Comparing Mycobacterium tuberculosis genomes using genome topology networks.

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Jiang, Jianping; Gu, Jianlei; Zhang, Liang; Zhang, Chenyi; Deng, Xiao; Dou, Tonghai; Zhao, Guoping; Zhou, Yan

2015-02-14

Over the last decade, emerging research methods, such as comparative genomic analysis and phylogenetic study, have yielded new insights into genotypes and phenotypes of closely related bacterial strains. Several findings have revealed that genomic structural variations (SVs), including gene gain/loss, gene duplication and genome rearrangement, can lead to different phenotypes among strains, and an investigation of genes affected by SVs may extend our knowledge of the relationships between SVs and phenotypes in microbes, especially in pathogenic bacteria. In this work, we introduce a 'Genome Topology Network' (GTN) method based on gene homology and gene locations to analyze genomic SVs and perform phylogenetic analysis. Furthermore, the concept of 'unfixed ortholog' has been proposed, whose members are affected by SVs in genome topology among close species. To improve the precision of 'unfixed ortholog' recognition, a strategy to detect annotation differences and complete gene annotation was applied. To assess the GTN method, a set of thirteen complete M. tuberculosis genomes was analyzed as a case study. GTNs with two different gene homology-assigning methods were built, the Clusters of Orthologous Groups (COG) method and the orthoMCL clustering method, and two phylogenetic trees were constructed accordingly, which may provide additional insights into whole genome-based phylogenetic analysis. We obtained 24 unfixable COG groups, of which most members were related to immunogenicity and drug resistance, such as PPE-repeat proteins (COG5651) and transcriptional regulator TetR gene family members (COG1309). The GTN method has been implemented in PERL and released on our website. The tool can be downloaded from http://homepage.fudan.edu.cn/zhouyan/gtn/ , and allows re-annotating the 'lost' genes among closely related genomes, analyzing genes affected by SVs, and performing phylogenetic analysis. With this tool, many immunogenic-related and drug resistance-related genes

Seeing Eye to Eye: Predicting Teacher-Student Agreement on Classroom Social Networks

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Neal, Jennifer Watling; Cappella, Elise; Wagner, Caroline; Atkins, Marc S.

2010-01-01

This study examines the association between classroom characteristics and teacher-student agreement in perceptions of students’ classroom peer networks. Social network, peer nomination, and observational data were collected from a sample of second through fourth grade teachers (N=33) and students (N=669) in 33 classrooms across five high poverty urban schools. Results demonstrate that variation in teacher-student agreement on the structure of students’ peer networks can be explained, in part, by developmental factors and classroom characteristics. Developmental increases in network density partially mediated the positive relationship between grade level and teacher-student agreement. Larger class sizes and higher levels of normative aggressive behavior resulted in lower levels of teacher-student agreement. Teachers’ levels of classroom organization had mixed influences, with behavior management negatively predicting agreement, and productivity positively predicting agreement. These results underscore the importance of the classroom context in shaping teacher and student perceptions of peer networks. PMID:21666768

Integration of genomic information with biological networks using Cytoscape.

Science.gov (United States)

Bauer-Mehren, Anna

2013-01-01

Cytoscape is an open-source software for visualizing, analyzing, and modeling biological networks. This chapter explains how to use Cytoscape to analyze the functional effect of sequence variations in the context of biological networks such as protein-protein interaction networks and signaling pathways. The chapter is divided into five parts: (1) obtaining information about the functional effect of sequence variation in a Cytoscape readable format, (2) loading and displaying different types of biological networks in Cytoscape, (3) integrating the genomic information (SNPs and mutations) with the biological networks, and (4) analyzing the effect of the genomic perturbation onto the network structure using Cytoscape built-in functions. Finally, we briefly outline how the integrated data can help in building mathematical network models for analyzing the effect of the sequence variation onto the dynamics of the biological system. Each part is illustrated by step-by-step instructions on an example use case and visualized by many screenshots and figures.

PARTNERS IN LEARNING NETWORK FOR UKRAINIAN TEACHERS

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K. Sereda

2011-05-01

Full Text Available The network «Partners in Learning Network» is presented in the article – the Ukrainian segment of global educational community. PILN is created with support of the Microsoft company for teachers who use information communication technology in their professional work. The PILN's purpose and value for Ukrainian teachers, for their professional dialogue and collaboration are described in the article. Functions of PILN's communities for teacher’s cooperation, the joint decision of questions and an exchange of ideas and of technique, teaching tools for increase of level of ICT introduction in educational process are described.

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...

Networking and professional development among teachers of Early Childhood Education

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Rosario Mérida Serrano

2017-06-01

Full Text Available This paper evaluates the professional development of 24 teachers involved in the Early Childhood Education-CPD Centre for Teachers-University Network ([blind review]. Collaborative research-action is carried out with teachers and pupils of Early Childhood Education, an adviser from the Continuing Professional Development (CPD Centre for Teachers, researchers, and teacher training undergraduates from the University of [blind review] ([blind review]. Taking a qualitative approach, through interviews, focus groups, and research journals, the benefits obtained by the teachers through their involvement in the [blind review] network are identified: (1 Their colleagues offer them emotional support and provide examples of good practices; (2 The teacher training undergraduates provide technological resources and the possibility of calmly observing what goes on in the classroom; (3 The researchers foster processes of reflection about practice and endorse the validity of the Project Approach; (4 The adviser provides continuing professional development.

Enumeration of smallest intervention strategies in genome-scale metabolic networks.

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Axel von Kamp

2014-01-01

Full Text Available One ultimate goal of metabolic network modeling is the rational redesign of biochemical networks to optimize the production of certain compounds by cellular systems. Although several constraint-based optimization techniques have been developed for this purpose, methods for systematic enumeration of intervention strategies in genome-scale metabolic networks are still lacking. In principle, Minimal Cut Sets (MCSs; inclusion-minimal combinations of reaction or gene deletions that lead to the fulfilment of a given intervention goal provide an exhaustive enumeration approach. However, their disadvantage is the combinatorial explosion in larger networks and the requirement to compute first the elementary modes (EMs which itself is impractical in genome-scale networks. We present MCSEnumerator, a new method for effective enumeration of the smallest MCSs (with fewest interventions in genome-scale metabolic network models. For this we combine two approaches, namely (i the mapping of MCSs to EMs in a dual network, and (ii a modified algorithm by which shortest EMs can be effectively determined in large networks. In this way, we can identify the smallest MCSs by calculating the shortest EMs in the dual network. Realistic application examples demonstrate that our algorithm is able to list thousands of the most efficient intervention strategies in genome-scale networks for various intervention problems. For instance, for the first time we could enumerate all synthetic lethals in E.coli with combinations of up to 5 reactions. We also applied the new algorithm exemplarily to compute strain designs for growth-coupled synthesis of different products (ethanol, fumarate, serine by E.coli. We found numerous new engineering strategies partially requiring less knockouts and guaranteeing higher product yields (even without the assumption of optimal growth than reported previously. The strength of the presented approach is that smallest intervention strategies can be

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

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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

Building an Online Community: Student Teachers' Perceptions on the Advantages of Using Social Networking Services in a Teacher Education Program

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Habibi, Akhmad; Mukinin, Amirul; Riyanto, Yatim; Prasohjo, Lantip Diat; Sulistiyo, Urip; Sofwan, Muhammad; Saudagar, Ferdiaz

2018-01-01

This inquiry examined student teachers' perceptions on the advantages of using Social Networking Services (SNS) in an English teacher education program at a public university in Jambi, Indonesia to ease the communication, supervision, discussion, and report submissions between supervisors and student teachers. The networking types included in the…

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

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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…

An Integrative Bioinformatics Framework for Genome-scale Multiple Level Network Reconstruction of Rice

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Liu Lili

2013-06-01

Full Text Available Understanding how metabolic reactions translate the genome of an organism into its phenotype is a grand challenge in biology. Genome-wide association studies (GWAS statistically connect genotypes to phenotypes, without any recourse to known molecular interactions, whereas a molecular mechanistic description ties gene function to phenotype through gene regulatory networks (GRNs, protein-protein interactions (PPIs and molecular pathways. Integration of different regulatory information levels of an organism is expected to provide a good way for mapping genotypes to phenotypes. However, the lack of curated metabolic model of rice is blocking the exploration of genome-scale multi-level network reconstruction. Here, we have merged GRNs, PPIs and genome-scale metabolic networks (GSMNs approaches into a single framework for rice via omics’ regulatory information reconstruction and integration. Firstly, we reconstructed a genome-scale metabolic model, containing 4,462 function genes, 2,986 metabolites involved in 3,316 reactions, and compartmentalized into ten subcellular locations. Furthermore, 90,358 pairs of protein-protein interactions, 662,936 pairs of gene regulations and 1,763 microRNA-target interactions were integrated into the metabolic model. Eventually, a database was developped for systematically storing and retrieving the genome-scale multi-level network of rice. This provides a reference for understanding genotype-phenotype relationship of rice, and for analysis of its molecular regulatory network.

Reconstructing transcriptional regulatory networks through genomics data

OpenAIRE

Sun, Ning; Zhao, Hongyu

2009-01-01

One central problem in biology is to understand how gene expression is regulated under different conditions. Microarray gene expression data and other high throughput data have made it possible to dissect transcriptional regulatory networks at the genomics level. Owing to the very large number of genes that need to be studied, the relatively small number of data sets available, the noise in the data and the different natures of the distinct data types, network inference presents great challen...

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

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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. © 2013 Wiley Periodicals, Inc.

Teacher Professionalization in the Age of Social Networking Sites

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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…

Pre-Service Teachers' and Teacher-Educators' Experiences and Attitudes toward Using Social Networking Sites for Collaborative Learning

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Soomro, Kamal Ahmed; Kale, Ugur; Zai, Sajid Yousuf

2014-01-01

Extensive use of social networking sites by students and teachers makes educators and researchers to think whether they can be incorporated in instructional process to facilitate students' learning. This survey-based study records and examines Pakistani pre-service teachers' and teacher-educators' current uses of Facebook, and their attitudes…

Combinatorial aspects of genome rearrangements and haplotype networks

OpenAIRE

Labarre , Anthony

2008-01-01

The dissertation covers two problems motivated by computational biology: genome rearrangements, and haplotype networks. Genome rearrangement problems are a particular case of edit distance problems, where one seeks to transform two given objects into one another using as few operations as possible, with the additional constraint that the set of allowed operations is fixed beforehand; we are also interested in computing the corresponding distances between those objects, i.e. merely computing t...

Metabolite coupling in genome-scale metabolic networks

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Palsson Bernhard Ø

2006-03-01

Full Text Available Abstract Background Biochemically detailed stoichiometric matrices have now been reconstructed for various bacteria, yeast, and for the human cardiac mitochondrion based on genomic and proteomic data. These networks have been manually curated based on legacy data and elementally and charge balanced. Comparative analysis of these well curated networks is now possible. Pairs of metabolites often appear together in several network reactions, linking them topologically. This co-occurrence of pairs of metabolites in metabolic reactions is termed herein "metabolite coupling." These metabolite pairs can be directly computed from the stoichiometric matrix, S. Metabolite coupling is derived from the matrix ŜŜT, whose off-diagonal elements indicate the number of reactions in which any two metabolites participate together, where Ŝ is the binary form of S. Results Metabolite coupling in the studied networks was found to be dominated by a relatively small group of highly interacting pairs of metabolites. As would be expected, metabolites with high individual metabolite connectivity also tended to be those with the highest metabolite coupling, as the most connected metabolites couple more often. For metabolite pairs that are not highly coupled, we show that the number of reactions a pair of metabolites shares across a metabolic network closely approximates a line on a log-log scale. We also show that the preferential coupling of two metabolites with each other is spread across the spectrum of metabolites and is not unique to the most connected metabolites. We provide a measure for determining which metabolite pairs couple more often than would be expected based on their individual connectivity in the network and show that these metabolites often derive their principal biological functions from existing in pairs. Thus, analysis of metabolite coupling provides information beyond that which is found from studying the individual connectivity of individual

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

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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

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

DEFF Research Database (Denmark)

Baber, Sikunder Ali

" and shows how a number of professional associations have become as networks of learning to encourage the continuing professional education of both pre-service and in-service teachers in the context of Pakistan. A case of the Mathematics Association of Pakistan (MAP) as a Network of Learning is presented....... 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......Importance of the professional development of teachers has been recognized and research has contributed greatly in terms of proposing variety of approaches for the development of teachers,both pre-service and in-service. Among them, networking among teachers, teacher educators,curriculum developers...

Practical Value of Food Pathogen Traceability through Building a Whole-Genome Sequencing Network and Database.

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Allard, Marc W; Strain, Errol; Melka, David; Bunning, Kelly; Musser, Steven M; Brown, Eric W; Timme, Ruth

2016-08-01

The FDA has created a United States-based open-source whole-genome sequencing network of state, federal, international, and commercial partners. The GenomeTrakr network represents a first-of-its-kind distributed genomic food shield for characterizing and tracing foodborne outbreak pathogens back to their sources. The GenomeTrakr network is leading investigations of outbreaks of foodborne illnesses and compliance actions with more accurate and rapid recalls of contaminated foods as well as more effective monitoring of preventive controls for food manufacturing environments. An expanded network would serve to provide an international rapid surveillance system for pathogen traceback, which is critical to support an effective public health response to bacterial outbreaks. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

Reconsidering the concept of nursing as handled by Japanese nursing teachers : The nursing network formed by innovative nursing teachers

OpenAIRE

山梨, 八重子; ヤマナシ, ヤエコ; Yamanashi, Yaeko

2017-01-01

The purpose of this paper is to clarify the originality of nursing given by nursing teachers. From the results, I concluded that, taking nursing from the viewpoint of Kant education, all teachers including the nursing teachers, and nursing teachers make teachers and others to bring out the important nursing skills in themselves. Further the network formed from these interactions is the origin of the nursing provided by nursing teachers.

Parallel or convergent evolution in human population genomic data revealed by genotype networks

OpenAIRE

Vahdati, Ali R; Wagner, Andreas

2016-01-01

Background Genotype networks are representations of genetic variation data that are complementary to phylogenetic trees. A genotype network is a graph whose nodes are genotypes (DNA sequences) with the same broadly defined phenotype. Two nodes are connected if they differ in some minimal way, e.g., in a single nucleotide. Results We analyze human genome variation data from the 1,000 genomes project, and construct haploid genotype (haplotype) networks for 12,235 protein coding genes. The struc...

Unethical Behaviours Preservice Teachers Encounter on Social Networks

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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…

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

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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…

Primary School Teachers and Outdoor Education: Varying Levels of Teacher Leadership in Informal Networks of Peers

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Hovardas, Tasos

2016-01-01

The study concentrated on an area in Greece with a multiplicity of sites for outdoor education. Informal networks of teachers were detected through a snowball technique and data were collected by means of a questionnaire and semi-structured interviews. A typology was first enriched to account for teacher interaction. This typology was then…

A Survey of K-12 Teachers' Utilization of Social Networks as a Professional Resource

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Hunter, Leah J.; Hall, Cristin M.

2018-01-01

Teachers are increasingly using social networks, including social media and other Internet applications, to look for educational resources. This study shares results from a survey examining patterns of social network application use among K-12 teachers in the United States. A sample of 154 teachers (18 males, 136 females) in the United States…

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

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Van Waes, Sara; Van den Bossche, Piet; Moolenaar, Nienke M.|info:eu-repo/dai/nl/304352802; 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

Genome-scale reconstruction of the Saccharomyces cerevisiae metabolic network

DEFF Research Database (Denmark)

Förster, Jochen; Famili, I.; Fu, P.

2003-01-01

The metabolic network in the yeast Saccharomyces cerevisiae was reconstructed using currently available genomic, biochemical, and physiological information. The metabolic reactions were compartmentalized between the cytosol and the mitochondria, and transport steps between the compartments...

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

Predictive genomics: A cancer hallmark network framework for predicting tumor clinical phenotypes using genome sequencing data

OpenAIRE

Wang, Edwin; Zaman, Naif; Mcgee, Shauna; Milanese, Jean-Sébastien; Masoudi-Nejad, Ali; O'Connor, Maureen

2014-01-01

We discuss a cancer hallmark network framework for modelling genome-sequencing data to predict cancer clonal evolution and associated clinical phenotypes. Strategies of using this framework in conjunction with genome sequencing data in an attempt to predict personalized drug targets, drug resistance, and metastasis for a cancer patient, as well as cancer risks for a healthy individual are discussed. Accurate prediction of cancer clonal evolution and clinical phenotypes will have substantial i...

Parallel or convergent evolution in human population genomic data revealed by genotype networks.

Science.gov (United States)

R Vahdati, Ali; Wagner, Andreas

2016-08-02

Genotype networks are representations of genetic variation data that are complementary to phylogenetic trees. A genotype network is a graph whose nodes are genotypes (DNA sequences) with the same broadly defined phenotype. Two nodes are connected if they differ in some minimal way, e.g., in a single nucleotide. We analyze human genome variation data from the 1,000 genomes project, and construct haploid genotype (haplotype) networks for 12,235 protein coding genes. The structure of these networks varies widely among genes, indicating different patterns of variation despite a shared evolutionary history. We focus on those genes whose genotype networks show many cycles, which can indicate homoplasy, i.e., parallel or convergent evolution, on the sequence level. For 42 genes, the observed number of cycles is so large that it cannot be explained by either chance homoplasy or recombination. When analyzing possible explanations, we discovered evidence for positive selection in 21 of these genes and, in addition, a potential role for constrained variation and purifying selection. Balancing selection plays at most a small role. The 42 genes with excess cycles are enriched in functions related to immunity and response to pathogens. Genotype networks are representations of genetic variation data that can help understand unusual patterns of genomic variation.

Integration of expression data in genome-scale metabolic network reconstructions

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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.

Network Biomarkers of Bladder Cancer Based on a Genome-Wide Genetic and Epigenetic Network Derived from Next-Generation Sequencing Data.

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Li, Cheng-Wei; Chen, Bor-Sen

2016-01-01

Epigenetic and microRNA (miRNA) regulation are associated with carcinogenesis and the development of cancer. By using the available omics data, including those from next-generation sequencing (NGS), genome-wide methylation profiling, candidate integrated genetic and epigenetic network (IGEN) analysis, and drug response genome-wide microarray analysis, we constructed an IGEN system based on three coupling regression models that characterize protein-protein interaction networks (PPINs), gene regulatory networks (GRNs), miRNA regulatory networks (MRNs), and epigenetic regulatory networks (ERNs). By applying system identification method and principal genome-wide network projection (PGNP) to IGEN analysis, we identified the core network biomarkers to investigate bladder carcinogenic mechanisms and design multiple drug combinations for treating bladder cancer with minimal side-effects. The progression of DNA repair and cell proliferation in stage 1 bladder cancer ultimately results not only in the derepression of miR-200a and miR-200b but also in the regulation of the TNF pathway to metastasis-related genes or proteins, cell proliferation, and DNA repair in stage 4 bladder cancer. We designed a multiple drug combination comprising gefitinib, estradiol, yohimbine, and fulvestrant for treating stage 1 bladder cancer with minimal side-effects, and another multiple drug combination comprising gefitinib, estradiol, chlorpromazine, and LY294002 for treating stage 4 bladder cancer with minimal side-effects.

Microarray Data Processing Techniques for Genome-Scale Network Inference from Large Public Repositories.

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Chockalingam, Sriram; Aluru, Maneesha; Aluru, Srinivas

2016-09-19

Pre-processing of microarray data is a well-studied problem. Furthermore, all popular platforms come with their own recommended best practices for differential analysis of genes. However, for genome-scale network inference using microarray data collected from large public repositories, these methods filter out a considerable number of genes. This is primarily due to the effects of aggregating a diverse array of experiments with different technical and biological scenarios. Here we introduce a pre-processing pipeline suitable for inferring genome-scale gene networks from large microarray datasets. We show that partitioning of the available microarray datasets according to biological relevance into tissue- and process-specific categories significantly extends the limits of downstream network construction. We demonstrate the effectiveness of our pre-processing pipeline by inferring genome-scale networks for the model plant Arabidopsis thaliana using two different construction methods and a collection of 11,760 Affymetrix ATH1 microarray chips. Our pre-processing pipeline and the datasets used in this paper are made available at http://alurulab.cc.gatech.edu/microarray-pp.

Optimal knockout strategies in genome-scale metabolic networks using particle swarm optimization.

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Nair, Govind; Jungreuthmayer, Christian; Zanghellini, Jürgen

2017-02-01

Knockout strategies, particularly the concept of constrained minimal cut sets (cMCSs), are an important part of the arsenal of tools used in manipulating metabolic networks. Given a specific design, cMCSs can be calculated even in genome-scale networks. We would however like to find not only the optimal intervention strategy for a given design but the best possible design too. Our solution (PSOMCS) is to use particle swarm optimization (PSO) along with the direct calculation of cMCSs from the stoichiometric matrix to obtain optimal designs satisfying multiple objectives. To illustrate the working of PSOMCS, we apply it to a toy network. Next we show its superiority by comparing its performance against other comparable methods on a medium sized E. coli core metabolic network. PSOMCS not only finds solutions comparable to previously published results but also it is orders of magnitude faster. Finally, we use PSOMCS to predict knockouts satisfying multiple objectives in a genome-scale metabolic model of E. coli and compare it with OptKnock and RobustKnock. PSOMCS finds competitive knockout strategies and designs compared to other current methods and is in some cases significantly faster. It can be used in identifying knockouts which will force optimal desired behaviors in large and genome scale metabolic networks. It will be even more useful as larger metabolic models of industrially relevant organisms become available.

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

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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…

An evaluation of a professional learning network for computer science teachers

Science.gov (United States)

Cutts, Quintin; Robertson, Judy; Donaldson, Peter; O'Donnell, Laurie

2017-01-01

This paper describes and evaluates aspects of a professional development programme for existing CS teachers in secondary schools (PLAN C) which was designed to support teachers at a time of substantial curricular change. The paper's particular focus is on the formation of a teacher professional development network across several hundred teachers and a wide geographical area. Evidence from a series of observations and teacher surveys over a two-year period is analysed with respect to the project's programme theory in order to illustrate not only whether it worked as intended, by why. Results indicate that the PLAN C design has been successful in increasing teachers' professional confidence and appears to have catalysed powerful change in attitudes to learning. Presentation of challenging pedagogical content knowledge and conceptual frameworks, high-quality teacher-led professional dialogue, along with the space for reflection and classroom trials, triggered examination of the teachers' own current practices.

