nelore beef cattle.

    Science.gov (United States)

    Mudadu, Maurício A; Porto-Neto, Laercio R; Mokry, Fabiana B; Tizioto, Polyana C; Oliveira, Priscila S N; Tullio, Rymer R; Nassu, Renata T; Niciura, Simone C M; Tholon, Patrícia; Alencar, Maurício M; Higa, Roberto H; Rosa, Antônio N; Feijó, Gélson L D; Ferraz, André L J; Silva, Luiz O C; Medeiros, Sérgio R; Lanna, Dante P; Nascimento, Michele L; Chaves, Amália S; Souza, Andrea R D L; Packer, Irineu U; Torres, Roberto A A; Siqueira, Fabiane; Mourão, Gerson B; Coutinho, Luiz L; Reverter, Antonio; Regitano, Luciana C A

    2016-03-15

    Nelore is the major beef cattle breed in Brazil with more than 130 million heads. Genome-wide association studies (GWAS) are often used to associate markers and genomic regions to growth and meat quality traits that can be used to assist selection programs. An alternative methodology to traditional GWAS that involves the construction of gene network interactions, derived from results of several GWAS is the AWM (Association Weight Matrices)/PCIT (Partial Correlation and Information Theory). With the aim of evaluating the genetic architecture of Brazilian Nelore cattle, we used high-density SNP genotyping data (~770,000 SNP) from 780 Nelore animals comprising 34 half-sibling families derived from highly disseminated and unrelated sires from across Brazil. The AWM/PCIT methodology was employed to evaluate the genes that participate in a series of eight phenotypes related to growth and meat quality obtained from this Nelore sample. Our results indicate a lack of structuring between the individuals studied since principal component analyses were not able to differentiate families by its sires or by its ancestral lineages. The application of the AWM/PCIT methodology revealed a trio of transcription factors (comprising VDR, LHX9 and ZEB1) which in combination connected 66 genes through 359 edges and whose biological functions were inspected, some revealing to participate in biological growth processes in literature searches. The diversity of the Nelore sample studied is not high enough to differentiate among families neither by sires nor by using the available ancestral lineage information. The gene networks constructed from the AWM/PCIT methodology were a useful alternative in characterizing genes and gene networks that were allegedly influential in growth and meat quality traits in Nelore cattle.

  13. atBioNet– an integrated network analysis tool for genomics and biomarker discovery

    Directory of Open Access Journals (Sweden)

    Ding Yijun

    2012-07-01

    Full Text Available Abstract Background Large amounts of mammalian protein-protein interaction (PPI data have been generated and are available for public use. From a systems biology perspective, Proteins/genes interactions encode the key mechanisms distinguishing disease and health, and such mechanisms can be uncovered through network analysis. An effective network analysis tool should integrate different content-specific PPI databases into a comprehensive network format with a user-friendly platform to identify key functional modules/pathways and the underlying mechanisms of disease and toxicity. Results atBioNet integrates seven publicly available PPI databases into a network-specific knowledge base. Knowledge expansion is achieved by expanding a user supplied proteins/genes list with interactions from its integrated PPI network. The statistically significant functional modules are determined by applying a fast network-clustering algorithm (SCAN: a Structural Clustering Algorithm for Networks. The functional modules can be visualized either separately or together in the context of the whole network. Integration of pathway information enables enrichment analysis and assessment of the biological function of modules. Three case studies are presented using publicly available disease gene signatures as a basis to discover new biomarkers for acute leukemia, systemic lupus erythematosus, and breast cancer. The results demonstrated that atBioNet can not only identify functional modules and pathways related to the studied diseases, but this information can also be used to hypothesize novel biomarkers for future analysis. Conclusion atBioNet is a free web-based network analysis tool that provides a systematic insight into proteins/genes interactions through examining significant functional modules. The identified functional modules are useful for determining underlying mechanisms of disease and biomarker discovery. It can be accessed at: http

  14. MOVE : A Multi-Level Ontology-Based Visualization and Exploration Framework for Genomic Networks

    NARCIS (Netherlands)

    Bosman, Diederik W.J.; Blom, Evert-Jan; Ogao, Patrick J.; Kuipers, Oscar P.; Roerdink, Jos B.T.M.; Wingender, E.

    2007-01-01

    Among the various research areas that comprise bioinformatics, systems biology is gaining increasing attention. An important goal of systems biology is the unraveling of dynamic interactions between components of living cells (e.g., proteins, genes). These interactions exist among others on genomic,

  15. Regulatory network construction in Arabidopsis by using genome-wide gene expression quantitative trait loci

    NARCIS (Netherlands)

    Keurentjes, Joost J.B.; Fu, Jingyuan; Terpstra, Inez R.; Garcia, Juan M.; Ackerveken, Guido van den; Snoek, L. Basten; Peeters, Anton J.M.; Vreugdenhil, Dick; Koornneef, Maarten; Jansen, Ritsert C.

    2007-01-01

    Accessions of a plant species can show considerable genetic differences that are analyzed effectively by using recombinant inbred line (RIL) populations. Here we describe the results of genome-wide expression variation analysis in an RIL population of Arabidopsis thaliana. For many genes, variation

  16. Network-based Phenome-Genome Association Prediction by Bi-Random Walk: e0125138

    National Research Council Canada - National Science Library

    MaoQiang Xie; YingJie Xu; YaoGong Zhang; TaeHyun Hwang; Rui Kuang

    2015-01-01

      Motivation The availability of ontologies and systematic documentations of phenotypes and their genetic associations has enabled large-scale network-based global analyses of the association between...

  17. A multi-tissue type genome-scale metabolic network for analysis of whole-body systems physiology

    Directory of Open Access Journals (Sweden)

    Feist Adam M

    2011-10-01

    Full Text Available Abstract Background Genome-scale metabolic reconstructions provide a biologically meaningful mechanistic basis for the genotype-phenotype relationship. The global human metabolic network, termed Recon 1, has recently been reconstructed allowing the systems analysis of human metabolic physiology and pathology. Utilizing high-throughput data, Recon 1 has recently been tailored to different cells and tissues, including the liver, kidney, brain, and alveolar macrophage. These models have shown utility in the study of systems medicine. However, no integrated analysis between human tissues has been done. Results To describe tissue-specific functions, Recon 1 was tailored to describe metabolism in three human cells: adipocytes, hepatocytes, and myocytes. These cell-specific networks were manually curated and validated based on known cellular metabolic functions. To study intercellular interactions, a novel multi-tissue type modeling approach was developed to integrate the metabolic functions for the three cell types, and subsequently used to simulate known integrated metabolic cycles. In addition, the multi-tissue model was used to study diabetes: a pathology with systemic properties. High-throughput data was integrated with the network to determine differential metabolic activity between obese and type II obese gastric bypass patients in a whole-body context. Conclusion The multi-tissue type modeling approach presented provides a platform to study integrated metabolic states. As more cell and tissue-specific models are released, it is critical to develop a framework in which to study their interdependencies.

  18. Candidate states of Helicobacter pylori's genome-scale metabolic network upon application of "loop law" thermodynamic constraints.

    Science.gov (United States)

    Price, Nathan D; Thiele, Ines; Palsson, Bernhard Ø

    2006-06-01

    Constraint-based modeling has proven to be a useful tool in the analysis of biochemical networks. To date, most studies in this field have focused on the use of linear constraints, resulting from mass balance and capacity constraints, which lead to the definition of convex solution spaces. One additional constraint arising out of thermodynamics is known as the "loop law" for reaction fluxes, which states that the net flux around a closed biochemical loop must be zero because no net thermodynamic driving force exists. The imposition of the loop-law can lead to nonconvex solution spaces making the analysis of the consequences of its imposition challenging. A four-step approach is developed here to apply the loop-law to study metabolic network properties: 1), determine linear equality constraints that are necessary (but not necessarily sufficient) for thermodynamic feasibility; 2), tighten V(max) and V(min) constraints to enclose the remaining nonconvex space; 3), uniformly sample the convex space that encloses the nonconvex space using standard Monte Carlo techniques; and 4), eliminate from the resulting set all solutions that violate the loop-law, leaving a subset of steady-state solutions. This subset of solutions represents a uniform random sample of the space that is defined by the additional imposition of the loop-law. This approach is used to evaluate the effect of imposing the loop-law on predicted candidate states of the genome-scale metabolic network of Helicobacter pylori.

  19. Identification of a gene module associated with BMD through the integration of network analysis and genome-wide association data.

    Science.gov (United States)

    Farber, Charles R

    2010-11-01

    Bone mineral density (BMD) is influenced by a complex network of gene interactions; therefore, elucidating the relationships between genes and how those genes, in turn, influence BMD is critical for developing a comprehensive understanding of osteoporosis. To investigate the role of transcriptional networks in the regulation of BMD, we performed a weighted gene coexpression network analysis (WGCNA) using microarray expression data on monocytes from young individuals with low or high BMD. WGCNA groups genes into modules based on patterns of gene coexpression. and our analysis identified 11 gene modules. We observed that the overall expression of one module (referred to as module 9) was significantly higher in the low-BMD group (p = .03). Module 9 was highly enriched for genes belonging to the immune system-related gene ontology (GO) category "response to virus" (p = 7.6 × 10(-11)). Using publically available genome-wide association study data, we independently validated the importance of module 9 by demonstrating that highly connected module 9 hubs were more likely, relative to less highly connected genes, to be genetically associated with BMD. This study highlights the advantages of systems-level analyses to uncover coexpression modules associated with bone mass and suggests that particular monocyte expression patterns may mediate differences in BMD.

  20. MetaNetVar: Pipeline for applying network analysis tools for genomic variants analysis.

    Science.gov (United States)

    Moyer, Eric; Hagenauer, Megan; Lesko, Matthew; Francis, Felix; Rodriguez, Oscar; Nagarajan, Vijayaraj; Huser, Vojtech; Busby, Ben

    2016-01-01

    Network analysis can make variant analysis better. There are existing tools like HotNet2 and dmGWAS that can provide various analytical methods. We developed a prototype of a pipeline called MetaNetVar that allows execution of multiple tools. The code is published at https://github.com/NCBI-Hackathons/Network_SNPs. A working prototype is published as an Amazon Machine Image - ami-4510312f .

  1. Supporting and Supervising Teachers Working With Adults Learning English. CAELA Network Brief

    Science.gov (United States)

    Young, Sarah

    2009-01-01

    This brief provides an overview of the knowledge and skills that administrators need in order to support and supervise teachers of adult English language learners. It begins with a review of resources and literature related to teacher supervision in general and to adult ESL education. It continues with information on the background and…

  2. Attracting, Retaining, and Developing Quality Teachers in Small Schools. Small Schools Network Information Exchange No. 5.

    Science.gov (United States)

    Regional Laboratory for Educational Improvement of the Northeast & Islands, Andover, MA.

    This collection of articles gathers reprinted materials on teacher attraction and retention for small and rural school districts. The material is organized in two sections: (1) Attracting and Retaining Quality Teachers and (2) Challenging and Enriching Current Staff. Reprints from a number of publications present strategies for addressing the…

  3. Determinants of Motivation in Teachers: A Study of Private Secondary Schools Chain Networks in Bahawalpur

    Science.gov (United States)

    Nawaz, Nosheen; Yasin, Hina

    2015-01-01

    Retaining quality employees is the dream of every organization. This research focuses on a big issue arising in the education sector. A large number of teachers are incoming and leaving the private schools of Bahawalpur. Lack of motivation is a major cause of teachers' turnover. Aspire of this research is to find the factors which can motivate…

  4. School Improvement and Staff Development. Documentation and Evaluation Study. A Texas Teacher Corps Network Conference.

    Science.gov (United States)

    Weibly, Gary W.; Olivarez, Ruben Dario

    Summaries are given of the formal presentations, seminar group discussions, and problem solving sessions of a Teacher Corps conference on professional improvement by means of inservice teacher education and improvement of individual school climates. Evaluation of the conference is presented in the form of the Context/Input/Process/Product (CIPP)…

  5. AGI's Earth Science Week and Education Resources Network: Connecting Teachers to Geoscience Organizations and Classroom Resources that Support NGSS Implementation

    Science.gov (United States)

    Robeck, E.; Camphire, G.; Brendan, S.; Celia, T.

    2016-12-01

    There exists a wide array of high quality resources to support K-12 teaching and motivate student interest in the geosciences. Yet, connecting teachers to those resources can be a challenge. Teachers working to implement the NGSS can benefit from accessing the wide range of existing geoscience resources, and from becoming part of supportive networks of geoscience educators, researchers, and advocates. Engaging teachers in such networks can be facilitated by providing them with information about organizations, resources, and opportunities. The American Geoscience Institute (AGI) has developed two key resources that have great value in supporting NGSS implement in these ways. Those are Earth Science Week, and the Education Resources Network in AGI's Center for Geoscience and Society. For almost twenty years, Earth Science Week, has been AGI's premier annual outreach program designed to celebrate the geosciences. Through its extensive web-based resources, as well as the physical kits of posters, DVDs, calendars and other printed materials, Earth Science Week offers an array of resources and opportunities to connect with the education-focused work of important geoscience organizations such as NASA, the National Park Service, HHMI, esri, and many others. Recently, AGI has initiated a process of tagging these and other resources to NGSS so as to facilitate their use as teachers develop their instruction. Organizing Earth Science Week around themes that are compatible with topics within NGSS contributes to the overall coherence of the diverse array of materials, while also suggesting potential foci for investigations and instructional units. More recently, AGI has launched its Center for Geoscience and Society, which is designed to engage the widest range of audiences in building geoscience awareness. As part of the Center's work, it has launched the Education Resources Network (ERN), which is an extensive searchable database of all manner of resources for geoscience

  6. A systems approach to predict oncometabolites via context-specific genome-scale metabolic networks.

    Directory of Open Access Journals (Sweden)

    Hojung Nam

    2014-09-01

    Full Text Available Altered metabolism in cancer cells has been viewed as a passive response required for a malignant transformation. However, this view has changed through the recently described metabolic oncogenic factors: mutated isocitrate dehydrogenases (IDH, succinate dehydrogenase (SDH, and fumarate hydratase (FH that produce oncometabolites that competitively inhibit epigenetic regulation. In this study, we demonstrate in silico predictions of oncometabolites that have the potential to dysregulate epigenetic controls in nine types of cancer by incorporating massive scale genetic mutation information (collected from more than 1,700 cancer genomes, expression profiling data, and deploying Recon 2 to reconstruct context-specific genome-scale metabolic models. Our analysis predicted 15 compounds and 24 substructures of potential oncometabolites that could result from the loss-of-function and gain-of-function mutations of metabolic enzymes, respectively. These results suggest a substantial potential for discovering unidentified oncometabolites in various forms of cancers.

  7. Genome-scale cold stress response regulatory networks in ten Arabidopsis thaliana ecotypes

    DEFF Research Database (Denmark)

    Barah, Pankaj; Jayavelu, Naresh Doni; Rasmussen, Simon

    2013-01-01

    BACKGROUND: Low temperature leads to major crop losses every year. Although several studies have been conducted focusing on diversity of cold tolerance level in multiple phenotypically divergent Arabidopsis thaliana (A. thaliana) ecotypes, genome-scale molecular understanding is still lacking...... using Arabidopsis NimbleGen ATH6 microarrays. In total 6061 transcripts were significantly cold regulated (p majority of the transcripts (75%) showed ecotype specific expression pattern. By using sequence data...... available from Arabidopsis thaliana 1001 genome project, we further investigated sequence polymorphisms in the core cold stress regulon genes. Significant numbers of non-synonymous amino acid changes were observed in the coding region of the CBF regulon genes. Considering the limited knowledge about...

  8. Genomic and Network Patterns of Schizophrenia Genetic Variation in Human Evolutionary Accelerated Regions

    OpenAIRE

    Xu, Ke; Schadt, Eric E.; Pollard, Katherine S.; Roussos, Panos; Joel T Dudley

    2015-01-01

    The population persistence of schizophrenia despite associated reductions in fitness and fecundity suggests that the genetic basis of schizophrenia has a complex evolutionary history. A recent meta-analysis of schizophrenia genome-wide association studies offers novel opportunities for assessment of the evolutionary trajectories of schizophrenia-associated loci. In this study, we hypothesize that components of the genetic architecture of schizophrenia are attributable to human lineage-specifi...

  9. Genomic and Network Patterns of Schizophrenia Genetic Variation in Human Evolutionary Accelerated Regions

    OpenAIRE

    Xu, Ke; Schadt, Eric E.; Pollard, Katherine S.; Roussos, Panos; Dudley, Joel T

    2015-01-01

    The population persistence of schizophrenia despite associated reductions in fitness and fecundity suggests that the genetic basis of schizophrenia has a complex evolutionary history. A recent meta-analysis of schizophrenia genome-wide association studies offers novel opportunities for assessment of the evolutionary trajectories of schizophrenia-associated loci. In this study, we hypothesize that components of the genetic architecture of schizophrenia are attributable to human lineage-specifi...

  10. Data-driven integration of genome-scale regulatory and metabolic network models

    Directory of Open Access Journals (Sweden)

    Saheed eImam

    2015-05-01

    Full Text Available Microbes are diverse and extremely versatile organisms that play vital roles in all ecological niches. Understanding and harnessing microbial systems will be key to the sustainability of our planet. One approach to improving our knowledge of microbial processes is through data-driven and mechanism-informed computational modeling. Individual models of biological networks (such as metabolism, transcription and signaling have played pivotal roles in driving microbial research through the years. These networks, however, are highly interconnected and function in concert – a fact that has led to the development of a variety of approaches aimed at simulating the integrated functions of two or more network types. Though the task of integrating these different models is fraught with new challenges, the large amounts of high-throughput data sets being generated, and algorithms being developed, means that the time is at hand for concerted efforts to build integrated regulatory-metabolic networks in a data-driven fashion. In this perspective, we review current approaches for constructing integrated regulatory-metabolic models and outline new strategies for future development of these network models for any microbial system.

  11. Genome-scale metabolic network validation of Shewanella oneidensis using transposon insertion frequency analysis.

    Directory of Open Access Journals (Sweden)

    Hong Yang

    2014-09-01

    Full Text Available Transposon mutagenesis, in combination with parallel sequencing, is becoming a powerful tool for en-masse mutant analysis. A probability generating function was used to explain observed miniHimar transposon insertion patterns, and gene essentiality calls were made by transposon insertion frequency analysis (TIFA. TIFA incorporated the observed genome and sequence motif bias of the miniHimar transposon. The gene essentiality calls were compared to: 1 previous genome-wide direct gene-essentiality assignments; and, 2 flux balance analysis (FBA predictions from an existing genome-scale metabolic model of Shewanella oneidensis MR-1. A three-way comparison between FBA, TIFA, and the direct essentiality calls was made to validate the TIFA approach. The refinement in the interpretation of observed transposon insertions demonstrated that genes without insertions are not necessarily essential, and that genes that contain insertions are not always nonessential. The TIFA calls were in reasonable agreement with direct essentiality calls for S. oneidensis, but agreed more closely with E. coli essentiality calls for orthologs. The TIFA gene essentiality calls were in good agreement with the MR-1 FBA essentiality predictions, and the agreement between TIFA and FBA predictions was substantially better than between the FBA and the direct gene essentiality predictions.

  12. Genome-scale reconstruction and analysis of the Pseudomonas putida KT2440 metabolic network facilitates applications in biotechnology.

    Directory of Open Access Journals (Sweden)

    Jacek Puchałka

    2008-10-01

    Full Text Available A cornerstone of biotechnology is the use of microorganisms for the efficient production of chemicals and the elimination of harmful waste. Pseudomonas putida is an archetype of such microbes due to its metabolic versatility, stress resistance, amenability to genetic modifications, and vast potential for environmental and industrial applications. To address both the elucidation of the metabolic wiring in P. putida and its uses in biocatalysis, in particular for the production of non-growth-related biochemicals, we developed and present here a genome-scale constraint-based model of the metabolism of P. putida KT2440. Network reconstruction and flux balance analysis (FBA enabled definition of the structure of the metabolic network, identification of knowledge gaps, and pin-pointing of essential metabolic functions, facilitating thereby the refinement of gene annotations. FBA and flux variability analysis were used to analyze the properties, potential, and limits of the model. These analyses allowed identification, under various conditions, of key features of metabolism such as growth yield, resource distribution, network robustness, and gene essentiality. The model was validated with data from continuous cell cultures, high-throughput phenotyping data, (13C-measurement of internal flux distributions, and specifically generated knock-out mutants. Auxotrophy was correctly predicted in 75% of the cases. These systematic analyses revealed that the metabolic network structure is the main factor determining the accuracy of predictions, whereas biomass composition has negligible influence. Finally, we drew on the model to devise metabolic engineering strategies to improve production of polyhydroxyalkanoates, a class of biotechnologically useful compounds whose synthesis is not coupled to cell survival. The solidly validated model yields valuable insights into genotype-phenotype relationships and provides a sound framework to explore this versatile

  13. Genome-Scale Architecture of Small Molecule Regulatory Networks and the Fundamental Trade-Off between Regulation and Enzymatic Activity

    Directory of Open Access Journals (Sweden)

    Ed Reznik

    2017-09-01

    Full Text Available Metabolic flux is in part regulated by endogenous small molecules that modulate the catalytic activity of an enzyme, e.g., allosteric inhibition. In contrast to transcriptional regulation of enzymes, technical limitations have hindered the production of a genome-scale atlas of small molecule-enzyme regulatory interactions. Here, we develop a framework leveraging the vast, but fragmented, biochemical literature to reconstruct and analyze the small molecule regulatory network (SMRN of the model organism Escherichia coli, including the primary metabolite regulators and enzyme targets. Using metabolic control analysis, we prove a fundamental trade-off between regulation and enzymatic activity, and we combine it with metabolomic measurements and the SMRN to make inferences on the sensitivity of enzymes to their regulators. Generalizing the analysis to other organisms, we identify highly conserved regulatory interactions across evolutionarily divergent species, further emphasizing a critical role for small molecule interactions in the maintenance of metabolic homeostasis.

  14. From the chromatin interaction network to the organization of the human genome into replication N/U-domains

    Science.gov (United States)

    Boulos, Rasha E.; Julienne, Hanna; Baker, Antoine; Chen, Chun-Long; Petryk, Nataliya; Kahli, Malik; dʼAubenton-Carafa, Yves; Goldar, Arach; Jensen, Pablo; Hyrien, Olivier; Thermes, Claude; Arneodo, Alain; Audit, Benjamin

    2014-11-01

    The three-dimensional (3D) architecture of the mammalian nucleus is now being unraveled thanks to the recent development of chromatin conformation capture (3C) technologies. Here we report the results of a combined multiscale analysis of genome-wide mean replication timing and chromatin conformation data that reveal some intimate relationships between chromatin folding and human DNA replication. We previously described megabase replication N/U-domains as mammalian multiorigin replication units, and showed that their borders are ‘master’ replication initiation zones that likely initiate cascades of origin firing responsible for the stereotypic replication of these domains. Here, we demonstrate that replication N/U-domains correspond to the structural domains of self-interacting chromatin, and that their borders act as insulating regions both in high-throughput 3C (Hi-C) data and high-resolution 3C (4C) experiments. Further analyses of Hi-C data using a graph-theoretical approach reveal that N/U-domain borders are long-distance, interconnected hubs of the chromatin interaction network. Overall, these results and the observation that a well-defined ordering of chromatin states exists from N/U-domain borders to centers suggest that ‘master’ replication initiation zones are at the heart of a high-order, epigenetically controlled 3D organization of the human genome.

  15. English Language Teachers as a Dissenter on a Social Networking Site

    Directory of Open Access Journals (Sweden)

    Radzuwan Ab Rashid

    2016-07-01

    Full Text Available This paper explores how teachers discursively construct socially desirable identities to sustain their engagement in the Facebook Timeline community. Data were gathered from the Status updates and Comments on 29 Timelines belonged to Malaysian English language teachers who were purposively chosen as they often posted and commented on teaching-related issues on their Timelines. The analysis shows that the commonest form of identity construction on the teachers’ Timelines was as a dissenter which had been carefully constructed to present positive self-images and cast blames on other people. The teachers questioned the expectations of the people around them, as they perceive that the expectations are unrealistic. This paper concludes that the teachers were being strategic in their postings where they provide justification for their views and ascribe particular identities to other people in the process of constructing their own identity as a dissenter.

  16. RRW: repeated random walks on genome-scale protein networks for local cluster discovery

    Directory of Open Access Journals (Sweden)

    Can Tolga

    2009-09-01

    Full Text Available Abstract Background We propose an efficient and biologically sensitive algorithm based on repeated random walks (RRW for discovering functional modules, e.g., complexes and pathways, within large-scale protein networks. Compared to existing cluster identification techniques, RRW implicitly makes use of network topology, edge weights, and long range interactions between proteins. Results We apply the proposed technique on a functional network of yeast genes and accurately identify statistically significant clusters of proteins. We validate the biological significance of the results using known complexes in the MIPS complex catalogue database and well-characterized biological processes. We find that 90% of the created clusters have the majority of their catalogued proteins belonging to the same MIPS complex, and about 80% have the majority of their proteins involved in the same biological process. We compare our method to various other clustering techniques, such as the Markov Clustering Algorithm (MCL, and find a significant improvement in the RRW clusters' precision and accuracy values. Conclusion RRW, which is a technique that exploits the topology of the network, is more precise and robust in finding local clusters. In addition, it has the added flexibility of being able to find multi-functional proteins by allowing overlapping clusters.

  17. Genome-wide genetic interaction analysis of glaucoma using expert knowledge derived from human phenotype networks.

    Science.gov (United States)

    Hu, Ting; Darabos, Christian; Cricco, Maria E; Kong, Emily; Moore, Jason H

    2015-01-01

    The large volume of GWAS data poses great computational challenges for analyzing genetic interactions associated with common human diseases. We propose a computational framework for characterizing epistatic interactions among large sets of genetic attributes in GWAS data. We build the human phenotype network (HPN) and focus around a disease of interest. In this study, we use the GLAUGEN glaucoma GWAS dataset and apply the HPN as a biological knowledge-based filter to prioritize genetic variants. Then, we use the statistical epistasis network (SEN) to identify a significant connected network of pairwise epistatic interactions among the prioritized SNPs. These clearly highlight the complex genetic basis of glaucoma. Furthermore, we identify key SNPs by quantifying structural network characteristics. Through functional annotation of these key SNPs using Biofilter, a software accessing multiple publicly available human genetic data sources, we find supporting biomedical evidences linking glaucoma to an array of genetic diseases, proving our concept. We conclude by suggesting hypotheses for a better understanding of the disease.

  18. Counting and Correcting Thermodynamically Infeasible Flux Cycles in Genome-Scale Metabolic Networks

    Directory of Open Access Journals (Sweden)

    Andrea De Martino

    2013-10-01

    Full Text Available Thermodynamics constrains the flow of matter in a reaction network to occur through routes along which the Gibbs energy decreases, implying that viable steady-state flux patterns should be void of closed reaction cycles. Identifying and removing cycles in large reaction networks can unfortunately be a highly challenging task from a computational viewpoint. We propose here a method that accomplishes it by combining a relaxation algorithm and a Monte Carlo procedure to detect loops, with ad hoc rules (discussed in detail to eliminate them. As test cases, we tackle (a the problem of identifying infeasible cycles in the E. coli metabolic network and (b the problem of correcting thermodynamic infeasibilities in the Flux-Balance-Analysis solutions for 15 human cell-type-specific metabolic networks. Results for (a are compared with previous analyses of the same issue, while results for (b are weighed against alternative methods to retrieve thermodynamically viable flux patterns based on minimizing specific global quantities. Our method, on the one hand, outperforms previous techniques and, on the other, corrects loopy solutions to Flux Balance Analysis. As a byproduct, it also turns out to be able to reveal possible inconsistencies in model reconstructions.

  19. Identification and characterization of starch and inulin modifying network of Aspergillus niger by functional genomics

    NARCIS (Netherlands)

    Yuan, Xiao-Lian

    2008-01-01

    Aspergillus niger produces a wide variety of carbohydrate hydrolytic enzymes which have potential applications in the baking, starch, textile, food and feed industries. The goal of this thesis is to unravel the molecular mechanisms of starch and inulin modifying network of A. niger, in order to impr

  20. Language associations and collaborative support: language teacher associations as empowering spaces for professional networks

    OpenAIRE

    2012-01-01

    The LACS project (Language Associations and Collaborative Support) marked the first major cooperation between the European Centre for Modern Languages (ECML) and the Fédération Internationale des Professeurs de Langues Vivantes/International Federation of Language Teacher Associations (FIPLV). This article focuses on one aspect of the project, namely an exploration of issues affecting language teacher associations worldwide. It describes the research carried out into the associations' percept...

  1. 网络文化传播对师生关系的影响及对策%Countermeasures to Teacher-Student Relationship Influenced by Network Culture

    Institute of Scientific and Technical Information of China (English)

    闻彦; 罗玲云

    2012-01-01

    当前,网络文化传播对师生关系的发展有着明显的影响。网络文化传播的发散性影响着师生关系建立的基础,其交互性影响着师生关系的结构模式,同时它也促发了师生关系多模式的形成。在网络文化传播背景下,师生间知识传递的模式发生了改变,教师的知识权威与个人威望受到冲击,教师的控制力减弱。为了适应这些变化,优化网络文化传播下的师生关系,我们应扩大网络民主,畅通舆论通道;建设网络文化,塑造健康互信的师生网络形象;建设友好亲和的网络平台,完善网络事件处理机制、网上网下互动机制。%At present,the dissemination of network culture on the development of the relationship between teachers and students has significant influence.Network culture propagation of divergent effects of teacher-student relationship based on the interactive relationship between teachers and students,affects the structure pattern,at the same time it also facilitated the relationship between teachers and students more pattern formation.Cultural transmission in the network context,between teachers and students of knowledge transfer mode changed,teachers' knowledge authority and personal prestige suffered,teachers control weakened.In order to adapt to these changes,optimize the network culture communication between teachers and students,we should expand the network democracy,open public channel;construction of the network culture,shaping the health trust network image;construction of friendly affinity network platform,improve the network event processing mechanisms,a network of online interactive mechanism.

  2. Genome-scale reconstruction of the metabolic network in Yersinia pestis, strain 91001

    Energy Technology Data Exchange (ETDEWEB)

    Navid, A; Almaas, E

    2009-01-13

    The gram-negative bacterium Yersinia pestis, the aetiological agent of bubonic plague, is one the deadliest pathogens known to man. Despite its historical reputation, plague is a modern disease which annually afflicts thousands of people. Public safety considerations greatly limit clinical experimentation on this organism and thus development of theoretical tools to analyze the capabilities of this pathogen is of utmost importance. Here, we report the first genome-scale metabolic model of Yersinia pestis biovar Mediaevalis based both on its recently annotated genome, and physiological and biochemical data from literature. Our model demonstrates excellent agreement with Y. pestis known metabolic needs and capabilities. Since Y. pestis is a meiotrophic organism, we have developed CryptFind, a systematic approach to identify all candidate cryptic genes responsible for known and theoretical meiotrophic phenomena. In addition to uncovering every known cryptic gene for Y. pestis, our analysis of the rhamnose fermentation pathway suggests that betB is the responsible cryptic gene. Despite all of our medical advances, we still do not have a vaccine for bubonic plague. Recent discoveries of antibiotic resistant strains of Yersinia pestis coupled with the threat of plague being used as a bioterrorism weapon compel us to develop new tools for studying the physiology of this deadly pathogen. Using our theoretical model, we can study the cell's phenotypic behavior under different circumstances and identify metabolic weaknesses which may be harnessed for the development of therapeutics. Additionally, the automatic identification of cryptic genes expands the usage of genomic data for pharmaceutical purposes.

  3. Teacher Network of Relationships Inventory: measurement invariance of academically at-risk students across ages 6 to 15.

    Science.gov (United States)

    Wu, Jiun-Yu; Hughes, Jan N

    2015-03-01

    We tested the longitudinal measurement invariance of the Teacher Network of Relationships Inventory (TNRI), a teacher-report measure of teacher-student relationship quality (TSRQ), on a sample of 784 academically at-risk students across ages 6 to 15 years by comparing the model for each subsequent year with that of the previous year(s). The TNRI was constructed with 22 items to form 3 correlated factors: Warmth, Conflict, and Intimacy. Cronbach's alphas ranged from .87 to .96 across 9 years. Both metric and scalar measurement invariance held for 9 years, indicating that scores on the TNRI have similar meaning across these ages. The TNRI also demonstrated measurement invariance across gender and race/ethnicity. Findings support that the TNRI is an appropriate measure for investigating substantive issues related to developmental changes in TSRQ from early childhood through adolescence, including gender and ethnic/racial differences in TSRQ across these ages. Based on repeated-measures ANOVAs, each scale decreased across the 9 years, although the growth patterns for scales differed somewhat: Conflict had a linearly decreasing pattern, Warmth declined most notably as students make the transition to adolescence, whereas Intimacy scores dropped off noticeably at the transition from early to late childhood. Research limitations and implications for practice are discussed.

  4. Drug-target and disease networks: polypharmacology in the post-genomic era

    OpenAIRE

    Masoudi-Nejad, Ali; Mousavian, Zaynab; Bozorgmehr, Joseph H.

    2013-01-01

    With the growing understanding of complex diseases, the focus of drug discovery has shifted away from the well-accepted “one target, one drug” model, to a new “multi-target, multi-drug” model, aimed at systemically modulating multiple targets. Identification of the interaction between drugs and target proteins plays an important role in genomic drug discovery, in order to discover new drugs or novel targets for existing drugs. Due to the laborious and costly experimental process of drug-targe...

  5. Genome-scale reconstruction of the metabolic network in Yersinia pestis CO92

    Science.gov (United States)

    Navid, Ali; Almaas, Eivind

    2007-03-01

    The gram-negative bacterium Yersinia pestis is the causative agent of bubonic plague. Using publicly available genomic, biochemical and physiological data, we have developed a constraint-based flux balance model of metabolism in the CO92 strain (biovar Orientalis) of this organism. The metabolic reactions were appropriately compartmentalized, and the model accounts for the exchange of metabolites, as well as the import of nutrients and export of waste products. We have characterized the metabolic capabilities and phenotypes of this organism, after comparing the model predictions with available experimental observations to evaluate accuracy and completeness. We have also begun preliminary studies into how cellular metabolism affects virulence.

  6. ReacKnock: identifying reaction deletion strategies for microbial strain optimization based on genome-scale metabolic network.

    Directory of Open Access Journals (Sweden)

    Zixiang Xu

    Full Text Available Gene knockout has been used as a common strategy to improve microbial strains for producing chemicals. Several algorithms are available to predict the target reactions to be deleted. Most of them apply mixed integer bi-level linear programming (MIBLP based on metabolic networks, and use duality theory to transform bi-level optimization problem of large-scale MIBLP to single-level programming. However, the validity of the transformation was not proved. Solution of MIBLP depends on the structure of inner problem. If the inner problem is continuous, Karush-Kuhn-Tucker (KKT method can be used to reformulate the MIBLP to a single-level one. We adopt KKT technique in our algorithm ReacKnock to attack the intractable problem of the solution of MIBLP, demonstrated with the genome-scale metabolic network model of E. coli for producing various chemicals such as succinate, ethanol, threonine and etc. Compared to the previous methods, our algorithm is fast, stable and reliable to find the optimal solutions for all the chemical products tested, and able to provide all the alternative deletion strategies which lead to the same industrial objective.

  7. Genomic admixture tracks pulses of economic activity over 2,000 years in the Indian Ocean trading network.

    Science.gov (United States)

    Brucato, Nicolas; Kusuma, Pradiptajati; Beaujard, Philippe; Sudoyo, Herawati; Cox, Murray P; Ricaut, François-Xavier

    2017-06-07

    The Indian Ocean has long been a hub of interacting human populations. Following land- and sea-based routes, trade drove cultural contacts between far-distant ethnic groups in Asia, India, the Middle East and Africa, creating one of the world's first proto-globalized environments. However, the extent to which population mixing was mediated by trade is poorly understood. Reconstructing admixture times from genomic data in 3,006 individuals from 187 regional populations reveals a close association between bouts of human migration and trade volumes during the last 2,000 years across the Indian Ocean trading system. Temporal oscillations in trading activity match phases of contraction and expansion in migration, with high water marks following the expansion of the Silk Roads in the 5(th) century AD, the rise of maritime routes in the 11(th) century and a drastic restructuring of the trade network following the arrival of Europeans in the 16(th) century. The economic fluxes of the Indian Ocean trade network therefore directly shaped exchanges of genes, in addition to goods and concepts.

  8. An experimentally-supported genome-scale metabolic network reconstruction for Yersinia pestis CO92

    Directory of Open Access Journals (Sweden)

    Motin Vladimir L

    2011-10-01

    Full Text Available Abstract Background Yersinia pestis is a gram-negative bacterium that causes plague, a disease linked historically to the Black Death in Europe during the Middle Ages and to several outbreaks during the modern era. Metabolism in Y. pestis displays remarkable flexibility and robustness, allowing the bacterium to proliferate in both warm-blooded mammalian hosts and cold-blooded insect vectors such as fleas. Results Here we report a genome-scale reconstruction and mathematical model of metabolism for Y. pestis CO92 and supporting experimental growth and metabolite measurements. The model contains 815 genes, 678 proteins, 963 unique metabolites and 1678 reactions, accurately simulates growth on a range of carbon sources both qualitatively and quantitatively, and identifies gaps in several key biosynthetic pathways and suggests how those gaps might be filled. Furthermore, our model presents hypotheses to explain certain known nutritional requirements characteristic of this strain. Conclusions Y. pestis continues to be a dangerous threat to human health during modern times. The Y. pestis genome-scale metabolic reconstruction presented here, which has been benchmarked against experimental data and correctly reproduces known phenotypes, provides an in silico platform with which to investigate the metabolism of this important human pathogen.

  9. Computational modelling of genome-wide [corrected] transcription assembly networks using a fluidics analogy.

    Directory of Open Access Journals (Sweden)

    Yousry Y Azmy

    Full Text Available Understanding how a myriad of transcription regulators work to modulate mRNA output at thousands of genes remains a fundamental challenge in molecular biology. Here we develop a computational tool to aid in assessing the plausibility of gene regulatory models derived from genome-wide expression profiling of cells mutant for transcription regulators. mRNA output is modelled as fluid flow in a pipe lattice, with assembly of the transcription machinery represented by the effect of valves. Transcriptional regulators are represented as external pressure heads that determine flow rate. Modelling mutations in regulatory proteins is achieved by adjusting valves' on/off settings. The topology of the lattice is designed by the experimentalist to resemble the expected interconnection between the modelled agents and their influence on mRNA expression. Users can compare multiple lattice configurations so as to find the one that minimizes the error with experimental data. This computational model provides a means to test the plausibility of transcription regulation models derived from large genomic data sets.

  10. An Experimentally-Supported Genome-Scale Metabolic Network Reconstruction for Yersinia pestis CO92

    Energy Technology Data Exchange (ETDEWEB)

    Charusanti, Pep; Chauhan, Sadhana; Mcateer, Kathleen; Lerman, Joshua A.; Hyduke, Daniel R.; Motin, Vladimir L.; Ansong, Charles; Adkins, Joshua N.; Palsson, Bernhard O.

    2011-10-13

    Yersinia pestis is a gram-negative bacterium that causes plague, a disease linked historically to the Black Death in Europe during the Middle Ages and to several outbreaks during the modern era. Metabolism in Y. pestis displays remarkable flexibility and robustness, allowing the bacterium to proliferate in both warm-blooded mammalian hosts and cold-blooded insect vectors such as fleas. Here we report a genome-scale reconstruction and mathematical model of metabolism for Y. pestis CO92 and supporting experimental growth and metabolite measurements. The model contains 815 genes, 678 proteins, 963 unique metabolites and 1678 reactions, accurately simulates growth on a range of carbon sources both qualitatively and quantitatively, and identifies gaps in several key biosynthetic pathways and suggests how those gaps might be filled. Furthermore, our model presents hypotheses to explain certain known nutritional requirements characteristic of this strain. Y. pestis continues to be a dangerous threat to human health during modern times. The Y. pestis genome-scale metabolic reconstruction presented here, which has been benchmarked against experimental data and correctly reproduces known phenotypes, thus provides an in silico platform with which to investigate the metabolism of this important human pathogen.

  11. Genome-scale cold stress response regulatory networks in ten Arabidopsis thaliana ecotypes

    DEFF Research Database (Denmark)

    Barah, Pankaj; Jayavelu, Naresh Doni; Rasmussen, Simon;

    2013-01-01

    ontology (GO) categories were identified to delineate natural variation of cold stress regulated differential gene expression in the model plant A. thaliana. The predicted regulatory network model was able to identify new ecotype specific transcription factors and their regulatory interactions, which might...... using Arabidopsis NimbleGen ATH6 microarrays. In total 6061 transcripts were significantly cold regulated (p expression pattern. By using sequence data...

  12. Synthetic biology approaches in cancer immunotherapy, genetic network engineering, and genome editing.

    Science.gov (United States)

    Chakravarti, Deboki; Cho, Jang Hwan; Weinberg, Benjamin H; Wong, Nicole M; Wong, Wilson W

    2016-04-18

    Investigations into cells and their contents have provided evolving insight into the emergence of complex biological behaviors. Capitalizing on this knowledge, synthetic biology seeks to manipulate the cellular machinery towards novel purposes, extending discoveries from basic science to new applications. While these developments have demonstrated the potential of building with biological parts, the complexity of cells can pose numerous challenges. In this review, we will highlight the broad and vital role that the synthetic biology approach has played in applying fundamental biological discoveries in receptors, genetic circuits, and genome-editing systems towards translation in the fields of immunotherapy, biosensors, disease models and gene therapy. These examples are evidence of the strength of synthetic approaches, while also illustrating considerations that must be addressed when developing systems around living cells.

  13. The Fanconi anemia/BRCA gene network in zebrafish: Embryonic expression and comparative genomics

    Energy Technology Data Exchange (ETDEWEB)

    Titus, Tom A.; Yan Yilin; Wilson, Catherine; Starks, Amber M.; Frohnmayer, Jonathan D.; Bremiller, Ruth A.; Canestro, Cristian; Rodriguez-Mari, Adriana; He Xinjun [Institute of Neuroscience, University of Oregon, 1425 E. 13th Avenue, Eugene, OR 97403 (United States); Postlethwait, John H., E-mail: jpostle@uoneuro.uoregon.edu [Institute of Neuroscience, University of Oregon, 1425 E. 13th Avenue, Eugene, OR 97403 (United States)

    2009-07-31

    Fanconi anemia (FA) is a genetic disease resulting in bone marrow failure, high cancer risks, and infertility, and developmental anomalies including microphthalmia, microcephaly, hypoplastic radius and thumb. Here we present cDNA sequences, genetic mapping, and genomic analyses for the four previously undescribed zebrafish FA genes (fanci, fancj, fancm, and fancn), and show that they reverted to single copy after the teleost genome duplication. We tested the hypothesis that FA genes are expressed during embryonic development in tissues that are disrupted in human patients by investigating fanc gene expression patterns. We found fanc gene maternal message, which can provide Fanc proteins to repair DNA damage encountered in rapid cleavage divisions. Zygotic expression was broad but especially strong in eyes, central nervous system and hematopoietic tissues. In the pectoral fin bud at hatching, fanc genes were expressed specifically in the apical ectodermal ridge, a signaling center for fin/limb development that may be relevant to the radius/thumb anomaly of FA patients. Hatching embryos expressed fanc genes strongly in the oral epithelium, a site of squamous cell carcinomas in FA patients. Larval and adult zebrafish expressed fanc genes in proliferative regions of the brain, which may be related to microcephaly in FA. Mature ovaries and testes expressed fanc genes in specific stages of oocyte and spermatocyte development, which may be related to DNA repair during homologous recombination in meiosis and to infertility in human patients. The intestine strongly expressed some fanc genes specifically in proliferative zones. Our results show that zebrafish has a complete complement of fanc genes in single copy and that these genes are expressed in zebrafish embryos and adults in proliferative tissues that are often affected in FA patients. These results support the notion that zebrafish offers an attractive experimental system to help unravel mechanisms relevant not only

  14. The Networked Student Model for Construction of Personal Learning Environments: Balancing Teacher Control and Student Autonomy

    Science.gov (United States)

    Drexler, Wendy

    2010-01-01

    Principles of networked learning, constructivism, and connectivism inform the design of a test case through which secondary students construct personal learning environments for the purpose of independent inquiry. Emerging web applications and open educational resources are integrated to support a "Networked Student Model" that promotes…

  15. The Use of Social Network Sites by Prospective Physical Education and Sports Teachers (Gazi University Sample)

    Science.gov (United States)

    Yaman, Metin; Yaman, Cetin

    2014-01-01

    Social network sites are widely used by many people nowadays for various aims. Many researches have been done to analyze the usage of these sites in many different settings. In the literature the number of the studies investigating the university students' usage social network sites is limited. This research was carried out to determine the social…

  16. The Networked Student Model for Construction of Personal Learning Environments: Balancing Teacher Control and Student Autonomy

    Science.gov (United States)

    Drexler, Wendy

    2010-01-01

    Principles of networked learning, constructivism, and connectivism inform the design of a test case through which secondary students construct personal learning environments for the purpose of independent inquiry. Emerging web applications and open educational resources are integrated to support a "Networked Student Model" that promotes…

  17. The United States Culture Collection Network (USCCN): Enhancing Microbial Genomics Research through Living Microbe Culture Collections

    Energy Technology Data Exchange (ETDEWEB)

    Boundy-Mills, K.; Hess, Matthias; Bennett, A. R.; Ryan, Matthew; Kang, Seogchan; Nobles, David; Eisen, Jonathan A.; Inderbitzin, Patrik; Sitepu, Irnayuli R.; Torok, Tamas; Brown, Daniel R; Cho, Juliana; Wertz, John E.; Mukherjee, Supratim; Cady, Sherry L.; McCluskey, Kevin

    2015-09-01

    The mission of the United States Culture Collection Network (USCCN; http://usccn.org) is "to facilitate the safe and responsible utilization of microbial resources for research, education, industry, medicine, and agriculture for the betterment of human kind." Microbial culture collections are a key component of life science research, biotechnology, and emerging global biobased economies. Representatives and users of several microbial culture collections from the United States and Europe gathered at the University of California, Davis, to discuss how collections of microorganisms can better serve users and stakeholders and to showcase existing resources available in public culture collections.

  18. A genome-scale metabolic network reconstruction of tomato (Solanum lycopersicum L.) and its application to photorespiratory metabolism.

    Science.gov (United States)

    Yuan, Huili; Cheung, C Y Maurice; Poolman, Mark G; Hilbers, Peter A J; van Riel, Natal A W

    2016-01-01

    Tomato (Solanum lycopersicum L.) has been studied extensively due to its high economic value in the market, and high content in health-promoting antioxidant compounds. Tomato is also considered as an excellent model organism for studying the development and metabolism of fleshy fruits. However, the growth, yield and fruit quality of tomatoes can be affected by drought stress, a common abiotic stress for tomato. To investigate the potential metabolic response of tomato plants to drought, we reconstructed iHY3410, a genome-scale metabolic model of tomato leaf, and used this metabolic network to simulate tomato leaf metabolism. The resulting model includes 3410 genes and 2143 biochemical and transport reactions distributed across five intracellular organelles including cytosol, plastid, mitochondrion, peroxisome and vacuole. The model successfully described the known metabolic behaviour of tomato leaf under heterotrophic and phototrophic conditions. The in silico investigation of the metabolic characteristics for photorespiration and other relevant metabolic processes under drought stress suggested that: (i) the flux distributions through the mevalonate (MVA) pathway under drought were distinct from that under normal conditions; and (ii) the changes in fluxes through core metabolic pathways with varying flux ratio of RubisCO carboxylase to oxygenase may contribute to the adaptive stress response of plants. In addition, we improved on previous studies of reaction essentiality analysis for leaf metabolism by including potential alternative routes for compensating reaction knockouts. Altogether, the genome-scale model provides a sound framework for investigating tomato metabolism and gives valuable insights into the functional consequences of abiotic stresses. © 2015 The Authors.The Plant Journal published by Society for Experimental Biology and John Wiley & Sons Ltd.

  19. Transcriptional interference networks coordinate the expression of functionally-related genes clustered in the same genomic loci

    Directory of Open Access Journals (Sweden)

    Zsolt eBoldogkoi

    2012-07-01

    Full Text Available The regulation of gene expression is essential for normal functioning of biological systems in every form of life. Gene expression is primarily controlled at the level of transcription, especially at the phase of initiation. Non-coding RNAs are one of the major players at every level of genetic regulation, including the control of chromatin organisation, transcription, various post-transcriptional processes and translation. In this study, the Transcriptional Interference Network (TIN hypothesis was put forward in an attempt to explain the global expression of antisense RNAs and the overall occurrence of tandem gene clusters in the genomes of various biological systems ranging from viruses to mammalian cells. The TIN hypothesis suggests the existence of a novel layer of genetic regulation, based on the interactions between the transcriptional machineries of neighbouring genes at their overlapping regions, which are assumed to play a fundamental role in coordinating gene expression within a cluster of functionally-linked genes. It is claimed that the transcriptional overlaps between adjacent genes are much more widespread in genomes than is thought today. The Waterfall model of the TIN hypothesis postulates a unidirectional effect of upstream genes on the transcription of downstream genes within a cluster of tandemly-arrayed genes, while the Seesaw model proposes a mutual interdependence of gene expression between the oppositely-oriented genes. The TIN represents an auto-regulatory system with an exquisitely timed and highly synchronised cascade of gene expression in functionally-linked genes located in close physical proximity to each other. In this study, we focused on herpesviruses. The reason for this lies in the compressed nature of viral genes, which allows a tight regulation and an easier investigation of the transcriptional interactions between genes. However, I believe that the same or similar principles can be applied to cellular

  20. Acorn: A grid computing system for constraint based modeling and visualization of the genome scale metabolic reaction networks via a web interface

    Directory of Open Access Journals (Sweden)

    Bushell Michael E

    2011-05-01

    Full Text Available Abstract Background Constraint-based approaches facilitate the prediction of cellular metabolic capabilities, based, in turn on predictions of the repertoire of enzymes encoded in the genome. Recently, genome annotations have been used to reconstruct genome scale metabolic reaction networks for numerous species, including Homo sapiens, which allow simulations that provide valuable insights into topics, including predictions of gene essentiality of pathogens, interpretation of genetic polymorphism in metabolic disease syndromes and suggestions for novel approaches to microbial metabolic engineering. These constraint-based simulations are being integrated with the functional genomics portals, an activity that requires efficient implementation of the constraint-based simulations in the web-based environment. Results Here, we present Acorn, an open source (GNU GPL grid computing system for constraint-based simulations of genome scale metabolic reaction networks within an interactive web environment. The grid-based architecture allows efficient execution of computationally intensive, iterative protocols such as Flux Variability Analysis, which can be readily scaled up as the numbers of models (and users increase. The web interface uses AJAX, which facilitates efficient model browsing and other search functions, and intuitive implementation of appropriate simulation conditions. Research groups can install Acorn locally and create user accounts. Users can also import models in the familiar SBML format and link reaction formulas to major functional genomics portals of choice. Selected models and simulation results can be shared between different users and made publically available. Users can construct pathway map layouts and import them into the server using a desktop editor integrated within the system. Pathway maps are then used to visualise numerical results within the web environment. To illustrate these features we have deployed Acorn and created a

  1. Social Network to Support Parents and Teachers of Students with Multiple Disabilities

    Science.gov (United States)

    Nunes, Clarisse; Miranda, Guilhermina Lobato; Amaral, Isabel

    2017-01-01

    This study aimed to analyze how the Social Software tools could respond to the needs of parents and teachers of students with multiple disabilities in improving their practices, as well as provide information and resources related to the topic of multiple disabilities. The study was implemented in Portugal and involved 45 participants: 25 special…

  2. Teachers' Personal Learning Networks (PLNs): Exploring the Nature of Self-Initiated Professional Learning Online

    Science.gov (United States)

    Tour, Ekaterina

    2017-01-01

    In the field of Literacy Studies, online spaces have been recognised as providing many opportunities for spontaneous and self-initiated learning. While some progress has been made in understanding these important learning experiences, little attention has been paid to teachers' self-initiated professional learning. Contributing to the debates…

  3. Teachers' Personal Learning Networks (PLNs): Exploring the Nature of Self-Initiated Professional Learning Online

    Science.gov (United States)

    Tour, Ekaterina

    2017-01-01

    In the field of Literacy Studies, online spaces have been recognised as providing many opportunities for spontaneous and self-initiated learning. While some progress has been made in understanding these important learning experiences, little attention has been paid to teachers' self-initiated professional learning. Contributing to the debates…

  4. New York University: Documentation of the Teachers for a New Era Learning Network. Case Study

    Science.gov (United States)

    Academy for Educational Development, 2012

    2012-01-01

    The Academy for Educational Development (AED) sent a research team to New York University (NYU) on December 8-9, 2008 to conduct interviews with individuals who play important roles in the university's teacher preparation program. These interviews, along with additional documentation provided by NYU and identified by the AED research team, provide…

  5. Western Kentucky University: Documentation of the Teachers for a New Era Learning Network. Case Study

    Science.gov (United States)

    Academy for Educational Development, 2012

    2012-01-01

    The Academy for Educational Development (AED) sent a research team to Western Kentucky University (WKU) on June 19-20, 2008 to conduct interviews with individuals who play important roles in the university's teacher preparation program (see Appendix A). These interviews, along with additional documentation provided by WKU and identified by the AED…

  6. Genome-wide analysis of the homeobox C6 transcriptional network in prostate cancer.

    Science.gov (United States)

    McCabe, Colleen D; Spyropoulos, Demetri D; Martin, David; Moreno, Carlos S

    2008-03-15

    Homeobox transcription factors are developmentally regulated genes that play crucial roles in tissue patterning. Homeobox C6 (HOXC6) is overexpressed in prostate cancers and correlated with cancer progression, but the downstream targets of HOXC6 are largely unknown. We have performed genome-wide localization analysis to identify promoters bound by HOXC6 in prostate cancer cells. This analysis identified 468 reproducibly bound promoters whose associated genes are involved in functions such as cell proliferation and apoptosis. We have complemented these data with expression profiling of prostates from mice with homozygous disruption of the Hoxc6 gene to identify 31 direct regulatory target genes of HOXC6. We show that HOXC6 directly regulates expression of bone morphogenic protein 7, fibroblast growth factor receptor 2, insulin-like growth factor binding protein 3, and platelet-derived growth factor receptor alpha (PDGFRA) in prostate cells and indirectly influences the Notch and Wnt signaling pathways in vivo. We further show that inhibition of PDGFRA reduces proliferation of prostate cancer cells, and that overexpression of HOXC6 can overcome the effects of PDGFRA inhibition. HOXC6 regulates genes with both oncogenic and tumor suppressor activities as well as several genes such as CD44 that are important for prostate branching morphogenesis and metastasis to the bone microenvironment.

  7. Genome-wide RNAi screen for nuclear actin reveals a network of cofilin regulators.

    Science.gov (United States)

    Dopie, Joseph; Rajakylä, Eeva K; Joensuu, Merja S; Huet, Guillaume; Ferrantelli, Evelina; Xie, Tiao; Jäälinoja, Harri; Jokitalo, Eija; Vartiainen, Maria K

    2015-07-01

    Nuclear actin plays an important role in many processes that regulate gene expression. Cytoplasmic actin dynamics are tightly controlled by numerous actin-binding proteins, but regulation of nuclear actin has remained unclear. Here, we performed a genome-wide RNA interference (RNAi) screen in Drosophila cells to identify proteins that influence either nuclear polymerization or import of actin. We validate 19 factors as specific hits, and show that Chinmo (known as Bach2 in mammals), SNF4Aγ (Prkag1 in mammals) and Rab18 play a role in nuclear localization of actin in both fly and mammalian cells. We identify several new regulators of cofilin activity, and characterize modulators of both cofilin kinases and phosphatase. For example, Chinmo/Bach2, which regulates nuclear actin levels also in vivo, maintains active cofilin by repressing the expression of the kinase Cdi (Tesk in mammals). Finally, we show that Nup98 and lamin are candidates for regulating nuclear actin polymerization. Our screen therefore reveals new aspects of actin regulation and links nuclear actin to many cellular processes.

  8. Genome-wide survey of the seagrass Zostera muelleri suggests modification of the ethylene signalling network.

    Science.gov (United States)

    Golicz, Agnieszka A; Schliep, Martin; Lee, Huey Tyng; Larkum, Anthony W D; Dolferus, Rudy; Batley, Jacqueline; Chan, Chon-Kit Kenneth; Sablok, Gaurav; Ralph, Peter J; Edwards, David

    2015-03-01

    Seagrasses are flowering plants which grow fully submerged in the marine environment. They have evolved a range of adaptations to environmental challenges including light attenuation through water, the physical stress of wave action and tidal currents, high concentrations of salt, oxygen deficiency in marine sediment, and water-borne pollination. Although, seagrasses are a key stone species of the costal ecosystems, many questions regarding seagrass biology and evolution remain unanswered. Genome sequence data for the widespread Australian seagrass species Zostera muelleri were generated and the unassembled data were compared with the annotated genes of five sequenced plant species (Arabidopsis thaliana, Oryza sativa, Phoenix dactylifera, Musa acuminata, and Spirodela polyrhiza). Genes which are conserved between Z. muelleri and the five plant species were identified, together with genes that have been lost in Z. muelleri. The effect of gene loss on biological processes was assessed on the gene ontology classification level. Gene loss in Z. muelleri appears to influence some core biological processes such as ethylene biosynthesis. This study provides a foundation for further studies of seagrass evolution as well as the hormonal regulation of plant growth and development.

  9. Systematic construction of kinetic models from genome-scale metabolic networks.

    Directory of Open Access Journals (Sweden)

    Natalie J Stanford

    Full Text Available The quantitative effects of environmental and genetic perturbations on metabolism can be studied in silico using kinetic models. We present a strategy for large-scale model construction based on a logical layering of data such as reaction fluxes, metabolite concentrations, and kinetic constants. The resulting models contain realistic standard rate laws and plausible parameters, adhere to the laws of thermodynamics, and reproduce a predefined steady state. These features have not been simultaneously achieved by previous workflows. We demonstrate the advantages and limitations of the workflow by translating the yeast consensus metabolic network into a kinetic model. Despite crudely selected data, the model shows realistic control behaviour, a stable dynamic, and realistic response to perturbations in extracellular glucose concentrations. The paper concludes by outlining how new data can continuously be fed into the workflow and how iterative model building can assist in directing experiments.

  10. Genome-Wide Analysis of the TORC1 and Osmotic Stress Signaling Network in Saccharomyces cerevisiae

    Directory of Open Access Journals (Sweden)

    Jeremy Worley

    2016-02-01

    Full Text Available The Target of Rapamycin kinase Complex I (TORC1 is a master regulator of cell growth and metabolism in eukaryotes. Studies in yeast and human cells have shown that nitrogen/amino acid starvation signals act through Npr2/Npr3 and the small GTPases Gtr1/Gtr2 (Rags in humans to inhibit TORC1. However, it is unclear how other stress and starvation stimuli inhibit TORC1, and/or act in parallel with the TORC1 pathway, to control cell growth. To help answer these questions, we developed a novel automated pipeline and used it to measure the expression of a TORC1-dependent ribosome biogenesis gene (NSR1 during osmotic stress in 4700 Saccharomyces cerevisiae strains from the yeast knock-out collection. This led to the identification of 440 strains with significant and reproducible defects in NSR1 repression. The cell growth control and stress response proteins deleted in these strains form a highly connected network, including 56 proteins involved in vesicle trafficking and vacuolar function; 53 proteins that act downstream of TORC1 according to a rapamycin assay—including components of the HDAC Rpd3L, Elongator, and the INO80, CAF-1 and SWI/SNF chromatin remodeling complexes; over 100 proteins involved in signaling and metabolism; and 17 proteins that directly interact with TORC1. These data provide an important resource for labs studying cell growth control and stress signaling, and demonstrate the utility of our new, and easily adaptable, method for mapping gene regulatory networks.

  11. Evaluation of a partial genome screening of two asthma susceptibility regions using bayesian network based bayesian multilevel analysis of relevance.

    Directory of Open Access Journals (Sweden)

    Ildikó Ungvári

    Full Text Available Genetic studies indicate high number of potential factors related to asthma. Based on earlier linkage analyses we selected the 11q13 and 14q22 asthma susceptibility regions, for which we designed a partial genome screening study using 145 SNPs in 1201 individuals (436 asthmatic children and 765 controls. The results were evaluated with traditional frequentist methods and we applied a new statistical method, called bayesian network based bayesian multilevel analysis of relevance (BN-BMLA. This method uses bayesian network representation to provide detailed characterization of the relevance of factors, such as joint significance, the type of dependency, and multi-target aspects. We estimated posteriors for these relations within the bayesian statistical framework, in order to estimate the posteriors whether a variable is directly relevant or its association is only mediated.With frequentist methods one SNP (rs3751464 in the FRMD6 gene provided evidence for an association with asthma (OR = 1.43(1.2-1.8; p = 3×10(-4. The possible role of the FRMD6 gene in asthma was also confirmed in an animal model and human asthmatics.In the BN-BMLA analysis altogether 5 SNPs in 4 genes were found relevant in connection with asthma phenotype: PRPF19 on chromosome 11, and FRMD6, PTGER2 and PTGDR on chromosome 14. In a subsequent step a partial dataset containing rhinitis and further clinical parameters was used, which allowed the analysis of relevance of SNPs for asthma and multiple targets. These analyses suggested that SNPs in the AHNAK and MS4A2 genes were indirectly associated with asthma. This paper indicates that BN-BMLA explores the relevant factors more comprehensively than traditional statistical methods and extends the scope of strong relevance based methods to include partial relevance, global characterization of relevance and multi-target relevance.

  12. Genome-wide analysis of glucocorticoid receptor binding regions in adipocytes reveal gene network involved in triglyceride homeostasis.

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    Chi-Yi Yu

    Full Text Available Glucocorticoids play important roles in the regulation of distinct aspects of adipocyte biology. Excess glucocorticoids in adipocytes are associated with metabolic disorders, including central obesity, insulin resistance and dyslipidemia. To understand the mechanisms underlying the glucocorticoid action in adipocytes, we used chromatin immunoprecipitation sequencing to isolate genome-wide glucocorticoid receptor (GR binding regions (GBRs in 3T3-L1 adipocytes. Furthermore, gene expression analyses were used to identify genes that were regulated by glucocorticoids. Overall, 274 glucocorticoid-regulated genes contain or locate nearby GBR. We found that many GBRs were located in or nearby genes involved in triglyceride (TG synthesis (Scd-1, 2, 3, GPAT3, GPAT4, Agpat2, Lpin1, lipolysis (Lipe, Mgll, lipid transport (Cd36, Lrp-1, Vldlr, Slc27a2 and storage (S3-12. Gene expression analysis showed that except for Scd-3, the other 13 genes were induced in mouse inguinal fat upon 4-day glucocorticoid treatment. Reporter gene assays showed that except Agpat2, the other 12 glucocorticoid-regulated genes contain at least one GBR that can mediate hormone response. In agreement with the fact that glucocorticoids activated genes in both TG biosynthetic and lipolytic pathways, we confirmed that 4-day glucocorticoid treatment increased TG synthesis and lipolysis concomitantly in inguinal fat. Notably, we found that 9 of these 12 genes were induced in transgenic mice that have constant elevated plasma glucocorticoid levels. These results suggested that a similar mechanism was used to regulate TG homeostasis during chronic glucocorticoid treatment. In summary, our studies have identified molecular components in a glucocorticoid-controlled gene network involved in the regulation of TG homeostasis in adipocytes. Understanding the regulation of this gene network should provide important insight for future therapeutic developments for metabolic diseases.