Assembling networks of microbial genomes using linear programming.

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Holloway, Catherine; Beiko, Robert G

2010-11-20

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. 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. 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.

Teacher Candidates' Opinions Regarding Instructional and Safe Use of Social Networks and Internet Addiction Risk Levels

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Enis Fasli

2018-05-01

Full Text Available In conjunction with the development and advancement of internet technologies, social networking sites have created a socialization environment. Instructors point out that these tools must be used as an active and different form of communication with students. Also, participation of the students through social networking sites should be encouraged. However, the risk of internet addiction has also become widespread on the increase use of social networks. The aim of this research is to “determine the opinions of teacher candidates on the use of social networking sites in education and Internet addiction risk levels”. General survey model was used in this research in order to determine the opinions regarding social networks of teacher candidates from the education faculties in the Turkish Republic of Northern Cyprus and figure out their internet addiction risk levels. “Use of Social Networks in Education Scale” developed by Ozturk and Akgun and “Internet Addiction Test” developed by Young were used in this research. According to the results of the study, it has been figured out that almost all of the teacher candidates think that sharing information through social networking sites is either partially safe or not safe. Besides, most of the teacher candidates feel anxious about keeping information as confidential. Another important result is that teacher candidates are internet users at an average level. It also shows that they might spend too much time on the internet however they use internet in a controlled manner.

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

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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.

Social Network Analysis: A Simple but Powerful Tool for Identifying Teacher Leaders

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Smith, P. Sean; Trygstad, Peggy J.; Hayes, Meredith L.

2018-01-01

Instructional teacher leadership is central to a vision of distributed leadership. However, identifying instructional teacher leaders can be a daunting task, particularly for administrators who find themselves either newly appointed or faced with high staff turnover. This article describes the use of social network analysis (SNA), a simple but…

How the Formal and Informal Social Networks of Special Education Teachers Shape Their Practice

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Wong, Amie

2016-01-01

Teacher collaboration has long been considered to be a vehicle for educational improvement. Meanwhile, some teachers find themselves disconnected and isolated from their colleagues, in part due to the roles they serve in schools. There is little research information on the social networks of special education teachers. This study is intended to…

Birth of scale-free molecular networks and the number of distinct DNA and protein domains per genome.

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Rzhetsky, A; Gomez, S M

2001-10-01

Current growth in the field of genomics has provided a number of exciting approaches to the modeling of evolutionary mechanisms within the genome. Separately, dynamical and statistical analyses of networks such as the World Wide Web and the social interactions existing between humans have shown that these networks can exhibit common fractal properties-including the property of being scale-free. This work attempts to bridge these two fields and demonstrate that the fractal properties of molecular networks are linked to the fractal properties of their underlying genomes. We suggest a stochastic model capable of describing the evolutionary growth of metabolic or signal-transduction networks. This model generates networks that share important statistical properties (so-called scale-free behavior) with real molecular networks. In particular, the frequency of vertices connected to exactly k other vertices follows a power-law distribution. The shape of this distribution remains invariant to changes in network scale: a small subgraph has the same distribution as the complete graph from which it is derived. Furthermore, the model correctly predicts that the frequencies of distinct DNA and protein domains also follow a power-law distribution. Finally, the model leads to a simple equation linking the total number of different DNA and protein domains in a genome with both the total number of genes and the overall network topology. MatLab (MathWorks, Inc.) programs described in this manuscript are available on request from the authors. ar345@columbia.edu.

The Global Genome Biodiversity Network (GGBN) Data Standard specification

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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 PMID:27694206

The effect of electronic networking on preservice elementary teachers' science teaching self-efficacy and attitude towards science teaching

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Mathew, Nishi Mary

Preservice elementary teachers' science teaching efficacy and attitude towards science teaching are important determinants of whether and how they will teach science in their classrooms. Preservice teachers' understanding of science and science teaching experiences have an impact on their beliefs about their ability to teach science. This study had a quasi-experimental pretest-posttest control group design (N = 60). Preservice elementary teachers in this study were networked through the Internet (using e-mail, newsgroups, listserv, world wide web access and electronic mentoring) during their science methods class and student practicum. Electronic networking provides a social context in which to learn collaboratively, share and reflect upon science teaching experiences and practices, conduct tele-research effectively, and to meet the demands of student teaching through peer support. It was hoped that the activities over the electronic networks would provide them with positive and helpful science learning and teaching experiences. Self-efficacy was measured using a 23-item Likert scale instrument, the Science Teaching Efficacy Belief Instrument, Form-B (STEBI-B). Attitude towards science teaching was measured using the Revised Science Attitude Scale (RSAS). Analysis of covariance was used to analyze the data, with pretest scores as the covariate. Findings of this study revealed that prospective elementary teachers in the electronically networked group had better science teaching efficacy and personal science teaching efficacy as compared to the non-networked group of preservice elementary teachers. The science teaching outcome expectancy of prospective elementary teachers in the networked group was not greater than that of the prospective teachers in the non-networked group (at p < 0.05). Attitude towards science teaching was not significantly affected by networking. However, this is surmised to be related to the duration of the study. Information about the

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

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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…

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

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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…

BiologicalNetworks 2.0 - an integrative view of genome biology data

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Ponomarenko Julia

2010-12-01

Full Text Available Abstract Background A significant problem in the study of mechanisms of an organism's development is the elucidation of interrelated factors which are making an impact on the different levels of the organism, such as genes, biological molecules, cells, and cell systems. Numerous sources of heterogeneous data which exist for these subsystems are still not integrated sufficiently enough to give researchers a straightforward opportunity to analyze them together in the same frame of study. Systematic application of data integration methods is also hampered by a multitude of such factors as the orthogonal nature of the integrated data and naming problems. Results Here we report on a new version of BiologicalNetworks, a research environment for the integral visualization and analysis of heterogeneous biological data. BiologicalNetworks can be queried for properties of thousands of different types of biological entities (genes/proteins, promoters, COGs, pathways, binding sites, and other and their relations (interactions, co-expression, co-citations, and other. The system includes the build-pathways infrastructure for molecular interactions/relations and module discovery in high-throughput experiments. Also implemented in BiologicalNetworks are the Integrated Genome Viewer and Comparative Genomics Browser applications, which allow for the search and analysis of gene regulatory regions and their conservation in multiple species in conjunction with molecular pathways/networks, experimental data and functional annotations. Conclusions The new release of BiologicalNetworks together with its back-end database introduces extensive functionality for a more efficient integrated multi-level analysis of microarray, sequence, regulatory, and other data. BiologicalNetworks is freely available at http://www.biologicalnetworks.org.

A social network perspective on teacher collaboration in schools: Theory, methodology, and applications

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Moolenaar, Nienke

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

Networking and distance learning for teachers: A classification of possibilities

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Collis, Betty

1995-01-01

Computer based communication technologies, or what could be more conveniently called networking, are bringing new possibilities into teacher education in many different ways. As with distance education more generally they can facilitate flexibility in time and place of learning, but the range of

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

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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…

Teacher Agency in Educational Reform: Lessons from Social Networks Research

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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…

Conversational Networking: Why the Teacher Gets Most of the Lines.

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Thompson, Diane P.

1988-01-01

Describes the use of the English Natural Form Instruction (ENFI) computer conferencing system to teach language skills in college writing classes at Northern Virginia Community College. Highlights include local area networks; discourse processing; interactive writing; the teacher's role; textual analysis of writing by two classes; and other…

Funding Opportunity: Genomic Data Centers

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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,

Beyond the Labor Market Paradigm: A Social Network Perspective on Teacher Recruitment and Retention

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Baker-Doyle, Kira

2010-01-01

This article identifies limits of the dominant labor market perspective (LMP) in research on teacher recruitment and retention and describes how research that incorporates a social network perspective (SNP) can contribute to the knowledge base and development of teacher education, staffing, and professional development approaches. A discussion of…

The social fabric of elementary schools: a network typology of social interaction among teachers

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Moolenaar, N.M.; Sleegers, P.J.C.; Karsten, S.; Daly, A.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

The social fabric of elementary schools: A network typology of social interaction among teachers

NARCIS (Netherlands)

Moolenaar, Nienke; Sleegers, P.J.C.; Karsten, Sjoerd; Daly, Alan J.; Daly, A.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

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

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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

Our teacher likes you, so I like you: A social network approach to social referencing.

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Hendrickx, Marloes M H G; Mainhard, Tim; Boor-Klip, Henrike J; Brekelmans, Mieke

2017-08-01

A teacher is a social referent for peer liking and disliking when students adjust their evaluations of a peer based on their perceptions of teacher liking and disliking for this peer. The present study investigated social referencing as an intra-individual process that occurs over time, using stochastic actor-oriented modeling with RSiena. The co-evolution of peer-perceived teacher liking and disliking networks with peer liking and disliking networks was analyzed in 52 fifth-grade classes in the Netherlands, with 1370 students (M age =10.60). Results showed that when a student viewed the teacher to like a peer, this student would also like this peer. Regarding disliking, there was a stronger effect in the opposite direction, indicating that students' disliking a peer increased the likelihood that they would view the peer as disliked by the teacher as well. In sum, partial evidence for social referencing as an intra-individual process was found. For teachers this implies that the cues they provide regarding their liking of a student, and not necessarily their disliking, may affect individual peers' liking of this student. Copyright © 2017 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Genome-Scale Reconstruction of the Human Astrocyte Metabolic Network

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Mart?n-Jim?nez, Cynthia A.; Salazar-Barreto, Diego; Barreto, George E.; Gonz?lez, Janneth

2017-01-01

Astrocytes are the most abundant cells of the central nervous system; they have a predominant role in maintaining brain metabolism. In this sense, abnormal metabolic states have been found in different neuropathological diseases. Determination of metabolic states of astrocytes is difficult to model using current experimental approaches given the high number of reactions and metabolites present. Thus, genome-scale metabolic networks derived from transcriptomic data can be used as a framework t...

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...... was extensively validated against published flux data, and flux distribution values were found to correlate well between simulations and experiments. The split pathway of the lysine synthesis pathway of C. glutamicum was investigated, and it was found that the direct dehydrogenase variant gave a higher lysine...... yield than the alternative succinyl pathway at high lysine production rates. The NADPH demand of the network was not found to be critical for lysine production until lysine yields exceeded 55% (mmol lysine (mmol glucose)(-1)). The model was validated during growth on the organic acids acetate...

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

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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.

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

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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…

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

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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.

Developing a common framework for evaluating the implementation of genomic medicine interventions in clinical care: the IGNITE Network's Common Measures Working Group.

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Orlando, Lori A; Sperber, Nina R; Voils, Corrine; Nichols, Marshall; Myers, Rachel A; Wu, R Ryanne; Rakhra-Burris, Tejinder; Levy, Kenneth D; Levy, Mia; Pollin, Toni I; Guan, Yue; Horowitz, Carol R; Ramos, Michelle; Kimmel, Stephen E; McDonough, Caitrin W; Madden, Ebony B; Damschroder, Laura J

2018-06-01

PurposeImplementation research provides a structure for evaluating the clinical integration of genomic medicine interventions. This paper describes the Implementing Genomics in Practice (IGNITE) Network's efforts to promote (i) a broader understanding of genomic medicine implementation research and (ii) the sharing of knowledge generated in the network.MethodsTo facilitate this goal, the IGNITE Network Common Measures Working Group (CMG) members adopted the Consolidated Framework for Implementation Research (CFIR) to guide its approach to identifying constructs and measures relevant to evaluating genomic medicine as a whole, standardizing data collection across projects, and combining data in a centralized resource for cross-network analyses.ResultsCMG identified 10 high-priority CFIR constructs as important for genomic medicine. Of those, eight did not have standardized measurement instruments. Therefore, we developed four survey tools to address this gap. In addition, we identified seven high-priority constructs related to patients, families, and communities that did not map to CFIR constructs. Both sets of constructs were combined to create a draft genomic medicine implementation model.ConclusionWe developed processes to identify constructs deemed valuable for genomic medicine implementation and codified them in a model. These resources are freely available to facilitate knowledge generation and sharing across the field.

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…

Vocational Education Teachers' Personal Network at School as a Resource for Innovative Work Behaviour

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Messmann, Gerhard; Mulder, Regina H.; Palonen, Tuire

2018-01-01

Purpose: This paper aims to investigate the role of characteristics of vocational education teachers' personal network at the workplace for determining the resources that enable them to cope with innovation-related demands at work. Design/methodology/approach: A survey study with 48 vocational education teachers is carried out. Social network…

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

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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.

Building an Online Community: Student Teachers’ Perceptions on the Advantages of Using Social Networking Services in A Teacher Education Program

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Akhmad HABIBI

2018-01-01

Full Text Available This inquiry examined student teachers' perceptions on the advantages of using Social Networking Services (SNS in an English teacher education program at a public university in Jambi, Indonesia to ease the communication, supervision, discussion, and report submissions between supervisors and student teachers. The networking types included in the program are Whatsapp, Telegram, Email, and Google Form. The method of the research was qualitative through using focus group discussions as the technique of collecting data involving forty-two student teachers. We organized our analysis and discussion around their perceptions and the contexts in which the advantages they perceived emerge. The analyses of the texts revealed that two salient themes with their sub-themes related to the advantages of using Social Networking Services (SNS in a teacher education program were social interaction (peer discussion and platform to interact with supervisors or lecturers and learning motivation and experience supports (self-directed learning, promotes critical thinking, content engagement. Some pedagogical and social implications are also discussed.

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

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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.

Environmental versatility promotes modularity in genome-scale metabolic networks.

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Samal, Areejit; Wagner, Andreas; Martin, Olivier C

2011-08-24

The ubiquity of modules in biological networks may result from an evolutionary benefit of a modular organization. For instance, modularity may increase the rate of adaptive evolution, because modules can be easily combined into new arrangements that may benefit their carrier. Conversely, modularity may emerge as a by-product of some trait. We here ask whether this last scenario may play a role in genome-scale metabolic networks that need to sustain life in one or more chemical environments. For such networks, we define a network module as a maximal set of reactions that are fully coupled, i.e., whose fluxes can only vary in fixed proportions. This definition overcomes limitations of purely graph based analyses of metabolism by exploiting the functional links between reactions. We call a metabolic network viable in a given chemical environment if it can synthesize all of an organism's biomass compounds from nutrients in this environment. An organism's metabolism is highly versatile if it can sustain life in many different chemical environments. We here ask whether versatility affects the modularity of metabolic networks. Using recently developed techniques to randomly sample large numbers of viable metabolic networks from a vast space of metabolic networks, we use flux balance analysis to study in silico metabolic networks that differ in their versatility. We find that highly versatile networks are also highly modular. They contain more modules and more reactions that are organized into modules. Most or all reactions in a module are associated with the same biochemical pathways. Modules that arise in highly versatile networks generally involve reactions that process nutrients or closely related chemicals. We also observe that the metabolism of E. coli is significantly more modular than even our most versatile networks. Our work shows that modularity in metabolic networks can be a by-product of functional constraints, e.g., the need to sustain life in multiple

Environmental versatility promotes modularity in genome-scale metabolic networks

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Wagner Andreas

2011-08-01

Full Text Available Abstract Background The ubiquity of modules in biological networks may result from an evolutionary benefit of a modular organization. For instance, modularity may increase the rate of adaptive evolution, because modules can be easily combined into new arrangements that may benefit their carrier. Conversely, modularity may emerge as a by-product of some trait. We here ask whether this last scenario may play a role in genome-scale metabolic networks that need to sustain life in one or more chemical environments. For such networks, we define a network module as a maximal set of reactions that are fully coupled, i.e., whose fluxes can only vary in fixed proportions. This definition overcomes limitations of purely graph based analyses of metabolism by exploiting the functional links between reactions. We call a metabolic network viable in a given chemical environment if it can synthesize all of an organism's biomass compounds from nutrients in this environment. An organism's metabolism is highly versatile if it can sustain life in many different chemical environments. We here ask whether versatility affects the modularity of metabolic networks. Results Using recently developed techniques to randomly sample large numbers of viable metabolic networks from a vast space of metabolic networks, we use flux balance analysis to study in silico metabolic networks that differ in their versatility. We find that highly versatile networks are also highly modular. They contain more modules and more reactions that are organized into modules. Most or all reactions in a module are associated with the same biochemical pathways. Modules that arise in highly versatile networks generally involve reactions that process nutrients or closely related chemicals. We also observe that the metabolism of E. coli is significantly more modular than even our most versatile networks. Conclusions Our work shows that modularity in metabolic networks can be a by-product of functional

Teacher Training through Social Networking Platforms: A Case Study on Facebook

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Çevik, Yasemin Demiraslan; Çelik, Serkan; Haslaman, Tülin

2014-01-01

Numerous studies have attempted to explain the role of social networking platforms within educational environments, though none of them has reported on their potential for enhancing professional development in education. The purpose of this qualitative research was to explore the reflections of prospective teachers who were assigned to design and…

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

IdentiCS – Identification of coding sequence and in silico reconstruction of the metabolic network directly from unannotated low-coverage bacterial genome sequence

Directory of Open Access Journals (Sweden)

Zeng An-Ping

2004-08-01

Full Text Available Abstract Background A necessary step for a genome level analysis of the cellular metabolism is the in silico reconstruction of the metabolic network from genome sequences. The available methods are mainly based on the annotation of genome sequences including two successive steps, the prediction of coding sequences (CDS and their function assignment. The annotation process takes time. The available methods often encounter difficulties when dealing with unfinished error-containing genomic sequence. Results In this work a fast method is proposed to use unannotated genome sequence for predicting CDSs and for an in silico reconstruction of metabolic networks. Instead of using predicted genes or CDSs to query public databases, entries from public DNA or protein databases are used as queries to search a local database of the unannotated genome sequence to predict CDSs. Functions are assigned to the predicted CDSs simultaneously. The well-annotated genome of Salmonella typhimurium LT2 is used as an example to demonstrate the applicability of the method. 97.7% of the CDSs in the original annotation are correctly identified. The use of SWISS-PROT-TrEMBL databases resulted in an identification of 98.9% of CDSs that have EC-numbers in the published annotation. Furthermore, two versions of sequences of the bacterium Klebsiella pneumoniae with different genome coverage (3.9 and 7.9 fold, respectively are examined. The results suggest that a 3.9-fold coverage of the bacterial genome could be sufficiently used for the in silico reconstruction of the metabolic network. Compared to other gene finding methods such as CRITICA our method is more suitable for exploiting sequences of low genome coverage. Based on the new method, a program called IdentiCS (Identification of Coding Sequences from Unfinished Genome Sequences is delivered that combines the identification of CDSs with the reconstruction, comparison and visualization of metabolic networks (free to download

Network Thermodynamic Curation of Human and Yeast Genome-Scale Metabolic Models

Science.gov (United States)

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

2014-01-01

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. PMID:25028891

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

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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.

PRED-CLASS: cascading neural networks for generalized protein classification and genome-wide applications.

Science.gov (United States)

Pasquier, C; Promponas, V J; Hamodrakas, S J

2001-08-15

A cascading system of hierarchical, artificial neural networks (named PRED-CLASS) is presented for the generalized classification of proteins into four distinct classes-transmembrane, fibrous, globular, and mixed-from information solely encoded in their amino acid sequences. The architecture of the individual component networks is kept very simple, reducing the number of free parameters (network synaptic weights) for faster training, improved generalization, and the avoidance of data overfitting. Capturing information from as few as 50 protein sequences spread among the four target classes (6 transmembrane, 10 fibrous, 13 globular, and 17 mixed), PRED-CLASS was able to obtain 371 correct predictions out of a set of 387 proteins (success rate approximately 96%) unambiguously assigned into one of the target classes. The application of PRED-CLASS to several test sets and complete proteomes of several organisms demonstrates that such a method could serve as a valuable tool in the annotation of genomic open reading frames with no functional assignment or as a preliminary step in fold recognition and ab initio structure prediction methods. Detailed results obtained for various data sets and completed genomes, along with a web sever running the PRED-CLASS algorithm, can be accessed over the World Wide Web at http://o2.biol.uoa.gr/PRED-CLASS.

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. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.

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

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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…

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

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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

The Power of the Network: Teach for America's Impact on the Deregulation of Teacher Education

Science.gov (United States)

Kretchmar, Kerry; Sondel, Beth; Ferrare, Joseph J.

2018-01-01

In this article, we illustrate the relationships between Teach For America (TFA) and the deregulation of university-based teacher education programs. We use policy network analysis to create a visual representation of TFA's connections to individuals, organizations, and private corporations who are working to shift the way teachers are prepared.…

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

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 self-concepts. We analyzed cross-sectional surveys of 929 9th-12th grade low-income minority adolescents in Los Angeles assessing self-concept, social networks, and 30-day use of alcohol, marijuana and other drugs. We performed generalized estimating equations, accounting for clustering at the school level and controlling for family and peer influences and contextual factors. We also tested whether self-concept-mediated associations between relationships with teachers or coaches and 30-day substance use. More perceived teacher support was associated with lower odds of marijuana and other drug use and better academic and behavioral self-concepts. Behavioral self-concept mediated the associations between teacher support and substance use. By facilitating relationships with adults and improving teachers' capacity to build supportive environments, schools may positively shape how adolescents see themselves, which might help reduce adolescent substance use. © 2016, American School Health Association.

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.

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.

Comprehensive Mapping of Pluripotent Stem Cell Metabolism Using Dynamic Genome-Scale Network Modeling

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Sriram Chandrasekaran

2017-12-01

Full Text Available Summary: Metabolism is an emerging stem cell hallmark tied to cell fate, pluripotency, and self-renewal, yet systems-level understanding of stem cell metabolism has been limited by the lack of genome-scale network models. Here, we develop a systems approach to integrate time-course metabolomics data with a computational model of metabolism to analyze the metabolic state of naive and primed murine pluripotent stem cells. Using this approach, we find that one-carbon metabolism involving phosphoglycerate dehydrogenase, folate synthesis, and nucleotide synthesis is a key pathway that differs between the two states, resulting in differential sensitivity to anti-folates. The model also predicts that the pluripotency factor Lin28 regulates this one-carbon metabolic pathway, which we validate using metabolomics data from Lin28-deficient cells. Moreover, we identify and validate metabolic reactions related to S-adenosyl-methionine production that can differentially impact histone methylation in naive and primed cells. Our network-based approach provides a framework for characterizing metabolic changes influencing pluripotency and cell fate. : Chandrasekaran et al. use computational modeling, metabolomics, and metabolic inhibitors to discover metabolic differences between various pluripotent stem cell states and infer their impact on stem cell fate decisions. Keywords: systems biology, stem cell biology, metabolism, genome-scale modeling, pluripotency, histone methylation, naive (ground state, primed state, cell fate, metabolic network

German MedicalTeachingNetwork (MDN) implementing national standards for teacher training.