  13. Folate network genetic variation, plasma homocysteine, and global genomic methylation content: a genetic association study

    Directory of Open Access Journals (Sweden)

    Wernimont Susan M

    2011-11-01

    Full Text Available Abstract Background Sequence variants in genes functioning in folate-mediated one-carbon metabolism are hypothesized to lead to changes in levels of homocysteine and DNA methylation, which, in turn, are associated with risk of cardiovascular disease. Methods 330 SNPs in 52 genes were studied in relation to plasma homocysteine and global genomic DNA methylation. SNPs were selected based on functional effects and gene coverage, and assays were completed on the Illumina Goldengate platform. Age-, smoking-, and nutrient-adjusted genotype--phenotype associations were estimated in regression models. Results Using a nominal P ≤ 0.005 threshold for statistical significance, 20 SNPs were associated with plasma homocysteine, 8 with Alu methylation, and 1 with LINE-1 methylation. Using a more stringent false discovery rate threshold, SNPs in FTCD, SLC19A1, and SLC19A3 genes remained associated with plasma homocysteine. Gene by vitamin B-6 interactions were identified for both Alu and LINE-1 methylation, and epistatic interactions with the MTHFR rs1801133 SNP were identified for the plasma homocysteine phenotype. Pleiotropy involving the MTHFD1L and SARDH genes for both plasma homocysteine and Alu methylation phenotypes was identified. Conclusions No single gene was associated with all three phenotypes, and the set of the most statistically significant SNPs predictive of homocysteine or Alu or LINE-1 methylation was unique to each phenotype. Genetic variation in folate-mediated one-carbon metabolism, other than the well-known effects of the MTHFR c.665C>T (known as c.677 C>T, rs1801133, p.Ala222Val, is predictive of cardiovascular disease biomarkers.

  14. A yeast-based genomic strategy highlights the cell protein networks altered by FTase inhibitor peptidomimetics

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    Porcu Giampiero

    2010-07-01

    Full Text Available Abstract Background Farnesyltransferase inhibitors (FTIs are anticancer agents developed to inhibit Ras oncoprotein activities. FTIs of different chemical structure act via a conserved mechanism in eukaryotic cells. They have low toxicity and are active on a wide range of tumors in cellular and animal models, independently of the Ras activation state. Their ultimate mechanism of action, however, remains undetermined. FTase has hundred of substrates in human cells, many of which play a pivotal role in either tumorigenesis or in pro-survival pathways. This lack of knowledge probably accounts for the failure of FTIs at clinical stage III for most of the malignancies treated, with the notable exception of haematological malignancies. Understanding which cellular pathways are the ultimate targets of FTIs in different tumor types and the basis of FTI resistance is required to improve the efficacy of FTIs in cancer treatment. Results Here we used a yeast-based cellular assay to define the transcriptional changes consequent to FTI peptidomimetic administration in conditions that do not substantially change Ras membrane/cytosol distribution. Yeast and cancer cell lines were used to validate the results of the network analysis. The transcriptome of yeast cells treated with FTase inhibitor I was compared with that of untreated cells and with an isogenic strain genetically inhibited for FTase activity (Δram1. Cells treated with GGTI-298 were analyzed in a parallel study to validate the specificity of the FTI response. Network analysis, based on gene ontology criteria, identified a cell cycle gene cluster up-regulated by FTI treatment that has the Aurora A kinase IPL1 and the checkpoint protein MAD2 as hubs. Moreover, TORC1-S6K-downstream effectors were found to be down-regulated in yeast and mammalian FTI-treated cells. Notably only FTIs, but not genetic inhibition of FTase, elicited up-regulation of ABC/transporters. Conclusions This work provides a view

  15. Identification of networks of co-occurring, tumor-related DNA copy number changes using a genome-wide scoring approach.

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    Christiaan Klijn

    2010-01-01

    Full Text Available Tumorigenesis is a multi-step process in which normal cells transform into malignant tumors following the accumulation of genetic mutations that enable them to evade the growth control checkpoints that would normally suppress their growth or result in apoptosis. It is therefore important to identify those combinations of mutations that collaborate in cancer development and progression. DNA copy number alterations (CNAs are one of the ways in which cancer genes are deregulated in tumor cells. We hypothesized that synergistic interactions between cancer genes might be identified by looking for regions of co-occurring gain and/or loss. To this end we developed a scoring framework to separate truly co-occurring aberrations from passenger mutations and dominant single signals present in the data. The resulting regions of high co-occurrence can be investigated for between-region functional interactions. Analysis of high-resolution DNA copy number data from a panel of 95 hematological tumor cell lines correctly identified co-occurring recombinations at the T-cell receptor and immunoglobulin loci in T- and B-cell malignancies, respectively, showing that we can recover truly co-occurring genomic alterations. In addition, our analysis revealed networks of co-occurring genomic losses and gains that are enriched for cancer genes. These networks are also highly enriched for functional relationships between genes. We further examine sub-networks of these networks, core networks, which contain many known cancer genes. The core network for co-occurring DNA losses we find seems to be independent of the canonical cancer genes within the network. Our findings suggest that large-scale, low-intensity copy number alterations may be an important feature of cancer development or maintenance by affecting gene dosage of a large interconnected network of functionally related genes.

  16. Genome-wide analysis of the human p53 transcriptional network unveils a lncRNA tumour suppressor signature.

    Science.gov (United States)

    Sánchez, Yolanda; Segura, Victor; Marín-Béjar, Oskar; Athie, Alejandro; Marchese, Francesco P; González, Jovanna; Bujanda, Luis; Guo, Shuling; Matheu, Ander; Huarte, Maite

    2014-12-19

    Despite the inarguable relevance of p53 in cancer, genome-wide studies relating endogenous p53 activity to the expression of lncRNAs in human cells are still missing. Here, by integrating RNA-seq with p53 ChIP-seq analyses of a human cancer cell line under DNA damage, we define a high-confidence set of 18 lncRNAs that are p53 transcriptional targets. We demonstrate that two of the p53-regulated lncRNAs are required for the efficient binding of p53 to some of its target genes, modulating the p53 transcriptional network and contributing to apoptosis induction by DNA damage. We also show that the expression of p53-lncRNAs is lowered in colorectal cancer samples, constituting a tumour suppressor signature with high diagnostic power. Thus, p53-regulated lncRNAs establish a positive regulatory feedback loop that enhances p53 tumour suppressor activity. Furthermore, the signature defined by p53-regulated lncRNAs supports their potential use in the clinic as biomarkers and therapeutic targets.

  17. Genome-wide analysis of PDZ domain binding reveals inherent functional overlap within the PDZ interaction network.

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    Aartjan J W te Velthuis

    Full Text Available Binding selectivity and cross-reactivity within one of the largest and most abundant interaction domain families, the PDZ family, has long been enigmatic. The complete human PDZ domain complement (the PDZome consists of 267 domains and we applied here a Bayesian selectivity model to predict hundreds of human PDZ domain interactions, using target sequences of 22,997 non-redundant proteins. Subsequent analysis of these binding scores shows that PDZs can be divided into two genome-wide clusters that coincide well with the division between canonical class 1 and 2 PDZs. Within the class 1 PDZs we observed binding overlap at unprecedented levels, mediated by two residues at positions 1 and 5 of the second α-helix of the binding pocket. Eight PDZ domains were subsequently selected for experimental binding studies and to verify the basics of our predictions. Overall, the PDZ domain class 1 cross-reactivity identified here implies that auxiliary mechanisms must be in place to overcome this inherent functional overlap and to minimize cross-selectivity within the living cell. Indeed, when we superimpose PDZ domain binding affinities with gene ontologies, network topology data and the domain position within a PDZ superfamily protein, functional overlap is minimized and PDZ domains position optimally in the binding space. We therefore propose that PDZ domain selectivity is achieved through cellular context rather than inherent binding specificity.

  18. Genome-Wide Mapping of Collier In Vivo Binding Sites Highlights Its Hierarchical Position in Different Transcription Regulatory Networks.

    Directory of Open Access Journals (Sweden)

    Mathilde de Taffin

    Full Text Available Collier, the single Drosophila COE (Collier/EBF/Olf-1 transcription factor, is required in several developmental processes, including head patterning and specification of muscle and neuron identity during embryogenesis. To identify direct Collier (Col targets in different cell types, we used ChIP-seq to map Col binding sites throughout the genome, at mid-embryogenesis. In vivo Col binding peaks were associated to 415 potential direct target genes. Gene Ontology analysis revealed a strong enrichment in proteins with DNA binding and/or transcription-regulatory properties. Characterization of a selection of candidates, using transgenic CRM-reporter assays, identified direct Col targets in dorso-lateral somatic muscles and specific neuron types in the central nervous system. These data brought new evidence that Col direct control of the expression of the transcription regulators apterous and eyes-absent (eya is critical to specifying neuronal identities. They also showed that cross-regulation between col and eya in muscle progenitor cells is required for specification of muscle identity, revealing a new parallel between the myogenic regulatory networks operating in Drosophila and vertebrates. Col regulation of eya, both in specific muscle and neuronal lineages, may illustrate one mechanism behind the evolutionary diversification of Col biological roles.

  19. Climate Literacy and Energy Awareness Network (CLEAN) - Interactive Webinars for Teacher Professional Development

    Science.gov (United States)

    Grogan, M.; Ledley, T. S.; Buhr, S. M.

    2012-12-01

    Climate change will have far reaching impacts that the citizens of tomorrow will need to be prepared to address. In order for the citizens of tomorrow to be prepared, there is a clear need to support teachers in improving their understanding of the climate system and give them the resources to help their students develop that understanding. CLEAN (http://cleanet.org) is a National Science Digital Library (http://www.nsdl.org) project that is stewarding a collection of resources for teaching climate and energy science in grades 6-16. The collection contains classroom activities, lab demonstrations, visualizations, simulations, videos, and more. We have implemented a series of nine interactive webinars (iWebinars), each of which focuses on an aspect of the Essential Principles of Climate Science, pairs a scientist and a teacher to convey the science and how to teach that science using the vetted resources in the CLEAN collection, and gives the participants the opportunity to ask questions and discuss with the presenters and each other how they would use the resources in their classrooms and what else they would need to effectively teach the topic under discussion. The iWebinars were recorded and posted to the CLEAN portal (http://cleanet.org/clean/community/webinars/index.html) so that the participants and others can view them in the future. In this presentation, we will describe the scope and structure of the iWebinars; how the scientist's and teacher's presentations were coordinated to most effectively help the participants learn both the science and how to best convey it to their students; and how we involved the teachers in discussions to deepen their engagement and learning.

  20. Integrated genomics and proteomics define huntingtin CAG length-dependent networks in mice.

    Science.gov (United States)

    Langfelder, Peter; Cantle, Jeffrey P; Chatzopoulou, Doxa; Wang, Nan; Gao, Fuying; Al-Ramahi, Ismael; Lu, Xiao-Hong; Ramos, Eliana Marisa; El-Zein, Karla; Zhao, Yining; Deverasetty, Sandeep; Tebbe, Andreas; Schaab, Christoph; Lavery, Daniel J; Howland, David; Kwak, Seung; Botas, Juan; Aaronson, Jeffrey S; Rosinski, Jim; Coppola, Giovanni; Horvath, Steve; Yang, X William

    2016-04-01

    To gain insight into how mutant huntingtin (mHtt) CAG repeat length modifies Huntington's disease (HD) pathogenesis, we profiled mRNA in over 600 brain and peripheral tissue samples from HD knock-in mice with increasing CAG repeat lengths. We found repeat length-dependent transcriptional signatures to be prominent in the striatum, less so in cortex, and minimal in the liver. Coexpression network analyses revealed 13 striatal and 5 cortical modules that correlated highly with CAG length and age, and that were preserved in HD models and sometimes in patients. Top striatal modules implicated mHtt CAG length and age in graded impairment in the expression of identity genes for striatal medium spiny neurons and in dysregulation of cyclic AMP signaling, cell death and protocadherin genes. We used proteomics to confirm 790 genes and 5 striatal modules with CAG length-dependent dysregulation at the protein level, and validated 22 striatal module genes as modifiers of mHtt toxicities in vivo.

  1. Telepresence teacher professional development for physics and math constructs focused on US and Thai classrooms' TC-1 slinky seismometer networks

    Science.gov (United States)

    Livelybrooks, D.; Parris, B. A.; Cook, A.; Kant, M.; Wogan, N.; Zeryck, A.; Tulyatid, D.; Toomey, D. R.

    2015-12-01

    As part of the Broader Impacts of the Cascadia Initiative, a seismic study of the Cascadia margin, and the Magnetotelluric Observations of Cascadia using a Huge Array (MOCHA) collaboration we have developed school- and museum/library-based networks of TC-1 educational seismometers. The TC-1 is constructed such that its 'guts' are visible through an transparent acrylic outer cylinder, thus it is an excellent demonstration of how fundamental physics constructs can be leveraged to design and operate a vertical-channel seismometer capable of recording signals from large earthquakes world-wide. TC-1 (aka 'slinky seismometer') networks therefore serve as the application for projects-based learning (PBL) physics and data science instruction in Oregon and Thai classrooms. The TC-1 acts as a simple harmonic oscillator, employing electromagnetic induction of a moving magnet within a wire coil. Movement of the lower magnet within an electrically conductive pipe dampens motion such that P-, S- and Surface wave phases can be identified. Further, jAmaSeis software can be configured to simultaneously show live signals from three TC-1s and has tools necessary to pick phases for earthquake signals and, thus, locate earthquake epicenters. Leveraging a long-standing collaboration between the Royal Thai Distance Learning Foundation and the University of Oregon, we developed five, 2-hour, two-way teacher professional development sessions that were transmitted live to Thai K-12 teachers and others starting mid-August, 2015. As an example, one session emphasized hands-on activities to analyze the effect of spring stiffness, inertial mass and initial displacement on the resonance frequency of a simple oscillator. Another pedagogical goal was to elucidate how math is important to understanding the analysis of seismic data, for example, how cross-correlation is useful for distinguishing between genuine earthquake signals and, say, a truck rolling by a TC-1 station. UO graduate and

  2. Learning through Social Networking Sites--The Critical Role of the Teacher

    Science.gov (United States)

    Callaghan, Noelene; Bower, Matt

    2012-01-01

    This comparative case study examined factors affecting behaviour and learning in social networking sites (SNS). The behaviour and learning of two classes completing identical SNS based modules of work was observed and compared. All student contributions to the SNS were analysed, with the cognitive process dimension of the Revised Bloom's Taxonomy…

  3. Learning through Social Networking Sites--The Critical Role of the Teacher

    Science.gov (United States)

    Callaghan, Noelene; Bower, Matt

    2012-01-01

    This comparative case study examined factors affecting behaviour and learning in social networking sites (SNS). The behaviour and learning of two classes completing identical SNS based modules of work was observed and compared. All student contributions to the SNS were analysed, with the cognitive process dimension of the Revised Bloom's Taxonomy…

  4. Teacher Perception on Educational Informatics Network: A Qualitative Study of a Turkish Anatolian High School

    Science.gov (United States)

    Karalar, Halit; Dogan, Ugur

    2017-01-01

    FATIH Project carried out by the Turkish government is one of the comprehensive technology integration project in the World. With this project, interactive boards, tablets and multifunctional printers have been distributed to schools and Internet infrastructure of schools improved. EIN (Educational Informatics Network) platform, known as EBA…

  5. An Evolutionary Network of Genes Present in the Eukaryote Common Ancestor Polls Genomes on Eukaryotic and Mitochondrial Origin

    OpenAIRE

    Thiergart, T.; Landan, G; Schenk, M.; Dagan, T.; Martin, W F

    2012-01-01

    To test the predictions of competing and mutually exclusive hypotheses for the origin of eukaryotes, we identified from a sample of 27 sequenced eukaryotic and 994 sequenced prokaryotic genomes 571 genes that were present in the eukaryote common ancestor and that have homologues among eubacterial and archaebacterial genomes. Maximum-likelihood trees identified the prokaryotic genomes that most frequently contained genes branching as the sister to the eukaryotic nuclear homologues. Among the a...

  6. Network Analysis of Beliefs About the Scientific Enterprise: A comparison of scientists, middle school science teachers and eighth-grade science students

    Science.gov (United States)

    Peters-Burton, Erin; Baynard, Liz R.

    2013-11-01

    An understanding of the scientific enterprise is useful because citizens need to make systematic, rational decisions about projects involving scientific endeavors and technology, and a clearer understanding of scientific epistemology is beneficial because it could encourage more public engagement with science. The purpose of this study was to capture beliefs for three groups, scientists, secondary science teachers, and eighth-grade science students, about the ways scientific knowledge is generated and validated. Open-ended questions were framed by formal scientific epistemology and dimensions of epistemology recognized in the field of educational psychology. The resulting statements were placed in a card sort and mapped in a network analysis to communicate interconnections among ideas. Maps analyzed with multidimensional scaling revealed robust connections among students and scientists but not among teachers. Student and teacher maps illustrated the strongest connections among ideas about experiments while scientist maps present more descriptive and well-rounded ideas about the scientific enterprise. The students' map was robust in terms of numbers of ideas, but were lacking in a hierarchical organization of ideas. The teachers' map displayed an alignment with the learning standards of the state, but not a broader view of science. The scientists map displayed a hierarchy of ideas with elaboration of equally valued statements connected to several foundational statements. Network analysis can be helpful in forwarding the study of views of the nature of science because of the technique's ability to capture verbatim statements from participants and to display the strength of connections among the statements.

  7. 网络时代高校教师职业规范摭谈%Professional Norms of University Teachers in Network Age

    Institute of Scientific and Technical Information of China (English)

    吴丽容

    2014-01-01

    Network brings new challenges for the professional quality of university teachers; the problems of moral anomie, teaching anomie, and academic anomie are usually exposed. Teachers should allow smart phones get into the classroom and ready to accept network monitoring, which requires that teachers should achieve unified morality and knowledge, teaching of life, and strengthen opportune communications with each other, as well as the teachers' team should establish norms and improve system.%网络给高校教师的职业素质带来了全新的挑战,道德失范、教学失范、学术失范等问题时有曝光。教师应允许智能手机进入课堂并随时接受网络监督,这要求教师本人要德识统一、以身立教,教师之间要加强交流、及时通联,教师队伍要确立规范、完善制度。

  8. Stroke Genetics Network (SiGN) study: design and rationale for a genome-wide association study of ischemic stroke subtypes.

    Science.gov (United States)

    Meschia, James F; Arnett, Donna K; Ay, Hakan; Brown, Robert D; Benavente, Oscar R; Cole, John W; de Bakker, Paul I W; Dichgans, Martin; Doheny, Kimberly F; Fornage, Myriam; Grewal, Raji P; Gwinn, Katrina; Jern, Christina; Conde, Jordi Jimenez; Johnson, Julie A; Jood, Katarina; Laurie, Cathy C; Lee, Jin-Moo; Lindgren, Arne; Markus, Hugh S; McArdle, Patrick F; McClure, Leslie A; Mitchell, Braxton D; Schmidt, Reinhold; Rexrode, Kathryn M; Rich, Stephen S; Rosand, Jonathan; Rothwell, Peter M; Rundek, Tatjana; Sacco, Ralph L; Sharma, Pankaj; Shuldiner, Alan R; Slowik, Agnieszka; Wassertheil-Smoller, Sylvia; Sudlow, Cathie; Thijs, Vincent N S; Woo, Daniel; Worrall, Bradford B; Wu, Ona; Kittner, Steven J

    2013-10-01

    Meta-analyses of extant genome-wide data illustrate the need to focus on subtypes of ischemic stroke for gene discovery. The National Institute of Neurological Disorders and Stroke SiGN (Stroke Genetics Network) contributes substantially to meta-analyses that focus on specific subtypes of stroke. The National Institute of Neurological Disorders and Stroke SiGN includes ischemic stroke cases from 24 genetic research centers: 13 from the United States and 11 from Europe. Investigators harmonize ischemic stroke phenotyping using the Web-based causative classification of stroke system, with data entered by trained and certified adjudicators at participating genetic research centers. Through the Center for Inherited Diseases Research, the Network plans to genotype 10,296 carefully phenotyped stroke cases using genome-wide single nucleotide polymorphism arrays and adds to these another 4253 previously genotyped cases, for a total of 14,549 cases. To maximize power for subtype analyses, the study allocates genotyping resources almost exclusively to cases. Publicly available studies provide most of the control genotypes. Center for Inherited Diseases Research-generated genotypes and corresponding phenotypes will be shared with the scientific community through the US National Center for Biotechnology Information database of Genotypes and Phenotypes, and brain MRI studies will be centrally archived. The Stroke Genetics Network, with its emphasis on careful and standardized phenotyping of ischemic stroke and stroke subtypes, provides an unprecedented opportunity to uncover genetic determinants of ischemic stroke.

  9. Functional architecture and global properties of the Corynebacterium glutamicum regulatory network: Novel insights from a dataset with a high genomic coverage.

    Science.gov (United States)

    Freyre-González, Julio A; Tauch, Andreas

    2017-09-10

    Corynebacterium glutamicum is a Gram-positive, anaerobic, rod-shaped soil bacterium able to grow on a diversity of carbon sources like sugars and organic acids. It is a biotechnological relevant organism because of its highly efficient ability to biosynthesize amino acids, such as l-glutamic acid and l-lysine. Here, we reconstructed the most complete C. glutamicum regulatory network to date and comprehensively analyzed its global organizational properties, systems-level features and functional architecture. Our analyses show the tremendous power of Abasy Atlas to study the functional organization of regulatory networks. We created two models of the C. glutamicum regulatory network: all-evidences (containing both weak and strong supported interactions, genomic coverage=73%) and strongly-supported (only accounting for strongly supported evidences, genomic coverage=71%). Using state-of-the-art methodologies, we prove that power-law behaviors truly govern the connectivity and clustering coefficient distributions. We found a non-previously reported circuit motif that we named complex feed-forward motif. We highlighted the importance of feedback loops for the functional architecture, beyond whether they are statistically over-represented or not in the network. We show that the previously reported top-down approach is inadequate to infer the hierarchy governing a regulatory network because feedback bridges different hierarchical layers, and the top-down approach disregards the presence of intermodular genes shaping the integration layer. Our findings all together further support a diamond-shaped, three-layered hierarchy exhibiting some feedback between processing and coordination layers, which is shaped by four classes of systems-level elements: global regulators, locally autonomous modules, basal machinery and intermodular genes. Copyright © 2016 Elsevier B.V. All rights reserved.

  10. Mechanistically Distinct Pathways of Divergent Regulatory DNA Creation Contribute to Evolution of Human-Specific Genomic Regulatory Networks Driving Phenotypic Divergence of Homo sapiens.

    Science.gov (United States)

    Glinsky, Gennadi V

    2016-09-19

    Thousands of candidate human-specific regulatory sequences (HSRS) have been identified, supporting the hypothesis that unique to human phenotypes result from human-specific alterations of genomic regulatory networks. Collectively, a compendium of multiple diverse families of HSRS that are functionally and structurally divergent from Great Apes could be defined as the backbone of human-specific genomic regulatory networks. Here, the conservation patterns analysis of 18,364 candidate HSRS was carried out requiring that 100% of bases must remap during the alignments of human, chimpanzee, and bonobo sequences. A total of 5,535 candidate HSRS were identified that are: (i) highly conserved in Great Apes; (ii) evolved by the exaptation of highly conserved ancestral DNA; (iii) defined by either the acceleration of mutation rates on the human lineage or the functional divergence from non-human primates. The exaptation of highly conserved ancestral DNA pathway seems mechanistically distinct from the evolution of regulatory DNA segments driven by the species-specific expansion of transposable elements. Genome-wide proximity placement analysis of HSRS revealed that a small fraction of topologically associating domains (TADs) contain more than half of HSRS from four distinct families. TADs that are enriched for HSRS and termed rapidly evolving in humans TADs (revTADs) comprise 0.8-10.3% of 3,127 TADs in the hESC genome. RevTADs manifest distinct correlation patterns between placements of human accelerated regions, human-specific transcription factor-binding sites, and recombination rates. There is a significant enrichment within revTAD boundaries of hESC-enhancers, primate-specific CTCF-binding sites, human-specific RNAPII-binding sites, hCONDELs, and H3K4me3 peaks with human-specific enrichment at TSS in prefrontal cortex neurons (P Homo sapiens is driven by the evolution of human-specific genomic regulatory networks via at least two mechanistically distinct pathways of

  11. Systems genetics of obesity in an F2 pig model by genome-wide association, genetic network and pathway analyses

    DEFF Research Database (Denmark)

    Kogelman, Lisette; Pant, Sameer Dinkar; Fredholm, Merete;

    2014-01-01

    Obesity is a complex condition with world-wide exponentially rising prevalence rates, linked with severe diseases like Type 2 Diabetes. Economic and welfare consequences have led to a raised interest in a better understanding of the biological and genetic background. To date, whole genome...... of obesity-related phenotypes and genotyped using the 60K SNP chip. Firstly, Genome Wide Association (GWA) analysis was performed on the Obesity Index to locate candidate genomic regions that were further validated using combined Linkage Disequilibrium Linkage Analysis and investigated by evaluation...

  12. Systems genetics of obesity in an F2 pig model by genome-wide association, genetic network and pathway analyses

    DEFF Research Database (Denmark)

    Kogelman, Lisette; Pant, Sameer Dinkar; Fredholm, Merete

    2014-01-01

    Obesity is a complex condition with world-wide exponentially rising prevalence rates, linked with severe diseases like Type 2 Diabetes. Economic and welfare consequences have led to a raised interest in a better understanding of the biological and genetic background. To date, whole genome...... of obesity-related phenotypes and genotyped using the 60K SNP chip. Firstly, Genome Wide Association (GWA) analysis was performed on the Obesity Index to locate candidate genomic regions that were further validated using combined Linkage Disequilibrium Linkage Analysis and investigated by evaluation...

  13. News Competition: Physics Olympiad hits Thailand Report: Institute carries out survey into maths in physics at university Event: A day for everyone teaching physics Conference: Welsh conference celebrates birthday Schools: Researchers in Residence scheme set to close Teachers: A day for new physics teachers Social: Network combines fun and physics Forthcoming events

    Science.gov (United States)

    2011-09-01

    Competition: Physics Olympiad hits Thailand Report: Institute carries out survey into maths in physics at university Event: A day for everyone teaching physics Conference: Welsh conference celebrates birthday Schools: Researchers in Residence scheme set to close Teachers: A day for new physics teachers Social: Network combines fun and physics Forthcoming events

  14. Weighted gene co-expression network analysis in identification of metastasis-related genes of lung squamous cell carcinoma based on the Cancer Genome Atlas database

    Science.gov (United States)

    Tian, Feng; Zhao, Jinlong; Kang, Zhenxing

    2017-01-01

    Background Lung squamous cell carcinoma (lung SCC) is a common type of malignancy. Its pathogenesis mechanism of tumor development is unclear. The aim of this study was to identify key genes for diagnosis biomarkers in lung SCC metastasis. Methods We searched and downloaded mRNA expression data and clinical data from The Cancer Genome Atlas (TCGA) database to identify differences in mRNA expression of primary tumor tissues from lung SCC with and without metastasis. Gene co-expression network analysis, protein-protein interaction (PPI) network, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and quantitative real-time polymerase chain reactions (qRT-PCR) were used to explore the biological functions of the identified dysregulated genes. Results Four hundred and eighty-two differentially expressed genes (DEGs) were identified between lung SCC with and without metastasis. Nineteen modules were identified in lung SCC through weighted gene co-expression network analysis (WGCNA). Twenty-three DEGs and 26 DEGs were significantly enriched in the respective pink and black module. KEGG pathway analysis displayed that 26 DEGs in the black module were significantly enriched in bile secretion pathway. Forty-nine DEGs in the two gene co-expression module were used to construct PPI network. CFTR in the black module was the hub protein, had the connectivity with 182 genes. The results of qRT-PCR displayed that FIGF, SFTPD, DYNLRB2 were significantly down-regulated in the tumor samples of lung SCC with metastasis and CFTR, SCGB3A2, SSTR1, SCTR, ROPN1L had the down-regulation tendency in lung SCC with metastasis compared to lung SCC without metastasis. Conclusions The dysregulated genes including CFTR, SCTR and FIGF might be involved in the pathology of lung SCC metastasis and could be used as potential diagnosis biomarkers or therapeutic targets for lung SCC.

  15. Weighted gene co-expression network analysis in identification of metastasis-related genes of lung squamous cell carcinoma based on the Cancer Genome Atlas database.

    Science.gov (United States)

    Tian, Feng; Zhao, Jinlong; Fan, Xinlei; Kang, Zhenxing

    2017-01-01

    Lung squamous cell carcinoma (lung SCC) is a common type of malignancy. Its pathogenesis mechanism of tumor development is unclear. The aim of this study was to identify key genes for diagnosis biomarkers in lung SCC metastasis. We searched and downloaded mRNA expression data and clinical data from The Cancer Genome Atlas (TCGA) database to identify differences in mRNA expression of primary tumor tissues from lung SCC with and without metastasis. Gene co-expression network analysis, protein-protein interaction (PPI) network, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and quantitative real-time polymerase chain reactions (qRT-PCR) were used to explore the biological functions of the identified dysregulated genes. Four hundred and eighty-two differentially expressed genes (DEGs) were identified between lung SCC with and without metastasis. Nineteen modules were identified in lung SCC through weighted gene co-expression network analysis (WGCNA). Twenty-three DEGs and 26 DEGs were significantly enriched in the respective pink and black module. KEGG pathway analysis displayed that 26 DEGs in the black module were significantly enriched in bile secretion pathway. Forty-nine DEGs in the two gene co-expression module were used to construct PPI network. CFTR in the black module was the hub protein, had the connectivity with 182 genes. The results of qRT-PCR displayed that FIGF, SFTPD, DYNLRB2 were significantly down-regulated in the tumor samples of lung SCC with metastasis and CFTR, SCGB3A2, SSTR1, SCTR, ROPN1L had the down-regulation tendency in lung SCC with metastasis compared to lung SCC without metastasis. The dysregulated genes including CFTR, SCTR and FIGF might be involved in the pathology of lung SCC metastasis and could be used as potential diagnosis biomarkers or therapeutic targets for lung SCC.

  16. Using regulatory and epistatic networks to extend the findings of a genome scan: identifying the gene drivers of pigmentation in merino sheep.

    Science.gov (United States)

    García-Gámez, Elsa; Reverter, Antonio; Whan, Vicki; McWilliam, Sean M; Arranz, Juan José; Kijas, James

    2011-01-01

    Extending genome wide association analysis by the inclusion of gene expression data may assist in the dissection of complex traits. We examined piebald, a pigmentation phenotype in both human and Merino sheep, by analysing multiple data types using a systems approach. First, a case control analysis of 49,034 ovine SNP was performed which confirmed a multigenic basis for the condition. We combined these results with gene expression data from five tissue types analysed with a skin-specific microarray. Promoter sequence analysis of differentially expressed genes allowed us to reverse-engineer a regulatory network. Likewise, by testing two-loci models derived from all pair-wise comparisons across piebald-associated SNP, we generated an epistatic network. At the intersection of both networks, we identified thirteen genes with insulin-like growth factor binding protein 7 (IGFBP7), platelet-derived growth factor alpha (PDGFRA) and the tetraspanin platelet activator CD9 at the kernel of the intersection. Further, we report a number of differentially expressed genes in regions containing highly associated SNP including ATRN, DOCK7, FGFR1OP, GLI3, SILV and TBX15. The application of network theory facilitated co-analysis of genetic variation with gene expression, recapitulated aspects of the known molecular biology of skin pigmentation and provided insights into the transcription regulation and epistatic interactions involved in piebald Merino sheep.