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Lammerding-Koeppel, M; Ebert, T; Goerlitz, A; Karsten, G; Nounla, C; Schmidt, S; Stosch, C; Dieter, P

2016-01-01

An increasing demand for proof of professionalism in higher education strives for quality assurance (QA) and improvement in medical education. A wide range of teacher trainings is available to medical staff in Germany. Cross-institutional approval of individual certificates is usually a difficult and time consuming task for institutions. In case of non-acceptance it may hinder medical teachers in their professional mobility. The faculties of medicine aimed to develop a comprehensive national framework, to promote standards for formal faculty development programmes across institutions and to foster professionalization of medical teaching. Addressing the above challenges in a joint approach, the faculties set up the national MedicalTeacherNetwork (MDN). Great importance is attributed to work out nationally concerted standards for faculty development and an agreed-upon quality control process across Germany. Medical teachers benefit from these advantages due to portability of faculty development credentials from one faculty of medicine to another within the MDN system. The report outlines the process of setting up the MDN and the national faculty development programme in Germany. Success factors, strengths and limitations are discussed from an institutional, individual and general perspective. Faculties engaged in similar developments might be encouraged to transfer the MDN concept to their countries.

Blogging within a Social Networking Site as a Form of Literature Response in a Teacher Education Course

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Hutchison, Amy; Wang, Wei

2012-01-01

The purpose of this qualitative study was to document how pre-service teachers in a children's literature course experienced blogging on a social networking site as a form of literature response. Understanding how pre-service teachers experience these tools can inform the ways we instruct them to integrate Web 2.0 tools into their teaching.…

Construction and analysis of a genome-scale metabolic network for Bacillus licheniformis WX-02.

Science.gov (United States)

Guo, Jing; Zhang, Hong; Wang, Cheng; Chang, Ji-Wei; Chen, Ling-Ling

2016-05-01

We constructed the genome-scale metabolic network of Bacillus licheniformis (B. licheniformis) WX-02 by combining genomic annotation, high-throughput phenotype microarray (PM) experiments and literature-based metabolic information. The accuracy of the metabolic network was assessed by an OmniLog PM experiment. The final metabolic model iWX1009 contains 1009 genes, 1141 metabolites and 1762 reactions, and the predicted metabolic phenotypes showed an agreement rate of 76.8% with experimental PM data. In addition, key metabolic features such as growth yield, utilization of different substrates and essential genes were identified by flux balance analysis. A total of 195 essential genes were predicted from LB medium, among which 149 were verified with the experimental essential gene set of B. subtilis 168. With the removal of 5 reactions from the network, pathways for poly-γ-glutamic acid (γ-PGA) synthesis were optimized and the γ-PGA yield reached 83.8 mmol/h. Furthermore, the important metabolites and pathways related to γ-PGA synthesis and bacterium growth were comprehensively analyzed. The present study provides valuable clues for exploring the metabolisms and metabolic regulation of γ-PGA synthesis in B. licheniformis WX-02. Copyright © 2016 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.

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.

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.

Gymnasium network educational resource as a form of interactive communication of a teacher and a student

Directory of Open Access Journals (Sweden)

Sidorova N.N.

2017-08-01

Full Text Available this article presents the experience of the Surgut gymnasium «Laboratory Salahova» teachers in creating a network educational resource on various subjects. Developed course gives students and teachers an opportunity to increase the level of self-employment high-school students and to expand the distance learning in high school. The individual characteristics of every class are considered in the tasks, and this is an advantage of the course developed by the teachers of the gymnasium. The article gives examples of history lesson technological map with assignments and texts proposed for study and already-learned topic check.

Integration of Structural Dynamics and Molecular Evolution via Protein Interaction Networks: A New Era in Genomic Medicine

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

2016-01-01

Summary 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. PMID:26684487

Exploring Knowledge Processes Based on Teacher Research in a School-University Research Network of a Master's Program

Science.gov (United States)

Cornelissen, Frank; van Swet, Jacqueline; Beijaard, Douwe; Bergen, Theo

2013-01-01

School-university research networks aim at closer integration of research and practice by means of teacher research. Such practice-oriented research can benefit both schools and universities. This paper reports on a multiple-case study of five participants in a school-university research network in a Dutch master's program. The research question…

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…

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.

Switchgrass genomic diversity, ploidy, and evolution: novel insights from a network-based SNP discovery protocol.

Directory of Open Access Journals (Sweden)

Fei Lu

Full Text Available Switchgrass (Panicum virgatum L. is a perennial grass that has been designated as an herbaceous model biofuel crop for the United States of America. To facilitate accelerated breeding programs of switchgrass, we developed both an association panel and linkage populations for genome-wide association study (GWAS and genomic selection (GS. All of the 840 individuals were then genotyped using genotyping by sequencing (GBS, generating 350 GB of sequence in total. As a highly heterozygous polyploid (tetraploid and octoploid species lacking a reference genome, switchgrass is highly intractable with earlier methodologies of single nucleotide polymorphism (SNP discovery. To access the genetic diversity of species like switchgrass, we developed a SNP discovery pipeline based on a network approach called the Universal Network-Enabled Analysis Kit (UNEAK. Complexities that hinder single nucleotide polymorphism discovery, such as repeats, paralogs, and sequencing errors, are easily resolved with UNEAK. Here, 1.2 million putative SNPs were discovered in a diverse collection of primarily upland, northern-adapted switchgrass populations. Further analysis of this data set revealed the fundamentally diploid nature of tetraploid switchgrass. Taking advantage of the high conservation of genome structure between switchgrass and foxtail millet (Setaria italica (L. P. Beauv., two parent-specific, synteny-based, ultra high-density linkage maps containing a total of 88,217 SNPs were constructed. Also, our results showed clear patterns of isolation-by-distance and isolation-by-ploidy in natural populations of switchgrass. Phylogenetic analysis supported a general south-to-north migration path of switchgrass. In addition, this analysis suggested that upland tetraploid arose from upland octoploid. All together, this study provides unparalleled insights into the diversity, genomic complexity, population structure, phylogeny, phylogeography, ploidy, and evolutionary dynamics

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.

Vision from next generation sequencing: multi-dimensional genome-wide analysis for producing gene regulatory networks underlying retinal development, aging and disease.

Science.gov (United States)

Yang, Hyun-Jin; Ratnapriya, Rinki; Cogliati, Tiziana; Kim, Jung-Woong; Swaroop, Anand

2015-05-01

Genomics and genetics have invaded all aspects of biology and medicine, opening uncharted territory for scientific exploration. The definition of "gene" itself has become ambiguous, and the central dogma is continuously being revised and expanded. Computational biology and computational medicine are no longer intellectual domains of the chosen few. Next generation sequencing (NGS) technology, together with novel methods of pattern recognition and network analyses, has revolutionized the way we think about fundamental biological mechanisms and cellular pathways. In this review, we discuss NGS-based genome-wide approaches that can provide deeper insights into retinal development, aging and disease pathogenesis. We first focus on gene regulatory networks (GRNs) that govern the differentiation of retinal photoreceptors and modulate adaptive response during aging. Then, we discuss NGS technology in the context of retinal disease and develop a vision for therapies based on network biology. We should emphasize that basic strategies for network construction and analyses can be transported to any tissue or cell type. We believe that specific and uniform guidelines are required for generation of genome, transcriptome and epigenome data to facilitate comparative analysis and integration of multi-dimensional data sets, and for constructing networks underlying complex biological processes. As cellular homeostasis and organismal survival are dependent on gene-gene and gene-environment interactions, we believe that network-based biology will provide the foundation for deciphering disease mechanisms and discovering novel drug targets for retinal neurodegenerative diseases. Published by Elsevier Ltd.

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

NARCIS (Netherlands)

Schaub, Franz X.; Dhankani, Varsha; Berger, Ashton C.; Trivedi, Mihir; Richardson, Anne B.; Shaw, Reid; Zhao, Wei; Zhang, Xiaoyang; Ventura, Andrea; Liu, Yuexin; Ayer, Donald E.; Hurlin, Peter J.; Cherniack, Andrew D.; Eisenman, Robert N.; Bernard, Brady; Grandori, Carla; Caesar-Johnson, Samantha J.; Demchok, John A.; Felau, Ina; Kasapi, Melpomeni; Ferguson, Martin L.; Hutter, Carolyn M.; Sofia, Heidi J.; Tarnuzzer, Roy; Wang, Zhining; Yang, Liming; Zenklusen, Jean C.; Zhang, Jiashan (Julia); Chudamani, Sudha; Liu, Jia; Lolla, Laxmi; Naresh, Rashi; Pihl, Todd; Sun, Qiang; Wan, Yunhu; Wu, Ye; Cho, Juok; DeFreitas, Timothy; Frazer, Scott; Gehlenborg, Nils; Getz, Gad; Heiman, David I.; Kim, Jaegil; Lawrence, Michael S.; Lin, Pei; Meier, Sam; Noble, Michael S.; Saksena, Gordon; Voet, Doug; Zhang, Hailei; Bernard, Brady; Chambwe, Nyasha; Dhankani, Varsha; Knijnenburg, Theo; Kramer, Roger; Leinonen, Kalle; Liu, Yuexin; Miller, Michael; Reynolds, Sheila; Shmulevich, Ilya; Thorsson, Vesteinn; Zhang, Wei; Akbani, Rehan; Broom, Bradley M.; Hegde, Apurva M.; Ju, Zhenlin; Kanchi, Rupa S.; Korkut, Anil; Li, Jun; Liang, Han; Ling, Shiyun; Liu, Wenbin; Lu, Yiling; Mills, Gordon B.; Ng, Kwok Shing; Rao, Arvind; Ryan, Michael; Wang, Jing; Weinstein, John N.; Zhang, Jiexin; Abeshouse, Adam; Armenia, Joshua; Chakravarty, Debyani; Chatila, Walid K.; de Bruijn, Ino; Gao, Jianjiong; Gross, Benjamin E.; Heins, Zachary J.; Kundra, Ritika; La, Konnor; Ladanyi, Marc; Luna, Augustin; Nissan, Moriah G.; Ochoa, Angelica; Phillips, Sarah M.; Reznik, Ed; Sanchez-Vega, Francisco; Sander, Chris; Schultz, Nikolaus; Sheridan, Robert; Sumer, S. Onur; Sun, Yichao; Taylor, Barry S.; Wang, Jioajiao; Zhang, Hongxin; Anur, Pavana; Peto, Myron; Spellman, Paul; Benz, Christopher; Stuart, Joshua M.; Wong, Christopher K.; Yau, Christina; Hayes, D. Neil; Parker, Joel S.; Wilkerson, Matthew D.; Ally, Adrian; Balasundaram, Miruna; Bowlby, Reanne; Brooks, Denise; Carlsen, Rebecca; Chuah, Eric; Dhalla, Noreen; Holt, Robert; Jones, Steven J.M.; Kasaian, Katayoon; Lee, Darlene; Ma, Yussanne; Marra, Marco A.; Mayo, Michael; Moore, Richard A.; Mungall, Andrew J.; Mungall, Karen; Robertson, A. Gordon; Sadeghi, Sara; Schein, Jacqueline E.; Sipahimalani, Payal; Tam, Angela; Thiessen, Nina; Tse, Kane; Wong, Tina; Berger, Ashton C.; Beroukhim, Rameen; Cherniack, Andrew D.; Cibulskis, Carrie; Gabriel, Stacey B.; Gao, Galen F.; Ha, Gavin; Meyerson, Matthew; Schumacher, Steven E.; Shih, Juliann; Kucherlapati, Melanie H.; Kucherlapati, Raju S.; Baylin, Stephen; Cope, Leslie; Danilova, Ludmila; Bootwalla, Moiz S.; Lai, Phillip H.; Maglinte, Dennis T.; Van Den Berg, David J.; Weisenberger, Daniel J.; Auman, J. Todd; Balu, Saianand; Bodenheimer, Tom; Fan, Cheng; Hoadley, Katherine A.; Hoyle, Alan P.; Jefferys, Stuart R.; Jones, Corbin D.; Meng, Shaowu; Mieczkowski, Piotr A.; Mose, Lisle E.; Perou, Amy H.; Perou, Charles M.; Roach, Jeffrey; Shi, Yan; Simons, Janae V.; Skelly, Tara; Soloway, Matthew G.; Tan, Donghui; Veluvolu, Umadevi; Fan, Huihui; Hinoue, Toshinori; Laird, Peter W.; Shen, Hui; Zhou, Wanding; Bellair, Michelle; Chang, Kyle; Covington, Kyle; Creighton, Chad J.; Dinh, Huyen; Doddapaneni, Harsha Vardhan; Donehower, Lawrence A.; Drummond, Jennifer; Gibbs, Richard A.; Glenn, Robert; Hale, Walker; Han, Yi; Hu, Jianhong; Korchina, Viktoriya; Lee, Sandra; Lewis, Lora; Li, Wei; Liu, Xiuping; Morgan, Margaret; Morton, Donna; Muzny, Donna; Santibanez, Jireh; Sheth, Margi; Shinbrot, Eve; Wang, Linghua; Wang, Min; Wheeler, David A.; Xi, Liu; Zhao, Fengmei; Hess, Julian; Appelbaum, Elizabeth L.; Bailey, Matthew; Cordes, Matthew G.; Ding, Li; Fronick, Catrina C.; Fulton, Lucinda A.; Fulton, Robert S.; Kandoth, Cyriac; Mardis, Elaine R.; McLellan, Michael D.; Miller, Christopher A.; Schmidt, Heather K.; Wilson, Richard K.; Crain, Daniel; Curley, Erin; Gardner, Johanna; Lau, Kevin; Mallery, David; Morris, Scott; Paulauskis, Joseph; Penny, Robert; Shelton, Candace; Shelton, Troy; Sherman, Mark; Thompson, Eric; Yena, Peggy; Bowen, Jay; Gastier-Foster, Julie M.; Gerken, Mark; Leraas, Kristen M.; Lichtenberg, Tara M.; Ramirez, Nilsa C.; Wise, Lisa; Zmuda, Erik; Corcoran, Niall; Costello, Tony; Hovens, Christopher; Carvalho, Andre L.; de Carvalho, Ana C.; Fregnani, José H.; Longatto-Filho, Adhemar; Reis, Rui M.; Scapulatempo-Neto, Cristovam; Silveira, Henrique C.S.; Vidal, Daniel O.; Burnette, Andrew; Eschbacher, Jennifer; Hermes, Beth; Noss, Ardene; Singh, Rosy; Anderson, Matthew L.; Castro, Patricia D.; Ittmann, Michael; Huntsman, David; Kohl, Bernard; Le, Xuan; Thorp, Richard; Andry, Chris; Duffy, Elizabeth R.; Lyadov, Vladimir; Paklina, Oxana; Setdikova, Galiya; Shabunin, Alexey; Tavobilov, Mikhail; McPherson, Christopher; Warnick, Ronald; Berkowitz, Ross; Cramer, Daniel; Feltmate, Colleen; Horowitz, Neil; Kibel, Adam; Muto, Michael; Raut, Chandrajit P.; Malykh, Andrei; Barnholtz-Sloan, Jill S.; Barrett, Wendi; Devine, Karen; Fulop, Jordonna; Ostrom, Quinn T.; Shimmel, Kristen; Wolinsky, Yingli; Sloan, Andrew E.; De Rose, Agostino; Giuliante, Felice; Goodman, Marc; Karlan, Beth Y.; Hagedorn, Curt H.; Eckman, John; Harr, Jodi; Myers, Jerome; Tucker, Kelinda; Zach, Leigh Anne; Deyarmin, Brenda; Hu, Hai; Kvecher, Leonid; Larson, Caroline; Mural, Richard J.; Somiari, Stella; Vicha, Ales; Zelinka, Tomas; Bennett, Joseph; Iacocca, Mary; Rabeno, Brenda; Swanson, Patricia; Latour, Mathieu; Lacombe, Louis; Têtu, Bernard; Bergeron, Alain; McGraw, Mary; Staugaitis, Susan M.; Chabot, John; Hibshoosh, Hanina; Sepulveda, Antonia; Su, Tao; Wang, Timothy; Potapova, Olga; Voronina, Olga; Desjardins, Laurence; Mariani, Odette; Roman-Roman, Sergio; Sastre, Xavier; Stern, Marc Henri; Cheng, Feixiong; Signoretti, Sabina; Berchuck, Andrew; Bigner, Darell; Lipp, Eric; Marks, Jeffrey; McCall, Shannon; McLendon, Roger; Secord, Angeles; Sharp, Alexis; Behera, Madhusmita; Brat, Daniel J.; Chen, Amy; Delman, Keith; Force, Seth; Khuri, Fadlo; Magliocca, Kelly; Maithel, Shishir; Olson, Jeffrey J.; Owonikoko, Taofeek; Pickens, Alan; Ramalingam, Suresh; Shin, Dong M.; Sica, Gabriel; Van Meir, Erwin G.; Zhang, Hongzheng; Eijckenboom, Wil; Gillis, Ad; Korpershoek, Esther; Looijenga, Leendert; Oosterhuis, Wolter; Stoop, Hans; van Kessel, Kim E.; Zwarthoff, Ellen C.; Calatozzolo, Chiara; Cuppini, Lucia; Cuzzubbo, Stefania; DiMeco, Francesco; Finocchiaro, Gaetano; Mattei, Luca; Perin, Alessandro; Pollo, Bianca; Chen, Chu; Houck, John; Lohavanichbutr, Pawadee; Hartmann, Arndt; Stoehr, Christine; Stoehr, Robert; Taubert, Helge; Wach, Sven; Wullich, Bernd; Kycler, Witold; Murawa, Dawid; Wiznerowicz, Maciej; Chung, Ki; Edenfield, W. Jeffrey; Martin, Julie; Baudin, Eric; Bubley, Glenn; Bueno, Raphael; De Rienzo, Assunta; Richards, William G.; Kalkanis, Steven; Mikkelsen, Tom; Noushmehr, Houtan; Scarpace, Lisa; Girard, Nicolas; Aymerich, Marta; Campo, Elias; Giné, Eva; Guillermo, Armando López; Van Bang, Nguyen; Hanh, Phan Thi; Phu, Bui Duc; Tang, Yufang; Colman, Howard; Evason, Kimberley; Dottino, Peter R.; Martignetti, John A.; Gabra, Hani; Juhl, Hartmut; Akeredolu, Teniola; Stepa, Serghei; Hoon, Dave; Ahn, Keunsoo; Kang, Koo Jeong; Beuschlein, Felix; Breggia, Anne; Birrer, Michael; Bell, Debra; Borad, Mitesh; Bryce, Alan H.; Castle, Erik; Chandan, Vishal; Cheville, John; Copland, John A.; Farnell, Michael; Flotte, Thomas; Giama, Nasra; Ho, Thai; Kendrick, Michael; Kocher, Jean Pierre; Kopp, Karla; Moser, Catherine; Nagorney, David; O'Brien, Daniel; O'Neill, Brian Patrick; Patel, Tushar; Petersen, Gloria; Que, Florencia; Rivera, Michael; Roberts, Lewis; Smallridge, Robert; Smyrk, Thomas; Stanton, Melissa; Thompson, R. Houston; Torbenson, Michael; Yang, Ju Dong; Zhang, Lizhi; Brimo, Fadi; Ajani, Jaffer A.; Angulo Gonzalez, Ana Maria; Behrens, Carmen; Bondaruk, Jolanta; Broaddus, Russell; Czerniak, Bogdan; Esmaeli, Bita; Fujimoto, Junya; Gershenwald, Jeffrey; Guo, Charles; Lazar, Alexander J.; Logothetis, Christopher; Meric-Bernstam, Funda; Moran, Cesar; Ramondetta, Lois; Rice, David; Sood, Anil; Tamboli, Pheroze; Thompson, Timothy; Troncoso, Patricia; Tsao, Anne; Wistuba, Ignacio; Carter, Candace; Haydu, Lauren; Hersey, Peter; Jakrot, Valerie; Kakavand, Hojabr; Kefford, Richard; Lee, Kenneth; Long, Georgina; Mann, Graham; Quinn, Michael; Saw, Robyn; Scolyer, Richard; Shannon, Kerwin; Spillane, Andrew; Stretch, Jonathan; Synott, Maria; Thompson, John; Wilmott, James; Al-Ahmadie, Hikmat; Chan, Timothy A.; Ghossein, Ronald; Gopalan, Anuradha; Levine, Douglas A.; Reuter, Victor; Singer, Samuel; Singh, Bhuvanesh; Tien, Nguyen Viet; Broudy, Thomas; Mirsaidi, Cyrus; Nair, Praveen; Drwiega, Paul; Miller, Judy; Smith, Jennifer; Zaren, Howard; Park, Joong Won; Hung, Nguyen Phi; Kebebew, Electron; Linehan, W. Marston; Metwalli, Adam R.; Pacak, Karel; Pinto, Peter A.; Schiffman, Mark; Schmidt, Laura S.; Vocke, Cathy D.; Wentzensen, Nicolas; Worrell, Robert; Yang, Hannah; Moncrieff, Marc; Goparaju, Chandra; Melamed, Jonathan; Pass, Harvey; Botnariuc, Natalia; Caraman, Irina; Cernat, Mircea; Chemencedji, Inga; Clipca, Adrian; Doruc, Serghei; Gorincioi, Ghenadie; Mura, Sergiu; Pirtac, Maria; Stancul, Irina; Tcaciuc, Diana; Albert, Monique; Alexopoulou, Iakovina; Arnaout, Angel; Bartlett, John; Engel, Jay; Gilbert, Sebastien; Parfitt, Jeremy; Sekhon, Harman; Thomas, George; Rassl, Doris M.; Rintoul, Robert C.; Bifulco, Carlo; Tamakawa, Raina; Urba, Walter; Hayward, Nicholas; Timmers, Henri; Antenucci, Anna; Facciolo, Francesco; Grazi, Gianluca; Marino, Mirella; Merola, Roberta; de Krijger, Ronald; Gimenez-Roqueplo, Anne Paule; Piché, Alain; Chevalier, Simone; McKercher, Ginette; Birsoy, Kivanc; Barnett, Gene; Brewer, Cathy; Farver, Carol; Naska, Theresa; Pennell, Nathan A.; Raymond, Daniel; Schilero, Cathy; Smolenski, Kathy; Williams, Felicia; Morrison, Carl; Borgia, Jeffrey A.; Liptay, Michael J.; Pool, Mark; Seder, Christopher W.; Junker, Kerstin; Omberg, Larsson; Dinkin, Mikhail; Manikhas, George; Alvaro, Domenico; Bragazzi, Maria Consiglia; Cardinale, Vincenzo; Carpino, Guido; Gaudio, Eugenio; Chesla, David; Cottingham, Sandra; Dubina, Michael; Moiseenko, Fedor; Dhanasekaran, Renumathy; Becker, Karl Friedrich; Janssen, Klaus Peter; Slotta-Huspenina, Julia; Abdel-Rahman, Mohamed H.; Aziz, Dina; Bell, Sue; Cebulla, Colleen M.; Davis, Amy; Duell, Rebecca; Elder, J. Bradley; Hilty, Joe; Kumar, Bahavna; Lang, James; Lehman, Norman L.; Mandt, Randy; Nguyen, Phuong; Pilarski, Robert; Rai, Karan; Schoenfield, Lynn; Senecal, Kelly; Wakely, Paul; Hansen, Paul; Lechan, Ronald; Powers, James; Tischler, Arthur; Grizzle, William E.; Sexton, Katherine C.; Kastl, Alison; Henderson, Joel; Porten, Sima; Waldmann, Jens; Fassnacht, Martin; Asa, Sylvia L.; Schadendorf, Dirk; Couce, Marta; Graefen, Markus; Huland, Hartwig; Sauter, Guido; Schlomm, Thorsten; Simon, Ronald; Tennstedt, Pierre; Olabode, Oluwole; Nelson, Mark; Bathe, Oliver; Carroll, Peter R.; Chan, June M.; Disaia, Philip; Glenn, Pat; Kelley, Robin K.; Landen, Charles N.; Phillips, Joanna; Prados, Michael; Simko, Jeffry; Smith-McCune, Karen; VandenBerg, Scott; Roggin, Kevin; Fehrenbach, Ashley; Kendler, Ady; Sifri, Suzanne; Steele, Ruth; Jimeno, Antonio; Carey, Francis; Forgie, Ian; Mannelli, Massimo; Carney, Michael; Hernandez, Brenda; Campos, Benito; Herold-Mende, Christel; Jungk, Christin; Unterberg, Andreas; von Deimling, Andreas; Bossler, Aaron; Galbraith, Joseph; Jacobus, Laura; Knudson, Michael; Knutson, Tina; Ma, Deqin; Milhem, Mohammed; Sigmund, Rita; Godwin, Andrew K.; Madan, Rashna; Rosenthal, Howard G.; Adebamowo, Clement; Adebamowo, Sally N.; Boussioutas, Alex; Beer, David; Giordano, Thomas; Mes-Masson, Anne Marie; Saad, Fred; Bocklage, Therese; Landrum, Lisa; Mannel, Robert; Moore, Kathleen; Moxley, Katherine; Postier, Russel; Walker, Joan; Zuna, Rosemary; Feldman, Michael; Valdivieso, Federico; Dhir, Rajiv; Luketich, James; Mora Pinero, Edna M.; Quintero-Aguilo, Mario; Carlotti, Carlos Gilberto; Dos Santos, Jose Sebastião; Kemp, Rafael; Sankarankuty, Ajith; Tirapelli, Daniela; Catto, James; Agnew, Kathy; Swisher, Elizabeth; Creaney, Jenette; Robinson, Bruce; Shelley, Carl Simon; Godwin, Eryn M.; Kendall, Sara; Shipman, Cassaundra; Bradford, Carol; Carey, Thomas; Haddad, Andrea; Moyer, Jeffey; Peterson, Lisa; Prince, Mark; Rozek, Laura; Wolf, Gregory; Bowman, Rayleen; Fong, Kwun M.; Yang, Ian; Korst, Robert; Rathmell, W. Kimryn; Fantacone-Campbell, J. Leigh; Hooke, Jeffrey A.; Kovatich, Albert J.; Shriver, Craig D.; DiPersio, John; Drake, Bettina; Govindan, Ramaswamy; Heath, Sharon; Ley, Timothy; Van Tine, Brian; Westervelt, Peter; Rubin, Mark A.; Lee, Jung Il; Aredes, Natália D.; Mariamidze, Armaz