  17. Using regulatory and epistatic networks to extend the findings of a genome scan: identifying the gene drivers of pigmentation in merino sheep.

    Directory of Open Access Journals (Sweden)

    Elsa García-Gámez

    Full Text Available Extending genome wide association analysis by the inclusion of gene expression data may assist in the dissection of complex traits. We examined piebald, a pigmentation phenotype in both human and Merino sheep, by analysing multiple data types using a systems approach. First, a case control analysis of 49,034 ovine SNP was performed which confirmed a multigenic basis for the condition. We combined these results with gene expression data from five tissue types analysed with a skin-specific microarray. Promoter sequence analysis of differentially expressed genes allowed us to reverse-engineer a regulatory network. Likewise, by testing two-loci models derived from all pair-wise comparisons across piebald-associated SNP, we generated an epistatic network. At the intersection of both networks, we identified thirteen genes with insulin-like growth factor binding protein 7 (IGFBP7, platelet-derived growth factor alpha (PDGFRA and the tetraspanin platelet activator CD9 at the kernel of the intersection. Further, we report a number of differentially expressed genes in regions containing highly associated SNP including ATRN, DOCK7, FGFR1OP, GLI3, SILV and TBX15. The application of network theory facilitated co-analysis of genetic variation with gene expression, recapitulated aspects of the known molecular biology of skin pigmentation and provided insights into the transcription regulation and epistatic interactions involved in piebald Merino sheep.

  18. 2004 Structural, Function and Evolutionary Genomics

    Energy Technology Data Exchange (ETDEWEB)

    Douglas L. Brutlag Nancy Ryan Gray

    2005-03-23

    This Gordon conference will cover the areas of structural, functional and evolutionary genomics. It will take a systematic approach to genomics, examining the evolution of proteins, protein functional sites, protein-protein interactions, regulatory networks, and metabolic networks. Emphasis will be placed on what we can learn from comparative genomics and entire genomes and proteomes.

  19. Supporting Teachers in Climate Change Instruction - The Climate Literacy and Energy Awareness Network (CLEAN) Tool Kit

    Science.gov (United States)

    Gold, A. U.; Ledley, T. S.; Buhr, S. M.; Manduca, C. A.; Fox, S.; Kirk, K. B.; Grogan, M.; Niepold, F.; Carley, S.; Lynds, S. E.; Howell, C. D.

    2012-12-01

    The topic of climate change comes up regularly in news stories and household discussions. However, a recent poll among teenagers about their knowledge of climate change shows that teenagers' understanding of the basics of the climate system is minimal with 54% receiving a failing grade (Leiserowitz et al., 2011). The upcoming Next Generation Science Standards emphasize that solid knowledge about climate change and sustainability is essential for students to be prepared for the decisions the next generation of citizens will face. We summarize the needs described by educators in a national, multi-year informant pool study focused on climate instruction, and outline the demands the new Next Generation Science Standards are posing on educators, in terms of climate and sustainability instruction. We then showcase different tools available to educators to address these needs. The Climate Literacy and Energy Awareness Network (CLEAN, cleanet.org) supports educators in addressing these challenges and assists them in their teaching about climate topics. In this presentation we will demonstrate the various avenues through which the CLEAN portal can help educators improve their own climate and energy literacy, support them in determining why and how to effectively integrate the climate and energy principles into their teaching, and facilitate their successful use of the resources with their students. This will include a brief overview of the following features: a) The breadth of the collection , which contains over 450 reviewed resources, and the multi-faceted search that can help educators quickly find materials that are most relevant to their needs; b) Annotations of individual resources that provide information extracted from the reviews about the science, pedagogy, and teaching tips, as well as indicating the relevant climate or energy principles and the AAAS Benchmarks for Science Literacy, the National Science Education Standards, and the Guidelines for Excellence in

  20. Gene network analyses of first service conception in Brangus heifers: use of genome and trait associations, hypothalamic-transcriptome information, and transcription factors.

    Science.gov (United States)

    Fortes, M R S; Snelling, W M; Reverter, A; Nagaraj, S H; Lehnert, S A; Hawken, R J; DeAtley, K L; Peters, S O; Silver, G A; Rincon, G; Medrano, J F; Islas-Trejo, A; Thomas, M G

    2012-09-01

    Measures of heifer fertility are economically relevant traits for beef production systems and knowledge of candidate genes could be incorporated into future genomic selection strategies. Ten traits related to growth and fertility were measured in 890 Brangus heifers (3/8 Brahman × 5/8 Angus, from 67 sires). These traits were: BW and hip height adjusted to 205 and 365 d of age, postweaning ADG, yearling assessment of carcass traits (i.e., back fat thickness, intramuscular fat, and LM area), as well as heifer pregnancy and first service conception (FSC). These fertility traits were collected from controlled breeding seasons initiated with estrous synchronization and AI targeting heifers to calve by 24 mo of age. The BovineSNP50 BeadChip was used to ascertain 53,692 SNP genotypes for ∼802 heifers. Associations of genotypes and phenotypes were performed and SNP effects were estimated for each trait. Minimally associated SNP (P < 0.05) and their effects across the 10 traits formed the basis for an association weight matrix and its derived gene network related to FSC (57.3% success and heritability = 0.06 ± 0.05). These analyses yielded 1,555 important SNP, which inferred genes linked by 113,873 correlations within a network. Specifically, 1,386 SNP were nodes and the 5,132 strongest correlations (|r| ≥ 0.90) were edges. The network was filtered with genes queried from a transcriptome resource created from deep sequencing of RNA (i.e., RNA-Seq) from the hypothalamus of a prepubertal and a postpubertal Brangus heifer. The remaining hypothalamic-influenced network contained 978 genes connected by 2,560 edges or predicted gene interactions. This hypothalamic gene network was enriched with genes involved in axon guidance, which is a pathway known to influence pulsatile release of LHRH. There were 5 transcription factors with 21 or more connections: ZMAT3, STAT6, RFX4, PLAGL1, and NR6A1 for FSC. The SNP that identified these genes were intragenic and were on chromosomes

  1. The Relevance and Educational Value of Social Network Sites for Classroom Literacy Learning. A discussion based on empirical work with Norwegian students and teachers.

    Directory of Open Access Journals (Sweden)

    Håvard Skaar

    2011-12-01

    Full Text Available Web 2.0 allows young people to engage in new kinds of online participation, e.g. on social network sites. When young people produce digital texts to communicate with their friends or connect with them, they engage and integrate their literacy in their everyday lives. Social network sites are thus examples of how digital media open up spaces where literacy becomes part of young people’s social and cultural practices in new and unprecedented ways. Is this development relevant to school-based literacy learning? If so, how should it be met in the classroom? In the paper these questions are addressed against the backdrop of empirical work with Norwegian students and teachers. This material particularly reveals how students and teachers experience the relationship between educational and commercial aspects of young people’s cultural and social lives online. The analyses of the empirical material draw on work contained in New Literacy Studies and Media Education Research. In the discussion section it is argued that the relationship between the educational and commercial aspects of young people’s use of social network sites must be more closely examined in the light of how these activities actually relate to literacy learning in the classroom.

  2. Polygenic transmission and complex neuro developmental network for attention deficit hyperactivity disorder: genome-wide association study of both common and rare variants.

    Science.gov (United States)

    Yang, Li; Neale, Benjamin M; Liu, Lu; Lee, S Hong; Wray, Naomi R; Ji, Ning; Li, Haimei; Qian, Qiujin; Wang, Dongliang; Li, Jun; Faraone, Stephen V; Wang, Yufeng; Doyle, Alysa E; Reif, Andreas; Rothenberger, Aribert; Franke, Barbara; Sonuga-Barke, Edmund J S; Steinhausen, Hans-Christoph; Buitelaar, Jan K; Kuntsi, Jonna; Biederman, Joseph; Lesch, Klaus-Peter; Kent, Lindsey; Asherson, Philip; Oades, Robert D; Loo, Sandra K; Nelson, Stan F; Faraone, Stephen V; Smalley, Susan L; Banaschewski, Tobias; Arias Vasquez, Alejandro; Todorov, Alexandre; Charach, Alice; Miranda, Ana; Warnke, Andreas; Thapar, Anita; Neale, Benjamin M; Cormand, Bru; Freitag, Christine; Mick, Eric; Mulas, Fernando; Middleton, Frank; HakonarsonHakonarson, Hakon; Palmason, Haukur; Schäfer, Helmut; Roeyers, Herbert; McGough, James J; Romanos, Jasmin; Crosbie, Jennifer; Meyer, Jobst; Ramos-Quiroga, Josep Antoni; Sergeant, Joseph; Elia, Josephine; Langely, Kate; Nisenbaum, Laura; Romanos, Marcel; Daly, Mark J; Ribasés, Marta; Gill, Michael; O'Donovan, Michael; Owen, Michael; Casas, Miguel; Bayés, Mònica; Lambregts-Rommelse, Nanda; Williams, Nigel; Holmans, Peter; Anney, Richard J L; Ebstein, Richard P; Schachar, Russell; Medland, Sarah E; Ripke, Stephan; Walitza, Susanne; Nguyen, Thuy Trang; Renner, Tobias J; Hu, Xiaolan

    2013-07-01

    Attention-deficit hyperactivity disorder (ADHD) is a complex polygenic disorder. This study aimed to discover common and rare DNA variants associated with ADHD in a large homogeneous Han Chinese ADHD case-control sample. The sample comprised 1,040 cases and 963 controls. All cases met DSM-IV ADHD diagnostic criteria. We used the Affymetrix6.0 array to assay both single nucleotide polymorphisms (SNPs) and copy number variants (CNVs). Genome-wide association analyses were performed using PLINK. SNP-heritability and SNP-genetic correlations with ADHD in Caucasians were estimated with genome-wide complex trait analysis (GCTA). Pathway analyses were performed using the Interval enRICHment Test (INRICH), the Disease Association Protein-Protein Link Evaluator (DAPPLE), and the Genomic Regions Enrichment of Annotations Tool (GREAT). We did not find genome-wide significance for single SNPs but did find an increased burden of large, rare CNVs in the ADHD sample (P = 0.038). SNP-heritability was estimated to be 0.42 (standard error, 0.13, P = 0.0017) and the SNP-genetic correlation with European Ancestry ADHD samples was 0.39 (SE 0.15, P = 0.0072). The INRICH, DAPPLE, and GREAT analyses implicated several gene ontology cellular components, including neuron projections and synaptic components, which are consistent with a neurodevelopmental pathophysiology for ADHD. This study suggested the genetic architecture of ADHD comprises both common and rare variants. Some common causal variants are likely to be shared between Han Chinese and Caucasians. Complex neurodevelopmental networks may underlie ADHD's etiology.

  3. Plasmid flux in Escherichia coli ST131 sublineages, analyzed by plasmid constellation network (PLACNET, a new method for plasmid reconstruction from whole genome sequences.

    Directory of Open Access Journals (Sweden)

    Val F Lanza

    2014-12-01

    Full Text Available Bacterial whole genome sequence (WGS methods are rapidly overtaking classical sequence analysis. Many bacterial sequencing projects focus on mobilome changes, since macroevolutionary events, such as the acquisition or loss of mobile genetic elements, mainly plasmids, play essential roles in adaptive evolution. Existing WGS analysis protocols do not assort contigs between plasmids and the main chromosome, thus hampering full analysis of plasmid sequences. We developed a method (called plasmid constellation networks or PLACNET that identifies, visualizes and analyzes plasmids in WGS projects by creating a network of contig interactions, thus allowing comprehensive plasmid analysis within WGS datasets. The workflow of the method is based on three types of data: assembly information (including scaffold links and coverage, comparison to reference sequences and plasmid-diagnostic sequence features. The resulting network is pruned by expert analysis, to eliminate confounding data, and implemented in a Cytoscape-based graphic representation. To demonstrate PLACNET sensitivity and efficacy, the plasmidome of the Escherichia coli lineage ST131 was analyzed. ST131 is a globally spread clonal group of extraintestinal pathogenic E. coli (ExPEC, comprising different sublineages with ability to acquire and spread antibiotic resistance and virulence genes via plasmids. Results show that plasmids flux in the evolution of this lineage, which is wide open for plasmid exchange. MOBF12/IncF plasmids were pervasive, adding just by themselves more than 350 protein families to the ST131 pangenome. Nearly 50% of the most frequent γ-proteobacterial plasmid groups were found to be present in our limited sample of ten analyzed ST131 genomes, which represent the main ST131 sublineages.

  4. Plasmid flux in Escherichia coli ST131 sublineages, analyzed by plasmid constellation network (PLACNET), a new method for plasmid reconstruction from whole genome sequences.

    Science.gov (United States)

    Lanza, Val F; de Toro, María; Garcillán-Barcia, M Pilar; Mora, Azucena; Blanco, Jorge; Coque, Teresa M; de la Cruz, Fernando

    2014-12-01

    Bacterial whole genome sequence (WGS) methods are rapidly overtaking classical sequence analysis. Many bacterial sequencing projects focus on mobilome changes, since macroevolutionary events, such as the acquisition or loss of mobile genetic elements, mainly plasmids, play essential roles in adaptive evolution. Existing WGS analysis protocols do not assort contigs between plasmids and the main chromosome, thus hampering full analysis of plasmid sequences. We developed a method (called plasmid constellation networks or PLACNET) that identifies, visualizes and analyzes plasmids in WGS projects by creating a network of contig interactions, thus allowing comprehensive plasmid analysis within WGS datasets. The workflow of the method is based on three types of data: assembly information (including scaffold links and coverage), comparison to reference sequences and plasmid-diagnostic sequence features. The resulting network is pruned by expert analysis, to eliminate confounding data, and implemented in a Cytoscape-based graphic representation. To demonstrate PLACNET sensitivity and efficacy, the plasmidome of the Escherichia coli lineage ST131 was analyzed. ST131 is a globally spread clonal group of extraintestinal pathogenic E. coli (ExPEC), comprising different sublineages with ability to acquire and spread antibiotic resistance and virulence genes via plasmids. Results show that plasmids flux in the evolution of this lineage, which is wide open for plasmid exchange. MOBF12/IncF plasmids were pervasive, adding just by themselves more than 350 protein families to the ST131 pangenome. Nearly 50% of the most frequent γ-proteobacterial plasmid groups were found to be present in our limited sample of ten analyzed ST131 genomes, which represent the main ST131 sublineages.

  5. Overrepresentation of glutamate signaling in Alzheimer's disease: network-based pathway enrichment using meta-analysis of genome-wide association studies.

    Directory of Open Access Journals (Sweden)

    Eduardo Pérez-Palma

    Full Text Available Genome-wide association studies (GWAS have successfully identified several risk loci for Alzheimer's disease (AD. Nonetheless, these loci do not explain the entire susceptibility of the disease, suggesting that other genetic contributions remain to be identified. Here, we performed a meta-analysis combining data of 4,569 individuals (2,540 cases and 2,029 healthy controls derived from three publicly available GWAS in AD and replicated a broad genomic region (>248,000 bp associated with the disease near the APOE/TOMM40 locus in chromosome 19. To detect minor effect size contributions that could help to explain the remaining genetic risk, we conducted network-based pathway analyses either by extracting gene-wise p-values (GW, defined as the single strongest association signal within a gene, or calculated a more stringent gene-based association p-value using the extended Simes (GATES procedure. Comparison of these strategies revealed that ontological sub-networks (SNs involved in glutamate signaling were significantly overrepresented in AD (p<2.7×10(-11, p<1.9×10(-11; GW and GATES, respectively. Notably, glutamate signaling SNs were also found to be significantly overrepresented (p<5.1×10(-8 in the Alzheimer's disease Neuroimaging Initiative (ADNI study, which was used as a targeted replication sample. Interestingly, components of the glutamate signaling SNs are coordinately expressed in disease-related tissues, which are tightly related to known pathological hallmarks of AD. Our findings suggest that genetic variation within glutamate signaling contributes to the remaining genetic risk of AD and support the notion that functional biological networks should be targeted in future therapies aimed to prevent or treat this devastating neurological disorder.

  6. Systems-level cancer gene identification from protein interaction network topology applied to melanogenesis-related functional genomics data.

    Science.gov (United States)

    Milenkovic, Tijana; Memisevic, Vesna; Ganesan, Anand K; Przulj, Natasa

    2010-03-06

    Many real-world phenomena have been described in terms of large networks. Networks have been invaluable models for the understanding of biological systems. Since proteins carry out most biological processes, we focus on analysing protein-protein interaction (PPI) networks. Proteins interact to perform a function. Thus, PPI networks reflect the interconnected nature of biological processes and analysing their structural properties could provide insights into biological function and disease. We have already demonstrated, by using a sensitive graph theoretic method for comparing topologies of node neighbourhoods called 'graphlet degree signatures', that proteins with similar surroundings in PPI networks tend to perform the same functions. Here, we explore whether the involvement of genes in cancer suggests the similarity of their topological 'signatures' as well. By applying a series of clustering methods to proteins' topological signature similarities, we demonstrate that the obtained clusters are significantly enriched with cancer genes. We apply this methodology to identify novel cancer gene candidates, validating 80 per cent of our predictions in the literature. We also validate predictions biologically by identifying cancer-related negative regulators of melanogenesis identified in our siRNA screen. This is encouraging, since we have done this solely from PPI network topology. We provide clear evidence that PPI network structure around cancer genes is different from the structure around non-cancer genes. Understanding the underlying principles of this phenomenon is an open question, with a potential for increasing our understanding of complex diseases.

  7. KALEIDOSCOPE - THE LOOK OF PHYSICAL EDUCATION TEACHERS OF PORTO ALEGRE’S EDUCATION NETWORK FOR ETHNIC RACIAL ISSUES

    Directory of Open Access Journals (Sweden)

    Gabriela Nobre Bins

    2016-09-01

    Full Text Available This article presents the analysis of the responses of  Porto Alegre’s municipal physical education teachers to a questionnaire about racial ethnic issues. Through quantitative and qualitative analysis it presents a profile of what teachers think about this subject.

  8. A robust network of double-strand break repair pathways governs genome integrity during C. elegans development.

    NARCIS (Netherlands)

    Pontier, D.B.; Tijsterman, M.

    2009-01-01

    To preserve genomic integrity, various mechanisms have evolved to repair DNA double-strand breaks (DSBs). Depending on cell type or cell cycle phase, DSBs can be repaired error-free, by homologous recombination, or with concomitant loss of sequence information, via nonhomologous end-joining (NHEJ) o

  9. A robust network of double-strand break repair pathways governs genome integrity during C. elegans development.

    NARCIS (Netherlands)

    Pontier, D.B.; Tijsterman, M.

    2009-01-01

    To preserve genomic integrity, various mechanisms have evolved to repair DNA double-strand breaks (DSBs). Depending on cell type or cell cycle phase, DSBs can be repaired error-free, by homologous recombination, or with concomitant loss of sequence information, via nonhomologous end-joining (NHEJ)

  10. Genome-wide copy number variation study associates metabotropic glutamate receptor gene networks with attention deficit hyperactivity disorder.

    NARCIS (Netherlands)

    Elia, J.; Glessner, J.T.; Wang, K.; Takahashi, N.; Shtir, C.J.; Hadley, D.; Sleiman, P.M.; Zhang, H.; Kim, C.E.; Robison, R.; Lyon, G.J.; Flory, J.H.; Bradfield, J.P.; Imielinski, M.; Hou, C.; Frackelton, E.C.; Chiavacci, R.M.; Sakurai, T.; Rabin, C.; Middleton, F.A.; Thomas, K.A.; Garris, M.; Mentch, F.; Freitag, C.M.; Steinhausen, H.C.; Todorov, A.A.; Reif, A.; Rothenberger, A.; Franke, B.; Mick, E.O.; Roeyers, H.; Buitelaar, J.K.; Lesch, K.P.; Banaschewski, T.; Ebstein, R.P.; Mulas, F.; Oades, R.D.; Sergeant, J.A.; Sonuga-Barke, E.J.S.; Renner, T.J.; Romanos, M.; Romanos, J.; Warnke, A.; Walitza, S.; Meyer, J.; Palmason, H.; Seitz, C.; Loo, S.K.; Smalley, S.L.; Biederman, J.; Kent, L.; Asherson, P.; Anney, R.J.; Gaynor, J.W.; Shaw, P.; Devoto, M.; White, P.S.; Grant, S.F.; Buxbaum, J.D.; Rapoport, J.L.; Williams, N.M.; Nelson, S.F.; Faraone, S.V.; Hakonarson, H.

    2011-01-01

    Attention deficit hyperactivity disorder (ADHD) is a common, heritable neuropsychiatric disorder of unknown etiology. We performed a whole-genome copy number variation (CNV) study on 1,013 cases with ADHD and 4,105 healthy children of European ancestry using 550,000 SNPs. We evaluated statistically

  11. Clinical, polysomnographic and genome-wide association analyses of narcolepsy with cataplexy: a European Narcolepsy Network study

    National Research Council Canada - National Science Library

    Luca, G. De; Haba-Rubio, J; Dauvilliers, Y; Lammers, G.J; Overeem, S; Donjacour, C.E; Mayer, G; Javidi, S; Iranzo, A; Santamaria, J; Peraita-Aados, R; Hor, H; Kutalik, Z; Plazzi, G; Poli, F; Pizza, F; Arnulf, I; Leceneux, M; Bassetti, C; Mathis, J; Heinzer, R; Jennum, P; Knudsen, S; Geisler, P; Wierzbicka, A; Feketeova, E; Pfister, C; Khatami, R; Baumann, C; Tafti, M

    2013-01-01

    The aim of this study was to describe the clinical and PSG characteristics of narcolepsy with cataplexy and their genetic predisposition by using the retrospective patient database of the European Narcolepsy Network (EU-NN...

  12. GDTN: Genome-Based Delay Tolerant Network Formation in Heterogeneous 5G Using Inter-UA Collaboration

    National Research Council Canada - National Science Library

    You, Ilsun; Sharma, Vishal; Atiquzzaman, Mohammed; Choo, Kim-Kwang Raymond

    2016-01-01

    .... One potential solution is the inter-collaborative deployment of multiple radio devices in a 5G setting designed to meet exacting user demands, and facilitate the high data rate requirements in the underlying networks...

  13. ARACNe-AP: Gene Network Reverse Engineering through Adaptive Partitioning inference of Mutual Information. | Office of Cancer Genomics

    Science.gov (United States)

    The accurate reconstruction of gene regulatory networks from large scale molecular profile datasets represents one of the grand challenges of Systems Biology. The Algorithm for the Reconstruction of Accurate Cellular Networks (ARACNe) represents one of the most effective tools to accomplish this goal. However, the initial Fixed Bandwidth (FB) implementation is both inefficient and unable to deal with sample sets providing largely uneven coverage of the probability density space.

  14. MetaNetVar: Pipeline for applying network analysis tools for genomic variants analysis [version 1; referees: 3 approved

    Directory of Open Access Journals (Sweden)

    Eric Moyer

    2016-04-01

    Full Text Available Network analysis can make variant analysis better. There are existing tools like HotNet2 and dmGWAS that can provide various analytical methods. We developed a prototype of a pipeline called MetaNetVar that allows execution of multiple tools. The code is published at https://github.com/NCBI-Hackathons/Network_SNPs. A working prototype is published as an Amazon Machine Image - ami-4510312f .

  15. Genome-wide profiling of 24 hr diel rhythmicity in the water flea, Daphnia pulex: network analysis reveals rhythmic gene expression and enhances functional gene annotation.

    Science.gov (United States)

    Rund, Samuel S C; Yoo, Boyoung; Alam, Camille; Green, Taryn; Stephens, Melissa T; Zeng, Erliang; George, Gary F; Sheppard, Aaron D; Duffield, Giles E; Milenković, Tijana; Pfrender, Michael E

    2016-08-18

    Marine and freshwater zooplankton exhibit daily rhythmic patterns of behavior and physiology which may be regulated directly by the light:dark (LD) cycle and/or a molecular circadian clock. One of the best-studied zooplankton taxa, the freshwater crustacean Daphnia, has a 24 h diel vertical migration (DVM) behavior whereby the organism travels up and down through the water column daily. DVM plays a critical role in resource tracking and the behavioral avoidance of predators and damaging ultraviolet radiation. However, there is little information at the transcriptional level linking the expression patterns of genes to the rhythmic physiology/behavior of Daphnia. Here we analyzed genome-wide temporal transcriptional patterns from Daphnia pulex collected over a 44 h time period under a 12:12 LD cycle (diel) conditions using a cosine-fitting algorithm. We used a comprehensive network modeling and analysis approach to identify novel co-regulated rhythmic genes that have similar network topological properties and functional annotations as rhythmic genes identified by the cosine-fitting analyses. Furthermore, we used the network approach to predict with high accuracy novel gene-function associations, thus enhancing current functional annotations available for genes in this ecologically relevant model species. Our results reveal that genes in many functional groupings exhibit 24 h rhythms in their expression patterns under diel conditions. We highlight the rhythmic expression of immunity, oxidative detoxification, and sensory process genes. We discuss differences in the chronobiology of D. pulex from other well-characterized terrestrial arthropods. This research adds to a growing body of literature suggesting the genetic mechanisms governing rhythmicity in crustaceans may be divergent from other arthropod lineages including insects. Lastly, these results highlight the power of using a network analysis approach to identify differential gene expression and provide novel

  16. Supporting Teachers in Designing CSCL Activities: A Case Study of Principle-based Pedagogical Patterns in Networked Second Language Classrooms

    National Research Council Canada - National Science Library

    Yun Wen; Chee-Kit Looi; Wenli Chen

    2012-01-01

      This paper proposes the identification and use of principle-based pedagogical patterns to help teachers to translate design principles into actionable teaching activities, and to scaffold student...

  17. Murine hyperglycemic vasculopathy and cardiomyopathy: whole-genome gene expression analysis predicts cellular targets and regulatory networks influenced by mannose binding lectin

    Directory of Open Access Journals (Sweden)

    Chenhui eZou

    2012-02-01

    Full Text Available Hyperglycemia, in the absence of type 1 or 2 diabetes, is an independent risk factor for cardiovascular disease. We have previously demonstrated a central role for mannose binding lectin (MBL-mediated cardiac dysfunction in acute hyperglycemic mice. In this study, we applied whole genome microarray data analysis to investigate MBL’s role in systematic gene expression changes. The data predict possible intracellular events taking place in multiple cellular compartments such as enhanced insulin signaling pathway sensitivity, promoted mitochondrial respiratory function, improved cellular energy expenditure and protein quality control, improved cytoskeleton structure and facilitated intracellular trafficking, all of which may contribute to the organismal health of MBL null mice against acute hyperglycemia. Our data show a tight association between gene expression profile and tissue function which might be a very useful tool in predicting cellular targets and regulatory networks connected with in vivo observations, providing clues for further mechanistic studies.

  18. The Influence of Teacher Collaboration on Perceptions of Normative Culture: A Network Analysis of Site-Managed High Schools

    OpenAIRE

    Waite, Anisah

    2015-01-01

    The decentralization of school governance—often blended with market dynamics—has become a prominent strategy for lifting the performance of urban schools. This approach rests upon several assumptions, primarily that freedom from bureaucratic regulation will strengthen teacher community and result in more effective allocation of instructional resources. But do small autonomous high schools host such favorable social-organizational features? What drives collaborative relationships among teacher...

  19. 教师教育综合训练中心网络信息平台建设探究%Construction of Network Information Platform of Teachers Education Comprehensive Training Center

    Institute of Scientific and Technical Information of China (English)

    欧启忠

    2011-01-01

    广西师范学院教师教育综合训练中心借助先进的信息技术,整合校内的教师教育资源,构建了一个包含“未来教师空间站”、实验教学系统、实验教学、实验室管理系统和创新体系的网络信息平台,有效实现网上辅助教学和网络化、智能化管理,促进师范生和在职教师的教师教育技能培养,推动了民族地区基础教育教师专业化发展.%The teacher education comprehensive training center of Guangxi Teachers University built up a creative network information platform by integrating the campus teacher education resources and advanced information technologies. The platform includes the space for future teacher, the experimental teaching and management systems as well as labs management system which can realize the network-aided teaching and intelligent network-based management. It will promote the education skills of pedagogic students and in-service teachers and to contribute to the development of teachers' specialization of elementary education in minority areas.

  20. Genome and metabolic network of Candidatus Phaeomarinobacter ectocarpi Ec32, a new candidate genus of Alphaproteobacteria frequently associated with brown algae

    Directory of Open Access Journals (Sweden)

    Simon M Dittami

    2014-07-01

    Full Text Available Rhizobiales and related orders of Alphaproteobacteria comprise several genera of nodule-inducing symbiotic bacteria associated with plant roots. Here we describe the genome and the metabolic network of Candidatus Phaeomarinobacter ectocarpi Ec32, a member of a new candidate genus closely related to Rhizobiales and found in association with cultures of the filamentous brown algal model Ectocarpus. The Ca. P. ectocarpi genome encodes numerous metabolic pathways that may be relevant for this bacterium to interact with algae. Notably, it possesses a large set of glycoside hydrolases and transporters, which may serve to process and assimilate algal metabolites. It also harbors several proteins likely to be involved in the synthesis of algal hormones such as auxins and cytokinins, as well as the vitamins pyridoxine, biotin, and thiamine. As of today, Ca. P. ectocarpi has not been successfully cultured, and identical 16S rDNA sequences have been found exclusively associated with Ectocarpus. However, related sequences (≥ 97% identity have also been detected free-living and in a Fucus vesiculosus microbiome barcoding project, indicating that the candidate genus Phaeomarinobacter may comprise several species, which may colonize different niches.

  1. A brassinosteroid transcriptional network revealed by genome-wide identification of BESI target genes in Arabidopsis thaliana.

    Science.gov (United States)

    Yu, Xiaofei; Li, Lei; Zola, Jaroslaw; Aluru, Maneesha; Ye, Huaxun; Foudree, Andrew; Guo, Hongqing; Anderson, Sarah; Aluru, Srinivas; Liu, Peng; Rodermel, Steve; Yin, Yanhai

    2011-02-01

    Brassinosteroids (BRs) are important regulators for plant growth and development. BRs signal to control the activities of the BES1 and BZR1 family transcription factors. The transcriptional network through which BES1 and BZR regulate large number of target genes is mostly unknown. By combining chromatin immunoprecipitation coupled with Arabidopsis tiling arrays (ChIP-chip) and gene expression studies, we have identified 1609 putative BES1 target genes, 404 of which are regulated by BRs and/or in gain-of-function bes1-D mutant. BES1 targets contribute to BR responses and interactions with other hormonal or light signaling pathways. Computational modeling of gene expression data using Algorithm for the Reconstruction of Accurate Cellular Networks (ARACNe) reveals that BES1-targeted transcriptional factors form a gene regulatory network (GRN). Mutants of many genes in the network displayed defects in BR responses. Moreover, we found that BES1 functions to inhibit chloroplast development by repressing the expression of GLK1 and GLK2 transcription factors, confirming a hypothesis generated from the GRN. Our results thus provide a global view of BR regulated gene expression and a GRN that guides future studies in understanding BR-regulated plant growth.