2018-01-01

Although the MYC oncogene has been implicated in cancer, a systematic assessment of alterations of MYC, related transcription factors, and co-regulatory proteins, forming the proximal MYC network (PMN), across human cancers is lacking. Using computational approaches, we define genomic and proteomic

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

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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.

Controlling gene networks and cell fate with precision-targeted DNA-binding proteins and small-molecule-based genome readers.

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Eguchi, Asuka; Lee, Garrett O; Wan, Fang; Erwin, Graham S; Ansari, Aseem Z

2014-09-15

Transcription factors control the fate of a cell by regulating the expression of genes and regulatory networks. Recent successes in inducing pluripotency in terminally differentiated cells as well as directing differentiation with natural transcription factors has lent credence to the efforts that aim to direct cell fate with rationally designed transcription factors. Because DNA-binding factors are modular in design, they can be engineered to target specific genomic sequences and perform pre-programmed regulatory functions upon binding. Such precision-tailored factors can serve as molecular tools to reprogramme or differentiate cells in a targeted manner. Using different types of engineered DNA binders, both regulatory transcriptional controls of gene networks, as well as permanent alteration of genomic content, can be implemented to study cell fate decisions. In the present review, we describe the current state of the art in artificial transcription factor design and the exciting prospect of employing artificial DNA-binding factors to manipulate the transcriptional networks as well as epigenetic landscapes that govern cell fate.

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

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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.

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

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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

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

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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

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

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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.

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

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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.

A Network-Based Approach to Prioritize Results from Genome-Wide Association Studies

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Akula, Nirmala; Baranova, Ancha; Seto, Donald; Solka, Jeffrey; Nalls, Michael A.; Singleton, Andrew; Ferrucci, Luigi; Tanaka, Toshiko; Bandinelli, Stefania; Cho, Yoon Shin; Kim, Young Jin; Lee, Jong-Young; Han, Bok-Ghee; McMahon, Francis J.

2011-01-01

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. PMID:21915301

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

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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

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

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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…

Social Media Use and Teacher Ethics

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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…

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

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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.

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. Copyright © 2015 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

Network analysis of genomic alteration profiles reveals co-altered functional modules and driver genes for glioblastoma.

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Gu, Yunyan; Wang, Hongwei; Qin, Yao; Zhang, Yujing; Zhao, Wenyuan; Qi, Lishuang; Zhang, Yuannv; Wang, Chenguang; Guo, Zheng

2013-03-01

The heterogeneity of genetic alterations in human cancer genomes presents a major challenge to advancing our understanding of cancer mechanisms and identifying cancer driver genes. To tackle this heterogeneity problem, many approaches have been proposed to investigate genetic alterations and predict driver genes at the individual pathway level. However, most of these approaches ignore the correlation of alteration events between pathways and miss many genes with rare alterations collectively contributing to carcinogenesis. Here, we devise a network-based approach to capture the cooperative functional modules hidden in genome-wide somatic mutation and copy number alteration profiles of glioblastoma (GBM) from The Cancer Genome Atlas (TCGA), where a module is a set of altered genes with dense interactions in the protein interaction network. We identify 7 pairs of significantly co-altered modules that involve the main pathways known to be altered in GBM (TP53, RB and RTK signaling pathways) and highlight the striking co-occurring alterations among these GBM pathways. By taking into account the non-random correlation of gene alterations, the property of co-alteration could distinguish oncogenic modules that contain driver genes involved in the progression of GBM. The collaboration among cancer pathways suggests that the redundant models and aggravating models could shed new light on the potential mechanisms during carcinogenesis and provide new indications for the design of cancer therapeutic strategies.

Network-assisted crop systems genetics: network inference and integrative analysis.

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Lee, Tak; Kim, Hyojin; Lee, Insuk

2015-04-01

Although next-generation sequencing (NGS) technology has enabled the decoding of many crop species genomes, most of the underlying genetic components for economically important crop traits remain to be determined. Network approaches have proven useful for the study of the reference plant, Arabidopsis thaliana, and the success of network-based crop genetics will also require the availability of a genome-scale functional networks for crop species. In this review, we discuss how to construct functional networks and elucidate the holistic view of a crop system. The crop gene network then can be used for gene prioritization and the analysis of resequencing-based genome-wide association study (GWAS) data, the amount of which will rapidly grow in the field of crop science in the coming years. Copyright © 2015 Elsevier Ltd. All rights reserved.

Cytoscape: the network visualization tool for GenomeSpace workflows [v2; ref status: indexed, http://f1000r.es/47f

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Barry Demchak

2014-08-01

Full Text Available Modern genomic analysis often requires workflows incorporating multiple best-of-breed tools. GenomeSpace is a web-based visual workbench that combines a selection of these tools with mechanisms that create data flows between them. One such tool is Cytoscape 3, a popular application that enables analysis and visualization of graph-oriented genomic networks. As Cytoscape runs on the desktop, and not in a web browser, integrating it into GenomeSpace required special care in creating a seamless user experience and enabling appropriate data flows. In this paper, we present the design and operation of the Cytoscape GenomeSpace app, which accomplishes this integration, thereby providing critical analysis and visualization functionality for GenomeSpace users. It has been downloaded over 850 times since the release of its first version in September, 2013.

Cytoscape: the network visualization tool for GenomeSpace workflows [v1; ref status: indexed, http://f1000r.es/3ph

Directory of Open Access Journals (Sweden)

Barry Demchak

2014-07-01

Full Text Available Modern genomic analysis often requires workflows incorporating multiple best-ofbreed tools. GenomeSpace is a web-based visual workbench that combines a selection of these tools with mechanisms that create data flows between them. One such tool is Cytoscape 3, a popular application that enables analysis and visualization of graph-oriented genomic networks. As Cytoscape runs on the desktop, and not in a web browser, integrating it into GenomeSpace required special care in creating a seamless user experience and enabling appropriate data flows. In this paper, we present the design and operation of the Cytoscape GenomeSpace app, which accomplishes this integration, thereby providing critical analysis and visualization functionality for GenomeSpace users. It has been downloaded it over 850 times since the release of its first version in September, 2013.

Framework for network modularization and Bayesian network analysis to investigate the perturbed metabolic network

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Kim Hyun

2011-12-01

Full Text Available Abstract Background Genome-scale metabolic network models have contributed to elucidating biological phenomena, and predicting gene targets to engineer for biotechnological applications. With their increasing importance, their precise network characterization has also been crucial for better understanding of the cellular physiology. Results We herein introduce a framework for network modularization and Bayesian network analysis (FMB to investigate organism’s metabolism under perturbation. FMB reveals direction of influences among metabolic modules, in which reactions with similar or positively correlated flux variation patterns are clustered, in response to specific perturbation using metabolic flux data. With metabolic flux data calculated by constraints-based flux analysis under both control and perturbation conditions, FMB, in essence, reveals the effects of specific perturbations on the biological system through network modularization and Bayesian network analysis at metabolic modular level. As a demonstration, this framework was applied to the genetically perturbed Escherichia coli metabolism, which is a lpdA gene knockout mutant, using its genome-scale metabolic network model. Conclusions After all, it provides alternative scenarios of metabolic flux distributions in response to the perturbation, which are complementary to the data obtained from conventionally available genome-wide high-throughput techniques or metabolic flux analysis.

Framework for network modularization and Bayesian network analysis to investigate the perturbed metabolic network.

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Kim, Hyun Uk; Kim, Tae Yong; Lee, Sang Yup

2011-01-01

Genome-scale metabolic network models have contributed to elucidating biological phenomena, and predicting gene targets to engineer for biotechnological applications. With their increasing importance, their precise network characterization has also been crucial for better understanding of the cellular physiology. We herein introduce a framework for network modularization and Bayesian network analysis (FMB) to investigate organism's metabolism under perturbation. FMB reveals direction of influences among metabolic modules, in which reactions with similar or positively correlated flux variation patterns are clustered, in response to specific perturbation using metabolic flux data. With metabolic flux data calculated by constraints-based flux analysis under both control and perturbation conditions, FMB, in essence, reveals the effects of specific perturbations on the biological system through network modularization and Bayesian network analysis at metabolic modular level. As a demonstration, this framework was applied to the genetically perturbed Escherichia coli metabolism, which is a lpdA gene knockout mutant, using its genome-scale metabolic network model. After all, it provides alternative scenarios of metabolic flux distributions in response to the perturbation, which are complementary to the data obtained from conventionally available genome-wide high-throughput techniques or metabolic flux analysis.

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.

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

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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

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

"Harnessing genomics to improve health in India" – an executive course to support genomics policy

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Acharya Tara

2004-05-01

Full Text Available Abstract Background The benefits of scientific medicine have eluded millions in developing countries and the genomics revolution threatens to increase health inequities between North and South. India, as a developing yet also industrialized country, is uniquely positioned to pioneer science policy innovations to narrow the genomics divide. Recognizing this, the Indian Council of Medical Research and the University of Toronto Joint Centre for Bioethics conducted a Genomics Policy Executive Course in January 2003 in Kerala, India. The course provided a forum for stakeholders to discuss the relevance of genomics for health in India. This article presents the course findings and recommendations formulated by the participants for genomics policy in India. Methods The course goals were to familiarize participants with the implications of genomics for health in India; analyze and debate policy and ethical issues; and develop a multi-sectoral opinion leaders' network to share perspectives. To achieve these goals, the course brought together representatives of academic research centres, biotechnology companies, regulatory bodies, media, voluntary, and legal organizations to engage in discussion. Topics included scientific advances in genomics, followed by innovations in business models, public sector perspectives, ethics, legal issues and national innovation systems. Results Seven main recommendations emerged: increase funding for healthcare research with appropriate emphasis on genomics; leverage India's assets such as traditional knowledge and genomic diversity in consultation with knowledge-holders; prioritize strategic entry points for India; improve industry-academic interface with appropriate incentives to improve public health and the nation's wealth; develop independent, accountable, transparent regulatory systems to ensure that ethical, legal and social issues are addressed for a single entry, smart and effective system; engage the public and

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

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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.

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

"Follow" Me: Networked Professional Learning for Teachers

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Holmes, Kathryn; Preston, Greg; Shaw, Kylie; Buchanan, Rachel

2013-01-01

Effective professional learning for teachers is fundamental for any school system aiming to make transformative and sustainable change to teacher practice. This paper investigates the efficacy of Twitter as a medium for teachers to participate in professional learning by analysing the tweets of 30 influential users of the popular medium. We find…

Computational solution to automatically map metabolite libraries in the context of genome scale metabolic networks

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Benjamin eMerlet

2016-02-01

Full Text Available This article describes a generic programmatic method for mapping chemical compound libraries on organism-specific metabolic networks from various databases (KEGG, BioCyc and flat file formats (SBML and Matlab files. We show how this pipeline was successfully applied to decipher the coverage of chemical libraries set up by two metabolomics facilities MetaboHub (French National infrastructure for metabolomics and fluxomics and Glasgow Polyomics on the metabolic networks available in the MetExplore web server. The present generic protocol is designed to formalize and reduce the volume of information transfer between the library and the network database. Matching of metabolites between libraries and metabolic networks is based on InChIs or InChIKeys and therefore requires that these identifiers are specified in both libraries and networks.In addition to providing covering statistics, this pipeline also allows the visualization of mapping results in the context of metabolic networks.In order to achieve this goal we tackled issues on programmatic interaction between two servers, improvement of metabolite annotation in metabolic networks and automatic loading of a mapping in genome scale metabolic network analysis tool MetExplore. It is important to note that this mapping can also be performed on a single or a selection of organisms of interest and is thus not limited to large facilities.

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

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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.

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

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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.

Exploiting a Reference Genome in Terms of Duplications: The Network of Paralogs and Single Copy Genes in Arabidopsis thaliana

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Mara Sangiovanni

2013-12-01

Full Text Available Arabidopsis thaliana became the model organism for plant studies because of its small diploid genome, rapid lifecycle and short adult size. Its genome was the first among plants to be sequenced, becoming the reference in plant genomics. However, the Arabidopsis genome is characterized by an inherently complex organization, since it has undergone ancient whole genome duplications, followed by gene reduction, diploidization events and extended rearrangements, which relocated and split up the retained portions. These events, together with probable chromosome reductions, dramatically increased the genome complexity, limiting its role as a reference. The identification of paralogs and single copy genes within a highly duplicated genome is a prerequisite to understand its organization and evolution and to improve its exploitation in comparative genomics. This is still controversial, even in the widely studied Arabidopsis genome. This is also due to the lack of a reference bioinformatics pipeline that could exhaustively identify paralogs and singleton genes. We describe here a complete computational strategy to detect both duplicated and single copy genes in a genome, discussing all the methodological issues that may strongly affect the results, their quality and their reliability. This approach was used to analyze the organization of Arabidopsis nuclear protein coding genes, and besides classifying computationally defined paralogs into networks and single copy genes into different classes, it unraveled further intriguing aspects concerning the genome annotation and the gene relationships in this reference plant species. Since our results may be useful for comparative genomics and genome functional analyses, we organized a dedicated web interface to make them accessible to the scientific community.

MutaNET: a tool for automated analysis of genomic mutations in gene regulatory networks.

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Hollander, Markus; Hamed, Mohamed; Helms, Volkhard; Neininger, Kerstin

2018-03-01

Mutations in genomic key elements can influence gene expression and function in various ways, and hence greatly contribute to the phenotype. We developed MutaNET to score the impact of individual mutations on gene regulation and function of a given genome. MutaNET performs statistical analyses of mutations in different genomic regions. The tool also incorporates the mutations in a provided gene regulatory network to estimate their global impact. The integration of a next-generation sequencing pipeline enables calling mutations prior to the analyses. As application example, we used MutaNET to analyze the impact of mutations in antibiotic resistance (AR) genes and their potential effect on AR of bacterial strains. MutaNET is freely available at https://sourceforge.net/projects/mutanet/. It is implemented in Python and supported on Mac OS X, Linux and MS Windows. Step-by-step instructions are available at http://service.bioinformatik.uni-saarland.de/mutanet/. volkhard.helms@bioinformatik.uni-saarland.de. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

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

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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…

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

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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.

THE INTERIM RESULTS AND THE WAYS TO IMPLEMENT THE PROGRAMS TEACHER TRAINING IN NETWORK FORM

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A. A. Tolsteneva

2016-01-01

Full Text Available The paper presents the results of approbation of new modules primary educational undergraduate specialties Group expanded education and pedagogy (training areas-economics, involving academic mobility of students of universities in terms of networking of Novosibirsk and Nizhny Novgorod pedagogical universities. The article describes the structure of established affiliate networks, conducted pedagogical and methodical analysis modules have passed testing, recommendations for improvement and suggested ways for the development of a modular approach to building educational programs in teacher education system. The implementation of educational modules require their integration into the curricula of the Nizhny Novgorod State Pedagogical University, with no loss of content, giving the existing curriculum structure saturation. Thus, it was achieved 100% consistency of curriculum, opening further opportunities for the implementation of educational programs in terms of networking.

Population genomics of the Arabidopsis thaliana flowering time gene network.

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Flowers, Jonathan M; Hanzawa, Yoshie; Hall, Megan C; Moore, Richard C; Purugganan, Michael D

2009-11-01

The time to flowering is a key component of the life-history strategy of the model plant Arabidopsis thaliana that varies quantitatively among genotypes. A significant problem for evolutionary and ecological genetics is to understand how natural selection may operate on this ecologically significant trait. Here, we conduct a population genomic study of resequencing data from 52 genes in the flowering time network. McDonald-Kreitman tests of neutrality suggested a strong excess of amino acid polymorphism when pooling across loci. This excess of replacement polymorphism across the flowering time network and a skewed derived frequency spectrum toward rare alleles for both replacement and noncoding polymorphisms relative to synonymous changes is consistent with a large class of deleterious polymorphisms segregating in these genes. Assuming selective neutrality of synonymous changes, we estimate that approximately 30% of amino acid polymorphisms are deleterious. Evidence of adaptive substitution is less prominent in our analysis. The photoperiod regulatory gene, CO, and a gibberellic acid transcription factor, AtMYB33, show evidence of adaptive fixation of amino acid mutations. A test for extended haplotypes revealed no examples of flowering time alleles with haplotypes comparable in length to those associated with the null fri(Col) allele reported previously. This suggests that the FRI gene likely has a uniquely intense or recent history of selection among the flowering time genes considered here. Although there is some evidence for adaptive evolution in these life-history genes, it appears that slightly deleterious polymorphisms are a major component of natural molecular variation in the flowering time network of A. thaliana.

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...

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

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Jongeneel, C Victor; Achinike-Oduaran, Ovokeraye; Adebiyi, Ezekiel; Adebiyi, Marion; Adeyemi, Seun; Akanle, Bola; Aron, Shaun; Ashano, Efejiro; Bendou, Hocine; Botha, Gerrit; Chimusa, Emile; Choudhury, Ananyo; Donthu, Ravikiran; Drnevich, Jenny; Falola, Oluwadamila; Fields, Christopher J; Hazelhurst, Scott; Hendry, Liesl; Isewon, Itunuoluwa; Khetani, Radhika S; Kumuthini, Judit; Kimuda, Magambo Phillip; Magosi, Lerato; Mainzer, Liudmila Sergeevna; Maslamoney, Suresh; Mbiyavanga, Mamana; Meintjes, Ayton; Mugutso, Danny; Mpangase, Phelelani; Munthali, Richard; Nembaware, Victoria; Ndhlovu, Andrew; Odia, Trust; Okafor, Adaobi; Oladipo, Olaleye; Panji, Sumir; Pillay, Venesa; Rendon, Gloria; Sengupta, Dhriti; Mulder, Nicola

2017-06-01

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.

Integration of Genome-Wide TF Binding and Gene Expression Data to Characterize Gene Regulatory Networks in Plant Development.

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Chen, Dijun; Kaufmann, Kerstin

2017-01-01

Key transcription factors (TFs) controlling the morphogenesis of flowers and leaves have been identified in the model plant Arabidopsis thaliana. Recent genome-wide approaches based on chromatin immunoprecipitation (ChIP) followed by high-throughput DNA sequencing (ChIP-seq) enable systematic identification of genome-wide TF binding sites (TFBSs) of these regulators. Here, we describe a computational pipeline for analyzing ChIP-seq data to identify TFBSs and to characterize gene regulatory networks (GRNs) with applications to the regulatory studies of flower development. In particular, we provide step-by-step instructions on how to download, analyze, visualize, and integrate genome-wide data in order to construct GRNs for beginners of bioinformatics. The practical guide presented here is ready to apply to other similar ChIP-seq datasets to characterize GRNs of interest.

Network Graph Analysis of Gene-Gene Interactions in Genome-Wide Association Study Data

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Sungyoung Lee

2012-12-01

Full Text Available Most common complex traits, such as obesity, hypertension, diabetes, and cancers, are known to be associated with multiple genes, environmental factors, and their epistasis. Recently, the development of advanced genotyping technologies has allowed us to perform genome-wide association studies (GWASs. For detecting the effects of multiple genes on complex traits, many approaches have been proposed for GWASs. Multifactor dimensionality reduction (MDR is one of the powerful and efficient methods for detecting high-order gene-gene (GxG interactions. However, the biological interpretation of GxG interactions identified by MDR analysis is not easy. In order to aid the interpretation of MDR results, we propose a network graph analysis to elucidate the meaning of identified GxG interactions. The proposed network graph analysis consists of three steps. The first step is for performing GxG interaction analysis using MDR analysis. The second step is to draw the network graph using the MDR result. The third step is to provide biological evidence of the identified GxG interaction using external biological databases. The proposed method was applied to Korean Association Resource (KARE data, containing 8838 individuals with 327,632 single-nucleotide polymorphisms, in order to perform GxG interaction analysis of body mass index (BMI. Our network graph analysis successfully showed that many identified GxG interactions have known biological evidence related to BMI. We expect that our network graph analysis will be helpful to interpret the biological meaning of GxG interactions.

Network graph analysis of gene-gene interactions in genome-wide association study data.

Science.gov (United States)

Lee, Sungyoung; Kwon, Min-Seok; Park, Taesung

2012-12-01

Most common complex traits, such as obesity, hypertension, diabetes, and cancers, are known to be associated with multiple genes, environmental factors, and their epistasis. Recently, the development of advanced genotyping technologies has allowed us to perform genome-wide association studies (GWASs). For detecting the effects of multiple genes on complex traits, many approaches have been proposed for GWASs. Multifactor dimensionality reduction (MDR) is one of the powerful and efficient methods for detecting high-order gene-gene (GxG) interactions. However, the biological interpretation of GxG interactions identified by MDR analysis is not easy. In order to aid the interpretation of MDR results, we propose a network graph analysis to elucidate the meaning of identified GxG interactions. The proposed network graph analysis consists of three steps. The first step is for performing GxG interaction analysis using MDR analysis. The second step is to draw the network graph using the MDR result. The third step is to provide biological evidence of the identified GxG interaction using external biological databases. The proposed method was applied to Korean Association Resource (KARE) data, containing 8838 individuals with 327,632 single-nucleotide polymorphisms, in order to perform GxG interaction analysis of body mass index (BMI). Our network graph analysis successfully showed that many identified GxG interactions have known biological evidence related to BMI. We expect that our network graph analysis will be helpful to interpret the biological meaning of GxG interactions.

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…

On the formation of the network community of supplementary education teachers (from the experience of Children's Creativity Center with the study of applied economics)

OpenAIRE

Galina Nekrasova; Elena Shigareva; Raisa Artemova; Irina Nelyubina

2014-01-01

The online communities of teachers for professional communication and development of information and educational environment of subject teaching is actual nowadays. The authors describe the experience of Children’s Creativity Center in creation the network community for teachers of technology and educational specialists of additional education.

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/.

A Computational Solution to Automatically Map Metabolite Libraries in the Context of Genome Scale Metabolic Networks.

Science.gov (United States)

Merlet, Benjamin; Paulhe, Nils; Vinson, Florence; Frainay, Clément; Chazalviel, Maxime; Poupin, Nathalie; Gloaguen, Yoann; Giacomoni, Franck; Jourdan, Fabien

2016-01-01

This article describes a generic programmatic method for mapping chemical compound libraries on organism-specific metabolic networks from various databases (KEGG, BioCyc) and flat file formats (SBML and Matlab files). We show how this pipeline was successfully applied to decipher the coverage of chemical libraries set up by two metabolomics facilities MetaboHub (French National infrastructure for metabolomics and fluxomics) and Glasgow Polyomics (GP) on the metabolic networks available in the MetExplore web server. The present generic protocol is designed to formalize and reduce the volume of information transfer between the library and the network database. Matching of metabolites between libraries and metabolic networks is based on InChIs or InChIKeys and therefore requires that these identifiers are specified in both libraries and networks. In addition to providing covering statistics, this pipeline also allows the visualization of mapping results in the context of metabolic networks. In order to achieve this goal, we tackled issues on programmatic interaction between two servers, improvement of metabolite annotation in metabolic networks and automatic loading of a mapping in genome scale metabolic network analysis tool MetExplore. It is important to note that this mapping can also be performed on a single or a selection of organisms of interest and is thus not limited to large facilities.

Genomics With Cloud Computing

Directory of Open Access Journals (Sweden)

Sukhamrit Kaur

2015-04-01

Full Text Available Abstract Genomics is study of genome which provides large amount of data for which large storage and computation power is needed. These issues are solved by cloud computing that provides various cloud platforms for genomics. These platforms provides many services to user like easy access to data easy sharing and transfer providing storage in hundreds of terabytes more computational power. Some cloud platforms are Google genomics DNAnexus and Globus genomics. Various features of cloud computing to genomics are like easy access and sharing of data security of data less cost to pay for resources but still there are some demerits like large time needed to transfer data less network bandwidth.

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

Science.gov (United States)

Levering, Jennifer; Fiedler, Tomas; Sieg, Antje; van Grinsven, Koen W A; Hering, Silvio; Veith, Nadine; Olivier, Brett G; Klett, Lara; Hugenholtz, Jeroen; Teusink, Bas; Kreikemeyer, Bernd; Kummer, Ursula

2016-08-20

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. Initially, we based the reconstruction on genome annotations and already existing and curated metabolic networks of Bacillus subtilis, Escherichia coli, Lactobacillus plantarum and Lactococcus lactis. This initial draft was manually curated with the final reconstruction accounting for 480 genes associated with 576 reactions and 558 metabolites. In order to constrain the model further, we performed growth experiments of wild type and arcA deletion strains of S. pyogenes M49 in a chemically defined medium and calculated nutrient uptake and production fluxes. We additionally performed amino acid auxotrophy experiments to test the consistency of the model. The established genome-scale model can be used to understand the growth requirements of the human pathogen S. pyogenes and define optimal and suboptimal conditions, but also to describe differences and similarities between S. pyogenes and related lactic acid bacteria such as L. lactis in order to find strategies to reduce the growth of the pathogen and propose drug targets. Copyright © 2016 Elsevier B.V. All rights reserved.

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

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.

Network analysis of epidermal growth factor signaling using integrated genomic, proteomic and phosphorylation data.

Directory of Open Access Journals (Sweden)

Katrina M Waters

Full Text Available To understand how integration of multiple data types can help decipher cellular responses at the systems level, we analyzed the mitogenic response of human mammary epithelial cells to epidermal growth factor (EGF using whole genome microarrays, mass spectrometry-based proteomics and large-scale western blots with over 1000 antibodies. A time course analysis revealed significant differences in the expression of 3172 genes and 596 proteins, including protein phosphorylation changes measured by western blot. Integration of these disparate data types showed that each contributed qualitatively different components to the observed cell response to EGF and that varying degrees of concordance in gene expression and protein abundance measurements could be linked to specific biological processes. Networks inferred from individual data types were relatively limited, whereas networks derived from the integrated data recapitulated the known major cellular responses to EGF and exhibited more highly connected signaling nodes than networks derived from any individual dataset. While cell cycle regulatory pathways were altered as anticipated, we found the most robust response to mitogenic concentrations of EGF was induction of matrix metalloprotease cascades, highlighting the importance of the EGFR system as a regulator of the extracellular environment. These results demonstrate the value of integrating multiple levels of biological information to more accurately reconstruct networks of cellular response.

Network Analysis of Epidermal Growth Factor Signaling using Integrated Genomic, Proteomic and Phosphorylation Data

Energy Technology Data Exchange (ETDEWEB)

Waters, Katrina M.; Liu, Tao; Quesenberry, Ryan D.; Willse, Alan R.; Bandyopadhyay, Somnath; Kathmann, Loel E.; Weber, Thomas J.; Smith, Richard D.; Wiley, H. S.; Thrall, Brian D.

2012-03-29

To understand how integration of multiple data types can help decipher cellular responses at the systems level, we analyzed the mitogenic response of human mammary epithelial cells to epidermal growth factor (EGF) using whole genome microarrays, mass spectrometry-based proteomics and large-scale western blots with over 1000 antibodies. A time course analysis revealed significant differences in the expression of 3172 genes and 596 proteins, including protein phosphorylation changes measured by western blot. Integration of these disparate data types showed that each contributed qualitatively different components to the observed cell response to EGF and that varying degrees of concordance in gene expression and protein abundance measurements could be linked to specific biological processes. Networks inferred from individual data types were relatively limited, whereas networks derived from the integrated data recapitulated the known major cellular responses to EGF and exhibited more highly connected signaling nodes than networks derived from any individual dataset. While cell cycle regulatory pathways were altered as anticipated, we found the most robust response to mitogenic concentrations of EGF was induction of matrix metalloprotease cascades, highlighting the importance of the EGFR system as a regulator of the extracellular environment. These results demonstrate the value of integrating multiple levels of biological information to more accurately reconstruct networks of cellular response.

Puzzles in modern biology. V. Why are genomes overwired?

Science.gov (United States)

Frank, Steven A

2017-01-01

Many factors affect eukaryotic gene expression. Transcription factors, histone codes, DNA folding, and noncoding RNA modulate expression. Those factors interact in large, broadly connected regulatory control networks. An engineer following classical principles of control theory would design a simpler regulatory network. Why are genomes overwired? Neutrality or enhanced robustness may lead to the accumulation of additional factors that complicate network architecture. Dynamics progresses like a ratchet. New factors get added. Genomes adapt to the additional complexity. The newly added factors can no longer be removed without significant loss of fitness. Alternatively, highly wired genomes may be more malleable. In large networks, most genomic variants tend to have a relatively small effect on gene expression and trait values. Many small effects lead to a smooth gradient, in which traits may change steadily with respect to underlying regulatory changes. A smooth gradient may provide a continuous path from a starting point up to the highest peak of performance. A potential path of increasing performance promotes adaptability and learning. Genomes gain by the inductive process of natural selection, a trial and error learning algorithm that discovers general solutions for adapting to environmental challenge. Similarly, deeply and densely connected computational networks gain by various inductive trial and error learning procedures, in which the networks learn to reduce the errors in sequential trials. Overwiring alters the geometry of induction by smoothing the gradient along the inductive pathways of improving performance. Those overwiring benefits for induction apply to both natural biological networks and artificial deep learning networks.

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…

Teachers, Arts Practice and Pedagogy

Science.gov (United States)

Franks, Anton; Thomson, Pat; Hall, Chris; Jones, Ken

2014-01-01

What are possible overlaps between arts practice and school pedagogy? How is teacher subjectivity and pedagogy affected when teachers engage with arts practice, in particular, theatre practices? We draw on research conducted into the Learning Performance Network (LPN), a project that involved school teachers working with the Royal Shakespeare…

Identifying all moiety conservation laws in genome-scale metabolic networks.

Science.gov (United States)

De Martino, Andrea; De Martino, Daniele; Mulet, Roberto; Pagnani, Andrea

2014-01-01

The stoichiometry of a metabolic network gives rise to a set of conservation laws for the aggregate level of specific pools of metabolites, which, on one hand, pose dynamical constraints that cross-link the variations of metabolite concentrations and, on the other, provide key insight into a cell's metabolic production capabilities. When the conserved quantity identifies with a chemical moiety, extracting all such conservation laws from the stoichiometry amounts to finding all non-negative integer solutions of a linear system, a programming problem known to be NP-hard. We present an efficient strategy to compute the complete set of integer conservation laws of a genome-scale stoichiometric matrix, also providing a certificate for correctness and maximality of the solution. Our method is deployed for the analysis of moiety conservation relationships in two large-scale reconstructions of the metabolism of the bacterium E. coli, in six tissue-specific human metabolic networks, and, finally, in the human reactome as a whole, revealing that bacterial metabolism could be evolutionarily designed to cover broader production spectra than human metabolism. Convergence to the full set of moiety conservation laws in each case is achieved in extremely reduced computing times. In addition, we uncover a scaling relation that links the size of the independent pool basis to the number of metabolites, for which we present an analytical explanation.

Identifying all moiety conservation laws in genome-scale metabolic networks.

Directory of Open Access Journals (Sweden)

Andrea De Martino

Full Text Available The stoichiometry of a metabolic network gives rise to a set of conservation laws for the aggregate level of specific pools of metabolites, which, on one hand, pose dynamical constraints that cross-link the variations of metabolite concentrations and, on the other, provide key insight into a cell's metabolic production capabilities. When the conserved quantity identifies with a chemical moiety, extracting all such conservation laws from the stoichiometry amounts to finding all non-negative integer solutions of a linear system, a programming problem known to be NP-hard. We present an efficient strategy to compute the complete set of integer conservation laws of a genome-scale stoichiometric matrix, also providing a certificate for correctness and maximality of the solution. Our method is deployed for the analysis of moiety conservation relationships in two large-scale reconstructions of the metabolism of the bacterium E. coli, in six tissue-specific human metabolic networks, and, finally, in the human reactome as a whole, revealing that bacterial metabolism could be evolutionarily designed to cover broader production spectra than human metabolism. Convergence to the full set of moiety conservation laws in each case is achieved in extremely reduced computing times. In addition, we uncover a scaling relation that links the size of the independent pool basis to the number of metabolites, for which we present an analytical explanation.

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

Genomics Portals: integrative web-platform for mining genomics data.

Science.gov (United States)

Shinde, Kaustubh; Phatak, Mukta; Johannes, Freudenberg M; Chen, Jing; Li, Qian; Vineet, Joshi K; Hu, Zhen; Ghosh, Krishnendu; Meller, Jaroslaw; Medvedovic, Mario

2010-01-13

A large amount of experimental data generated by modern high-throughput technologies is available through various public repositories. Our knowledge about molecular interaction networks, functional biological pathways and transcriptional regulatory modules is rapidly expanding, and is being organized in lists of functionally related genes. Jointly, these two sources of information hold a tremendous potential for gaining new insights into functioning of living systems. Genomics Portals platform integrates access to an extensive knowledge base and a large database of human, mouse, and rat genomics data with basic analytical visualization tools. It provides the context for analyzing and interpreting new experimental data and the tool for effective mining of a large number of publicly available genomics datasets stored in the back-end databases. The uniqueness of this platform lies in the volume and the diversity of genomics data that can be accessed and analyzed (gene expression, ChIP-chip, ChIP-seq, epigenomics, computationally predicted binding sites, etc), and the integration with an extensive knowledge base that can be used in such analysis. The integrated access to primary genomics data, functional knowledge and analytical tools makes Genomics Portals platform a unique tool for interpreting results of new genomics experiments and for mining the vast amount of data stored in the Genomics Portals backend databases. Genomics Portals can be accessed and used freely at http://GenomicsPortals.org.

Genome plasticity and systems evolution in Streptomyces

Science.gov (United States)

2012-01-01

Background Streptomycetes are filamentous soil-dwelling bacteria. They are best known as the producers of a great variety of natural products such as antibiotics, antifungals, antiparasitics, and anticancer agents and the decomposers of organic substances for carbon recycling. They are also model organisms for the studies of gene regulatory networks, morphological differentiation, and stress response. The availability of sets of genomes from closely related Streptomyces strains makes it possible to assess the mechanisms underlying genome plasticity and systems adaptation. Results We present the results of a comprehensive analysis of the genomes of five Streptomyces species with distinct phenotypes. These streptomycetes have a pan-genome comprised of 17,362 orthologous families which includes 3,096 components in the core genome, 5,066 components in the dispensable genome, and 9,200 components that are uniquely present in only one species. The core genome makes up about 33%-45% of each genome repertoire. It contains important genes for Streptomyces biology including those involved in gene regulation, secretion, secondary metabolism and morphological differentiation. Abundant duplicate genes have been identified, with 4%-11% of the whole genomes composed of lineage-specific expansions (LSEs), suggesting that frequent gene duplication or lateral gene transfer events play a role in shaping the genome diversification within this genus. Two patterns of expansion, single gene expansion and chromosome block expansion are observed, representing different scales of duplication. Conclusions Our results provide a catalog of genome components and their potential functional roles in gene regulatory networks and metabolic networks. The core genome components reveal the minimum requirement for streptomycetes to sustain a successful lifecycle in the soil environment, reflecting the effects of both genome evolution and environmental stress acting upon the expressed phenotypes. A

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

.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...... 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...

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.

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

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...... 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...

Dimensions of social learning in teacher education: an exemplary case study

OpenAIRE

Van den Beemt, Antoine; Vrieling, Emmy

2016-01-01

Growing attention can be noticed for social learning in teacher groups as a stimulus for teachers’ professional development. Research shows the importance of understanding the role and impact of informal social networks on teacher professional development. This paper describes a rich case study of student teachers, in-service teachers and teacher training educators collaborating in networks. Based on the ‘Dimensions of Social Learning (DSL)-Framework’ that includes 4 dimensions and 11 indicat...

Contemporary Network Proteomics and Its Requirements

Science.gov (United States)

Goh, Wilson Wen Bin; Wong, Limsoon; Sng, Judy Chia Ghee

2013-01-01

The integration of networks with genomics (network genomics) is a familiar field. Conventional network analysis takes advantage of the larger coverage and relative stability of gene expression measurements. Network proteomics on the other hand has to develop further on two critical factors: (1) expanded data coverage and consistency, and (2) suitable reference network libraries, and data mining from them. Concerning (1) we discuss several contemporary themes that can improve data quality, which in turn will boost the outcome of downstream network analysis. For (2), we focus on network analysis developments, specifically, the need for context-specific networks and essential considerations for localized network analysis. PMID:24833333

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

Integrative Analysis of Genetic, Genomic, and Phenotypic Data for Ethanol Behaviors: A Network-Based Pipeline for Identifying Mechanisms and Potential Drug Targets.

Science.gov (United States)

Bogenpohl, James W; Mignogna, Kristin M; Smith, Maren L; Miles, Michael F

2017-01-01

Complex behavioral traits, such as alcohol abuse, are caused by an interplay of genetic and environmental factors, producing deleterious functional adaptations in the central nervous system. The long-term behavioral consequences of such changes are of substantial cost to both the individual and society. Substantial progress has been made in the last two decades in understanding elements of brain mechanisms underlying responses to ethanol in animal models and risk factors for alcohol use disorder (AUD) in humans. However, treatments for AUD remain largely ineffective and few medications for this disease state have been licensed. Genome-wide genetic polymorphism analysis (GWAS) in humans, behavioral genetic studies in animal models and brain gene expression studies produced by microarrays or RNA-seq have the potential to produce nonbiased and novel insight into the underlying neurobiology of AUD. However, the complexity of such information, both statistical and informational, has slowed progress toward identifying new targets for intervention in AUD. This chapter describes one approach for integrating behavioral, genetic, and genomic information across animal model and human studies. The goal of this approach is to identify networks of genes functioning in the brain that are most relevant to the underlying mechanisms of a complex disease such as AUD. We illustrate an example of how genomic studies in animal models can be used to produce robust gene networks that have functional implications, and to integrate such animal model genomic data with human genetic studies such as GWAS for AUD. We describe several useful analysis tools for such studies: ComBAT, WGCNA, and EW_dmGWAS. The end result of this analysis is a ranking of gene networks and identification of their cognate hub genes, which might provide eventual targets for future therapeutic development. Furthermore, this combined approach may also improve our understanding of basic mechanisms underlying gene x

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

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.

Genomics Portals: integrative web-platform for mining genomics data

Directory of Open Access Journals (Sweden)

Ghosh Krishnendu

2010-01-01

Full Text Available Abstract Background A large amount of experimental data generated by modern high-throughput technologies is available through various public repositories. Our knowledge about molecular interaction networks, functional biological pathways and transcriptional regulatory modules is rapidly expanding, and is being organized in lists of functionally related genes. Jointly, these two sources of information hold a tremendous potential for gaining new insights into functioning of living systems. Results Genomics Portals platform integrates access to an extensive knowledge base and a large database of human, mouse, and rat genomics data with basic analytical visualization tools. It provides the context for analyzing and interpreting new experimental data and the tool for effective mining of a large number of publicly available genomics datasets stored in the back-end databases. The uniqueness of this platform lies in the volume and the diversity of genomics data that can be accessed and analyzed (gene expression, ChIP-chip, ChIP-seq, epigenomics, computationally predicted binding sites, etc, and the integration with an extensive knowledge base that can be used in such analysis. Conclusion The integrated access to primary genomics data, functional knowledge and analytical tools makes Genomics Portals platform a unique tool for interpreting results of new genomics experiments and for mining the vast amount of data stored in the Genomics Portals backend databases. Genomics Portals can be accessed and used freely at http://GenomicsPortals.org.

SolCyc: a database hub at the Sol Genomics Network (SGN) for the manual curation of metabolic networks in Solanum and Nicotiana specific databases

Science.gov (United States)

Foerster, Hartmut; Bombarely, Aureliano; Battey, James N D; Sierro, Nicolas; Ivanov, Nikolai V; Mueller, Lukas A

2018-01-01

Abstract SolCyc is the entry portal to pathway/genome databases (PGDBs) for major species of the Solanaceae family hosted at the Sol Genomics Network. Currently, SolCyc comprises six organism-specific PGDBs for tomato, potato, pepper, petunia, tobacco and one Rubiaceae, coffee. The metabolic networks of those PGDBs have been computationally predicted by the pathologic component of the pathway tools software using the manually curated multi-domain database MetaCyc (http://www.metacyc.org/) as reference. SolCyc has been recently extended by taxon-specific databases, i.e. the family-specific SolanaCyc database, containing only curated data pertinent to species of the nightshade family, and NicotianaCyc, a genus-specific database that stores all relevant metabolic data of the Nicotiana genus. Through manual curation of the published literature, new metabolic pathways have been created in those databases, which are complemented by the continuously updated, relevant species-specific pathways from MetaCyc. At present, SolanaCyc comprises 199 pathways and 29 superpathways and NicotianaCyc accounts for 72 pathways and 13 superpathways. Curator-maintained, taxon-specific databases such as SolanaCyc and NicotianaCyc are characterized by an enrichment of data specific to these taxa and free of falsely predicted pathways. Both databases have been used to update recently created Nicotiana-specific databases for Nicotiana tabacum, Nicotiana benthamiana, Nicotiana sylvestris and Nicotiana tomentosiformis by propagating verifiable data into those PGDBs. In addition, in-depth curation of the pathways in N.tabacum has been carried out which resulted in the elimination of 156 pathways from the 569 pathways predicted by pathway tools. Together, in-depth curation of the predicted pathway network and the supplementation with curated data from taxon-specific databases has substantially improved the curation status of the species–specific N.tabacum PGDB. The implementation of this

The cluster analysis based on non-teacher artificial neural network for the danger prediction of coal spontaneous fire

Energy Technology Data Exchange (ETDEWEB)

Wang, D.; Wang, J. [China University of Mining and Technology (China)

1999-04-01

This paper focuses on the problem of predicting the danger level of spontaneous fire in coal mines. Firstly, the inadequacy of the present artificial neural networks prediction model is analysed. Then a new cluster model based on non-teacher neural network is constructed according to the danger judgement standards given by experts. On this basis, by adopting the error square sum criterion and its algorithm, the corresponding prediction software is developed and applied in two working faces of Chaili Coal Mine. The forecasting result is importantly significant for the prevention of spontaneous fire. 4 refs., 1 fig., 1 tab.