  2. Clinical, polysomnographic and genome-wide association analyses of narcolepsy with cataplexy: a European Narcolepsy Network study

    NARCIS (Netherlands)

    Luca, G. De; Haba-Rubio, J.; Dauvilliers, Y.; Lammers, G.J.; Overeem, S.; Donjacour, C.E.; Mayer, G.; Javidi, S.; Iranzo, A.; Santamaria, J.; Peraita-Adrados, R.; Hor, H.; Kutalik, Z.; Plazzi, G.; Poli, F.; Pizza, F.; Arnulf, I.; Lecendreux, M.; Bassetti, C.; Mathis, J.; Heinzer, R.; Jennum, P.; Knudsen, S.; Geisler, P.; Wierzbicka, A.; Feketeova, E.; Pfister, C.; Khatami, R.; Baumann, C.; Tafti, M.

    2013-01-01

    The aim of this study was to describe the clinical and PSG characteristics of narcolepsy with cataplexy and their genetic predisposition by using the retrospective patient database of the European Narcolepsy Network (EU-NN). We have analysed retrospective data of 1099 patients with narcolepsy diagno

  3. A systems-level approach to parental genomic imprinting: the imprinted gene network includes extracellular matrix genes and regulates cell cycle exit and differentiation.

    Science.gov (United States)

    Al Adhami, Hala; Evano, Brendan; Le Digarcher, Anne; Gueydan, Charlotte; Dubois, Emeric; Parrinello, Hugues; Dantec, Christelle; Bouschet, Tristan; Varrault, Annie; Journot, Laurent

    2015-03-01

    Genomic imprinting is an epigenetic mechanism that restrains the expression of ∼ 100 eutherian genes in a parent-of-origin-specific manner. The reason for this selective targeting of genes with seemingly disparate molecular functions is unclear. In the present work, we show that imprinted genes are coexpressed in a network that is regulated at the transition from proliferation to quiescence and differentiation during fibroblast cell cycle withdrawal, adipogenesis in vitro, and muscle regeneration in vivo. Imprinted gene regulation is not linked to alteration of DNA methylation or to perturbation of monoallelic, parent-of-origin-dependent expression. Overexpression and knockdown of imprinted gene expression alters the sensitivity of preadipocytes to contact inhibition and adipogenic differentiation. In silico and in cellulo experiments showed that the imprinted gene network includes biallelically expressed, nonimprinted genes. These control the extracellular matrix composition, cell adhesion, cell junction, and extracellular matrix-activated and growth factor-activated signaling. These observations show that imprinted genes share a common biological process that may account for their seemingly diverse roles in embryonic development, obesity, diabetes, muscle physiology, and neoplasm.

  4. Unraveling the regulatory network of IncA/C plasmid mobilization: When genomic islands hijack conjugative elements.

    Science.gov (United States)

    Carraro, Nicolas; Matteau, Dominick; Burrus, Vincent; Rodrigue, Sébastien

    2015-01-01

    Conjugative plasmids of the A/C incompatibility group (IncA/C) have become substantial players in the dissemination of multidrug resistance. These large conjugative plasmids are characterized by their broad host-range, extended spectrum of antimicrobials resistance, and prevalence in enteric bacteria recovered from both environmental and clinical settings. Until recently, relatively little was known about the basic biology of IncA/C plasmids, mostly because of the hindrance of multidrug resistance for molecular biology experiments. To circumvent this issue, we previously developed pVCR94ΔX, a convenient prototype that codes for a reduced set of antibiotic resistances. Using pVCR94ΔX, we then characterized the regulatory pathway governing IncA/C plasmid dissemination. We found that the expression of roughly 2 thirds of the genes encoded by this plasmid, including large operons involved in the conjugation process, depends on an FlhCD-like master activator called AcaCD. Beyond the mobility of IncA/C plasmids, AcaCD was also shown to play a key role in the mobilization of different classes of genomic islands (GIs) identified in various pathogenic bacteria. By doing so, IncA/C plasmids can have a considerable impact on bacterial genomes plasticity and evolution.

  5. Genome-wide identification of regulatory elements and reconstruction of gene regulatory networks of the green alga Chlamydomonas reinhardtii under carbon deprivation.

    Directory of Open Access Journals (Sweden)

    Flavia Vischi Winck

    Full Text Available The unicellular green alga Chlamydomonas reinhardtii is a long-established model organism for studies on photosynthesis and carbon metabolism-related physiology. Under conditions of air-level carbon dioxide concentration [CO2], a carbon concentrating mechanism (CCM is induced to facilitate cellular carbon uptake. CCM increases the availability of carbon dioxide at the site of cellular carbon fixation. To improve our understanding of the transcriptional control of the CCM, we employed FAIRE-seq (formaldehyde-assisted Isolation of Regulatory Elements, followed by deep sequencing to determine nucleosome-depleted chromatin regions of algal cells subjected to carbon deprivation. Our FAIRE data recapitulated the positions of known regulatory elements in the promoter of the periplasmic carbonic anhydrase (Cah1 gene, which is upregulated during CCM induction, and revealed new candidate regulatory elements at a genome-wide scale. In addition, time series expression patterns of 130 transcription factor (TF and transcription regulator (TR genes were obtained for cells cultured under photoautotrophic condition and subjected to a shift from high to low [CO2]. Groups of co-expressed genes were identified and a putative directed gene-regulatory network underlying the CCM was reconstructed from the gene expression data using the recently developed IOTA (inner composition alignment method. Among the candidate regulatory genes, two members of the MYB-related TF family, Lcr1 (Low-CO 2 response regulator 1 and Lcr2 (Low-CO2 response regulator 2, may play an important role in down-regulating the expression of a particular set of TF and TR genes in response to low [CO2]. The results obtained provide new insights into the transcriptional control of the CCM and revealed more than 60 new candidate regulatory genes. Deep sequencing of nucleosome-depleted genomic regions indicated the presence of new, previously unknown regulatory elements in the C. reinhardtii genome

  6. Predicting distinct organization of transcription factor binding sites on the promoter regions: a new genome-based approach to expand human embryonic stem cell regulatory network.

    Science.gov (United States)

    Hosseinpour, Batool; Bakhtiarizadeh, Mohammad Reza; Khosravi, Pegah; Ebrahimie, Esmaeil

    2013-12-01

    Self-proliferation and differentiation into distinct cell types have been made stem cell as a promising target for regenerative medicine. Several key genes can regulate self-renewal and pluripotency of embryonic stem cells (hESCs). They work together and build a transcriptional hierarchy. Coexpression and coregulation of genes control by common regulatory elements on the promoter regions. Consequently, distinct organization and combination of transcription factor binding sites (TFBSs modules) on promoter regions, in view of order and distance, lead to a common specific expression pattern within a set of genes. To gain insights into transcriptional regulation of hESCs, we selected promoter regions of eleven common expressed hESC genes including SOX2, LIN28, STAT3, NANOG, LEFTB, TDGF1, POU5F1, FOXD3, TERF1, REX1 and GDF3 to predict activating regulatory modules on promoters and discover key corresponding transcription factors. Then, promoter regions in human genome were explored for modules and 328 genes containing the same modules were detected. Using microarray data, we verified that 102 of 328 genes commonly upregulate in hESCs. Also, using output data of DNA-protein interaction assays, we found that 42 of all predicted genes are targets of SOX2, NANOG and POU5F1. Additionally, a protein interaction network of hESC genes was constructed based on biological processes, and interestingly, 126 downregulated genes along with upregulated ones identified by promoter analysis were predicted in the network. Based on the results, we suggest that the identified genes, coregulating with common hESC genes, represent a novel approach for gene discovery based on whole genome promoter analysis irrespective of gene expression. Altogether, promoter profiling can be used to expand hESC transcriptional regulatory circuitry by analysis of shared functional sequences between genes. This approach provides a clear image on underlying regulatory mechanism of gene expression profile and

  7. Genome-wide mRNA and miRNA expression profiling reveal multiple regulatory networks in colorectal cancer

    DEFF Research Database (Denmark)

    Vishnubalaji, R; Hamam, R; Abdulla, M-H;

    2015-01-01

    upregulated and 1902 downregulated genes in CRC. Pathway analysis revealed significant enrichment in cell cycle, integrated cancer, Wnt (wingless-type MMTV integration site family member), matrix metalloproteinase, and TGF-β pathways in CRC. Pharmacological inhibition of Wnt (using XAV939 or IWP-2) or TGF......-β (using SB-431542) pathways led to dose- and time-dependent inhibition of CRC cell growth. Similarly, our data revealed up- (42) and downregulated (61) microRNAs in the same matched samples. Using target prediction and bioinformatics, ~77% of the upregulated genes were predicted to be targeted by micro...... in cell proliferation, and migration in vitro. Concordantly, small interfering RNA-mediated knockdown of EZH2 led to similar effects on CRC cell growth in vitro. Therefore, our data have revealed several hundred potential miRNA-mRNA regulatory networks in CRC and suggest targeting relevant networks...

  8. Identification of regulatory network topological units coordinating the genome-wide transcriptional response to glucose in Escherichia coli

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    Gosset Guillermo

    2007-06-01

    Full Text Available Abstract Background Glucose is the preferred carbon and energy source for Escherichia coli. A complex regulatory network coordinates gene expression, transport and enzyme activities in response to the presence of this sugar. To determine the extent of the cellular response to glucose, we applied an approach combining global transcriptome and regulatory network analyses. Results Transcriptome data from isogenic wild type and crp- strains grown in Luria-Bertani medium (LB or LB + 4 g/L glucose (LB+G were analyzed to identify differentially transcribed genes. We detected 180 and 200 genes displaying increased and reduced relative transcript levels in the presence of glucose, respectively. The observed expression pattern in LB was consistent with a gluconeogenic metabolic state including active transport and interconversion of small molecules and macromolecules, induction of protease-encoding genes and a partial heat shock response. In LB+G, catabolic repression was detected for transport and metabolic interconversion activities. We also detected an increased capacity for de novo synthesis of nucleotides, amino acids and proteins. Cluster analysis of a subset of genes revealed that CRP mediates catabolite repression for most of the genes displaying reduced transcript levels in LB+G, whereas Fis participates in the upregulation of genes under this condition. An analysis of the regulatory network, in terms of topological functional units, revealed 8 interconnected modules which again exposed the importance of Fis and CRP as directly responsible for the coordinated response of the cell. This effect was also seen with other not extensively connected transcription factors such as FruR and PdhR, which showed a consistent response considering media composition. Conclusion This work allowed the identification of eight interconnected regulatory network modules that includes CRP, Fis and other transcriptional factors that respond directly or indirectly to the

  9. The Roles of Religious Culture and Moral Knowledge Teachers in Organizing Their Students Relationships with Social Networks

    Science.gov (United States)

    Turan, Emine Zehra; Isçitürk, Gökçe Becit

    2017-01-01

    In parallel to the improvements experienced in information and communication systems in recent years, any use of Internet, especially the social networks by children and adolescents has been noticed to be increasing gradually. Use of social networks that starts at early ages has exposed children to some dangers. For that reason, the responsibility…

  10. Predicting Pre-Service Classroom Teachers' Civil Servant Recruitment Examination's Educational Sciences Test Scores Using Artificial Neural Networks

    Science.gov (United States)

    Demir, Metin

    2015-01-01

    This study predicts the number of correct answers given by pre-service classroom teachers in Civil Servant Recruitment Examination's (CSRE) educational sciences test based on their high school grade point averages, university entrance scores, and grades (mid-term and final exams) from their undergraduate educational courses. This study was…

  11. Geographical origin of Plasmodium vivax in the Republic of Korea: haplotype network analysis based on the parasite's mitochondrial genome

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    Iwagami Moritoshi

    2010-06-01

    Full Text Available Abstract Background The Republic of Korea (South Korea is one of the countries where vivax malaria had been successfully eradicated by the late 1970s. However, re-emergence of vivax malaria in South Korea was reported in 1993. Several epidemiological studies and some genetic studies using antigenic molecules of Plasmodium vivax in the country have been reported, but the evolutionary history of P. vivax has not been fully understood. In this study, the origin of the South Korean P. vivax population was estimated by molecular phylogeographic analysis. Methods A haplotype network analysis based on P. vivax mitochondrial (mt DNA sequences was conducted on 11 P. vivax isolates from South Korea and another 282 P. vivax isolates collected worldwide. Results The network analysis of P. vivax mtDNA sequences showed that the coexistence of two different groups (A and B in South Korea. Groups A and B were identical or close to two different populations in southern China. Conclusions Although the direct introduction of the two P. vivax populations in South Korea were thought to have been from North Korea, the results of this analysis suggest the genealogical origin to be the two different populations in southern China.

  12. Genome-wide analysis of primary CD4+ and CD8+ T cell transcriptomes shows evidence for a network of enriched pathways associated with HIV disease

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    Wang Bin

    2011-03-01

    Full Text Available Abstract Background HIV preferentially infects CD4+ T cells, and the functional impairment and numerical decline of CD4+ and CD8+ T cells characterize HIV disease. The numerical decline of CD4+ and CD8+ T cells affects the optimal ratio between the two cell types necessary for immune regulation. Therefore, this work aimed to define the genomic basis of HIV interactions with the cellular transcriptome of both CD4+ and CD8+ T cells. Results Genome-wide transcriptomes of primary CD4+ and CD8+ T cells from HIV+ patients were analyzed at different stages of HIV disease using Illumina microarray. For each cell subset, pairwise comparisons were performed and differentially expressed (DE genes were identified (fold change >2 and B-statistic >0 followed by quantitative PCR validation. Gene ontology (GO analysis of DE genes revealed enriched categories of complement activation, actin filament, proteasome core and proton-transporting ATPase complex. By gene set enrichment analysis (GSEA, a network of enriched pathways functionally connected by mitochondria was identified in both T cell subsets as a transcriptional signature of HIV disease progression. These pathways ranged from metabolism and energy production (TCA cycle and OXPHOS to mitochondria meditated cell apoptosis and cell cycle dysregulation. The most unique and significant feature of our work was that the non-progressing status in HIV+ long-term non-progressors was associated with MAPK, WNT, and AKT pathways contributing to cell survival and anti-viral responses. Conclusions These data offer new comparative insights into HIV disease progression from the aspect of HIV-host interactions at the transcriptomic level, which will facilitate the understanding of the genetic basis of transcriptomic interaction of HIV in vivo and how HIV subverts the human gene machinery at the individual cell type level.

  13. A Network Analysis of the Teachers and Graduate Students’ Research Topics in the Field of Mass Communication

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    Ming-Shu Yuan

    2013-06-01

    Full Text Available The completion of a master’s thesis requires the advisor’s guidance on topic selection, data collection, analysis, interpretation and writing. The advisory committee’s input also contributes to the work. This study conducted content analysis and network analysis on a sample of 547 master’s theses from eight departments of the College of Journalism and Communications of Shih Hsin University to examine the relationships between the advisors and committee members as well as the connections of research topics. The results showed that the topic “lifestyle” have attracted cross-department research interests in the college. The academic network of the college is rather loose, and serving university administration duties may have broadened a faculty member’s centrality in the network. The Department of Communications Management and the Graduate Institute of Communications served as the bridges for the inter-departmental communication in the network. One can understand the interrelations among professors and departments through study on network analysis of thesis as to identify the characteristics of each department, as well as to reveal invisible relations of academic network and scholarly communication. [Article content in Chinese

  14. TRFBA: an algorithm to integrate genome-scale metabolic and transcriptional regulatory networks with incorporation of expression data.

    Science.gov (United States)

    Motamedian, Ehsan; Mohammadi, Maryam; Shojaosadati, Seyed Abbas; Heydari, Mona

    2017-04-01

    Integration of different biological networks and data-types has been a major challenge in systems biology. The present study introduces the transcriptional regulated flux balance analysis (TRFBA) algorithm that integrates transcriptional regulatory and metabolic models using a set of expression data for various perturbations. TRFBA considers the expression levels of genes as a new continuous variable and introduces two new linear constraints. The first constraint limits the rate of reaction(s) supported by a metabolic gene using a constant parameter (C) that converts the expression levels to the upper bounds of the reactions. Considering the concept of constraint-based modeling, the second set of constraints correlates the expression level of each target gene with that of its regulating genes. A set of constraints and binary variables was also added to prevent the second set of constraints from overlapping. TRFBA was implemented on Escherichia coli and Saccharomyces cerevisiae models to estimate growth rates under various environmental and genetic perturbations. The error sensitivity to the algorithm parameter was evaluated to find the best value of C. The results indicate a significant improvement in the quantitative prediction of growth in comparison with previously presented algorithms. The robustness of the algorithm to change in the expression data and the regulatory network was tested to evaluate the effect of noisy and incomplete data. Furthermore, the use of added constraints for perturbations without their gene expression profile demonstrates that these constraints can be applied to improve the growth prediction of FBA. TRFBA is implemented in Matlab software and requires COBRA toolbox. Source code is freely available at http://sbme.modares.ac.ir . : motamedian@modares.ac.ir. Supplementary data are available at Bioinformatics online.

  15. Unraveling Fungal Radiation Resistance Regulatory Networks through the Genome-Wide Transcriptome and Genetic Analyses of Cryptococcus neoformans

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    Kwang-Woo Jung

    2016-11-01

    Full Text Available The basidiomycetous fungus Cryptococcus neoformans has been known to be highly radiation resistant and has been found in fatal radioactive environments such as the damaged nuclear reactor at Chernobyl. To elucidate the mechanisms underlying the radiation resistance phenotype of C. neoformans, we identified genes affected by gamma radiation through genome-wide transcriptome analysis and characterized their functions. We found that genes involved in DNA damage repair systems were upregulated in response to gamma radiation. Particularly, deletion of recombinase RAD51 and two DNA-dependent ATPase genes, RAD54 and RDH54, increased cellular susceptibility to both gamma radiation and DNA-damaging agents. A variety of oxidative stress response genes were also upregulated. Among them, sulfiredoxin contributed to gamma radiation resistance in a peroxiredoxin/thioredoxin-independent manner. Furthermore, we found that genes involved in molecular chaperone expression, ubiquitination systems, and autophagy were induced, whereas genes involved in the biosynthesis of proteins and fatty acids/sterols were downregulated. Most importantly, we discovered a number of novel C. neoformans genes, the expression of which was modulated by gamma radiation exposure, and their deletion rendered cells susceptible to gamma radiation exposure, as well as DNA damage insults. Among these genes, we found that a unique transcription factor containing the basic leucine zipper domain, named Bdr1, served as a regulator of the gamma radiation resistance of C. neoformans by controlling expression of DNA repair genes, and its expression was regulated by the evolutionarily conserved DNA damage response protein kinase Rad53. Taken together, the current transcriptome and functional analyses contribute to the understanding of the unique molecular mechanism of the radiation-resistant fungus C. neoformans.

  16. Using a genome-scale metabolic network model to elucidate the mechanism of chloroquine action in Plasmodium falciparum

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    Shivendra G. Tewari

    2017-08-01

    Full Text Available Chloroquine, long the default first-line treatment against malaria, is now abandoned in large parts of the world because of widespread drug-resistance in Plasmodium falciparum. In spite of its importance as a cost-effective and efficient drug, a coherent understanding of the cellular mechanisms affected by chloroquine and how they influence the fitness and survival of the parasite remains elusive. Here, we used a systems biology approach to integrate genome-scale transcriptomics to map out the effects of chloroquine, identify targeted metabolic pathways, and translate these findings into mechanistic insights. Specifically, we first developed a method that integrates transcriptomic and metabolomic data, which we independently validated against a recently published set of such data for Krebs-cycle mutants of P. falciparum. We then used the method to calculate the effect of chloroquine treatment on the metabolic flux profiles of P. falciparum during the intraerythrocytic developmental cycle. The model predicted dose-dependent inhibition of DNA replication, in agreement with earlier experimental results for both drug-sensitive and drug-resistant P. falciparum strains. Our simulations also corroborated experimental findings that suggest differences in chloroquine sensitivity between ring- and schizont-stage P. falciparum. Our analysis also suggests that metabolic fluxes that govern reduced thioredoxin and phosphoenolpyruvate synthesis are significantly decreased and are pivotal to chloroquine-based inhibition of P. falciparum DNA replication. The consequences of impaired phosphoenolpyruvate synthesis and redox metabolism are reduced carbon fixation and increased oxidative stress, respectively, both of which eventually facilitate killing of the parasite. Our analysis suggests that a combination of chloroquine (or an analogue and another drug, which inhibits carbon fixation and/or increases oxidative stress, should increase the clearance of P

  17. Modeling the Differences in Biochemical Capabilities of Pseudomonas Species by Flux Balance Analysis: How Good Are Genome-Scale Metabolic Networks at Predicting the Differences?

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    Parizad Babaei

    2014-01-01

    Full Text Available To date, several genome-scale metabolic networks have been reconstructed. These models cover a wide range of organisms, from bacteria to human. Such models have provided us with a framework for systematic analysis of metabolism. However, little effort has been put towards comparing biochemical capabilities of closely related species using their metabolic models. The accuracy of a model is highly dependent on the reconstruction process, as some errors may be included in the model during reconstruction. In this study, we investigated the ability of three Pseudomonas metabolic models to predict the biochemical differences, namely, iMO1086, iJP962, and iSB1139, which are related to P. aeruginosa PAO1, P. putida KT2440, and P. fluorescens SBW25, respectively. We did a comprehensive literature search for previous works containing biochemically distinguishable traits over these species. Amongst more than 1700 articles, we chose a subset of them which included experimental results suitable for in silico simulation. By simulating the conditions provided in the actual biological experiment, we performed case-dependent tests to compare the in silico results to the biological ones. We found out that iMO1086 and iJP962 were able to predict the experimental data and were much more accurate than iSB1139.

  18. Large-scale analysis of genome and transcriptome alterations in multiple tumors unveils novel cancer-relevant splicing networks

    Science.gov (United States)

    Sebestyén, Endre; Singh, Babita; Miñana, Belén; Pagès, Amadís; Mateo, Francesca; Pujana, Miguel Angel; Valcárcel, Juan; Eyras, Eduardo

    2016-01-01

    Alternative splicing is regulated by multiple RNA-binding proteins and influences the expression of most eukaryotic genes. However, the role of this process in human disease, and particularly in cancer, is only starting to be unveiled. We systematically analyzed mutation, copy number, and gene expression patterns of 1348 RNA-binding protein (RBP) genes in 11 solid tumor types, together with alternative splicing changes in these tumors and the enrichment of binding motifs in the alternatively spliced sequences. Our comprehensive study reveals widespread alterations in the expression of RBP genes, as well as novel mutations and copy number variations in association with multiple alternative splicing changes in cancer drivers and oncogenic pathways. Remarkably, the altered splicing patterns in several tumor types recapitulate those of undifferentiated cells. These patterns are predicted to be mainly controlled by MBNL1 and involve multiple cancer drivers, including the mitotic gene NUMA1. We show that NUMA1 alternative splicing induces enhanced cell proliferation and centrosome amplification in nontumorigenic mammary epithelial cells. Our study uncovers novel splicing networks that potentially contribute to cancer development and progression. PMID:27197215

  19. Social Media Use and Teacher Ethics

    Science.gov (United States)

    Warnick, Bryan R.; Bitters, Todd A.; Falk, Thomas M.; Kim, Sang Hyun

    2016-01-01

    Teacher use of social networking sites such as Facebook has presented some ethical dilemmas for policy makers. In this article, we argue that schools are justified in taking action against teachers when evidence emerges from social networking sites that teachers are (a) doing something that is illegal, (b) doing something that reflects badly on…

  20. Combined genome-wide expression profiling and targeted RNA interference in primary mouse macrophages reveals perturbation of transcriptional networks associated with interferon signalling

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    Craigon Marie

    2009-08-01

    Full Text Available Abstract Background Interferons (IFNs are potent antiviral cytokines capable of reprogramming the macrophage phenotype through the induction of interferon-stimulated genes (ISGs. Here we have used targeted RNA interference to suppress the expression of a number of key genes associated with IFN signalling in murine macrophages prior to stimulation with interferon-gamma. Genome-wide changes in transcript abundance caused by siRNA activity were measured using exon-level microarrays in the presence or absence of IFNγ. Results Transfection of murine bone-marrow derived macrophages (BMDMs with a non-targeting (control siRNA and 11 sequence-specific siRNAs was performed using a cationic lipid transfection reagent (Lipofectamine2000 prior to stimulation with IFNγ. Total RNA was harvested from cells and gene expression measured on Affymetrix GeneChip Mouse Exon 1.0 ST Arrays. Network-based analysis of these data revealed six siRNAs to cause a marked shift in the macrophage transcriptome in the presence or absence IFNγ. These six siRNAs targeted the Ifnb1, Irf3, Irf5, Stat1, Stat2 and Nfkb2 transcripts. The perturbation of the transcriptome by the six siRNAs was highly similar in each case and affected the expression of over 600 downstream transcripts. Regulated transcripts were clustered based on co-expression into five major groups corresponding to transcriptional networks associated with the type I and II IFN response, cell cycle regulation, and NF-KB signalling. In addition we have observed a significant non-specific immune stimulation of cells transfected with siRNA using Lipofectamine2000, suggesting use of this reagent in BMDMs, even at low concentrations, is enough to induce a type I IFN response. Conclusion Our results provide evidence that the type I IFN response in murine BMDMs is dependent on Ifnb1, Irf3, Irf5, Stat1, Stat2 and Nfkb2, and that siRNAs targeted to these genes results in perturbation of key transcriptional networks associated

  1. Phenome-wide association study (PheWAS for detection of pleiotropy within the Population Architecture using Genomics and Epidemiology (PAGE Network.

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    Sarah A Pendergrass

    Full Text Available Using a phenome-wide association study (PheWAS approach, we comprehensively tested genetic variants for association with phenotypes available for 70,061 study participants in the Population Architecture using Genomics and Epidemiology (PAGE network. Our aim was to better characterize the genetic architecture of complex traits and identify novel pleiotropic relationships. This PheWAS drew on five population-based studies representing four major racial/ethnic groups (European Americans (EA, African Americans (AA, Hispanics/Mexican-Americans, and Asian/Pacific Islanders in PAGE, each site with measurements for multiple traits, associated laboratory measures, and intermediate biomarkers. A total of 83 single nucleotide polymorphisms (SNPs identified by genome-wide association studies (GWAS were genotyped across two or more PAGE study sites. Comprehensive tests of association, stratified by race/ethnicity, were performed, encompassing 4,706 phenotypes mapped to 105 phenotype-classes, and association results were compared across study sites. A total of 111 PheWAS results had significant associations for two or more PAGE study sites with consistent direction of effect with a significance threshold of p<0.01 for the same racial/ethnic group, SNP, and phenotype-class. Among results identified for SNPs previously associated with phenotypes such as lipid traits, type 2 diabetes, and body mass index, 52 replicated previously published genotype-phenotype associations, 26 represented phenotypes closely related to previously known genotype-phenotype associations, and 33 represented potentially novel genotype-phenotype associations with pleiotropic effects. The majority of the potentially novel results were for single PheWAS phenotype-classes, for example, for CDKN2A/B rs1333049 (previously associated with type 2 diabetes in EA a PheWAS association was identified for hemoglobin levels in AA. Of note, however, GALNT2 rs2144300 (previously associated with high

  2. On genomics, kin, and privacy.

    Science.gov (United States)

    Telenti, Amalio; Ayday, Erman; Hubaux, Jean Pierre

    2014-01-01

    The storage of greater numbers of exomes or genomes raises the question of loss of privacy for the individual and for families if genomic data are not properly protected. Access to genome data may result from a personal decision to disclose, or from gaps in protection. In either case, revealing genome data has consequences beyond the individual, as it compromises the privacy of family members. Increasing availability of genome data linked or linkable to metadata through online social networks and services adds one additional layer of complexity to the protection of genome privacy.  The field of computer science and information technology offers solutions to secure genomic data so that individuals, medical personnel or researchers can access only the subset of genomic information required for healthcare or dedicated studies.

  3. Nebraska Earth Science Education Network: Enhancing the NASA, University, and Pre-College Science Teacher Connection with Electronic Communication

    Science.gov (United States)

    Gosselin, David C.

    1997-01-01

    The primary goals of this project were to: 1. Promote and enhance K-12 earth science education; and enhance the access to and exchange of information through the use of digital networks in K-12 institutions. We have achieved these two goals. Through the efforts of many individuals at the University of Nebraska-Lincoln (UNL), Nebraska Earth Science Education Network (NESEN) has become a viable and beneficial interdisciplinary outreach program for K-12 educators in Nebraska. Over the last three years, the NASA grant has provided personnel and equipment to maintain, expand and develop NESEN into a program that is recognized by its membership as a valuable source of information and expertise in earth systems science. Because NASA funding provided a framework upon which to build, other external sources of funding have become available to support NESEN programs.

  4. Cancer genomics identifies regulatory gene networks associated with the transition from dysplasia to advanced lung adenocarcinomas induced by c-Raf-1.

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    Astrid Rohrbeck

    Full Text Available BACKGROUND: Lung cancer is a leading cause of cancer morbidity. To improve an understanding of molecular causes of disease a transgenic mouse model was investigated where targeted expression of the serine threonine kinase c-Raf to respiratory epithelium induced initially dysplasia and subsequently adenocarcinomas. This enables dissection of genetic events associated with precancerous and cancerous lesions. METHODOLOGY/PRINCIPAL FINDINGS: By laser microdissection cancer cell populations were harvested and subjected to whole genome expression analyses. Overall 473 and 541 genes were significantly regulated, when cancer versus transgenic and non-transgenic cells were compared, giving rise to three distinct and one common regulatory gene network. At advanced stages of tumor growth predominately repression of gene expression was observed, but genes previously shown to be up-regulated in dysplasia were also up-regulated in solid tumors. Regulation of developmental programs as well as epithelial mesenchymal and mesenchymal endothelial transition was a hall mark of adenocarcinomas. Additionally, genes coding for cell adhesion, i.e. the integrins and the tight and gap junction proteins were repressed, whereas ligands for receptor tyrosine kinase such as epi- and amphiregulin were up-regulated. Notably, Vegfr- 2 and its ligand Vegfd, as well as Notch and Wnt signalling cascades were regulated as were glycosylases that influence cellular recognition. Other regulated signalling molecules included guanine exchange factors that play a role in an activation of the MAP kinases while several tumor suppressors i.e. Mcc, Hey1, Fat3, Armcx1 and Reck were significantly repressed. Finally, probable molecular switches forcing dysplastic cells into malignantly transformed cells could be identified. CONCLUSIONS/SIGNIFICANCE: This study provides insight into molecular pertubations allowing dysplasia to progress further to adenocarcinoma induced by exaggerted c-Raf kinase

  5. Red de comunidades de aprendizaje, un espacio para la formación de formadores/ Learning network community, a space for the formation of teachers

    Directory of Open Access Journals (Sweden)

    Jorge Iván Ríos Rivera

    2007-01-01

    Full Text Available Cuando se habla de ambientes de aprendizaje se acude a un concepto muy necesitado para el desarrollo de la educación de hoy. Este, no se ha abordado, de manera detenida y profunda cuando se incorpora en los discursos de las TIC. Por ello se presenta en una de las materializaciones más promisorias del momento, llamada las comunidades de aprendizaje, además, pueden ser pensadas como espacios de formación de formadores dónde se propician muchas de las transformaciones requeridas en los docentes para la educación del nuevo mileno. El texto parte de la idea de formar a un maestro para contrarrestar el impacto de la escuela paralela a través de la creación de un “ecosistema comunicativo”, se relaciona la noción de ambiente de aprendizaje, en cada uno de sus componentes, Ambiente y aprendizaje, con el concepto de Redes de aprendizaje y comunidades de aprendizaje, para finalmente, ilustrar el modelo de red de comunidades de aprendizaje vivido desde la experiencia del proyecto REDES (MEN-UPB. When it is talked about learning environments, it is referred a much needed concept to the development of the nowadays education. This concept has not been treated in a deep and consciously way, when it has been incorporated to the speeches about the Information and communication technology (ICT. That is why is presented in one of the most hopefully materialization: the learning community, this could be also thought as a formation space for educators, a space where are favored many of the required transformation of the new millennium teachers. This article begins with the idea of educate a teacher, to counter the parallel school impact through the creation of a “communicative ecosystem”, then it is related the notion of learning environment, in each one of its components: environment and learning, with the concept of learning network and learning community. This article finishes with the illustration of the learning community network model

  6. Genome-wide association study of white blood cell count in 16,388 African Americans: the continental origins and genetic epidemiology network (COGENT.

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    Alexander P Reiner

    2011-06-01

    Full Text Available Total white blood cell (WBC and neutrophil counts are lower among individuals of African descent due to the common African-derived "null" variant of the Duffy Antigen Receptor for Chemokines (DARC gene. Additional common genetic polymorphisms were recently associated with total WBC and WBC sub-type levels in European and Japanese populations. No additional loci that account for WBC variability have been identified in African Americans. In order to address this, we performed a large genome-wide association study (GWAS of total WBC and cell subtype counts in 16,388 African-American participants from 7 population-based cohorts available in the Continental Origins and Genetic Epidemiology Network. In addition to the DARC locus on chromosome 1q23, we identified two other regions (chromosomes 4q13 and 16q22 associated with WBC in African Americans (P<2.5×10(-8. The lead SNP (rs9131 on chromosome 4q13 is located in the CXCL2 gene, which encodes a chemotactic cytokine for polymorphonuclear leukocytes. Independent evidence of the novel CXCL2 association with WBC was present in 3,551 Hispanic Americans, 14,767 Japanese, and 19,509 European Americans. The index SNP (rs12149261 on chromosome 16q22 associated with WBC count is located in a large inter-chromosomal segmental duplication encompassing part of the hydrocephalus inducing homolog (HYDIN gene. We demonstrate that the chromosome 16q22 association finding is most likely due to a genotyping artifact as a consequence of sequence similarity between duplicated regions on chromosomes 16q22 and 1q21. Among the WBC loci recently identified in European or Japanese populations, replication was observed in our African-American meta-analysis for rs445 of CDK6 on chromosome 7q21 and rs4065321 of PSMD3-CSF3 region on chromosome 17q21. In summary, the CXCL2, CDK6, and PSMD3-CSF3 regions are associated with WBC count in African American and other populations. We also demonstrate that large inter

  7. Genetic and Proteomic Interrogation of Lower Confidence Candidate Genes Reveals Signaling Networks in beta-Catenin-Active Cancers | Office of Cancer Genomics

    Science.gov (United States)

    Genome-scale expression studies and comprehensive loss-of-function genetic screens have focused almost exclusively on the highest confidence candidate genes. Here, we describe a strategy for characterizing the lower confidence candidates identified by such approaches.

  8. Les réseaux d'enseignants – Quels sont les comportements rédactionnels des locuteurs ? What are editorial behaviors on French teachers networks?

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    Isabelle Quentin

    2012-10-01

    Full Text Available Depuis une dizaine d'années, des enseignants créent et animent, en dehors des stricts circuits institutionnels, des réseaux d'échanges professionnels en s'appuyant sur les technologies du web participatif. Encore peu étudiés, plusieurs de ces réseaux en ligne connaissent aujourd'hui une forte audience. Cet article a plus spécifiquement pour objet de proposer et de tester une méthode nous permettant de rendre compte des comportements rédactionnels des enseignants qui s'expriment sur les forums hébergés par ces réseaux professionnels. Notre corpus est composé de 91 fils de discussion publiés sur le forum du réseau Pédago2.0. Ce réseau professionnel rassemble près de 500 professeurs en histoire et géographie. La plupart d'entre eux sont fortement investis dans l'association Les Clionautes et peuvent être qualifiés d'enseignants innovants. L'analyse de données quantitatives ainsi que des messages publiés sur le forum Pédago2.0, nous ont permis de mettre en lumière différents modes implicites de fonctionnement que nous présentons dans cet article.Over the past decade, teachers have created and animated corporate networks based on technologies of the Web 2.0 outside the strict institutional hierarchy. Yet little studied, many of these online networks are now welcomed with great success. The aim of this article is to provide a framework enabling us to identify significant aspects of teachers' behavior when they talk on newsgroups hosted through these networks. We tested our framework on a corpus of 91 threads of discussion published on the Pédago2.0 newsgroup. This professional network gathers nearly 500 French history and geography teachers. Most of these teachers are deeply implicated in an association, Les Clionautes, and can be described as innovating teachers. Quantitative data and posted messages analysis allowed us to highlight some implicit functioning rules, which we are presenting in this article.

  9. Programmatic Issues in Teacher Education: The Texas Teacher Corps Experience.

    Science.gov (United States)

    Olivarez, Ruben Dario, Ed.

    Various aspects of program planning and implementation in the Texas Teacher Corps Network are explored. The following topics are covered: 1) program conceptualization and design; 2) intern and team leader recruitment; 3) Teacher Corps experiences dealing with graduate admission processes and their implications for change; 4) management of Teacher…

  10. Cancer genomics

    DEFF Research Database (Denmark)

    Norrild, Bodil; Guldberg, Per; Ralfkiær, Elisabeth Methner

    2007-01-01

    Almost all cells in the human body contain a complete copy of the genome with an estimated number of 25,000 genes. The sequences of these genes make up about three percent of the genome and comprise the inherited set of genetic information. The genome also contains information that determines whe...

  11. Human social genomics.

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    Steven W Cole

    2014-08-01

    Full Text Available A growing literature in human social genomics has begun to analyze how everyday life circumstances influence human gene expression. Social-environmental conditions such as urbanity, low socioeconomic status, social isolation, social threat, and low or unstable social status have been found to associate with differential expression of hundreds of gene transcripts in leukocytes and diseased tissues such as metastatic cancers. In leukocytes, diverse types of social adversity evoke a common conserved transcriptional response to adversity (CTRA characterized by increased expression of proinflammatory genes and decreased expression of genes involved in innate antiviral responses and antibody synthesis. Mechanistic analyses have mapped the neural "social signal transduction" pathways that stimulate CTRA gene expression in response to social threat and may contribute to social gradients in health. Research has also begun to analyze the functional genomics of optimal health and thriving. Two emerging opportunities now stand to revolutionize our understanding of the everyday life of the human genome: network genomics analyses examining how systems-level capabilities emerge from groups of individual socially sensitive genomes and near-real-time transcriptional biofeedback to empirically optimize individual well-being in the context of the unique genetic, geographic, historical, developmental, and social contexts that jointly shape the transcriptional realization of our innate human genomic potential for thriving.

  12. Red de docentes de inglés: ¿una posibilidad para la continuidad de grupos de estudio? An English teachers' network: is it a possibility for continuing study groups?

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    G. Nathaly Aldana Prieto

    2011-12-01

    Full Text Available Resumen En la actualidad se promueve la formación de redes de docentes para trabajar en agendas construidas de manera colaborativa, continua, flexible, y conforme a sus necesidades. Reportamos una investigación cualitativa con cinco profesoras de inglés de colegios públicos de Bogotá participantes en un programa de formación permanente. Los profesores conformaron grupos de estudio para realizar un proyecto de investigación-acción. Al concluir dicho programa, las docentes iniciaron un trabajo en red, tendiente a continuar su desarrollo profesional. La información recolectada a través de diarios, cuestionarios y entrevistas, permitió determinar los factores que se asocian a la continuidad de los grupos de estudio que surgieron en el programa de formación permanente, así como algunas implicaciones para el trabajo en red.Abstract Nowadays the development of networking on the part of teachers is promoted in order to work with agendas built in a collaborative, continuous, and flexible way, as well as in accordance with teachers' needs. We report on qualitative research of five English teachers in public schools in Bogotá. They took part in a professional development programme and met in study groups in order to conduct an action research project. At the end of the programme the teachers started working as a net with the intent to continue their professional development. Information gathered through journals, surveys, and interviews allowed us to identify factors associated with the continuity of the study groups which emerged in the professional development programme as well as some implications for networking.

  13. Complex networks theory for analyzing metabolic networks

    Institute of Scientific and Technical Information of China (English)

    ZHAO Jing; YU Hong; LUO Jianhua; CAO Z.W.; LI Yixue

    2006-01-01

    One of the main tasks of post-genomic informatics is to systematically investigate all molecules and their interactions within a living cell so as to understand how these molecules and the interactions between them relate to the function of the organism,while networks are appropriate abstract description of all kinds of interactions. In the past few years, great achievement has been made in developing theory of complex networks for revealing the organizing principles that govern the formation and evolution of various complex biological, technological and social networks. This paper reviews the accomplishments in constructing genome-based metabolic networks and describes how the theory of complex networks is applied to analyze metabolic networks.

  14. Teacher Perceptions of Teacher Bullying

    Science.gov (United States)

    Zerillo, Christine; Osterman, Karen F

    2011-01-01

    This mixed-methods study examined elementary teachers' perceptions of teacher-student bullying. Grounded in previous research on peer bullying, the study posed several questions: to what extent did teachers perceive bullying of students by other teachers as a serious matter requiring intervention? Did they perceive teacher bullying as more serious…

  15. Teacher educators modelling their teachers?

    NARCIS (Netherlands)

    Timmerman, Greetje

    2009-01-01

    The teacher educator is always also a teacher, and as a role model may have an important impact on student teachers' views on teaching. However, what is the impact of these teacher educator's own role models on their teaching views and practices? Do teacher educators simply imitate the positive role

  16. Teacher educators modelling their teachers?

    NARCIS (Netherlands)

    Timmerman, Greetje

    2009-01-01

    The teacher educator is always also a teacher, and as a role model may have an important impact on student teachers' views on teaching. However, what is the impact of these teacher educator's own role models on their teaching views and practices? Do teacher educators simply imitate the positive role

  17. Gene network analyses of first service conception in Brangus heifers: Use of genome and trait associations, hypothalamic-transcriptome information, and transcription factors

    Science.gov (United States)

    Measures of heifer fertility are economically relevant traits for beef production systems and knowledge of candidate genes could be incorporated into future genomic selection strategies. Ten traits related to growth and fertility were measured in 890 Brangus heifers (3/8 Brahman × 5/8 Angus, from 6...

  18. A genome-wide search for linkage to asthma phenotypes in the genetics of asthma international network families : evidence for a major susceptibility locus on chromosome 2p

    NARCIS (Netherlands)

    Pillai, SG; Chiano, MN; White, NJ; Speer, M; Barnes, KC; Carlsen, K; Gerritsen, Jorrit; Helms, P; Lenney, W; Silverman, M; Sly, P; Sundy, J; Tsanakas, J; von Berg, A; Whyte, M; Varsani, S; Skelding, P; Hauser, M; Vance, J; Pericak-Vance, M; Burns, DK; Middleton, LT; Brewster, [No Value; Anderson, WH; Riley, JH

    2006-01-01

    Asthma is a complex disease and the intricate interplay between genetic and environmental factors underlies the overall phenotype of the disease. Families with at least two siblings with asthma were collected from Europe, Australia and the US. A genome scan using a set of 364 families with a panel o

  19. Decoding genome-wide GadEWX-transcriptional regulatory networks reveals multifaceted cellular responses to acid stress in Escherichia coli

    DEFF Research Database (Denmark)

    Seo, Sang Woo; Kim, Donghyuk; O'Brien, Edward J.;

    2015-01-01

    The regulators GadE, GadW and GadX (which we refer to as GadEWX) play a critical role in the transcriptional regulation of the glutamate-dependent acid resistance (GDAR) system in Escherichia coli K-12 MG1655. However, the genome-wide regulatory role of GadEWX is still unknown. Here we comprehens...

  20. Combating Teacher Burnout

    Science.gov (United States)

    Williams, Cheryl Scott

    2012-01-01

    Generation Y teachers--those under 30 years of age--have higher expectations for technology than their colleagues from earlier generations--for good reason. Improved instructional and networking technology is one important aspect of a modern high-performing workplace. This generational difference is important, since a majority of seasoned…

  1. Meta-Analysis of Genome-Wide Association Studies and Network Analysis-Based Integration with Gene Expression Data Identify New Suggestive Loci and Unravel a Wnt-Centric Network Associated with Dupuytren’s Disease

    Science.gov (United States)

    Becker, Kerstin; Siegert, Sabine; Toliat, Mohammad Reza; Du, Juanjiangmeng; Casper, Ramona; Dolmans, Guido H.; Werker, Paul M.; Tinschert, Sigrid; Franke, Andre; Gieger, Christian; Strauch, Konstantin; Nothnagel, Michael; Nürnberg, Peter; Hennies, Hans Christian

    2016-01-01

    Dupuytren´s disease, a fibromatosis of the connective tissue in the palm, is a common complex disease with a strong genetic component. Up to date nine genetic loci have been found to be associated with the disease. Six of these loci contain genes that code for Wnt signalling proteins. In spite of this striking first insight into the genetic factors in Dupuytren´s disease, much of the inherited risk in Dupuytren´s disease still needs to be discovered. The already identified loci jointly explain ~1% of the heritability in this disease. To further elucidate the genetic basis of Dupuytren´s disease, we performed a genome-wide meta-analysis combining three genome-wide association study (GWAS) data sets, comprising 1,580 cases and 4,480 controls. We corroborated all nine previously identified loci, six of these with genome-wide significance (p-value Dupuytren´s disease. PMID:27467239

  2. The Cancer Target Discovery and Development Network Dashboard Allows Users to Search for Interesting Data and Results | Office of Cancer Genomics

    Science.gov (United States)

    The CTD2 Dashboard hosts analyzed data and other evidence generated by the CTD2 Network. It is a web interface for the research community to browse and search CTD2 Network data related to genes, proteins, and compounds from individual CTD2 Centers, or explore observations across multiple Centers.

  3. GLAMM: Genome-Linked Application for Metabolic Maps

    Energy Technology Data Exchange (ETDEWEB)

    Bates, John; Chivian, Dylan; Arkin, Adam

    2011-05-29

    The Genome-Linked Application for Metabolic Maps (GLAMM) is a unified web interface for visualizing metabolic networks, reconstructing metabolic networks from annotated genome data, visualizing experimental data in the context of metabolic networks, and investigating the construction of novel, transgenic pathways. This simple, user-friendly interface is tightly integrated with the comparative genomics tools of MicrobesOnline. GLAMM is available for free to the scientific community at glamm.lbl.gov.

  4. GLAMM: Genome-Linked Application for Metabolic Maps

    Energy Technology Data Exchange (ETDEWEB)

    Bates, John; Chivian, Dylan; Arkin, Adam

    2011-05-29

    The Genome-Linked Application for Metabolic Maps (GLAMM) is a unified web interface for visualizing metabolic networks, reconstructing metabolic networks from annotated genome data, visualizing experimental data in the context of metabolic networks, and investigating the construction of novel, transgenic pathways. This simple, user-friendly interface is tightly integrated with the comparative genomics tools of MicrobesOnline. GLAMM is available for free to the scientific community at glamm.lbl.gov.

  5. “It’s just really not me”: How pre-service English teachers from a traditional teacher education program experience student-teaching in charter-school networks

    Directory of Open Access Journals (Sweden)

    April S. Salerno

    2016-12-01

    Full Text Available Though teacher educators nationwide are considering ways to provide urban placements for pre-service teachers (PSTs, little research has examined how PSTs experience placements in schools operated by charter management organizations (CMOs. This study considers CMOs—which often hold particular instructional and classroom management philosophies—as a specific type of school-based learning environment. We draw from a Discourse analytic theoretical framework using qualitative methodology to study how three English education focal PSTs experience disconnections between student-teaching placements at CMO schools and their teacher education program. Findings suggest three ways teacher educators can support PSTs in navigating school-based learning. PSTs in this study experienced contexts and philosophies that varied greatly between their schools and teacher education program. Implications include: (1 PSTs must feel that others in their schools value their learning; (2 PSTs in cohorts must feel they belong to learning communities; and (3 PSTs need support in confronting paradoxes they face between theory and practice.

  6. Poster: the macaque genome.

    Science.gov (United States)

    2007-04-13

    The rhesus macaque (Macaca mulatta) facilitates an extraordinary range of biomedical and basic research, and the publication of the genome only makes it a more powerful model for studies of human disease; moreover, the macaque's position relative to humans and chimpanzees affords the opportunity to learn about the processes that have shaped the last 25 million years of primate evolution. To allow users to explore these themes of the macaque genome, Science has created a special interactive version of the poster published in the print edition of the 13 April 2007 issue. The interactive version includes additional text and exploration, as well as embedded video featuring seven scientists discussing the importance of the macaque and its genome sequence in studies of biomedicine and evolution. We have also created an accompanying teaching resource, including a lesson plan aimed at teachers of advanced high school life science students, for exploring what a comparison of the macaque and human genomes can tell us about human biology and evolution. These items are free to all site visitors.

  7. Exploration of the construction of productive practice teachers' team in network technology specialty%网络技术专业生产性实训教师队伍建设探索

    Institute of Scientific and Technical Information of China (English)

    陈春燕

    2015-01-01

    职业教育的宗旨是学生能力的培养,学生能力的形成依赖于老师有针对性的训练,因此要办好职业教育,建设一支高素质的实训教学团队是前提。以网络技术专业生产性实训教师队伍建设为例,讨论了切实可能的生产性实训教学教师队伍建设的途径和方法。%Occupation education purpose is to cultivate the students' ability, the formation of the students' ability is dependent on the teachers targeted training. therefore, to run the occupation education, to build a high-quality teaching team is the premise. This paper, taking the construction of network technology professional productive practice teachers' team as an example, the feasible ways and methods of construction of teachers' team is discussed.

  8. Impact of Campus Network Culture on the Construction of Teachers' Ethics and the Countermeasures%校园网络文化对师德师风建设的影响及对策

    Institute of Scientific and Technical Information of China (English)

    邹嵩晖

    2014-01-01

    网络是一柄双刃剑。作为影响广泛的第四媒体,互联网正以惊人的速度影响着人类和社会发展进程,毫无疑问,网络文化已成为影响高校教师价值导向、思想品德、行为模式、道德观念的重要力量。在网络文化的冲击和挑战下,加强与改进高校师德师风建设已成为当前的新课题。%The Internet is a double-edged sword. As the fourth medium with an extensive influence, the Internet has been influ-encing the process of human and society with an amazing speed. Undoubtedly, the network culture has become a major force in-fluencing college teachers' value orientation, ethics, behavior patterns and moral concepts. Under the impact and challenge of the network culture, to strengthen and improve the construction of college teachers' ethics has become a new topic currently.

  9. Genome-wide Reconstruction of OxyR and SoxRS Transcriptional Regulatory Networks under Oxidative Stress in Escherichia coli K-12 MG1655

    Directory of Open Access Journals (Sweden)

    Sang Woo Seo

    2015-08-01

    Full Text Available Three transcription factors (TFs, OxyR, SoxR, and SoxS, play a critical role in transcriptional regulation of the defense system for oxidative stress in bacteria. However, their full genome-wide regulatory potential is unknown. Here, we perform a genome-scale reconstruction of the OxyR, SoxR, and SoxS regulons in Escherichia coli K-12 MG1655. Integrative data analysis reveals that a total of 68 genes in 51 transcription units (TUs belong to these regulons. Among them, 48 genes showed more than 2-fold changes in expression level under single-TF-knockout conditions. This reconstruction expands the genome-wide roles of these factors to include direct activation of genes related to amino acid biosynthesis (methionine and aromatic amino acids, cell wall synthesis (lipid A biosynthesis and peptidoglycan growth, and divalent metal ion transport (Mn2+, Zn2+, and Mg2+. Investigating the co-regulation of these genes with other stress-response TFs reveals that they are independently regulated by stress-specific TFs.

  10. My teacher

    Institute of Scientific and Technical Information of China (English)

    严嘉爱

    2007-01-01

    @@ My name is Yanjiaai. I am 14 years old. I study in YuYing School. My Chinese teacher and English teacher is Miss Du, she is tall and thin, and she is very strict. My math teacher is Miss Zhang, she is short and strong, she is very strick too. But they are very nice, I love my teachers!

  11. iRegNet3D: three-dimensional integrated regulatory network for the genomic analysis of coding and non-coding disease mutations.

    Science.gov (United States)

    Liang, Siqi; Tippens, Nathaniel D; Zhou, Yaoda; Mort, Matthew; Stenson, Peter D; Cooper, David N; Yu, Haiyuan

    2017-01-18

    The mechanistic details of most disease-causing mutations remain poorly explored within the context of regulatory networks. We present a high-resolution three-dimensional integrated regulatory network (iRegNet3D) in the form of a web tool, where we resolve the interfaces of all known transcription factor (TF)-TF, TF-DNA and chromatin-chromatin interactions for the analysis of both coding and non-coding disease-associated mutations to obtain mechanistic insights into their functional impact. Using iRegNet3D, we find that disease-associated mutations may perturb the regulatory network through diverse mechanisms including chromatin looping. iRegNet3D promises to be an indispensable tool in large-scale sequencing and disease association studies.

  12. ePhenotyping for Abdominal Aortic Aneurysm in the Electronic Medical Records and Genomics (eMERGE) Network: Algorithm Development and Konstanz Information Miner Workflow

    Science.gov (United States)

    Borthwick, Kenneth M; Smelser, Diane T; Bock, Jonathan A; Elmore, James R; Ryer, Evan J; Ye, Zi; Pacheco, Jennifer A.; Carrell, David S.; Michalkiewicz, Michael; Thompson, William K; Pathak, Jyotishman; Bielinski, Suzette J; Denny, Joshua C; Linneman, James G; Peissig, Peggy L; Kho, Abel N; Gottesman, Omri; Parmar, Harpreet; Kullo, Iftikhar J; McCarty, Catherine A; Böttinger, Erwin P; Larson, Eric B; Jarvik, Gail P; Harley, John B; Bajwa, Tanvir; Franklin, David P; Carey, David J; Kuivaniemi, Helena; Tromp, Gerard

    2015-01-01

    Background and objective We designed an algorithm to identify abdominal aortic aneurysm cases and controls from electronic health records to be shared and executed within the “electronic Medical Records and Genomics” (eMERGE) Network. Materials and methods Structured Query Language, was used to script the algorithm utilizing “Current Procedural Terminology” and “International Classification of Diseases” codes, with demographic and encounter data to classify individuals as case, control, or excluded. The algorithm was validated using blinded manual chart review at three eMERGE Network sites and one non-eMERGE Network site. Validation comprised evaluation of an equal number of predicted cases and controls selected at random from the algorithm predictions. After validation at the three eMERGE Network sites, the remaining eMERGE Network sites performed verification only. Finally, the algorithm was implemented as a workflow in the Konstanz Information Miner, which represented the logic graphically while retaining intermediate data for inspection at each node. The algorithm was configured to be independent of specific access to data and was exportable (without data) to other sites. Results The algorithm demonstrated positive predictive values (PPV) of 92.8% (CI: 86.8-96.7) and 100% (CI: 97.0-100) for cases and controls, respectively. It performed well also outside the eMERGE Network. Implementation of the transportable executable algorithm as a Konstanz Information Miner workflow required much less effort than implementation from pseudo code, and ensured that the logic was as intended. Discussion and conclusion This ePhenotyping algorithm identifies abdominal aortic aneurysm cases and controls from the electronic health record with high case and control PPV necessary for research purposes, can be disseminated easily, and applied to high-throughput genetic and other studies. PMID:27054044

  13. Genome-Wide Investigation Using sRNA-Seq, Degradome-Seq and Transcriptome-Seq Reveals Regulatory Networks of microRNAs and Their Target Genes in Soybean during Soybean mosaic virus Infection.

    Directory of Open Access Journals (Sweden)

    Hui Chen

    Full Text Available MicroRNAs (miRNAs play key roles in a variety of cellular processes through regulation of their target gene expression. Accumulated experimental evidence has demonstrated that infections by viruses are associated with the altered expression profile of miRNAs and their mRNA targets in the host. However, the regulatory network of miRNA-mRNA interactions during viral infection remains largely unknown. In this study, we performed small RNA (sRNA-seq, degradome-seq and as well as a genome-wide transcriptome analysis to profile the global gene and miRNA expression in soybean following infections by three different Soybean mosaic virus (SMV isolates, L (G2 strain, LRB (G2 strain and G7 (G7 strain. sRNA-seq analyses revealed a total of 253 soybean miRNAs with a two-fold or greater change in abundance compared with the mock-inoculated control. 125 transcripts were identified as the potential cleavage targets of 105 miRNAs and validated by degradome-seq analyses. Genome-wide transcriptome analysis showed that total 2679 genes are differentially expressed in response to SMV infection including 71 genes predicted as involved in defense response. Finally, complex miRNA-mRNA regulatory networks were derived using the RNAseq, small RNAseq and degradome data. This work represents a comprehensive, global approach to examining virus-host interactions. Genes responsive to SMV infection are identified as are their potential miRNA regulators. Additionally, regulatory changes of the miRNAs themselves are described and the regulatory relationships were supported with degradome data. Taken together these data provide new insights into molecular SMV-soybean interactions and offer candidate miRNAs and their targets for further elucidation of the SMV infection process.

  14. NEWEST teachers

    Science.gov (United States)

    1996-01-01

    NEWEST, or NASA Educational Workshops for Elementary School Teachers, is a two-week honors program for teachers, sponsored by NASA, the National Science Teachers Association, the National Council of Teachers of Mathematics and the International Technology Education-Association. A total of 25 teachers from the United States and U.S. State Department schools in Europe are chosen to work with NASA and other federal agency science and engineering professionals. Pictured, participants make hot air balloons as part of their activities.

  15. Fueling Future with Algal Genomics

    Energy Technology Data Exchange (ETDEWEB)

    Grigoriev, Igor

    2012-07-05

    Algae constitute a major component of fundamental eukaryotic diversity, play profound roles in the carbon cycle, and are prominent candidates for biofuel production. The US Department of Energy Joint Genome Institute (JGI) is leading the world in algal genome sequencing (http://jgi.doe.gov/Algae) and contributes of the algal genome projects worldwide (GOLD database, 2012). The sequenced algal genomes offer catalogs of genes, networks, and pathways. The sequenced first of its kind genomes of a haptophyte E.huxleyii, chlorarachniophyte B.natans, and cryptophyte G.theta fill the gaps in the eukaryotic tree of life and carry unique genes and pathways as well as molecular fossils of secondary endosymbiosis. Natural adaptation to conditions critical for industrial production is encoded in algal genomes, for example, growth of A.anophagefferens at very high cell densities during the harmful algae blooms or a global distribution across diverse environments of E.huxleyii, able to live on sparse nutrients due to its expanded pan-genome. Communications and signaling pathways can be derived from simple symbiotic systems like lichens or complex marine algae metagenomes. Collectively these datasets derived from algal genomics contribute to building a comprehensive parts list essential for algal biofuel development.

  16. Early Career Support Program: Telecommunication Mentoring for Rural Teachers.

    Science.gov (United States)

    Thoresen, Carol

    1997-01-01

    Describes the Early Career Support Program (STEP) which uses the Montana Educational Telecommunication Network (METNET) to connect early career teachers in Montana with mentors. Contains 20 references. (DDR)

  17. Antarctic Genomics

    Directory of Open Access Journals (Sweden)

    Alex D. Rogers

    2006-03-01

    Full Text Available With the development of genomic science and its battery of technologies, polar biology stands on the threshold of a revolution, one that will enable the investigation of important questions of unprecedented scope and with extraordinary depth and precision. The exotic organisms of polar ecosystems are ideal candidates for genomic analysis. Through such analyses, it will be possible to learn not only the novel features that enable polar organisms to survive, and indeed thrive, in their extreme environments, but also fundamental biological principles that are common to most, if not all, organisms. This article aims to review recent developments in Antarctic genomics and to demonstrate the global context of such studies.

  18. Genome-Wide Binding Analysis of the Transcription Activator IDEAL PLANT ARCHITECTURE1 Reveals a Complex Network Regulating Rice Plant Architecture[W

    Science.gov (United States)

    Lu, Zefu; Yu, Hong; Xiong, Guosheng; Wang, Jing; Jiao, Yongqing; Liu, Guifu; Jing, Yanhui; Meng, Xiangbing; Hu, Xingming; Qian, Qian; Fu, Xiangdong; Wang, Yonghong; Li, Jiayang

    2013-01-01

    IDEAL PLANT ARCHITECTURE1 (IPA1) is critical in regulating rice (Oryza sativa) plant architecture and substantially enhances grain yield. To elucidate its molecular basis, we first confirmed IPA1 as a functional transcription activator and then identified 1067 and 2185 genes associated with IPA1 binding sites in shoot apices and young panicles, respectively, through chromatin immunoprecipitation sequencing assays. The SQUAMOSA PROMOTER BINDING PROTEIN-box direct binding core motif GTAC was highly enriched in IPA1 binding peaks; interestingly, a previously uncharacterized indirect binding motif TGGGCC/T was found to be significantly enriched through the interaction of IPA1 with proliferating cell nuclear antigen PROMOTER BINDING FACTOR1 or PROMOTER BINDING FACTOR2. Genome-wide expression profiling by RNA sequencing revealed IPA1 roles in diverse pathways. Moreover, our results demonstrated that IPA1 could directly bind to the promoter of rice TEOSINTE BRANCHED1, a negative regulator of tiller bud outgrowth, to suppress rice tillering, and directly and positively regulate DENSE AND ERECT PANICLE1, an important gene regulating panicle architecture, to influence plant height and panicle length. The elucidation of target genes of IPA1 genome-wide will contribute to understanding the molecular mechanisms underlying plant architecture and to facilitating the breeding of elite varieties with ideal plant architecture. PMID:24170127

  19. Genome-wide binding analysis of the transcription activator ideal plant architecture1 reveals a complex network regulating rice plant architecture.

    Science.gov (United States)

    Lu, Zefu; Yu, Hong; Xiong, Guosheng; Wang, Jing; Jiao, Yongqing; Liu, Guifu; Jing, Yanhui; Meng, Xiangbing; Hu, Xingming; Qian, Qian; Fu, Xiangdong; Wang, Yonghong; Li, Jiayang

    2013-10-01

    Ideal plant architecture1 (IPA1) is critical in regulating rice (Oryza sativa) plant architecture and substantially enhances grain yield. To elucidate its molecular basis, we first confirmed IPA1 as a functional transcription activator and then identified 1067 and 2185 genes associated with IPA1 binding sites in shoot apices and young panicles, respectively, through chromatin immunoprecipitation sequencing assays. The Squamosa promoter binding protein-box direct binding core motif GTAC was highly enriched in IPA1 binding peaks; interestingly, a previously uncharacterized indirect binding motif TGGGCC/T was found to be significantly enriched through the interaction of IPA1 with proliferating cell nuclear antigen promoter binding factor1 or promoter binding factor2. Genome-wide expression profiling by RNA sequencing revealed IPA1 roles in diverse pathways. Moreover, our results demonstrated that IPA1 could directly bind to the promoter of rice teosinte branched1, a negative regulator of tiller bud outgrowth, to suppress rice tillering, and directly and positively regulate dense and erect panicle1, an important gene regulating panicle architecture, to influence plant height and panicle length. The elucidation of target genes of IPA1 genome-wide will contribute to understanding the molecular mechanisms underlying plant architecture and to facilitating the breeding of elite varieties with ideal plant architecture.

  20. Teacher Inequality

    Directory of Open Access Journals (Sweden)

    Andrew J. Wayne

    2002-06-01

    Full Text Available When discussing the teacher quality gap, policy makers have tended to focus on teacher certification, degrees, and experience. These indicators have become key benchmarks for progress toward equality of educational opportunity, in part for lack of additional teacher quality indicators. This article turns attention to teachers' academic skills. National data on teachers' entrance examination scores and college selectivity reveal substantial disparities by school poverty level. The findings commend attention to the gap in academic skills in the formulation of future policy and research on the teacher quality gap.