Genome projects and the functional-genomic era.

Science.gov (United States)

Sauer, Sascha; Konthur, Zoltán; Lehrach, Hans

2005-12-01

The problems we face today in public health as a result of the -- fortunately -- increasing age of people and the requirements of developing countries create an urgent need for new and innovative approaches in medicine and in agronomics. Genomic and functional genomic approaches have a great potential to at least partially solve these problems in the future. Important progress has been made by procedures to decode genomic information of humans, but also of other key organisms. The basic comprehension of genomic information (and its transfer) should now give us the possibility to pursue the next important step in life science eventually leading to a basic understanding of biological information flow; the elucidation of the function of all genes and correlative products encoded in the genome, as well as the discovery of their interactions in a molecular context and the response to environmental factors. As a result of the sequencing projects, we are now able to ask important questions about sequence variation and can start to comprehensively study the function of expressed genes on different levels such as RNA, protein or the cell in a systematic context including underlying networks. In this article we review and comment on current trends in large-scale systematic biological research. A particular emphasis is put on technology developments that can provide means to accomplish the tasks of future lines of functional genomics.

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.

Increasing Secondary Teachers' Capacity to Integrate the Arts

Science.gov (United States)

Richard, Byron; Treichel, Christa J.

2013-01-01

Examples from a team of collaborating secondary teachers--one visual arts teacher and one science teacher--highlight key aspects of this professional development project in arts integration. The article traces a regional network designed to build teacher capacity with implications for the design, effectiveness, and sustainability of professional…

Learners in dialogue. Teacher experise and learning in the context of genetic testing

NARCIS (Netherlands)

van der Zande, P.A.M.|info:eu-repo/dai/nl/304827363

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

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.

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

When teacher clusters work: selected experiences of South African ...

African Journals Online (AJOL)

Recent scholarship on teacher professional development has shown renewed interest in collaborative forms of teacher learning. Networks, communities of practice and clusters are related concepts that describe forms of collaboration between schools and/or teachers that encourage such learning. In South Africa, teacher ...

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.

Genome-wide association studies dissect the genetic networks underlying agronomical traits in soybean.

Science.gov (United States)

Fang, Chao; Ma, Yanming; Wu, Shiwen; Liu, Zhi; Wang, Zheng; Yang, Rui; Hu, Guanghui; Zhou, Zhengkui; Yu, Hong; Zhang, Min; Pan, Yi; Zhou, Guoan; Ren, Haixiang; Du, Weiguang; Yan, Hongrui; Wang, Yanping; Han, Dezhi; Shen, Yanting; Liu, Shulin; Liu, Tengfei; Zhang, Jixiang; Qin, Hao; Yuan, Jia; Yuan, Xiaohui; Kong, Fanjiang; Liu, Baohui; Li, Jiayang; Zhang, Zhiwu; Wang, Guodong; Zhu, Baoge; Tian, Zhixi

2017-08-24

Soybean (Glycine max [L.] Merr.) is one of the most important oil and protein crops. Ever-increasing soybean consumption necessitates the improvement of varieties for more efficient production. However, both correlations among different traits and genetic interactions among genes that affect a single trait pose a challenge to soybean breeding. To understand the genetic networks underlying phenotypic correlations, we collected 809 soybean accessions worldwide and phenotyped them for two years at three locations for 84 agronomic traits. Genome-wide association studies identified 245 significant genetic loci, among which 95 genetically interacted with other loci. We determined that 14 oil synthesis-related genes are responsible for fatty acid accumulation in soybean and function in line with an additive model. Network analyses demonstrated that 51 traits could be linked through the linkage disequilibrium of 115 associated loci and these links reflect phenotypic correlations. We revealed that 23 loci, including the known Dt1, E2, E1, Ln, Dt2, Fan, and Fap loci, as well as 16 undefined associated loci, have pleiotropic effects on different traits. This study provides insights into the genetic correlation among complex traits and will facilitate future soybean functional studies and breeding through molecular design.

MOST-visualization: software for producing automated textbook-style maps of genome-scale metabolic networks.

Science.gov (United States)

Kelley, James J; Maor, Shay; Kim, Min Kyung; Lane, Anatoliy; Lun, Desmond S

2017-08-15

Visualization of metabolites, reactions and pathways in genome-scale metabolic networks (GEMs) can assist in understanding cellular metabolism. Three attributes are desirable in software used for visualizing GEMs: (i) automation, since GEMs can be quite large; (ii) production of understandable maps that provide ease in identification of pathways, reactions and metabolites; and (iii) visualization of the entire network to show how pathways are interconnected. No software currently exists for visualizing GEMs that satisfies all three characteristics, but MOST-Visualization, an extension of the software package MOST (Metabolic Optimization and Simulation Tool), satisfies (i), and by using a pre-drawn overview map of metabolism based on the Roche map satisfies (ii) and comes close to satisfying (iii). MOST is distributed for free on the GNU General Public License. The software and full documentation are available at http://most.ccib.rutgers.edu/. dslun@rutgers.edu. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

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.

How Teachers Learn and Change in Reciprocal Learning Space

Institute of Scientific and Technical Information of China (English)

Xuefeng HUANG

2017-01-01

This paper reports the impact of a new Canada and China school network on its participating teachers in the context of the Canada-China Partnership Grant Project.Eight schools formed four pairs of sister schools,and teachers in these schools created collaborations embedded in their practices.The data include interviews of teachers and principals in both countries and records of teachers' cross-cultural collaborations.Informed by the literature on teacher learning and professional learning communities,this paper shows benefits of international teacher communities.Also,it explores a new approach to research that features spatiality considerations reflecting a new trend in the comparative education literature.Focusing on teacher knowledge and practice,it shows reciprocal effects of collaboration in the international school network.Finally,this paper links the research results to the literature in a way that highlights the potential of international teacher professional learning communities and contributions of this kind of practice and research.

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

Coping in an HIV/AIDS-dominated context: teachers promoting resilience in schools.

Science.gov (United States)

Ebersöhn, Liesel; Ferreira, Ronél

2011-08-01

This paper explains how teachers in schools function as resources to buoy resilience in the face of human immunodeficiency virus/acquired immune deficiency syndrome-compounded adversities. We draw on participatory reflection and action data from a longitudinal study with teachers (n = 57, 5 males, 52 females) from six schools in three South African provinces. The study tracks the psychosocial support offered by teachers following their participation in the Supportive Teachers, Assets and Resilience project. Verbatim interview transcriptions were thematically analysed and three themes (as well as subthemes and categories) emerged: (i) Teachers use resources to promote resilience in schools [teachers use (a) systems and (b) neighbourhood health and social development services to identify and refer vulnerable cases]; (ii) Teachers form partnerships to promote resilience in schools [teacher partnerships include (a) children and families, (b) community volunteers and (c) community organizations, businesses and government] and (iii) School-based support is offered to vulnerable individuals [by means of (a) vegetable gardens, (b) emotional and health support and (c) capacity development opportunities]. We conclude that teachers can promote resilience in schools by establishing networks with service providers that function across systems to support vulnerable groups. We theorize that the core of systemic networks is relationships, that relationship-driven support networks mitigate the effects of cumulative risk and school-based networks can enable schools to function as resilience-promoting resources.

Design and Realization of Network Teaching System

Directory of Open Access Journals (Sweden)

Ji Shan Shan

2016-01-01

Full Text Available Since 21 century, with the wide spread in family and public, network has been applied in many new fields, and the application in classes is of no exception. In traditional education, teachers give lessons to students face to face. Hence, the teaching quality depends largely on the quality and initiative of the individual teacher. However, the serious disadvantages of this mode are that teachers completely dominate the classroom and may ignore the subjective cognition role of the students, which may be bad for the growth of creativity and the innovative thinking ability. Obviously, traditional education mode cannot meet the requirements of the this new era which leads to the booming developing tendency of the network. As a new teaching measure, scientifically combining modern information technology and teaching practice, network teaching not only changes the traditional education by the means and form, but even also gives new meanings to teaching concept, process, method as well as teacher-student role and other deep levels. With the help of network teaching system, on-line classroom learning, relevant information systematization, standardization and automation, this system provides students with an efficient online learning method with high quality. This also helps to solve the disadvantages of the traditional teaching mode and promote the teaching methods to a new stage. It improves the network teaching platform, enriches the network teaching resources, and establishes a network teaching system, so as to improve information quality of teachers and students and assist in improving teaching quality of schools.

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 sapiens is driven by the evolution of human-specific genomic regulatory networks via at least two mechanistically distinct pathways of creation of

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. Published by Oxford University Press 2017. This work is written by US Government employees and are in the public domain in the US.

TCGA study identifies genomic features of cervical cancer

Science.gov (United States)

Investigators with The Cancer Genome Atlas (TCGA) Research Network have identified novel genomic and molecular characteristics of cervical cancer that will aid in subclassification of the disease and may help target therapies that are most appropriate for each patient.

Modeling genome-wide dynamic regulatory network in mouse lungs with influenza infection using high-dimensional ordinary differential equations.

Science.gov (United States)

Wu, Shuang; Liu, Zhi-Ping; Qiu, Xing; Wu, Hulin

2014-01-01

The immune response to viral infection is regulated by an intricate network of many genes and their products. The reverse engineering of gene regulatory networks (GRNs) using mathematical models from time course gene expression data collected after influenza infection is key to our understanding of the mechanisms involved in controlling influenza infection within a host. A five-step pipeline: detection of temporally differentially expressed genes, clustering genes into co-expressed modules, identification of network structure, parameter estimate refinement, and functional enrichment analysis, is developed for reconstructing high-dimensional dynamic GRNs from genome-wide time course gene expression data. Applying the pipeline to the time course gene expression data from influenza-infected mouse lungs, we have identified 20 distinct temporal expression patterns in the differentially expressed genes and constructed a module-based dynamic network using a linear ODE model. Both intra-module and inter-module annotations and regulatory relationships of our inferred network show some interesting findings and are highly consistent with existing knowledge about the immune response in mice after influenza infection. The proposed method is a computationally efficient, data-driven pipeline bridging experimental data, mathematical modeling, and statistical analysis. The application to the influenza infection data elucidates the potentials of our pipeline in providing valuable insights into systematic modeling of complicated biological processes.

Overseas Teachers and Assistants--Making Their Stay Worthwhile.

Science.gov (United States)

Wilson, James; Sarre, Winifred

1993-01-01

Presents general comments outlining the major features of the needs of teachers and assistants from overseas and discusses in-school needs and roles of such teachers and assistants separately. These comments touch on salary, social networks, family support, accommodation, general induction, the position of the native-speaking teacher, important…

Genome-wide association study of smoking initiation and current smoking

DEFF Research Database (Denmark)

Vink, Jacqueline M; Smit, August B; de Geus, Eco J C

2009-01-01

For the identification of genes associated with smoking initiation and current smoking, genome-wide association analyses were carried out in 3497 subjects. Significant genes that replicated in three independent samples (n = 405, 5810, and 1648) were visualized into a biologically meaningful network......) and cell-adhesion molecules (e.g., CDH23). We conclude that a network-based genome-wide association approach can identify genes influencing smoking behavior....

Generalizing genetical genomics: getting added value from environmental perturbation.

Science.gov (United States)

Li, Yang; Breitling, Rainer; Jansen, Ritsert C

2008-10-01

Genetical genomics is a useful approach for studying the effect of genetic perturbations on biological systems at the molecular level. However, molecular networks depend on the environmental conditions and, thus, a comprehensive understanding of biological systems requires studying them across multiple environments. We propose a generalization of genetical genomics, which combines genetic and sensibly chosen environmental perturbations, to study the plasticity of molecular networks. This strategy forms a crucial step toward understanding why individuals respond differently to drugs, toxins, pathogens, nutrients and other environmental influences. Here we outline a strategy for selecting and allocating individuals to particular treatments, and we discuss the promises and pitfalls of the generalized genetical genomics approach.

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.

Genome-wide association study and annotating candidate gene networks affecting age at first calving in Nellore cattle.

Science.gov (United States)

Mota, R R; Guimarães, S E F; Fortes, M R S; Hayes, B; Silva, F F; Verardo, L L; Kelly, M J; de Campos, C F; Guimarães, J D; Wenceslau, R R; Penitente-Filho, J M; Garcia, J F; Moore, S

2017-12-01

We performed a genome-wide mapping for the age at first calving (AFC) with the goal of annotating candidate genes that regulate fertility in Nellore cattle. Phenotypic data from 762 cows and 777k SNP genotypes from 2,992 bulls and cows were used. Single nucleotide polymorphism (SNP) effects based on the single-step GBLUP methodology were blocked into adjacent windows of 1 Megabase (Mb) to explain the genetic variance. SNP windows explaining more than 0.40% of the AFC genetic variance were identified on chromosomes 2, 8, 9, 14, 16 and 17. From these windows, we identified 123 coding protein genes that were used to build gene networks. From the association study and derived gene networks, putative candidate genes (e.g., PAPPA, PREP, FER1L6, TPR, NMNAT1, ACAD10, PCMTD1, CRH, OPKR1, NPBWR1 and NCOA2) and transcription factors (TF) (STAT1, STAT3, RELA, E2F1 and EGR1) were strongly associated with female fertility (e.g., negative regulation of luteinizing hormone secretion, folliculogenesis and establishment of uterine receptivity). Evidence suggests that AFC inheritance is complex and controlled by multiple loci across the genome. As several windows explaining higher proportion of the genetic variance were identified on chromosome 14, further studies investigating the interaction across haplotypes to better understand the molecular architecture behind AFC in Nellore cattle should be undertaken. © 2017 Blackwell Verlag GmbH.

Integration of Genome Scale Metabolic Networks and Gene Regulation of Metabolic Enzymes With Physiologically Based Pharmacokinetics.

Science.gov (United States)

Maldonado, Elaina M; Leoncikas, Vytautas; Fisher, Ciarán P; Moore, J Bernadette; Plant, Nick J; Kierzek, Andrzej M

2017-11-01

The scope of physiologically based pharmacokinetic (PBPK) modeling can be expanded by assimilation of the mechanistic models of intracellular processes from systems biology field. The genome scale metabolic networks (GSMNs) represent a whole set of metabolic enzymes expressed in human tissues. Dynamic models of the gene regulation of key drug metabolism enzymes are available. Here, we introduce GSMNs and review ongoing work on integration of PBPK, GSMNs, and metabolic gene regulation. We demonstrate example models. © 2017 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.

Genomic Enzymology: Web Tools for Leveraging Protein Family Sequence-Function Space and Genome Context to Discover Novel Functions.

Science.gov (United States)

Gerlt, John A

2017-08-22

The exponentially increasing number of protein and nucleic acid sequences provides opportunities to discover novel enzymes, metabolic pathways, and metabolites/natural products, thereby adding to our knowledge of biochemistry and biology. The challenge has evolved from generating sequence information to mining the databases to integrating and leveraging the available information, i.e., the availability of "genomic enzymology" web tools. Web tools that allow identification of biosynthetic gene clusters are widely used by the natural products/synthetic biology community, thereby facilitating the discovery of novel natural products and the enzymes responsible for their biosynthesis. However, many novel enzymes with interesting mechanisms participate in uncharacterized small-molecule metabolic pathways; their discovery and functional characterization also can be accomplished by leveraging information in protein and nucleic acid databases. This Perspective focuses on two genomic enzymology web tools that assist the discovery novel metabolic pathways: (1) Enzyme Function Initiative-Enzyme Similarity Tool (EFI-EST) for generating sequence similarity networks to visualize and analyze sequence-function space in protein families and (2) Enzyme Function Initiative-Genome Neighborhood Tool (EFI-GNT) for generating genome neighborhood networks to visualize and analyze the genome context in microbial and fungal genomes. Both tools have been adapted to other applications to facilitate target selection for enzyme discovery and functional characterization. As the natural products community has demonstrated, the enzymology community needs to embrace the essential role of web tools that allow the protein and genome sequence databases to be leveraged for novel insights into enzymological problems.

Annotating non-coding regions of the genome.

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Alexander, Roger P; Fang, Gang; Rozowsky, Joel; Snyder, Michael; Gerstein, Mark B

2010-08-01

Most of the human genome consists of non-protein-coding DNA. Recently, progress has been made in annotating these non-coding regions through the interpretation of functional genomics experiments and comparative sequence analysis. One can conceptualize functional genomics analysis as involving a sequence of steps: turning the output of an experiment into a 'signal' at each base pair of the genome; smoothing this signal and segmenting it into small blocks of initial annotation; and then clustering these small blocks into larger derived annotations and networks. Finally, one can relate functional genomics annotations to conserved units and measures of conservation derived from comparative sequence analysis.

Bladder Cancer Advocacy Network

Science.gov (United States)

... Grants Bladder Cancer Think Tank Bladder Cancer Research Network Bladder Cancer Genomics Consortium Get Involved Ways to ... us? Who we are The Bladder Cancer Advocacy Network (BCAN) is a community of patients, caregivers, survivors, ...

The Role of Informal Support Networks in Teaching the Nature of Science

Science.gov (United States)

Herman, Benjamin C.; Olson, Joanne K.; Clough, Michael P.

2017-06-01

This study reports the participation of 13 secondary science teachers in informal support networks and how that participation was associated with their nature of science (NOS) teaching practices 2 to 5 years after having graduated from the same science teacher education program. The nine teachers who participated in informal support networks taught the NOS at high/medium levels, while the four non-participating teachers taught the NOS at low levels. The nine high/medium NOS implementation teachers credited the informal support networks for maintaining/heightening their sense of responsibility for teaching NOS and for helping them navigate institutional constraints that impede effective NOS instruction. Several high/medium NOS instruction implementers initially struggled to autonomously frame and resolve the complexities experienced in schools and thus drew from the support networks to engage in more sophisticated forms of teacher decision-making. In contrast, the NOS pedagogical decisions of the four teachers not participating in support networks were governed primarily by the expectations and constraints experienced in their schools. Implications of this study include the need for reconsidering the structure of teacher mentorship programs to ensure they do not promote archaic science teaching practices that are at odds with reform efforts in science education.

A novel component of the mitochondrial genome segregation machinery in trypanosomes

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Anneliese Hoffmann

2016-07-01

Full Text Available We recently described a new component (TAC102 of the mitochondrial genome segregation machinery (mtGSM in the protozoan parasite Trypanosoma brucei. T. brucei belongs to a group of organisms that contain a single mitochondrial organelle with a single mitochondrial genome (mt-genome per cell. The mt-genome consists of 5000 minicircles (1 kb and 25 maxicircles (23 kb that are catenated into a large network. After replication of the network its segregation is driven by the separating basal bodies, which are homologous structures to the centrioles organizing the spindle apparatus in many eukaryotes. The structure connecting the basal body to the mt-genome was named the Tripartite Attachment Complex (TAC owing its name to the distribution across three areas in the cell including the two mitochondrial membranes.

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.

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.

Research Capacity-Building with New Technologies within New Communities of Practice: Reflections on the First Year of the Teacher Education Research Network

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Fowler, Zoe; Stanley, Grant; Murray, Jean; Jones, Marion; McNamara, Olwen

2013-01-01

This article focuses on a virtual research environment (VRE) and how it facilitated the networking of teacher educators participating in an Economic and Social Research Council-funded research capacity-building project. Using the theoretical lenses of situated learning and socio-cultural approaches to literacy, participants' ways of engaging with…

Teacher-Student Relationship and Facebook-Mediated Communication: Student Perceptions

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Hershkovzt, Arnon; Forkosh-Baruch, Alona

2017-01-01

Student-teacher relationships are vital to successful learning and teaching. Today, communication between students and teachers, a major component through which these relationships are facilitated, is taking place via social networking sites (SNS). In this study, we examined the associations between student-teacher relationship and student-teacher…

Puzzles in modern biology. V. Why are genomes overwired? [version 2; referees: 2 approved

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Steven A. Frank

2017-08-01

Full Text Available Many factors affect eukaryotic gene expression. Transcription factors, histone codes, DNA folding, and noncoding RNA modulate expression. Those factors interact in large, broadly connected regulatory control networks. An engineer following classical principles of control theory would design a simpler regulatory network. Why are genomes overwired? Neutrality or enhanced robustness may lead to the accumulation of additional factors that complicate network architecture. Dynamics progresses like a ratchet. New factors get added. Genomes adapt to the additional complexity. The newly added factors can no longer be removed without significant loss of fitness. Alternatively, highly wired genomes may be more malleable. In large networks, most genomic variants tend to have a relatively small effect on gene expression and trait values. Many small effects lead to a smooth gradient, in which traits may change steadily with respect to underlying regulatory changes. A smooth gradient may provide a continuous path from a starting point up to the highest peak of performance. A potential path of increasing performance promotes adaptability and learning. Genomes gain by the inductive process of natural selection, a trial and error learning algorithm that discovers general solutions for adapting to environmental challenge. Similarly, deeply and densely connected computational networks gain by various inductive trial and error learning procedures, in which the networks learn to reduce the errors in sequential trials. Overwiring alters the geometry of induction by smoothing the gradient along the inductive pathways of improving performance. Those overwiring benefits for induction apply to both natural biological networks and artificial deep learning networks.

Keystone Life Orientation (LO) teachers: Implications for educational ...

African Journals Online (AJOL)

Keystone Life Orientation (LO) teachers: Implications for educational, social, and ... characteristics and support networks needed by keystone Life Orientation (LO) ... In this study “keystone” refers to LO teachers who make a positive impact in ...

bNEAT: a Bayesian network method for detecting epistatic interactions in genome-wide association studies

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Chen Xue-wen

2011-07-01

Full Text Available Abstract Background Detecting epistatic interactions plays a significant role in improving pathogenesis, prevention, diagnosis and treatment of complex human diseases. A recent study in automatic detection of epistatic interactions shows that Markov Blanket-based methods are capable of finding genetic variants strongly associated with common diseases and reducing false positives when the number of instances is large. Unfortunately, a typical dataset from genome-wide association studies consists of very limited number of examples, where current methods including Markov Blanket-based method may perform poorly. Results To address small sample problems, we propose a Bayesian network-based approach (bNEAT to detect epistatic interactions. The proposed method also employs a Branch-and-Bound technique for learning. We apply the proposed method to simulated datasets based on four disease models and a real dataset. Experimental results show that our method outperforms Markov Blanket-based methods and other commonly-used methods, especially when the number of samples is small. Conclusions Our results show bNEAT can obtain a strong power regardless of the number of samples and is especially suitable for detecting epistatic interactions with slight or no marginal effects. The merits of the proposed approach lie in two aspects: a suitable score for Bayesian network structure learning that can reflect higher-order epistatic interactions and a heuristic Bayesian network structure learning method.

Stakeholder engagement: a key component of integrating genomic information into electronic health records.

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Hartzler, Andrea; McCarty, Catherine A; Rasmussen, Luke V; Williams, Marc S; Brilliant, Murray; Bowton, Erica A; Clayton, Ellen Wright; Faucett, William A; Ferryman, Kadija; Field, Julie R; Fullerton, Stephanie M; Horowitz, Carol R; Koenig, Barbara A; McCormick, Jennifer B; Ralston, James D; Sanderson, Saskia C; Smith, Maureen E; Trinidad, Susan Brown

2013-10-01

Integrating genomic information into clinical care and the electronic health record can facilitate personalized medicine through genetically guided clinical decision support. Stakeholder involvement is critical to the success of these implementation efforts. Prior work on implementation of clinical information systems provides broad guidance to inform effective engagement strategies. We add to this evidence-based recommendations that are specific to issues at the intersection of genomics and the electronic health record. We describe stakeholder engagement strategies employed by the Electronic Medical Records and Genomics Network, a national consortium of US research institutions funded by the National Human Genome Research Institute to develop, disseminate, and apply approaches that combine genomic and electronic health record data. Through select examples drawn from sites of the Electronic Medical Records and Genomics Network, we illustrate a continuum of engagement strategies to inform genomic integration into commercial and homegrown electronic health records across a range of health-care settings. We frame engagement as activities to consult, involve, and partner with key stakeholder groups throughout specific phases of health information technology implementation. Our aim is to provide insights into engagement strategies to guide genomic integration based on our unique network experiences and lessons learned within the broader context of implementation research in biomedical informatics. On the basis of our collective experience, we describe key stakeholder practices, challenges, and considerations for successful genomic integration to support personalized medicine.

Overrepresentation of glutamate signaling in Alzheimer's disease: network-based pathway enrichment using meta-analysis of genome-wide association studies.

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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.

Classroom Computer Network.

Science.gov (United States)

Lent, John

1984-01-01

This article describes a computer network system that connects several microcomputers to a single disk drive and one copy of software. Many schools are switching to networks as a cheaper and more efficient means of computer instruction. Teachers may be faced with copywriting problems when reproducing programs. (DF)

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

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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.

The Schoolhouse Network: How School Buildings Affect Teacher Collaboration

Science.gov (United States)

Spillane, James P.; Shirrell, Matthew

2018-01-01

In recent years, teacher collaboration has emerged as an important strategy to drive improvement, informed by research showing how on-the-job interactions can boost teacher development and effectiveness. Schools across the United States are adjusting their professional cultures and workplace practices in response, creating formal opportunities for…

Genome-wide identification of key modulators of gene-gene interaction networks in breast cancer.

Science.gov (United States)

Chiu, Yu-Chiao; Wang, Li-Ju; Hsiao, Tzu-Hung; Chuang, Eric Y; Chen, Yidong

2017-10-03

With the advances in high-throughput gene profiling technologies, a large volume of gene interaction maps has been constructed. A higher-level layer of gene-gene interaction, namely modulate gene interaction, is composed of gene pairs of which interaction strengths are modulated by (i.e., dependent on) the expression level of a key modulator gene. Systematic investigations into the modulation by estrogen receptor (ER), the best-known modulator gene, have revealed the functional and prognostic significance in breast cancer. However, a genome-wide identification of key modulator genes that may further unveil the landscape of modulated gene interaction is still lacking. We proposed a systematic workflow to screen for key modulators based on genome-wide gene expression profiles. We designed four modularity parameters to measure the ability of a putative modulator to perturb gene interaction networks. Applying the method to a dataset of 286 breast tumors, we comprehensively characterized the modularity parameters and identified a total of 973 key modulator genes. The modularity of these modulators was verified in three independent breast cancer datasets. ESR1, the encoding gene of ER, appeared in the list, and abundant novel modulators were illuminated. For instance, a prognostic predictor of breast cancer, SFRP1, was found the second modulator. Functional annotation analysis of the 973 modulators revealed involvements in ER-related cellular processes as well as immune- and tumor-associated functions. Here we present, as far as we know, the first comprehensive analysis of key modulator genes on a genome-wide scale. The validity of filtering parameters as well as the conservativity of modulators among cohorts were corroborated. Our data bring new insights into the modulated layer of gene-gene interaction and provide candidates for further biological investigations.

RegPrecise 3.0--a resource for genome-scale exploration of transcriptional regulation in bacteria.

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Novichkov, Pavel S; Kazakov, Alexey E; Ravcheev, Dmitry A; Leyn, Semen A; Kovaleva, Galina Y; Sutormin, Roman A; Kazanov, Marat D; Riehl, William; Arkin, Adam P; Dubchak, Inna; Rodionov, Dmitry A

2013-11-01

Genome-scale prediction of gene regulation and reconstruction of transcriptional regulatory networks in prokaryotes is one of the critical tasks of modern genomics. Bacteria from different taxonomic groups, whose lifestyles and natural environments are substantially different, possess highly diverged transcriptional regulatory networks. The comparative genomics approaches are useful for in silico reconstruction of bacterial regulons and networks operated by both transcription factors (TFs) and RNA regulatory elements (riboswitches). RegPrecise (http://regprecise.lbl.gov) is a web resource for collection, visualization and analysis of transcriptional regulons reconstructed by comparative genomics. We significantly expanded a reference collection of manually curated regulons we introduced earlier. RegPrecise 3.0 provides access to inferred regulatory interactions organized by phylogenetic, structural and functional properties. Taxonomy-specific collections include 781 TF regulogs inferred in more than 160 genomes representing 14 taxonomic groups of Bacteria. TF-specific collections include regulogs for a selected subset of 40 TFs reconstructed across more than 30 taxonomic lineages. Novel collections of regulons operated by RNA regulatory elements (riboswitches) include near 400 regulogs inferred in 24 bacterial lineages. RegPrecise 3.0 provides four classifications of the reference regulons implemented as controlled vocabularies: 55 TF protein families; 43 RNA motif families; ~150 biological processes or metabolic pathways; and ~200 effectors or environmental signals. Genome-wide visualization of regulatory networks and metabolic pathways covered by the reference regulons are available for all studied genomes. A separate section of RegPrecise 3.0 contains draft regulatory networks in 640 genomes obtained by an conservative propagation of the reference regulons to closely related genomes. RegPrecise 3.0 gives access to the transcriptional regulons reconstructed in

Ethical Considerations Related to Return of Results from Genomic Medicine Projects: The eMERGE Network (Phase III) Experience

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Fossey, Robyn; Kochan, David; Winkler, Erin; Pacyna, Joel E.; Olson, Janet; Thibodeau, Stephen; Connolly, John J.; Harr, Margaret; Behr, Meckenzie A.; Prows, Cynthia A.; Cobb, Beth; Myers, Melanie F.; Leslie, Nancy D.; Namjou-Khales, Bahram; Milo Rasouly, Hila; Wynn, Julia; Fedotov, Alexander; Chung, Wendy K.; Gharavi, Ali; Williams, Janet L.; Pais, Lynn; Holm, Ingrid; Aufox, Sharon; Smith, Maureen E.; Scrol, Aaron; Leppig, Kathleen; Jarvik, Gail P.; Wiesner, Georgia L.; Li, Rongling; Stroud, Mary; Smoller, Jordan W.; Sharp, Richard R.; Kullo, Iftikhar J.

2018-01-01

We examined the Institutional Review Board (IRB) process at 9 academic institutions in the electronic Medical Records and Genomics (eMERGE) Network, for proposed electronic health record-based genomic medicine studies, to identify common questions and concerns. Sequencing of 109 disease related genes and genotyping of 14 actionable variants is being performed in ~28,100 participants from the 9 sites. Pathogenic/likely pathogenic variants in actionable genes are being returned to study participants. We examined each site’s research protocols, informed-consent materials, and interactions with IRB staff. Research staff at each site completed questionnaires regarding their IRB interactions. The time to prepare protocols for IRB submission, number of revisions and time to approval ranged from 10–261 days, 0–11, and 11–90 days, respectively. IRB recommendations related to the readability of informed consent materials, specifying the full range of potential risks, providing options for receiving limited results or withdrawal, sharing of information with family members, and establishing the mechanisms to answer participant questions. IRBs reviewing studies that involve the return of results from genomic sequencing have a diverse array of concerns, and anticipating these concerns can help investigators to more effectively engage IRBs. PMID:29301385

Body maps on the human genome.

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Cherniak, Christopher; Rodriguez-Esteban, Raul

2013-12-20

Chromosomes have territories, or preferred locales, in the cell nucleus. When these sites are taken into account, some large-scale structure of the human genome emerges. The synoptic picture is that genes highly expressed in particular topologically compact tissues are not randomly distributed on the genome. Rather, such tissue-specific genes tend to map somatotopically onto the complete chromosome set. They seem to form a "genome homunculus": a multi-dimensional, genome-wide body representation extending across chromosome territories of the entire spermcell nucleus. The antero-posterior axis of the body significantly corresponds to the head-tail axis of the nucleus, and the dorso-ventral body axis to the central-peripheral nucleus axis. This large-scale genomic structure includes thousands of genes. One rationale for a homuncular genome structure would be to minimize connection costs in genetic networks. Somatotopic maps in cerebral cortex have been reported for over a century.

Teacher Professional Development with an Education for ...

African Journals Online (AJOL)

This national case study reports on the development of a national network, curriculum framework and resources for teacher education, with specific focus on the inclusion of environment and sustainability, also known as education for sustainable development (ESD) in the South African teacher education system. It reviews ...

Students' Voice: The Hopes and Fears of Student-Teacher Candidates

Science.gov (United States)

Shoyer, Shirli; Leshem, Shosh

2016-01-01

It is widely claimed that learners interpret new information and experiences through their existing network of knowledge, experience, and beliefs. Research on professional identities of teachers highlight the impact of biographical factors such as teachers schooling experiences, motivations for entering teacher education programs, their initial…

Cross-family translational genomics of abiotic stress-responsive genes between Arabidopsis and Medicago truncatula.

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Daejin Hyung

Full Text Available Cross-species translation of genomic information may play a pivotal role in applying biological knowledge gained from relatively simple model system to other less studied, but related, genomes. The information of abiotic stress (ABS-responsive genes in Arabidopsis was identified and translated into the legume model system, Medicago truncatula. Various data resources, such as TAIR/AtGI DB, expression profiles and literatures, were used to build a genome-wide list of ABS genes. tBlastX/BlastP similarity search tools and manual inspection of alignments were used to identify orthologous genes between the two genomes. A total of 1,377 genes were finally collected and classified into 18 functional criteria of gene ontology (GO. The data analysis according to the expression cues showed that there was substantial level of interaction among three major types (i.e., drought, salinity and cold stress of abiotic stresses. In an attempt to translate the ABS genes between these two species, genomic locations for each gene were mapped using an in-house-developed comparative analysis platform. The comparative analysis revealed that fragmental colinearity, represented by only 37 synteny blocks, existed between Arabidopsis and M. truncatula. Based on the combination of E-value and alignment remarks, estimated translation rate was 60.2% for this cross-family translation. As a prelude of the functional comparative genomic approaches, in-silico gene network/interactome analyses were conducted to predict key components in the ABS responses, and one of the sub-networks was integrated with corresponding comparative map. The results demonstrated that core members of the sub-network were well aligned with previously reported ABS regulatory networks. Taken together, the results indicate that network-based integrative approaches of comparative and functional genomics are important to interpret and translate genomic information for complex traits such as abiotic stresses.

Genome-wide network-based pathway analysis of CSF t-tau/Aβ1-42 ratio in the ADNI cohort.

Science.gov (United States)

Cong, Wang; Meng, Xianglian; Li, Jin; Zhang, Qiushi; Chen, Feng; Liu, Wenjie; Wang, Ying; Cheng, Sipu; Yao, Xiaohui; Yan, Jingwen; Kim, Sungeun; Saykin, Andrew J; Liang, Hong; Shen, Li

2017-05-30

The cerebrospinal fluid (CSF) levels of total tau (t-tau) and Aβ 1-42 are potential early diagnostic markers for probable Alzheimer's disease (AD). The influence of genetic variation on these CSF biomarkers has been investigated in candidate or genome-wide association studies (GWAS). However, the investigation of statistically modest associations in GWAS in the context of biological networks is still an under-explored topic in AD studies. The main objective of this study is to gain further biological insights via the integration of statistical gene associations in AD with physical protein interaction networks. The CSF and genotyping data of 843 study subjects (199 CN, 85 SMC, 239 EMCI, 207 LMCI, 113 AD) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) were analyzed. PLINK was used to perform GWAS on the t-tau/Aβ 1-42 ratio using quality controlled genotype data, including 563,980 single nucleotide polymorphisms (SNPs), with age, sex and diagnosis as covariates. Gene-level p-values were obtained by VEGAS2. Genes with p-value ≤ 0.05 were mapped on to a protein-protein interaction (PPI) network (9,617 nodes, 39,240 edges, from the HPRD Database). We integrated a consensus model strategy into the iPINBPA network analysis framework, and named it as CM-iPINBPA. Four consensus modules (CMs) were discovered by CM-iPINBPA, and were functionally annotated using the pathway analysis tool Enrichr. The intersection of four CMs forms a common subnetwork of 29 genes, including those related to tau phosphorylation (GSK3B, SUMO1, AKAP5, CALM1 and DLG4), amyloid beta production (CASP8, PIK3R1, PPA1, PARP1, CSNK2A1, NGFR, and RHOA), and AD (BCL3, CFLAR, SMAD1, and HIF1A). This study coupled a consensus module (CM) strategy with the iPINBPA network analysis framework, and applied it to the GWAS of CSF t-tau/Aβ1-42 ratio in an AD study. The genome-wide network analysis yielded 4 enriched CMs that share not only genes related to tau phosphorylation or amyloid beta

The sunflower genome provides insights into oil metabolism, flowering and Asterid evolution.

Science.gov (United States)

Badouin, Hélène; Gouzy, Jérôme; Grassa, Christopher J; Murat, Florent; Staton, S Evan; Cottret, Ludovic; Lelandais-Brière, Christine; Owens, Gregory L; Carrère, Sébastien; Mayjonade, Baptiste; Legrand, Ludovic; Gill, Navdeep; Kane, Nolan C; Bowers, John E; Hubner, Sariel; Bellec, Arnaud; Bérard, Aurélie; Bergès, Hélène; Blanchet, Nicolas; Boniface, Marie-Claude; Brunel, Dominique; Catrice, Olivier; Chaidir, Nadia; Claudel, Clotilde; Donnadieu, Cécile; Faraut, Thomas; Fievet, Ghislain; Helmstetter, Nicolas; King, Matthew; Knapp, Steven J; Lai, Zhao; Le Paslier, Marie-Christine; Lippi, Yannick; Lorenzon, Lolita; Mandel, Jennifer R; Marage, Gwenola; Marchand, Gwenaëlle; Marquand, Elodie; Bret-Mestries, Emmanuelle; Morien, Evan; Nambeesan, Savithri; Nguyen, Thuy; Pegot-Espagnet, Prune; Pouilly, Nicolas; Raftis, Frances; Sallet, Erika; Schiex, Thomas; Thomas, Justine; Vandecasteele, Céline; Varès, Didier; Vear, Felicity; Vautrin, Sonia; Crespi, Martin; Mangin, Brigitte; Burke, John M; Salse, Jérôme; Muños, Stéphane; Vincourt, Patrick; Rieseberg, Loren H; Langlade, Nicolas B

2017-06-01

The domesticated sunflower, Helianthus annuus L., is a global oil crop that has promise for climate change adaptation, because it can maintain stable yields across a wide variety of environmental conditions, including drought. Even greater resilience is achievable through the mining of resistance alleles from compatible wild sunflower relatives, including numerous extremophile species. Here we report a high-quality reference for the sunflower genome (3.6 gigabases), together with extensive transcriptomic data from vegetative and floral organs. The genome mostly consists of highly similar, related sequences and required single-molecule real-time sequencing technologies for successful assembly. Genome analyses enabled the reconstruction of the evolutionary history of the Asterids, further establishing the existence of a whole-genome triplication at the base of the Asterids II clade and a sunflower-specific whole-genome duplication around 29 million years ago. An integrative approach combining quantitative genetics, expression and diversity data permitted development of comprehensive gene networks for two major breeding traits, flowering time and oil metabolism, and revealed new candidate genes in these networks. We found that the genomic architecture of flowering time has been shaped by the most recent whole-genome duplication, which suggests that ancient paralogues can remain in the same regulatory networks for dozens of millions of years. This genome represents a cornerstone for future research programs aiming to exploit genetic diversity to improve biotic and abiotic stress resistance and oil production, while also considering agricultural constraints and human nutritional needs.

VitisNet: "Omics" integration through grapevine molecular networks.

Directory of Open Access Journals (Sweden)

Jérôme Grimplet

Full Text Available BACKGROUND: Genomic data release for the grapevine has increased exponentially in the last five years. The Vitis vinifera genome has been sequenced and Vitis EST, transcriptomic, proteomic, and metabolomic tools and data sets continue to be developed. The next critical challenge is to provide biological meaning to this tremendous amount of data by annotating genes and integrating them within their biological context. We have developed and validated a system of Grapevine Molecular Networks (VitisNet. METHODOLOGY/PRINCIPAL FINDINGS: The sequences from the Vitis vinifera (cv. Pinot Noir PN40024 genome sequencing project and ESTs from the Vitis genus have been paired and the 39,424 resulting unique sequences have been manually annotated. Among these, 13,145 genes have been assigned to 219 networks. The pathway sets include 88 "Metabolic", 15 "Genetic Information Processing", 12 "Environmental Information Processing", 3 "Cellular Processes", 21 "Transport", and 80 "Transcription Factors". The quantitative data is loaded onto molecular networks, allowing the simultaneous visualization of changes in the transcriptome, proteome, and metabolome for a given experiment. CONCLUSIONS/SIGNIFICANCE: VitisNet uses manually annotated networks in SBML or XML format, enabling the integration of large datasets, streamlining biological functional processing, and improving the understanding of dynamic processes in systems biology experiments. VitisNet is grounded in the Vitis vinifera genome (currently at 8x coverage and can be readily updated with subsequent updates of the genome or biochemical discoveries. The molecular network files can be dynamically searched by pathway name or individual genes, proteins, or metabolites through the MetNet Pathway database and web-portal at http://metnet3.vrac.iastate.edu/. All VitisNet files including the manual annotation of the grape genome encompassing pathway names, individual genes, their genome identifier, and chromosome

[Working and health conditions of preschool teachers of the public school network of Pelotas, State of Rio Grande do Sul, Brazil].

Science.gov (United States)

da Silva, Luciane Goulart; da Silva, Marcelo Cozzensa

2013-11-01

This study describes the working and health conditions of preschool teachers from the public school network in Pelotas, State of Rio Grande do Sul. A descriptive census was conducted in schools of the city and the state that offered preschool classes. The questionnaire included social and demographic, behavioral, nutritional, health and work issues. All teachers were female, more than 55% were classified as being overweight, 12.6% were smokers and 73% were not sufficiently physically active during their leisure time. With respect to the working conditions, 66.7% reported working in an uncomfortable posture, 40.5% considered the desks and furniture inadequate, 50.5% replied that the intervals between classes and activities are insufficient for resting. The prevalence of back, thoracic, neck and shoulder pain was high, and 17.8% tested positive for minor psychiatric disorders. The prevalence rates for occupational exposure and poor health conditions of preschool teachers are significant and can interfere in the quality of life and work of these individuals.

SCNS: a graphical tool for reconstructing executable regulatory networks from single-cell genomic data.

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Woodhouse, Steven; Piterman, Nir; Wintersteiger, Christoph M; Göttgens, Berthold; Fisher, Jasmin

2018-05-25

Reconstruction of executable mechanistic models from single-cell gene expression data represents a powerful approach to understanding developmental and disease processes. New ambitious efforts like the Human Cell Atlas will soon lead to an explosion of data with potential for uncovering and understanding the regulatory networks which underlie the behaviour of all human cells. In order to take advantage of this data, however, there is a need for general-purpose, user-friendly and efficient computational tools that can be readily used by biologists who do not have specialist computer science knowledge. The Single Cell Network Synthesis toolkit (SCNS) is a general-purpose computational tool for the reconstruction and analysis of executable models from single-cell gene expression data. Through a graphical user interface, SCNS takes single-cell qPCR or RNA-sequencing data taken across a time course, and searches for logical rules that drive transitions from early cell states towards late cell states. Because the resulting reconstructed models are executable, they can be used to make predictions about the effect of specific gene perturbations on the generation of specific lineages. SCNS should be of broad interest to the growing number of researchers working in single-cell genomics and will help further facilitate the generation of valuable mechanistic insights into developmental, homeostatic and disease processes.