  1. Identification of Topological Network Modules in Perturbed Protein Interaction Networks

    Science.gov (United States)

    Sardiu, Mihaela E.; Gilmore, Joshua M.; Groppe, Brad; Florens, Laurence; Washburn, Michael P.

    2017-01-01

    Biological networks consist of functional modules, however detecting and characterizing such modules in networks remains challenging. Perturbing networks is one strategy for identifying modules. Here we used an advanced mathematical approach named topological data analysis (TDA) to interrogate two perturbed networks. In one, we disrupted the S. cerevisiae INO80 protein interaction network by isolating complexes after protein complex components were deleted from the genome. In the second, we reanalyzed previously published data demonstrating the disruption of the human Sin3 network with a histone deacetylase inhibitor. Here we show that disrupted networks contained topological network modules (TNMs) with shared properties that mapped onto distinct locations in networks. We define TMNs as proteins that occupy close network positions depending on their coordinates in a topological space. TNMs provide new insight into networks by capturing proteins from different categories including proteins within a complex, proteins with shared biological functions, and proteins disrupted across networks. PMID:28272416

  2. Herbarium genomics

    DEFF Research Database (Denmark)

    Bakker, Freek T.; Lei, Di; Yu, Jiaying

    2016-01-01

    Herbarium genomics is proving promising as next-generation sequencing approaches are well suited to deal with the usually fragmented nature of archival DNA. We show that routine assembly of partial plastome sequences from herbarium specimens is feasible, from total DNA extracts and with specimens...... up to 146 years old. We use genome skimming and an automated assembly pipeline, Iterative Organelle Genome Assembly, that assembles paired-end reads into a series of candidate assemblies, the best one of which is selected based on likelihood estimation. We used 93 specimens from 12 different...... correlation between plastome coverage and nuclear genome size (C value) in our samples, but the range of C values included is limited. Finally, we conclude that routine plastome sequencing from herbarium specimens is feasible and cost-effective (compared with Sanger sequencing or plastome...

  3. Developing Pedagogy for Wireless Calculator Networks--and Researching Teacher Professional Development. Final Report. Part 2--Technical Report and Research Description to the National Science Foundation.

    Science.gov (United States)

    Owens, Douglas T.; Demana, Franklin; Abrahamson, A. Louis; Meagher, Michael; Herman, Marlena

    This project was designed to investigate the potential of classroom communication systems (CCSs) for facilitating effective teaching and creating effective learning environments. The study was specifically designed to examine the extent to which teachers use CCSs in their classrooms to facilitate environments which are learner-centered,…

  4. RIKEN mouse genome encyclopedia.

    Science.gov (United States)

    Hayashizaki, Yoshihide

    2003-01-01

    We have been working to establish the comprehensive mouse full-length cDNA collection and sequence database to cover as many genes as we can, named Riken mouse genome encyclopedia. Recently we are constructing higher-level annotation (Functional ANnoTation Of Mouse cDNA; FANTOM) not only with homology search based annotation but also with expression data profile, mapping information and protein-protein database. More than 1,000,000 clones prepared from 163 tissues were end-sequenced to classify into 159,789 clusters and 60,770 representative clones were fully sequenced. As a conclusion, the 60,770 sequences contained 33,409 unique. The next generation of life science is clearly based on all of the genome information and resources. Based on our cDNA clones we developed the additional system to explore gene function. We developed cDNA microarray system to print all of these cDNA clones, protein-protein interaction screening system, protein-DNA interaction screening system and so on. The integrated database of all the information is very useful not only for analysis of gene transcriptional network and for the connection of gene to phenotype to facilitate positional candidate approach. In this talk, the prospect of the application of these genome resourced should be discussed. More information is available at the web page: http://genome.gsc.riken.go.jp/.

  5. News Outreach: Polish physics club reaches out with practical demonstrations Networking: Online workspace helps teachers to share ideas Mauritius: Telescope inspires science specification Fusion: EFDA sparks resources Olympiad: British team enjoys success at the International Physics Olympiad 2009 Nanoscience: 'Quietest' building in the world opens in Bristol, UK Conference: University of Leicester hosts the GIREP EPEC 2009 international conference

    Science.gov (United States)

    2009-11-01

    Outreach: Polish physics club reaches out with practical demonstrations Networking: Online workspace helps teachers to share ideas Mauritius: Telescope inspires science specification Fusion: EFDA sparks resources Olympiad: British team enjoys success at the International Physics Olympiad 2009 Nanoscience: 'Quietest' building in the world opens in Bristol, UK Conference: University of Leicester hosts the GIREP EPEC 2009 international conference

  6. Genome Wide Expression Profiling of Cancer Cell Lines Cultured in Microgravity Reveals Significant Dysregulation of Cell Cycle and MicroRNA Gene Networks.

    Directory of Open Access Journals (Sweden)

    Prasanna Vidyasekar

    Full Text Available Zero gravity causes several changes in metabolic and functional aspects of the human body and experiments in space flight have demonstrated alterations in cancer growth and progression. This study reports the genome wide expression profiling of a colorectal cancer cell line-DLD-1, and a lymphoblast leukemic cell line-MOLT-4, under simulated microgravity in an effort to understand central processes and cellular functions that are dysregulated among both cell lines. Altered cell morphology, reduced cell viability and an aberrant cell cycle profile in comparison to their static controls were observed in both cell lines under microgravity. The process of cell cycle in DLD-1 cells was markedly affected with reduced viability, reduced colony forming ability, an apoptotic population and dysregulation of cell cycle genes, oncogenes, and cancer progression and prognostic markers. DNA microarray analysis revealed 1801 (upregulated and 2542 (downregulated genes (>2 fold in DLD-1 cultures under microgravity while MOLT-4 cultures differentially expressed 349 (upregulated and 444 (downregulated genes (>2 fold under microgravity. The loss in cell proliferative capacity was corroborated with the downregulation of the cell cycle process as demonstrated by functional clustering of DNA microarray data using gene ontology terms. The genome wide expression profile also showed significant dysregulation of post transcriptional gene silencing machinery and multiple microRNA host genes that are potential tumor suppressors and proto-oncogenes including MIR22HG, MIR17HG and MIR21HG. The MIR22HG, a tumor-suppressor gene was one of the highest upregulated genes in the microarray data showing a 4.4 log fold upregulation under microgravity. Real time PCR validated the dysregulation in the host gene by demonstrating a 4.18 log fold upregulation of the miR-22 microRNA. Microarray data also showed dysregulation of direct targets of miR-22, SP1, CDK6 and CCNA2.

  7. Yeast biological networks unfold the interplay of antioxidants, genome and phenotype, and reveal a novel regulator of the oxidative stress response.

    Directory of Open Access Journals (Sweden)

    Jose M Otero

    Full Text Available BACKGROUND: Identifying causative biological networks associated with relevant phenotypes is essential in the field of systems biology. We used ferulic acid (FA as a model antioxidant to characterize the global expression programs triggered by this small molecule and decipher the transcriptional network controlling the phenotypic adaptation of the yeast Saccharomyces cerevisiae. METHODOLOGY/PRINCIPAL FINDINGS: By employing a strict cut off value during gene expression data analysis, 106 genes were found to be involved in the cell response to FA, independent of aerobic or anaerobic conditions. Network analysis of the system guided us to a key target node, the FMP43 protein, that when deleted resulted in marked acceleration of cellular growth (∼15% in both minimal and rich media. To extend our findings to human cells and identify proteins that could serve as drug targets, we replaced the yeast FMP43 protein with its human ortholog BRP44 in the genetic background of the yeast strain Δfmp43. The conservation of the two proteins was phenotypically evident, with BRP44 restoring the normal specific growth rate of the wild type. We also applied homology modeling to predict the 3D structure of the FMP43 and BRP44 proteins. The binding sites in the homology models of FMP43 and BRP44 were computationally predicted, and further docking studies were performed using FA as the ligand. The docking studies demonstrated the affinity of FA towards both FMP43 and BRP44. CONCLUSIONS: This study proposes a hypothesis on the mechanisms yeast employs to respond to antioxidant molecules, while demonstrating how phenome and metabolome yeast data can serve as biomarkers for nutraceutical discovery and development. Additionally, we provide evidence for a putative therapeutic target, revealed by replacing the FMP43 protein with its human ortholog BRP44, a brain protein, and functionally characterizing the relevant mutant strain.

  8. Genomic SELEX: a discovery tool for genomic aptamers.

    Science.gov (United States)

    Zimmermann, Bob; Bilusic, Ivana; Lorenz, Christina; Schroeder, Renée

    2010-10-01

    Genomic SELEX is a discovery tool for genomic aptamers, which are genomically encoded functional domains in nucleic acid molecules that recognize and bind specific ligands. When combined with genomic libraries and using RNA-binding proteins as baits, Genomic SELEX used with high-throughput sequencing enables the discovery of genomic RNA aptamers and the identification of RNA-protein interaction networks. Here we describe how to construct and analyze genomic libraries, how to choose baits for selections, how to perform the selection procedure and finally how to analyze the enriched sequences derived from deep sequencing. As a control procedure, we recommend performing a "Neutral" SELEX experiment in parallel to the selection, omitting the selection step. This control experiment provides a background signal for comparison with the positively selected pool. We also recommend deep sequencing the initial library in order to facilitate the final in silico analysis of enrichment with respect to the initial levels. Counter selection procedures, using modified or inactive baits, allow strengthening the binding specificity of the winning selected sequences.

  9. Genome-wide analysis of the mouse lung transcriptome reveals novel molecular gene interaction networks and cell-specific expression signatures

    Directory of Open Access Journals (Sweden)

    Williams Robert W

    2011-05-01

    Full Text Available Abstract Background The lung is critical in surveillance and initial defense against pathogens. In humans, as in mice, individual genetic differences strongly modulate pulmonary responses to infectious agents, severity of lung disease, and potential allergic reactions. In a first step towards understanding genetic predisposition and pulmonary molecular networks that underlie individual differences in disease vulnerability, we performed a global analysis of normative lung gene expression levels in inbred mouse strains and a large family of BXD strains that are widely used for systems genetics. Our goal is to provide a key community resource on the genetics of the normative lung transcriptome that can serve as a foundation for experimental analysis and allow predicting genetic predisposition and response to pathogens, allergens, and xenobiotics. Methods Steady-state polyA+ mRNA levels were assayed across a diverse and fully genotyped panel of 57 isogenic strains using the Affymetrix M430 2.0 array. Correlations of expression levels between genes were determined. Global expression QTL (eQTL analysis and network covariance analysis was performed using tools and resources in GeneNetwork http://www.genenetwork.org. Results Expression values were highly variable across strains and in many cases exhibited a high heri-tability factor. Several genes which showed a restricted expression to lung tissue were identified. Using correlations between gene expression values across all strains, we defined and extended memberships of several important molecular networks in the lung. Furthermore, we were able to extract signatures of immune cell subpopulations and characterize co-variation and shared genetic modulation. Known QTL regions for respiratory infection susceptibility were investigated and several cis-eQTL genes were identified. Numerous cis- and trans-regulated transcripts and chromosomal intervals with strong regulatory activity were mapped. The Cyp1a1 P

  10. Reticulate evolution of the rye genome.

    Science.gov (United States)

    Martis, Mihaela M; Zhou, Ruonan; Haseneyer, Grit; Schmutzer, Thomas; Vrána, Jan; Kubaláková, Marie; König, Susanne; Kugler, Karl G; Scholz, Uwe; Hackauf, Bernd; Korzun, Viktor; Schön, Chris-Carolin; Dolezel, Jaroslav; Bauer, Eva; Mayer, Klaus F X; Stein, Nils

    2013-10-01

    Rye (Secale cereale) is closely related to wheat (Triticum aestivum) and barley (Hordeum vulgare). Due to its large genome (~8 Gb) and its regional importance, genome analysis of rye has lagged behind other cereals. Here, we established a virtual linear gene order model (genome zipper) comprising 22,426 or 72% of the detected set of 31,008 rye genes. This was achieved by high-throughput transcript mapping, chromosome survey sequencing, and integration of conserved synteny information of three sequenced model grass genomes (Brachypodium distachyon, rice [Oryza sativa], and sorghum [Sorghum bicolor]). This enabled a genome-wide high-density comparative analysis of rye/barley/model grass genome synteny. Seventeen conserved syntenic linkage blocks making up the rye and barley genomes were defined in comparison to model grass genomes. Six major translocations shaped the modern rye genome in comparison to a putative Triticeae ancestral genome. Strikingly dissimilar conserved syntenic gene content, gene sequence diversity signatures, and phylogenetic networks were found for individual rye syntenic blocks. This indicates that introgressive hybridizations (diploid or polyploidy hybrid speciation) and/or a series of whole-genome or chromosome duplications played a role in rye speciation and genome evolution.

  11. Teachers' Autonomy

    Science.gov (United States)

    Parker, Gemma

    2015-01-01

    This literature review begins by considering the concept of autonomy. The focus narrows to teacher autonomy specifically and a range of conceptualisations are summarised. Its influences and impact are discussed and the role which teacher autonomy plays in the wider issue of teacher professionalism is addressed. Central influences, including the UK…

  12. Genome-wide expression analysis of rice aquaporin genes and development of a functional gene network mediated by aquaporin expression in roots.

    Science.gov (United States)

    Nguyen, Minh Xuan; Moon, Sunok; Jung, Ki-Hong

    2013-10-01

    The world population continually faces challenges of water scarcity for agriculture. A common strategy called water-balance control has evolved to adapt plant growth to these challenges. Aquaporins are a family of integral membrane proteins that play a central role in water-balance control. In this study, we identified 34 members of the rice aquaporin gene family, adding a novel member to the previous list. A combination of phylogenetic tree and anatomical meta-expression profiling data consisting of 983 Affymetrix arrays and 209 Agilent 44 K arrays was used to identify tissue-preferred aquaporin genes and evaluate functional redundancy among aquaporin family members. Eight aquaporins showed root-preferred expression in the vegetative growth stage, while 4 showed leaf/shoot-preferred expression. Integrating stress-induced expression patterns into phylogenetic tree and semi-quantitative reverse transcriptase polymerase chain reaction (RT-PCR) analyses revealed that 3 rice aquaporin genes were markedly downregulated and 4 were upregulated by water deficiency in the root, suggesting that these candidate genes are key regulators of water uptake from the soil. Finally, we constructed a functional network of genes mediated by water stress and refined the network by confirming the differential expression using RT-PCR and real-time PCR. Our data will be useful to elucidate the molecular mechanism of water-balance control in rice root.

  13. IMP 2.0: a multi-species functional genomics portal for integration, visualization and prediction of protein functions and networks.

    Science.gov (United States)

    Wong, Aaron K; Krishnan, Arjun; Yao, Victoria; Tadych, Alicja; Troyanskaya, Olga G

    2015-07-01

    IMP (Integrative Multi-species Prediction), originally released in 2012, is an interactive web server that enables molecular biologists to interpret experimental results and to generate hypotheses in the context of a large cross-organism compendium of functional predictions and networks. The system provides biologists with a framework to analyze their candidate gene sets in the context of functional networks, expanding or refining their sets using functional relationships predicted from integrated high-throughput data. IMP 2.0 integrates updated prior knowledge and data collections from the last three years in the seven supported organisms (Homo sapiens, Mus musculus, Rattus norvegicus, Drosophila melanogaster, Danio rerio, Caenorhabditis elegans, and Saccharomyces cerevisiae) and extends function prediction coverage to include human disease. IMP identifies homologs with conserved functional roles for disease knowledge transfer, allowing biologists to analyze disease contexts and predictions across all organisms. Additionally, IMP 2.0 implements a new flexible platform for experts to generate custom hypotheses about biological processes or diseases, making sophisticated data-driven methods easily accessible to researchers. IMP does not require any registration or installation and is freely available for use at http://imp.princeton.edu.

  14. Genome databases

    Energy Technology Data Exchange (ETDEWEB)

    Courteau, J.

    1991-10-11

    Since the Genome Project began several years ago, a plethora of databases have been developed or are in the works. They range from the massive Genome Data Base at Johns Hopkins University, the central repository of all gene mapping information, to small databases focusing on single chromosomes or organisms. Some are publicly available, others are essentially private electronic lab notebooks. Still others limit access to a consortium of researchers working on, say, a single human chromosome. An increasing number incorporate sophisticated search and analytical software, while others operate as little more than data lists. In consultation with numerous experts in the field, a list has been compiled of some key genome-related databases. The list was not limited to map and sequence databases but also included the tools investigators use to interpret and elucidate genetic data, such as protein sequence and protein structure databases. Because a major goal of the Genome Project is to map and sequence the genomes of several experimental animals, including E. coli, yeast, fruit fly, nematode, and mouse, the available databases for those organisms are listed as well. The author also includes several databases that are still under development - including some ambitious efforts that go beyond data compilation to create what are being called electronic research communities, enabling many users, rather than just one or a few curators, to add or edit the data and tag it as raw or confirmed.

  15. Genomic Signal Processing: The Salient Issues

    Directory of Open Access Journals (Sweden)

    Shmulevich Ilya

    2004-01-01

    Full Text Available This paper considers key issues in the emerging field of genomic signal processing and its relationship to functional genomics. It focuses on some of the biological mechanisms driving the development of genomic signal processing, in addition to their manifestation in gene-expression-based classification and genetic network modeling. Certain problems are inherent. For instance, small-sample error estimation, variable selection, and model complexity are important issues for both phenotype classification and expression prediction used in network inference. A long-term goal is to develop intervention strategies to drive network behavior, which is briefly discussed. It is hoped that this nontechnical paper demonstrates that the field of signal processing has the potential to impact and help drive genomics research.

  16. The Human Genome Project: Biology, Computers, and Privacy.

    Science.gov (United States)

    Cutter, Mary Ann G.; Drexler, Edward; Gottesman, Kay S.; Goulding, Philip G.; McCullough, Laurence B.; McInerney, Joseph D.; Micikas, Lynda B.; Mural, Richard J.; Murray, Jeffrey C.; Zola, John

    This module, for high school teachers, is the second of two modules about the Human Genome Project (HGP) produced by the Biological Sciences Curriculum Study (BSCS). The first section of this module provides background information for teachers about the structure and objectives of the HGP, aspects of the science and technology that underlie the…

  17. Computational modeling with forward and reverse engineering links signaling network and genomic regulatory responses: NF-κB signaling-induced gene expression responses in inflammation

    Directory of Open Access Journals (Sweden)

    Peng Chien

    2010-06-01

    Full Text Available Abstract Background Signal transduction is the major mechanism through which cells transmit external stimuli to evoke intracellular biochemical responses. Diverse cellular stimuli create a wide variety of transcription factor activities through signal transduction pathways, resulting in different gene expression patterns. Understanding the relationship between external stimuli and the corresponding cellular responses, as well as the subsequent effects on downstream genes, is a major challenge in systems biology. Thus, a systematic approach is needed to integrate experimental data and theoretical hypotheses to identify the physiological consequences of environmental stimuli. Results We proposed a systematic approach that combines forward and reverse engineering to link the signal transduction cascade with the gene responses. To demonstrate the feasibility of our strategy, we focused on linking the NF-κB signaling pathway with the inflammatory gene regulatory responses because NF-κB has long been recognized to play a crucial role in inflammation. We first utilized forward engineering (Hybrid Functional Petri Nets to construct the NF-κB signaling pathway and reverse engineering (Network Components Analysis to build a gene regulatory network (GRN. Then, we demonstrated that the corresponding IKK profiles can be identified in the GRN and are consistent with the experimental validation of the IKK kinase assay. We found that the time-lapse gene expression of several cytokines and chemokines (TNF-α, IL-1, IL-6, CXCL1, CXCL2 and CCL3 is concordant with the NF-κB activity profile, and these genes have stronger influence strength within the GRN. Such regulatory effects have highlighted the crucial roles of NF-κB signaling in the acute inflammatory response and enhance our understanding of the systemic inflammatory response syndrome. Conclusion We successfully identified and distinguished the corresponding signaling profiles among three microarray

  18. Teacher Professional Development with an Education for ...

    African Journals Online (AJOL)

    Southern African Journal of Environmental Education ... South Africa: Development of a Network, Curriculum Framework and Resources for Teacher Education ... Similarly, it fails to support social innovation as a response to environment and ...

  19. "Does Knowing Stuff like PSHE and Citizenship Make Me a Better Teacher?": Student Teachers in the Teacher Training Figuration

    Science.gov (United States)

    Velija, Philippa; Capel, Susan; Katene, Will; Hayes, Sid

    2008-01-01

    One of the key elements of figurational sociology is the emphasis on understanding complex networks of interdependencies in which people are involved. The focal point of this paper is the process of initial teacher training (ITT) and the relationships of which student teachers are part during their ITT course. The paper does not look at what…

  20. Genomics of sex determination.

    Science.gov (United States)

    Zhang, Jisen; Boualem, Adnane; Bendahmane, Abdelhafid; Ming, Ray

    2014-04-01

    Sex determination is a major switch in the evolutionary history of angiosperm, resulting 11% monoecious and dioecious species. The genomic sequences of papaya sex chromosomes unveiled the molecular basis of recombination suppression in the sex determination region, and candidate genes for sex determination. Identification and analyses of sex determination genes in cucurbits and maize demonstrated conservation of sex determination mechanism in one lineage and divergence between the two systems. Epigenetic control and hormonal influence of sex determination were elucidated in both plants and animals. Intensive investigation of potential sex determination genes in model species will improve our understanding of sex determination gene network. Such network will in turn accelerate the identification of sex determination genes in dioecious species with sex chromosomes, which are burdensome due to no recombination in sex determining regions. The sex determination genes in dioecious species are crucial for understanding the origin of dioecy and sex chromosomes, particularly in their early stage of evolution.

  1. Marine genomics

    DEFF Research Database (Denmark)

    Oliveira Ribeiro, Ângela Maria; Foote, Andrew D.; Kupczok, Anne

    2017-01-01

    Marine ecosystems occupy 71% of the surface of our planet, yet we know little about their diversity. Although the inventory of species is continually increasing, as registered by the Census of Marine Life program, only about 10% of the estimated two million marine species are known. This lag......-throughput sequencing approaches have been helping to improve our knowledge of marine biodiversity, from the rich microbial biota that forms the base of the tree of life to a wealth of plant and animal species. In this review, we present an overview of the applications of genomics to the study of marine life, from...... evolutionary biology of non-model organisms to species of commercial relevance for fishing, aquaculture and biomedicine. Instead of providing an exhaustive list of available genomic data, we rather set to present contextualized examples that best represent the current status of the field of marine genomics....

  2. Cephalopod genomics

    DEFF Research Database (Denmark)

    Albertin, Caroline B.; Bonnaud, Laure; Brown, C. Titus

    2012-01-01

    The Cephalopod Sequencing Consortium (CephSeq Consortium) was established at a NESCent Catalysis Group Meeting, ``Paths to Cephalopod Genomics-Strategies, Choices, Organization,'' held in Durham, North Carolina, USA on May 24-27, 2012. Twenty-eight participants representing nine countries (Austria......, Australia, China, Denmark, France, Italy, Japan, Spain and the USA) met to address the pressing need for genome sequencing of cephalopod mollusks. This group, drawn from cephalopod biologists, neuroscientists, developmental and evolutionary biologists, materials scientists, bioinformaticians and researchers...... active in sequencing, assembling and annotating genomes, agreed on a set of cephalopod species of particular importance for initial sequencing and developed strategies and an organization (CephSeq Consortium) to promote this sequencing. The conclusions and recommendations of this meeting are described...

  3. Listeria Genomics

    Science.gov (United States)

    Cabanes, Didier; Sousa, Sandra; Cossart, Pascale

    The opportunistic intracellular foodborne pathogen Listeria monocytogenes has become a paradigm for the study of host-pathogen interactions and bacterial adaptation to mammalian hosts. Analysis of L. monocytogenes infection has provided considerable insight into how bacteria invade cells, move intracellularly, and disseminate in tissues, as well as tools to address fundamental processes in cell biology. Moreover, the vast amount of knowledge that has been gathered through in-depth comparative genomic analyses and in vivo studies makes L. monocytogenes one of the most well-studied bacterial pathogens. This chapter provides an overview of progress in the exploration of genomic, transcriptomic, and proteomic data in Listeria spp. to understand genome evolution and diversity, as well as physiological aspects of metabolism used by bacteria when growing in diverse environments, in particular in infected hosts.

  4. Teacher expertise

    DEFF Research Database (Denmark)

    Rasmussen, Jens

    and practice through development of better models for bridging the teaching at college and the internship teaching. The study was a longitudinal research and development project that followed teacher students during their first three years of a four year teacher education program after the teacher education....... The question is how teacher preparation leads to effective teachers. The study Expert in Teaching paid special attention to the intention of connecting coursework more directly to practice in pre-service teacher education. The overall objective of the study was to strengthen the relationship between theory...... between college and practice teaching. These actions were evaluated in relation to a two-dimensional framework of criteria for teacher expertise. One dimension consists of three different knowledge forms (scientific, professional, and practice knowledge), the other in the goals set in the national...

  5. Genome-wide screening reveals an EMT molecular network mediated by Sonic hedgehog-Gli1 signaling in pancreatic cancer cells.

    Directory of Open Access Journals (Sweden)

    Xuanfu Xu

    Full Text Available AIMS: The role of sonic hedgehog (SHH in epithelial mesenchymal transition (EMT of pancreatic cancer (PC is known, however, its mechanism is unclear. Because SHH promotes tumor development predominantly through Gli1, we sought to understand its mechanism by identifying Gli1 targets in pancreatic cancer cells. METHODS: First, we investigated invasion, migration, and EMT in PC cells transfected with lentiviral Gli1 interference vectors or SHH over-expression vectors in vitro and in vivo. Next, we determined the target gene profiles of Gli1 in PC cells using cDNA microarray assays. Finally, the primary regulatory networks downstream of SHH-Gli1 signaling in PC cells were studied through functional analyses of these targets. RESULTS: Our results indicate there is decreased E-cadherin expression upon increased expression of SHH/Gli1. Migration of PC cells increased significantly in a dose-dependent manner within 24 hours of Gli1 expression (P<0.05. The ratio of liver metastasis and intrasplenic miniature metastasis increased markedly upon activation of SHH-Gli1 signals in nude mice. Using cDNA microarray, we identified 278 upregulated and 59 downregulated genes upon Gli1 expression in AsPC-1 cells. The data indicate that SHH-Gli1 signals promote EMT by mediating a complex signaling network including TGFβ, Ras, Wnt, growth factors, PI3K/AKT, integrins, transmembrane 4 superfamily (TM4SF, and S100A4. CONCLUSION: Our results suggest that targeting the molecular connections established between SHH-Gli1 signaling and EMT could provide effective therapies for PC.

  6. Further Evidence for the Impact of a Genome-Wide-Supported Psychosis Risk Variant in ZNF804A on the Theory of Mind Network

    Science.gov (United States)

    Mohnke, Sebastian; Erk, Susanne; Schnell, Knut; Schütz, Claudia; Romanczuk-Seiferth, Nina; Grimm, Oliver; Haddad, Leila; Pöhland, Lydia; Garbusow, Maria; Schmitgen, Mike M; Kirsch, Peter; Esslinger, Christine; Rietschel, Marcella; Witt, Stephanie H; Nöthen, Markus M; Cichon, Sven; Mattheisen, Manuel; Mühleisen, Thomas; Jensen, Jimmy; Schott, Björn H; Maier, Wolfgang; Heinz, Andreas; Meyer-Lindenberg, Andreas; Walter, Henrik

    2014-01-01

    The single-nucleotide polymorphism (SNP) rs1344706 in ZNF804A is one of the best-supported risk variants for psychosis. We hypothesized that this SNP contributes to the development of schizophrenia by affecting the ability to understand other people's mental states. This skill, commonly referred to as Theory of Mind (ToM), has consistently been found to be impaired in schizophrenia. Using functional magnetic resonance imaging, we previously showed that in healthy individuals rs1344706 impacted on activity and connectivity of key areas of the ToM network, including the dorsomedial prefrontal cortex, temporo-parietal junction, and the posterior cingulate cortex, which show aberrant activity in schizophrenia patients, too. We aimed to replicate these results in an independent sample of 188 healthy German volunteers. In order to assess the reliability of brain activity elicited by the ToM task, 25 participants performed the task twice with an interval of 14 days showing excellent accordance in recruitment of key ToM areas. Confirming our previous results, we observed decreasing activity of the left temporo-parietal junction, dorsomedial prefrontal cortex, and the posterior cingulate cortex with increasing number of risk alleles during ToM. Complementing our replication sample with the discovery sample, analyzed in a previous report (total N=297), further revealed negative genotype effects in the left dorsomedial prefrontal cortex as well as in the temporal and parietal regions. In addition, as shown previously, rs1344706 risk allele dose positively predicted increased frontal–temporo-parietal connectivity. These findings confirm the effects of the psychosis risk variant in ZNF804A on the dysfunction of the ToM network. PMID:24247043

  7. Genome Sequencing

    DEFF Research Database (Denmark)

    Sato, Shusei; Andersen, Stig Uggerhøj

    2014-01-01

    The current Lotus japonicus reference genome sequence is based on a hybrid assembly of Sanger TAC/BAC, Sanger shotgun and Illumina shotgun sequencing data generated from the Miyakojima-MG20 accession. It covers nearly all expressed L. japonicus genes and has been annotated mainly based on transcr......The current Lotus japonicus reference genome sequence is based on a hybrid assembly of Sanger TAC/BAC, Sanger shotgun and Illumina shotgun sequencing data generated from the Miyakojima-MG20 accession. It covers nearly all expressed L. japonicus genes and has been annotated mainly based...

  8. The Global Invertebrate Genomics Alliance (GIGA). 2014. Developing Community Resources to Study Diverse Invertebrate Genomes

    NARCIS (Netherlands)

    Pomponi, S.A.

    2014-01-01

    Over 95% of all metazoan (animal) species comprise the “invertebrates,” but very few genomes from these organisms have been sequenced. We have, therefore, formed a “Global Invertebrate Genomics Alliance” (GIGA). Our intent is to build a collaborative network of diverse scientists to tackle major cha

  9. The Global Invertebrate Genomics Alliance (GIGA). 2014. Developing Community Resources to Study Diverse Invertebrate Genomes

    NARCIS (Netherlands)

    Pomponi, S.A.

    2014-01-01

    Over 95% of all metazoan (animal) species comprise the “invertebrates,” but very few genomes from these organisms have been sequenced. We have, therefore, formed a “Global Invertebrate Genomics Alliance” (GIGA). Our intent is to build a collaborative network of diverse scientists to tackle major

  10. A Program for Teaching the Teachers.

    Science.gov (United States)

    Cline, Hugh F.; Anderson, Jana

    1984-01-01

    The Educational Testing Service, supported by International Business Machines (IBM), has trained secondary school teachers to demonstrate how microcomputers can aid in preparing students for today's technological world. Various aspects of these programs are described. Lists of teacher training institutes and related network schools in California,…

  11. Telecommunications in Florida: Training Materials for Teachers.

    Science.gov (United States)

    Eason, Mike; And Others

    1994-01-01

    Describes the use of the Florida Information Resource Network (FIRN) in Florida public schools. Highlights include electronic mail exchanges; online conferences; remote research; classroom resources; training initiatives for teachers to learn about telecommunications; access to other systems and databases; and inservice, hands-on teacher training.…

  12. Using Neural Network to Evaluate University Teachers' Experimental Teaching Quality%基于神经网络的高校实验教学质量评价研究

    Institute of Scientific and Technical Information of China (English)

    谢红艳; 朱允华; 刘俊; 杨晓燕; 胡劲松; 秦志峰

    2015-01-01

    在分析了高校教师实验教学质量评价特点的基础上,构建了一种基于模糊理论与神经网络的高校教师实验教学质量评价体系。该模型将教学评价指标概念量化成确定的数据作为网络的输入,模糊综合评价结果作为输出。该方法既克服了评价主体在评价过程中的主观因素,又得到了满意的评价结果,具有广泛的适用性。%Based on the analysis of features of Experimental teaching quality appraisal of teacher sin colleges and universities, an evaluation model of university teachers’ Experimental teaching quality based on fuzzy theory and BP neural network is introduced. The model transforms teaching evaluation indicators into qualiifed data as BP network input and takes fuzzy synthetic evaluation results as output. the method can both overcome the subjective factors of evaluation main body in evaluation process and bring the satisfactory evaluating results and it has the widespread serviceability.

  13. Science Teachers Sharing Artifacts from Practice like Students’ Tablet Productions

    DEFF Research Database (Denmark)

    Nielsen, Birgitte Lund

    2013-01-01

    to support the success of integrating technology. Experiences from a large-scale, long-term TPD project for primary and secondary science teachers supporting the teachers in trying out innovative practices and new ICT tools in own classes, and in sharing artifacts from these trials in teacher networks...

  14. Developing and Assessing Teachers' Knowledge of Game-Based Learning

    Science.gov (United States)

    Shah, Mamta; Foster, Aroutis

    2015-01-01

    Research focusing on the development and assessment of teacher knowledge in game-based learning is in its infancy. A mixed-methods study was undertaken to educate pre-service teachers in game-based learning using the Game Network Analysis (GaNA) framework. Fourteen pre-service teachers completed a methods course, which prepared them in game…

  15. NASE Training Courses in Astronomy for Teachers throughout the World

    Science.gov (United States)

    Ros, Rosa M.

    2012-01-01

    Network for Astronomy School Education, NASE, is a project that is organizing courses for teachers throughout the entire world. The main objective of the project is to prepare secondary and primary school teachers in astronomy. Students love to know more about astronomy and teachers have the opportunity to observe the sky that every school has…

  16. NASE Training Courses in Astronomy for Teachers throughout the World

    Science.gov (United States)

    Ros, Rosa M.

    2012-01-01

    Network for Astronomy School Education, NASE, is a project that is organizing courses for teachers throughout the entire world. The main objective of the project is to prepare secondary and primary school teachers in astronomy. Students love to know more about astronomy and teachers have the opportunity to observe the sky that every school has…

  17. Developing and Assessing Teachers' Knowledge of Game-Based Learning

    Science.gov (United States)

    Shah, Mamta; Foster, Aroutis

    2015-01-01

    Research focusing on the development and assessment of teacher knowledge in game-based learning is in its infancy. A mixed-methods study was undertaken to educate pre-service teachers in game-based learning using the Game Network Analysis (GaNA) framework. Fourteen pre-service teachers completed a methods course, which prepared them in game…

  18. Ancient genomics

    DEFF Research Database (Denmark)

    Der Sarkissian, Clio; Allentoft, Morten Erik; Avila Arcos, Maria del Carmen;

    2015-01-01

    , archaic hominins, ancient pathogens and megafaunal species. Those have revealed important functional and phenotypic information, as well as unexpected adaptation, migration and admixture patterns. As such, the field of aDNA has entered the new era of genomics and has provided valuable information when...

  19. Cephalopod genomics

    DEFF Research Database (Denmark)

    Albertin, Caroline B.; Bonnaud, Laure; Brown, C. Titus

    2012-01-01

    The Cephalopod Sequencing Consortium (CephSeq Consortium) was established at a NESCent Catalysis Group Meeting, ``Paths to Cephalopod Genomics-Strategies, Choices, Organization,'' held in Durham, North Carolina, USA on May 24-27, 2012. Twenty-eight participants representing nine countries (Austri...

  20. Ancient genomics

    DEFF Research Database (Denmark)

    Der Sarkissian, Clio; Allentoft, Morten Erik; Avila Arcos, Maria del Carmen

    2015-01-01

    by increasing the number of sequence reads to billions effectively means that contamination issues that have haunted aDNA research for decades, particularly in human studies, can now be efficiently and confidently quantified. At present, whole genomes have been sequenced from ancient anatomically modern humans...

  1. Teacher Portfolios: Pathways to Teacher Empowerment.

    Science.gov (United States)

    Beck, Judy; Weiland, Lynn

    2001-01-01

    Describes three types of teacher portfolios: employment portfolio, learning portfolio, and assessment portfolio. Provides information from the Learning Community program that uses teacher portfolios in teacher education. (ASK)

  2. Disentangling the microRNA regulatory milieu in multiple myeloma: integrative genomics analysis outlines mixed miRNA-TF circuits and pathway-derived networks modulated in t(4;14) patients

    Science.gov (United States)

    Manzoni, Martina; Todoerti, Katia; Taiana, Elisa; Sales, Gabriele; Morgan, Gareth J.; Tonon, Giovanni; Amodio, Nicola; Tassone, Pierfrancesco; Neri, Antonino; Agnelli, Luca; Romualdi, Chiara; Bortoluzzi, Stefania

    2016-01-01

    The identification of overexpressed miRNAs in multiple myeloma (MM) has progressively added a further level of complexity to MM biology. miRNA and gene expression profiles of two large representative MM datasets, available from retrospective and prospective series and encompassing a total of 249 patients at diagnosis, were analyzed by means of in silico integrative genomics methods, based on MAGIA2 and Micrographite computational procedures. We first identified relevant miRNA/transcription factors/target gene regulation circuits in the disease and linked them to biological processes. Members of the miR-99b/let-7e/miR-125a cluster, or of its paralog, upregulated in t(4;14), were connected with the specific transcription factors PBX1 and CEBPA and several target genes. These results were validated in two additional independent plasma cell tumor datasets. Then, we reconstructed a non-redundant miRNA-gene regulatory network in MM, linking miRNAs, such as let-7g, miR-19a, mirR-20a, mir-21, miR-29 family, miR-34 family, miR-125b, miR-155, miR-221 to pathways associated with MM subtypes, in particular the ErbB, the Hippo, and the Acute myeloid leukemia associated pathways. PMID:26496024

  3. Quality Teacher Education via Distance Mode: A Caribbean Experience.

    Science.gov (United States)

    Hall, Winnifred M.; Marrett, Christine

    1996-01-01

    Reports on a study of the University of the West Indies Distance Teaching Experiment, which offers preservice teacher education via distance education using an interactive teleconference network. Surveys of participating teachers (n=169) indicated that the network had several of the desired infrastructures in place for conducting quality teacher…

  4. The concept of training in community network for teaching algebraic structures that are aimed to create a methodical competence of a mathematics teacher

    Directory of Open Access Journals (Sweden)

    Ирина Викторовна Кузнецова

    2012-12-01

    Full Text Available The paper proposes the concept of learning activities in online communities for teaching algebraic structures of the future teachers of mathematics, including a set of theoretical and methodological positions, laws, principles, factors, and pedagogical conditions of its implementation. Work is executed with support of the Russian fund of basic researches under the initiative project № 11-07-00733 «The Hypertext information retrieval thesaurus» a science Meta language» (structure; mathematical, linguistic and program maintenance; sections linguistics, mathematics, economy».

  5. How retrotransposons shape genome regulation.

    Science.gov (United States)

    Mita, Paolo; Boeke, Jef D

    2016-04-01

    Retrotransposons are mutagenic units able to move within the genome. Despite many defenses deployed by the host to suppress potentially harmful activities of retrotransposons, these genetic units have found ways to meld with normal cellular functions through processes of exaptation and domestication. The same host mechanisms targeting transposon mobility allow for expansion and rewiring of gene regulatory networks on an evolutionary time scale. Recent works demonstrating retrotransposon activity during development, cell differentiation and neurogenesis shed new light on unexpected activities of transposable elements. Moreover, new technological advances illuminated subtler nuances of the complex relationship between retrotransposons and the host genome, clarifying the role of retroelements in evolution, development and impact on human disease.

  6. The nuclear retention signal of HPV16 L2 protein is essential for incoming viral genome to transverse the trans-Golgi network

    Energy Technology Data Exchange (ETDEWEB)

    DiGiuseppe, Stephen; Bienkowska-Haba, Malgorzata; Hilbig, Lydia; Sapp, Martin, E-mail: msapp1@lsuhsc.edu

    2014-06-15

    The Human papillomavirus (HPV) capsid is composed of the major and minor capsid proteins, L1 and L2, respectively. Infectious entry requires a complex series of conformational changes in both proteins that lead to uptake and allow uncoating to occur. During entry, the capsid is disassembled and host cyclophilins dissociate L1 protein from the L2/DNA complex. Herein, we describe a mutant HPV16 L2 protein (HPV16 L2-R302/5A) that traffics pseudogenome to the trans-Golgi network (TGN) but fails to egress. Our data provide further evidence that HPV16 traffics through the TGN and demonstrates that L2 is essential for TGN egress. Furthermore, we show that cyclophilin activity is required for the L2/DNA complex to be transported to the TGN which is accompanied by a reduced L1 protein levels. - Highlights: • mNLS mutant HPV16 L2 protein traffics pseudogenome to the TGN but fails to egress. • Cyclophilin activity is required for trafficking of the L2/DNA complex to the TGN. • Majority of L1 protein is shed from the L2/DNA complex prior to reaching the TGN.

  7. 10 Ways to Recruit Teachers.

    Science.gov (United States)

    Stewart, Daisy

    1999-01-01

    Suggestions for recruiting teachers are as follow: talk to teens, recruit from within, involve counselors, target uncertain students, network, build relationships with tech prep, enlist military personnel, recruit extension agents, contact outplacement and employment services, and use distance-learning methods. (JOW)

  8. Successful Teachers Practice Perpetual Learning

    Science.gov (United States)

    Main, Marisa

    2007-01-01

    Successful teaching involves continuous learning, stimulation, motivation, and networking with other art educators. To help art teachers improve themselves, SchoolArts magazine recently organized the Folk Art Traditions and Beyond Seminar at Ghost Ranch in Santa Fe. In this article, the author describes the highlights of the Folk Art Traditions…

  9. 10 Ways to Recruit Teachers.

    Science.gov (United States)

    Stewart, Daisy

    1999-01-01

    Suggestions for recruiting teachers are as follow: talk to teens, recruit from within, involve counselors, target uncertain students, network, build relationships with tech prep, enlist military personnel, recruit extension agents, contact outplacement and employment services, and use distance-learning methods. (JOW)

  10. Social Networking Goes to School

    Science.gov (United States)

    Davis, Michelle R.

    2010-01-01

    Just a few years ago, social networking meant little more to educators than the headache of determining whether to penalize students for inappropriate activities captured on Facebook or MySpace. Now, teachers and students have an array of social-networking sites and tools--from Ning to VoiceThread and Second Life--to draw on for such serious uses…

  11. Ancient genomics.

    Science.gov (United States)

    Der Sarkissian, Clio; Allentoft, Morten E; Ávila-Arcos, María C; Barnett, Ross; Campos, Paula F; Cappellini, Enrico; Ermini, Luca; Fernández, Ruth; da Fonseca, Rute; Ginolhac, Aurélien; Hansen, Anders J; Jónsson, Hákon; Korneliussen, Thorfinn; Margaryan, Ashot; Martin, Michael D; Moreno-Mayar, J Víctor; Raghavan, Maanasa; Rasmussen, Morten; Velasco, Marcela Sandoval; Schroeder, Hannes; Schubert, Mikkel; Seguin-Orlando, Andaine; Wales, Nathan; Gilbert, M Thomas P; Willerslev, Eske; Orlando, Ludovic

    2015-01-19

    The past decade has witnessed a revolution in ancient DNA (aDNA) research. Although the field's focus was previously limited to mitochondrial DNA and a few nuclear markers, whole genome sequences from the deep past can now be retrieved. This breakthrough is tightly connected to the massive sequence throughput of next generation sequencing platforms and the ability to target short and degraded DNA molecules. Many ancient specimens previously unsuitable for DNA analyses because of extensive degradation can now successfully be used as source materials. Additionally, the analytical power obtained by increasing the number of sequence reads to billions effectively means that contamination issues that have haunted aDNA research for decades, particularly in human studies, can now be efficiently and confidently quantified. At present, whole genomes have been sequenced from ancient anatomically modern humans, archaic hominins, ancient pathogens and megafaunal species. Those have revealed important functional and phenotypic information, as well as unexpected adaptation, migration and admixture patterns. As such, the field of aDNA has entered the new era of genomics and has provided valuable information when testing specific hypotheses related to the past.

  12. Visualization for genomics: the Microbial Genome Viewer.

    NARCIS (Netherlands)

    Kerkhoven, R.; Enckevort, F.H.J. van; Boekhorst, J.; Molenaar, D.; Siezen, R.J.

    2004-01-01

    SUMMARY: A Web-based visualization tool, the Microbial Genome Viewer, is presented that allows the user to combine complex genomic data in a highly interactive way. This Web tool enables the interactive generation of chromosome wheels and linear genome maps from genome annotation data stored in a My

  13. The function genomics study

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    @@ Genomics is a biology term appeared ten years ago, used to describe the researches of genomic mapping, sequencing, and structure analysis, etc. Genomics, the first journal for publishing papers on genomics research was born in 1986. In the past decade, the concept of genomics has been widely accepted by scientists who are engaging in biology research. Meanwhile, the research scope of genomics has been extended continuously, from simple gene mapping and sequencing to function genomics study. To reflect the change, genomics is divided into two parts now, the structure genomics and the function genomics.

  14. Teacher agency

    DEFF Research Database (Denmark)

    Priestley, M.; Biesta, G.; Robinson, Sarah

    2015-01-01

    of the contexts within which teachers work – for example accountability mechanisms and other forms of output regulation of teachers’ work – leading to engagement with policy that is often instrumental and blighted by unintended consequences. In the chapter, we illustrate how a detailed understanding of teacher...

  15. Teacher Absenteeism.

    Science.gov (United States)

    Pohl, James M.

    2001-01-01

    Nationwide, there are several innovative approaches to substitute teacher staffing issues, including: increased substitute teacher pay and enlistment of local college students to substitute at least 3 days per week in exchange for tuition help and a guaranteed job after graduation. Incentive programs for low absenteeism rates are a good way to…

  16. Peer Coaching: Teachers Supporting Teachers.

    Science.gov (United States)

    Donegan, Mary M.; Ostrosky, Michaelene M.; Fowler, Susan A.

    2000-01-01

    This article describes peer coaching as a method for teacher improvement and offers guidelines for establishing a peer coaching program for early childhood and early childhood special education teachers and related services professionals. It also identifies common problems and possible solutions of peer coaching programs. Sample forms for use in…

  17. 师生暴力网络媒体报道研究%A Study on Network Media Reports of Student-Teacher Violence

    Institute of Scientific and Technical Information of China (English)

    杨汝军; 鞠玉翠

    2011-01-01

    师生暴力事件频频发生,网络媒体的相关报道与评论拓宽了言路,呈现出多样的话语方式,但专业声音的不足和深度剖析的缺乏使得网络报道的正面引领作用未能得到很好的发挥。在批评师德沦丧和教育弊端的同时,需要认清师生面临的现实困境,唤起师生对生命的基本尊重,更好地发挥网络媒体的积极作用。%Student-teacher violence happens frequently, and more chance to report and comment it is offered by internet. But the reports have not functioned well enough, because of the deficiency of professional and deep comments To make the internet reports functio

  18. Teacher agency:

    DEFF Research Database (Denmark)

    Robinson, Sarah; Priestley, Mark; Biesta, Gert

    2015-01-01

    The concept of teacher agency has emerged in recent literature as an alternative means of understanding how teachers might enact practice and engage with policy (e.g. Lasky, 2005; Leander & Osbourne, 2008; Ketelaar et al., 2012; Priestley, Biesta & Robinson, 2013). But what is agency? Agency...... remains an inexact and poorly conceptualised construct in much of the literature, where it is often not clear whether the term refers to an individual capacity of teachers to act agentically or to an emergent ‘ecological’ phenomenon dependent upon the quality of individuals’ engagement...... with their environments (Biesta & Tedder, 2007). In this chapter, we outline the latter conception of agency, developing a conceptual model for teacher agency that emphasizes the temporal and relational dimension of the achievement of agency. Why does this matter? Recent curriculum policy in many countries heralds a [re...

  19. Biology teachers

    African Journals Online (AJOL)

    Mathematics, Science and Biology teachers code switch when they teach. ... (by constantly translating back and forth), and argue for a 'separation approach' ..... for the classroom, only 3 students did not give an answer to this open-ended.

  20. Genome minimization method based on metabolic network analysis and its application to Escherichia coli%一种基于代谢网络分析最小化基因组的方法及其在大肠杆菌中的应用

    Institute of Scientific and Technical Information of China (English)

    汤彬彩; 郝彤; 袁倩倩; 陈涛; 马红武

    2013-01-01

    最小生命体的合成是合成生物学研究的重要方向.最小化基因组的同时而又不对细胞生长产生影响是代谢工程研究的一个重要目标.文中提出了一种从基因组尺度代谢网络模型出发,通过零通量反应删除及对非必需基因组合删除计算获得基因组最小化代谢网络模型的方法,利用该方法简化了大肠杆菌经典代谢网络模型iAF1260,由起始的1 260个基因简化得到了312个基因,而最优生物质生成速率保持不变.基因组最小化代谢网络模型预测了在细胞正常生长的前提下包含最少基因的代谢途径,为大肠杆菌获得最小基因组的湿实验设计提供了重要参考.%The minimum life is one of the most important research topics in synthetic biology.Minimizing a genome while at the same time maintaining an optimal growth of the cells is one of the important research objectives in metabolic engineering.Here we propose a genome minimization method based on genome scale metabolic network analysis.The metabolic network is minimized by first deleting the zero flux reactions from flux variability analysis,and then by repeatedly calculating the optimal growth rates after combinatorial deletion of the non-essential genes in the reduced network.We applied this method to the classic E.coli metabolic network model---iAF1260 and successfully reduced the number of genes in the model from 1 260 to 312 while maintaining the optimal growth rate unaffected.We also analyzed the metabolic pathways in the network with the minimized number of genes.The results provide some guidance for the design of wet experiments to obtain an E.coli minimal genome.

  1. Effective Teachers

    Directory of Open Access Journals (Sweden)

    Beverly A. King Miller

    2015-09-01

    Full Text Available This article focuses on the educational strategies that can be used to support female students of African descent in their persistence in science, technology, engineering, and mathematics (STEM education and careers. STEM careers have historically been White male and White female dominated, which has yielded an underrepresentation of those of African descent. Drawing from a grounded qualitative case study, the data used for this article share the responses of Afro-Caribbean females in STEM who have immigrated to the United States from the country of Panama. As Latinas, they are representative of the changing face in the American educational system—bilingual, multicultural, and of African descent. The strategies offered reflect their own teaching practices, their former teachers, or experiences with their children’s teachers. What emerged were descriptions of four strategies and behaviors of effective teachers that align with Ladson-Billings’s culturally relevant pedagogy and Gay’s culturally responsive teaching. Included in the findings are the high standards and expectations embodied by effective teachers that serve to positively inspire their students. Culturally responsive teachers create an atmosphere of learning that supports academic success, conveying their belief in their students’ ability based upon their own reflectivity. As the U.S. educational system continues to become multilingual and multicultural, there is need for strategies for the successful inclusion and progression of students in STEM educational pathways and careers. This will occur as teachers challenge themselves to be the agents of change in the lives of their students.

  2. Genome-wide Reconstruction of OxyR and SoxRS Transcriptional Regulatory Networks under Oxidative Stress in Escherichia coli K-12 MG1655

    DEFF Research Database (Denmark)

    Seo, Sang Woo; Kim, Donghyuk; Szubin, Richard;

    2015-01-01

    Three transcription factors (TFs), OxyR, SoxR, and SoxS, play a critical role in transcriptional regulation of the defense system for oxidative stress in bacteria. However, their full genome-wide regulatory potential is unknown. Here, we perform a genome-scale reconstruction of the OxyR, SoxR, an...

  3. How to Activate Teachers through Teacher Evaluation?

    Science.gov (United States)

    Tuytens, Melissa; Devos, Geert

    2014-01-01

    There is a general doubt on whether teacher evaluation can contribute to teachers' professional development. Recently, standards-based teacher evaluation has been introduced in many countries to improve teaching practice. This study wants to investigate which teacher evaluation procedural, leadership, and teacher characteristics can stimulate…

  4. Genome cartography: charting the apicomplexan genome.

    Science.gov (United States)

    Kissinger, Jessica C; DeBarry, Jeremy

    2011-08-01

    Genes reside in particular genomic contexts that can be mapped at many levels. Historically, 'genetic maps' were used primarily to locate genes. Recent technological advances in the determination of genome sequences have made the analysis and comparison of whole genomes possible and increasingly tractable. What do we see if we shift our focus from gene content (the 'inventory' of genes contained within a genome) to the composition and organization of a genome? This review examines what has been learned about the evolution of the apicomplexan genome as well as the significance and impact of genomic location on our understanding of the eukaryotic genome and parasite biology. Copyright © 2011 Elsevier Ltd. All rights reserved.

  5. Learning Networks, Networked Learning

    NARCIS (Netherlands)

    Sloep, Peter

    2011-01-01

    Sloep, P. B. (2011). Learning Networks, Networked Learning. Presentation at Annual Assembly of the European Society for the Systemic Innovation of Education - ESSIE. May, 27, 2011, Leuven, Belgium: Open University in the Netherlands.

  6. Learning Networks, Networked Learning

    NARCIS (Netherlands)

    Sloep, Peter; Berlanga, Adriana

    2010-01-01

    Sloep, P. B., & Berlanga, A. J. (2011). Learning Networks, Networked Learning [Redes de Aprendizaje, Aprendizaje en Red]. Comunicar, XIX(37), 55-63. Retrieved from http://dx.doi.org/10.3916/C37-2011-02-05

  7. Learning Networks, Networked Learning

    NARCIS (Netherlands)

    Sloep, Peter; Berlanga, Adriana

    2010-01-01

    Sloep, P. B., & Berlanga, A. J. (2011). Learning Networks, Networked Learning [Redes de Aprendizaje, Aprendizaje en Red]. Comunicar, XIX(37), 55-63. Retrieved from http://dx.doi.org/10.3916/C37-2011-02-05

  8. Modeling genomic regulatory networks with big data.

    Science.gov (United States)

    Bolouri, Hamid

    2014-05-01

    High-throughput sequencing, large-scale data generation projects, and web-based cloud computing are changing how computational biology is performed, who performs it, and what biological insights it can deliver. I review here the latest developments in available data, methods, and software, focusing on the modeling and analysis of the gene regulatory interactions in cells. Three key findings are: (i) although sophisticated computational resources are increasingly available to bench biologists, tailored ongoing education is necessary to avoid the erroneous use of these resources. (ii) Current models of the regulation of gene expression are far too simplistic and need updating. (iii) Integrative computational analysis of large-scale datasets is becoming a fundamental component of molecular biology. I discuss current and near-term opportunities and challenges related to these three points.

  9. Plant Genome Duplication Database.

    Science.gov (United States)

    Lee, Tae-Ho; Kim, Junah; Robertson, Jon S; Paterson, Andrew H

    2017-01-01

    Genome duplication, widespread in flowering plants, is a driving force in evolution. Genome alignments between/within genomes facilitate identification of homologous regions and individual genes to investigate evolutionary consequences of genome duplication. PGDD (the Plant Genome Duplication Database), a public web service database, provides intra- or interplant genome alignment information. At present, PGDD contains information for 47 plants whose genome sequences have been released. Here, we describe methods for identification and estimation of dates of genome duplication and speciation by functions of PGDD.The database is freely available at http://chibba.agtec.uga.edu/duplication/.

  10. 基于网络社交的高校教师科研互动管理平台的研究与设计%University Teacher Research Interaction Management Platform Study&Design Based on Networking Social

    Institute of Scientific and Technical Information of China (English)

    李玉军; 李梦洁; 鲍永瀚; 王方坊

    2011-01-01

    本文阐述了基于开源Wiki、Blog项目和内容管理系统CMS开发包,研究和设计基于网络社交的高校科研管理互动品台,利用oracle数据库的设计方法及其实现的关键技术,解决系统中对论文、项目成果、科研奖励、合作、科研人员、校级课题等管理的要求。根据网络社交关系理论建立比较稳定的学术合作关系,以促进高校教师学术科研能力的提高,保持高校教师与相关学科的前沿保持一致。在次基础上,将一些未涉密的科研项目及其内容予以公开,以吸引更多的学者、学生关注和到本校学习和工作,促进本校学术科研和教学研究氛围的形成。%This paper describes the open source-based Wiki,Blog and content management system CMS project development package,research and design web-based social interaction of university research management product platform,using oracle database design and implementation of key technologies,to solve the system of papers,project results,research awards,co-researchers,university issues and other management requirements.According to network theory to establish a relatively stable social relations of academic cooperation,to promote the research capacity of university teachers to improve academic,university teachers and related disciplines to maintain the leading edge consistent.In the second,based on secret research projects that are not its contents be made public,in order to attract more scholars and students concerned and to the school learning and work to promote academic research and university teaching and research atmosphere of the formation.

  11. Complex network perspective on structure and function of Staphylococcus aureus metabolic network

    Indian Academy of Sciences (India)

    L Ying; D W Ding

    2013-02-01

    With remarkable advances in reconstruction of genome-scale metabolic networks, uncovering complex network structure and function from these networks is becoming one of the most important topics in system biology. This work aims at studying the structure and function of Staphylococcus aureus (S. aureus) metabolic network by complex network methods. We first generated a metabolite graph from the recently reconstructed high-quality S. aureus metabolic network model. Then, based on `bow tie' structure character, we explain and discuss the global structure of S. aureus metabolic network. The functional significance, global structural properties, modularity and centrality analysis of giant strong component in S. aureus metabolic networks are studied.

  12. Rodent malaria parasites : genome organization & comparative genomics

    NARCIS (Netherlands)

    Kooij, Taco W.A.

    2006-01-01

    The aim of the studies described in this thesis was to investigate the genome organization of rodent malaria parasites (RMPs) and compare the organization and gene content of the genomes of RMPs and the human malaria parasite P. falciparum. The release of the complete genome sequence of P. falciparu

  13. Rodent malaria parasites : genome organization & comparative genomics

    NARCIS (Netherlands)

    Kooij, Taco W.A.

    2006-01-01

    The aim of the studies described in this thesis was to investigate the genome organization of rodent malaria parasites (RMPs) and compare the organization and gene content of the genomes of RMPs and the human malaria parasite P. falciparum. The release of the complete genome sequence of P.

  14. Network fingerprint: a knowledge-based characterization of biomedical networks

    Science.gov (United States)

    Cui, Xiuliang; He, Haochen; He, Fuchu; Wang, Shengqi; Li, Fei; Bo, Xiaochen

    2015-01-01

    It can be difficult for biomedical researchers to understand complex molecular networks due to their unfamiliarity with the mathematical concepts employed. To represent molecular networks with clear meanings and familiar forms for biomedical researchers, we introduce a knowledge-based computational framework to decipher biomedical networks by making systematic comparisons to well-studied “basic networks”. A biomedical network is characterized as a spectrum-like vector called “network fingerprint”, which contains similarities to basic networks. This knowledge-based multidimensional characterization provides a more intuitive way to decipher molecular networks, especially for large-scale network comparisons and clustering analyses. As an example, we extracted network fingerprints of 44 disease networks in the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. The comparisons among the network fingerprints of disease networks revealed informative disease-disease and disease-signaling pathway associations, illustrating that the network fingerprinting framework will lead to new approaches for better understanding of biomedical networks. PMID:26307246

  15. Learners in dialogue. Teacher experise and learning in the context of genetic testing

    OpenAIRE

    2011-01-01

    Learners in Dialogue; this thesis aims at the exploration of teacher expertise for teachers who want to teach genetics in the context of genetic testing and at finding ways to foster teacher learning concerning this expertise. Recent developments in the field of genomics will impact the daily practice of biology teachers who teach genetics in secondary education. A special focus was on moral reasoning because reasoning and decision-making based on genetic information in such test situations i...

  16. A network of networks.

    Science.gov (United States)

    Iedema, Rick; Verma, Raj; Wutzke, Sonia; Lyons, Nigel; McCaughan, Brian

    2017-04-10

    Purpose To further our insight into the role of networks in health system reform, the purpose of this paper is to investigate how one agency, the NSW Agency for Clinical Innovation (ACI), and the multiple networks and enabling resources that it encompasses, govern, manage and extend the potential of networks for healthcare practice improvement. Design/methodology/approach This is a case study investigation which took place over ten months through the first author's participation in network activities and discussions with the agency's staff about their main objectives, challenges and achievements, and with selected services around the state of New South Wales to understand the agency's implementation and large system transformation activities. Findings The paper demonstrates that ACI accommodates multiple networks whose oversight structures, self-organisation and systems change approaches combined in dynamic ways, effectively yield a diversity of network governances. Further, ACI bears out a paradox of "centralised decentralisation", co-locating agents of innovation with networks of implementation and evaluation expertise. This arrangement strengthens and legitimates the role of the strategic hybrid - the healthcare professional in pursuit of change and improvement, and enhances their influence and impact on the wider system. Research limitations/implications While focussing the case study on one agency only, this study is unique as it highlights inter-network connections. Contributing to the literature on network governance, this paper identifies ACI as a "network of networks" through which resources, expectations and stakeholder dynamics are dynamically and flexibly mediated and enhanced. Practical implications The co-location of and dynamic interaction among clinical networks may create synergies among networks, nurture "strategic hybrids", and enhance the impact of network activities on health system reform. Social implications Network governance requires more

  17. Implementing e-network-supported inquiry learning in science

    DEFF Research Database (Denmark)

    Williams, John; Cowie, Bronwen; Khoo, Elaine

    2013-01-01

    The successful implementation of electronically networked (e-networked) tools to support an inquiry-learning approach in secondary science classrooms is dependent on a range of factors spread between teachers, schools, and students. The teacher must have a clear understanding of the nature of inq...

  18. Teaming up: Linking collaboration networks, collective efficacy, and student achievement

    NARCIS (Netherlands)

    Moolenaar, Nienke M.; Sleegers, Peter J.C.; Daly, Alan J.

    2012-01-01

    Improving student achievement through teacher collaboration networks is a current focus of schools in many countries. Yet, empirical evidence on the relationship between teacher networks and student achievement and mechanisms that may explain this relationship is limited. This study examined the rel

  19. Network integration; Network integration

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    2000-02-29

    Together with the rapid spread of information network, a shift is seen from the conventional original network to the system based on the standard network also in the monitoring/control field. In the network construction in the monitoring/control field, Meidensha uses internet/intranet technology and multimedia technology and is working on the construction of multimedia network into which sound/image/data are integrated. The paper indicates an example of constructing a large-scale network based on the ATM network constructed by the company and an example of constructing a network based on the Ethernet. The image system is coded/decoded by MPEG2 encoder/decoder and delivered by ATM switch. The sound system is connected to ATM network via CLAD and constructs PBX net. The data system which intercommunicates among terminals interconnects routers on ATM network using TCP/IP. Further, it copes with difficulties such as cable cut by making a detour for the ATM network. (translated by NEDO)

  20. Teacher Lore. Fastback 477.

    Science.gov (United States)

    Schwarz, Gretchen

    This booklet offers a brief history of teacher lore, examines its theoretical bases, and summarizes its professional value, discussing how preservice teachers, inservice teachers, and others can use teacher lore for professional development. Teacher lore, or teacher narrative, includes fiction and nonfiction, oral storytelling, print, film,…