Developing and Assessing Teachers' Knowledge of Game-Based Learning

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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…

Research and Mass Deployment of Non-cognitive Authentication Strategy Based on Campus Wireless Network

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Huangfu Dapeng

2018-01-01

Full Text Available With the rapid development of Internet +, the dependence on wireless networks and wireless terminals are increasing. Campus wireless network has become the main network of teachers and students in campus on the internet. As there are uneven clients and a wide variety of intelligent terminals now. Simplified authentication and network security become the most urgent problem for wireless network. This paper used the Portal + Mac authentication method to realize the non-cognitive authentication of teachers and students on basis of the analysis of the advantages and disadvantages of mainstream authentication of campus wireless network, such as 802.1X authentication, Portal authentication, Mac authentication and DHCP authentication. Teachers and students only need portal certification at the first time, then surf the internet with non-perceived authentication at the second time and later. This method increases network security, and is better to meet the needs of teachers and students.

A Genome-Wide Association Study and Complex Network Identify Four Core Hub Genes in Bipolar Disorder

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Zengyan Xie

2017-12-01

Full Text Available Bipolar disorder is a common and severe mental illness with unsolved pathophysiology. A genome-wide association study (GWAS has been used to find a number of risk genes, but it is difficult for a GWAS to find genes indirectly associated with a disease. To find core hub genes, we introduce a network analysis after the GWAS was conducted. Six thousand four hundred fifty eight single nucleotide polymorphisms (SNPs with p < 0.01 were sifted out from Wellcome Trust Case Control Consortium (WTCCC dataset and mapped to 2045 genes, which are then compared with the protein–protein network. One hundred twelve genes with a degree >17 were chosen as hub genes from which five significant modules and four core hub genes (FBXL13, WDFY2, bFGF, and MTHFD1L were found. These core hub genes have not been reported to be directly associated with BD but may function by interacting with genes directly related to BD. Our method engenders new thoughts on finding genes indirectly associated with, but important for, complex diseases.

The evolutionary value of recombination is constrained by genome modularity.

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Darren P Martin

2005-10-01

Full Text Available Genetic recombination is a fundamental evolutionary mechanism promoting biological adaptation. Using engineered recombinants of the small single-stranded DNA plant virus, Maize streak virus (MSV, we experimentally demonstrate that fragments of genetic material only function optimally if they reside within genomes similar to those in which they evolved. The degree of similarity necessary for optimal functionality is correlated with the complexity of intragenomic interaction networks within which genome fragments must function. There is a striking correlation between our experimental results and the types of MSV recombinants that are detectable in nature, indicating that obligatory maintenance of intragenome interaction networks strongly constrains the evolutionary value of recombination for this virus and probably for genomes in general.

"Harnessing genomics to improve health in Africa" – an executive course to support genomics policy

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Singer Peter A

2005-01-01

Full Text Available Abstract Background Africa in the twenty-first century is faced with a heavy burden of disease, combined with ill-equipped medical systems and underdeveloped technological capacity. A major challenge for the international community is to bring scientific and technological advances like genomics to bear on the health priorities of poorer countries. The New Partnership for Africa's Development has identified science and technology as a key platform for Africa's renewal. Recognizing the timeliness of this issue, the African Centre for Technology Studies and the University of Toronto Joint Centre for Bioethics co-organized a course on Genomics and Public Health Policy in Nairobi, Kenya, the first of a series of similar courses to take place in the developing world. This article presents the findings and recommendations that emerged from this process, recommendations which suggest that a regional approach to developing sound science and technology policies is the key to harnessing genome-related biotechnology to improve health and contribute to human development in Africa. Methods The objectives of the course were to familiarize participants with the current status and implications of genomics for health in Africa; to provide frameworks for analyzing and debating the policy and ethical questions; and to begin developing a network across different sectors by sharing perspectives and building relationships. To achieve these goals the course brought together a diverse group of stakeholders from academic research centres, the media, non-governmental, voluntary and legal organizations to stimulate multi-sectoral debate around issues of policy. Topics included scientific advances in genomics innovation systems and business models, international regulatory frameworks, as well as ethical and legal issues. Results Seven main recommendations emerged: establish a network for sustained dialogue among participants; identify champions among politicians; use the

Recapitulating phylogenies using k-mers: from trees to networks.

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Bernard, Guillaume; Ragan, Mark A; Chan, Cheong Xin

2016-01-01

Ernst Haeckel based his landmark Tree of Life on the supposed ontogenic recapitulation of phylogeny, i.e. that successive embryonic stages during the development of an organism re-trace the morphological forms of its ancestors over the course of evolution. Much of this idea has since been discredited. Today, phylogenies are often based on families of molecular sequences. The standard approach starts with a multiple sequence alignment, in which the sequences are arranged relative to each other in a way that maximises a measure of similarity position-by-position along their entire length. A tree (or sometimes a network) is then inferred. Rigorous multiple sequence alignment is computationally demanding, and evolutionary processes that shape the genomes of many microbes (bacteria, archaea and some morphologically simple eukaryotes) can add further complications. In particular, recombination, genome rearrangement and lateral genetic transfer undermine the assumptions that underlie multiple sequence alignment, and imply that a tree-like structure may be too simplistic. Here, using genome sequences of 143 bacterial and archaeal genomes, we construct a network of phylogenetic relatedness based on the number of shared k -mers (subsequences at fixed length k ). Our findings suggest that the network captures not only key aspects of microbial genome evolution as inferred from a tree, but also features that are not treelike. The method is highly scalable, allowing for investigation of genome evolution across a large number of genomes. Instead of using specific regions or sequences from genome sequences, or indeed Haeckel's idea of ontogeny, we argue that genome phylogenies can be inferred using k -mers from whole-genome sequences. Representing these networks dynamically allows biological questions of interest to be formulated and addressed quickly and in a visually intuitive manner.

Information processing in network architecture of genome controlled signal transduction circuit. A proposed theoretical explanation.

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Chakraborty, Chiranjib; Sarkar, Bimal Kumar; Patel, Pratiksha; Agoramoorthy, Govindasamy

2012-01-01

In this paper, Shannon information theory has been applied to elaborate cell signaling. It is proposed that in the cellular network architecture, four components viz. source (DNA), transmitter (mRNA), receiver (protein) and destination (another protein) are involved. The message transmits from source (DNA) to transmitter (mRNA) and then passes through a noisy channel reaching finally the receiver (protein). The protein synthesis process is here considered as the noisy channel. Ultimately, signal is transmitted from receiver to destination (another protein). The genome network architecture elements were compared with genetic alphabet L = {A, C, G, T} with a biophysical model based on the popular Shannon information theory. This study found the channel capacity as maximum for zero error (sigma = 0) and at this condition, transition matrix becomes a unit matrix with rank 4. The transition matrix will be erroneous and finally at sigma = 1 channel capacity will be localized maxima with a value of 0.415 due to the increased value at sigma. On the other hand, minima exists at sigma = 0.75, where all transition probabilities become 0.25 and uncertainty will be maximum resulting in channel capacity with the minima value of zero.

Are there laws of genome evolution?

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Eugene V Koonin

2011-08-01

Full Text Available Research in quantitative evolutionary genomics and systems biology led to the discovery of several universal regularities connecting genomic and molecular phenomic variables. These universals include the log-normal distribution of the evolutionary rates of orthologous genes; the power law-like distributions of paralogous family size and node degree in various biological networks; the negative correlation between a gene's sequence evolution rate and expression level; and differential scaling of functional classes of genes with genome size. The universals of genome evolution can be accounted for by simple mathematical models similar to those used in statistical physics, such as the birth-death-innovation model. These models do not explicitly incorporate selection; therefore, the observed universal regularities do not appear to be shaped by selection but rather are emergent properties of gene ensembles. Although a complete physical theory of evolutionary biology is inconceivable, the universals of genome evolution might qualify as "laws of evolutionary genomics" in the same sense "law" is understood in modern physics.

Characterizing steady states of genome-scale metabolic networks in continuous cell cultures.

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Jorge Fernandez-de-Cossio-Diaz

2017-11-01

Full Text Available In the continuous mode of cell culture, a constant flow carrying fresh media replaces culture fluid, cells, nutrients and secreted metabolites. Here we present a model for continuous cell culture coupling intra-cellular metabolism to extracellular variables describing the state of the bioreactor, taking into account the growth capacity of the cell and the impact of toxic byproduct accumulation. We provide a method to determine the steady states of this system that is tractable for metabolic networks of arbitrary complexity. We demonstrate our approach in a toy model first, and then in a genome-scale metabolic network of the Chinese hamster ovary cell line, obtaining results that are in qualitative agreement with experimental observations. We derive a number of consequences from the model that are independent of parameter values. The ratio between cell density and dilution rate is an ideal control parameter to fix a steady state with desired metabolic properties. This conclusion is robust even in the presence of multi-stability, which is explained in our model by a negative feedback loop due to toxic byproduct accumulation. A complex landscape of steady states emerges from our simulations, including multiple metabolic switches, which also explain why cell-line and media benchmarks carried out in batch culture cannot be extrapolated to perfusion. On the other hand, we predict invariance laws between continuous cell cultures with different parameters. A practical consequence is that the chemostat is an ideal experimental model for large-scale high-density perfusion cultures, where the complex landscape of metabolic transitions is faithfully reproduced.

Globalisation and Transnational Teachers: South African Teacher Migration to the UK

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Sadhana Manik

2006-06-01

Full Text Available The globalisation of the world markets has paved the way for the movement of people with scarce skills such as teachers across national boundaries with relative ease. This paper focuses on the migration of teachers from South Africa to the UK using a qualitative, ethnographic approach. It argues that there are socio-cultural complexities in the transnational migration of SA teachers. It begins by identifying the reasons for teachers exiting the SA teaching fraternity to work in schools in London in the UK. Teachers’ experiences in the UK schools are then explored. The study revealed that teachers leaving SA had multiple reasons for going abroad. The migration of teachers from SA to the UK was influenced by the declining economic status of teaching as a profession in SA, and global labour market conditions. The majority of the migrant teachers who were interviewed had an existing social network in the UK, either friends or relatives. However, the gravity of teaching in a foreign country without next of kin took its toll and teachers spoke at length of the loneliness of being apart from immediate family. An overwhelming majority of migrant teachers experienced a culture shock in UK classrooms, especially discipline problems. Migrant teachers felt powerless, as UK policies tend to protect children, even if they misbehaved in the classroom. The paper concludes by highlighting the commodification of teachers; those who are able to trade their skills in a global market in return for socio-economic and career gains. The arrival of this breed of teacher is also facilitated by what D. Harvey terms the “time-space compression” of global society.

The Global Invertebrate Genomics Alliance (GIGA): Developing Community Resources to Study Diverse Invertebrate Genomes

KAUST Repository

Bracken-Grissom, Heather

2013-12-12

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 challenges (e.g., species selection, sample collection and storage, sequence assembly, annotation, analytical tools) associated with genome/transcriptome sequencing across a large taxonomic spectrum. We aim to promote standards that will facilitate comparative approaches to invertebrate genomics and collaborations across the international scientific community. Candidate study taxa include species from Porifera, Ctenophora, Cnidaria, Placozoa, Mollusca, Arthropoda, Echinodermata, Annelida, Bryozoa, and Platyhelminthes, among others. GIGA will target 7000 noninsect/nonnematode species, with an emphasis on marine taxa because of the unrivaled phyletic diversity in the oceans. Priorities for selecting invertebrates for sequencing will include, but are not restricted to, their phylogenetic placement; relevance to organismal, ecological, and conservation research; and their importance to fisheries and human health. We highlight benefits of sequencing both whole genomes (DNA) and transcriptomes and also suggest policies for genomic-level data access and sharing based on transparency and inclusiveness. The GIGA Web site () has been launched to facilitate this collaborative venture.

Public Access for Teaching Genomics, Proteomics, and Bioinformatics

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Campbell, A. Malcolm

2003-01-01

When the human genome project was conceived, its leaders wanted all researchers to have equal access to the data and associated research tools. Their vision of equal access provides an unprecedented teaching opportunity. Teachers and students have free access to the same databases that researchers are using. Furthermore, the recent movement to…

The Mosaic Ancestry of the Drosophila Genetic Reference Panel and the D. melanogaster Reference Genome Reveals a Network of Epistatic Fitness Interactions

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Pool, John E.

2015-01-01

North American populations of Drosophila melanogaster derive from both European and African source populations, but despite their importance for genetic research, patterns of ancestry along their genomes are largely undocumented. Here, I infer geographic ancestry along genomes of the Drosophila Genetic Reference Panel (DGRP) and the D. melanogaster reference genome, which may have implications for reference alignment, association mapping, and population genomic studies in Drosophila. Overall, the proportion of African ancestry was estimated to be 20% for the DGRP and 9% for the reference genome. Combining my estimate of admixture timing with historical records, I provide the first estimate of natural generation time for this species (approximately 15 generations per year). Ancestry levels were found to vary strikingly across the genome, with less African introgression on the X chromosome, in regions of high recombination, and at genes involved in specific processes (e.g., circadian rhythm). An important role for natural selection during the admixture process was further supported by evidence that many unlinked pairs of loci showed a deficiency of Africa–Europe allele combinations between them. Numerous epistatic fitness interactions may therefore exist between African and European genotypes, leading to ongoing selection against incompatible variants. By focusing on hubs in this network of fitness interactions, I identified a set of interacting loci that include genes with roles in sensation and neuropeptide/hormone reception. These findings suggest that admixed D. melanogaster samples could become an important study system for the genetics of early-stage isolation between populations. PMID:26354524

The Plant Genome Integrative Explorer Resource: PlantGenIE.org.

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Sundell, David; Mannapperuma, Chanaka; Netotea, Sergiu; Delhomme, Nicolas; Lin, Yao-Cheng; Sjödin, Andreas; Van de Peer, Yves; Jansson, Stefan; Hvidsten, Torgeir R; Street, Nathaniel R

2015-12-01

Accessing and exploring large-scale genomics data sets remains a significant challenge to researchers without specialist bioinformatics training. We present the integrated PlantGenIE.org platform for exploration of Populus, conifer and Arabidopsis genomics data, which includes expression networks and associated visualization tools. Standard features of a model organism database are provided, including genome browsers, gene list annotation, Blast homology searches and gene information pages. Community annotation updating is supported via integration of WebApollo. We have produced an RNA-sequencing (RNA-Seq) expression atlas for Populus tremula and have integrated these data within the expression tools. An updated version of the ComPlEx resource for performing comparative plant expression analyses of gene coexpression network conservation between species has also been integrated. The PlantGenIE.org platform provides intuitive access to large-scale and genome-wide genomics data from model forest tree species, facilitating both community contributions to annotation improvement and tools supporting use of the included data resources to inform biological insight. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

Social Networking Sites in the Classroom: Unveiling New Roles for Teachers and New Approaches to Online Course Design

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Jorge Eduardo Pineda Hoyos

2014-12-01

Full Text Available Web 2.0 tools in general and social networking sites in particular are very popular today in everyday life. However, their use in education has not been explored. This paper reports the findings of the implementation of a web 2.0 tool namely a social networking site as a web support for a face-to-face course. The findings show that the implementation of a web-based environment in a face-to-face course can be viewed from 5 different managerial areas: (1 logistics management, (2 information/knowledge management, (3 communication management, (4 class work extension management and (5 web-based environment easiness of accessibility. The conclusions of the study show that the implementation of the web-based environment unveils new roles for teachers and new approaches to design online or blended courses.

Online collaboration, teachers training and ICT in the classroom: a case study

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Risoleta DE JESUS PINTO

2013-12-01

Full Text Available ICT is changing not only ways of life, but also the individuals’ minds and cultures of different social groups.  For these reason, it is supposed that schools appear as innovation centers focused on the network society. However, previous research accomplished under the Network of Municipal Observatories for Literacy and Digital Inclusion has revealed that despite teachers in primary schools acknowledge the importance of digital technologies and the Internet, they occasionally use these technologies, justifying this low level of use on a lack of pedagogical skills. Additionally, the single teacher in primary schools has led to cultures of professional isolation that hinder the dynamics of networking, a fundamental dimension to the promotion of digital literacy.Given these facts and the theoretical review about learning in virtual environments, we offered an online teachers training course about ICT to primary schools teachers, in Santarém, Portugal. The results enhance the positive value of joint dynamics among teachers, which contributes to their professional development, as well as leads to the inclusion of ICT in the classroom.

Combating Teacher Burnout

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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…

fastBMA: scalable network inference and transitive reduction.

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Hung, Ling-Hong; Shi, Kaiyuan; Wu, Migao; Young, William Chad; Raftery, Adrian E; Yeung, Ka Yee

2017-10-01

Inferring genetic networks from genome-wide expression data is extremely demanding computationally. We have developed fastBMA, a distributed, parallel, and scalable implementation of Bayesian model averaging (BMA) for this purpose. fastBMA also includes a computationally efficient module for eliminating redundant indirect edges in the network by mapping the transitive reduction to an easily solved shortest-path problem. We evaluated the performance of fastBMA on synthetic data and experimental genome-wide time series yeast and human datasets. When using a single CPU core, fastBMA is up to 100 times faster than the next fastest method, LASSO, with increased accuracy. It is a memory-efficient, parallel, and distributed application that scales to human genome-wide expression data. A 10 000-gene regulation network can be obtained in a matter of hours using a 32-core cloud cluster (2 nodes of 16 cores). fastBMA is a significant improvement over its predecessor ScanBMA. It is more accurate and orders of magnitude faster than other fast network inference methods such as the 1 based on LASSO. The improved scalability allows it to calculate networks from genome scale data in a reasonable time frame. The transitive reduction method can improve accuracy in denser networks. fastBMA is available as code (M.I.T. license) from GitHub (https://github.com/lhhunghimself/fastBMA), as part of the updated networkBMA Bioconductor package (https://www.bioconductor.org/packages/release/bioc/html/networkBMA.html) and as ready-to-deploy Docker images (https://hub.docker.com/r/biodepot/fastbma/). © The Authors 2017. Published by Oxford University Press.

Exploring photosynthesis evolution by comparative analysis of metabolic networks between chloroplasts and photosynthetic bacteria

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Hou Jing

2006-04-01

Full Text Available Abstract Background Chloroplasts descended from cyanobacteria and have a drastically reduced genome following an endosymbiotic event. Many genes of the ancestral cyanobacterial genome have been transferred to the plant nuclear genome by horizontal gene transfer. However, a selective set of metabolism pathways is maintained in chloroplasts using both chloroplast genome encoded and nuclear genome encoded enzymes. As an organelle specialized for carrying out photosynthesis, does the chloroplast metabolic network have properties adapted for higher efficiency of photosynthesis? We compared metabolic network properties of chloroplasts and prokaryotic photosynthetic organisms, mostly cyanobacteria, based on metabolic maps derived from genome data to identify features of chloroplast network properties that are different from cyanobacteria and to analyze possible functional significance of those features. Results The properties of the entire metabolic network and the sub-network that consists of reactions directly connected to the Calvin Cycle have been analyzed using hypergraph representation. Results showed that the whole metabolic networks in chloroplast and cyanobacteria both possess small-world network properties. Although the number of compounds and reactions in chloroplasts is less than that in cyanobacteria, the chloroplast's metabolic network has longer average path length, a larger diameter, and is Calvin Cycle -centered, indicating an overall less-dense network structure with specific and local high density areas in chloroplasts. Moreover, chloroplast metabolic network exhibits a better modular organization than cyanobacterial ones. Enzymes involved in the same metabolic processes tend to cluster into the same module in chloroplasts. Conclusion In summary, the differences in metabolic network properties may reflect the evolutionary changes during endosymbiosis that led to the improvement of the photosynthesis efficiency in higher plants. Our

NASE Training Courses in Astronomy for Teachers throughout the World

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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…

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......-construct knowledge using a wide range of resources for meaning making and expression of ideas. These outcomes were, however, contingent on the interplay of teacher understanding of the nature of science inquiry and school provision of an effective technological infrastructure and support for flexible curriculum...... of inquiry, the school must provide effective technological infrastructure and sympathetic curriculum parameters, and the students need to be carefully scaffolded to the point of engaging with the inquiry process. Within this study, e-networks supported students to exercise agency, collaborate, and co...

Children Using "Facebook": Teachers' Discursive Constructions of Childhood

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Chang-Kredl, Sandra; Kozak, Stephanie

2018-01-01

Conceptualizations of childhood are powerful determinants of adults' interactions with children, and technology and social networking systems are affecting the nature of teachers' knowledge of childhood. We analyzed questionnaire responses from 57 elementary-level teachers from Quebec regarding children's use of "Facebook". Through…

Complete genome sequence of the myxobacterium Sorangium cellulosum

DEFF Research Database (Denmark)

Schneiker, S; Perlova, O; Kaiser, O

2007-01-01

The genus Sorangium synthesizes approximately half of the secondary metabolites isolated from myxobacteria, including the anti-cancer metabolite epothilone. We report the complete genome sequence of the model Sorangium strain S. cellulosum Soce56, which produces several natural products and has...... morphological and physiological properties typical of the genus. The circular genome, comprising 13,033,779 base pairs, is the largest bacterial genome sequenced to date. No global synteny with the genome of Myxococcus xanthus is apparent, revealing an unanticipated level of divergence between...... these myxobacteria. A large percentage of the genome is devoted to regulation, particularly post-translational phosphorylation, which probably supports the strain's complex, social lifestyle. This regulatory network includes the highest number of eukaryotic protein kinase-like kinases discovered in any organism...

International classroom teachers in need of professional development

DEFF Research Database (Denmark)

Lauridsen, Karen M.

International classroom teachers in need of professional development: Outcomes of the IntlUni Erasmus Academic Network project 2012-15 The IntlUni Erasmus Academic Network (2012-15) has addressed the opportunities and the challenges of the multicultural (international) classroom where higher educ...... and challenges in the multilingual and multicultural learning space. Final document of the IntlUni Erasmus Academic Network project 2012-15. Aarhus: IntlUni. http://intluni.eu/uploads/media/The_opportunities_and_challenges_of_the_MMLS_Final_report_sept_2015.pdf...... and reflect on their teaching processes and negotiate the learning processes with their students as well as manage and leverage diversity in the classroom. Therefore, one of the IntlUni Recommendations is for the higher education institutions to provide the necessary professional development and teacher...... sources (e.g. Gregersen-Hermans, 2016), all pointing towards the need for more professional development and training of higher education teachers teaching multicultural student cohorts. Based on these very recent sources, the paper will discuss and offer examples of how such activities may be organized...

Prokaryote genome fluidity: toward a system approach of the mobilome.

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Toussaint, Ariane; Chandler, Mick

2012-01-01

The importance of horizontal/lateral gene transfer (LGT) in shaping the genomes of prokaryotic organisms has been recognized in recent years as a result of analysis of the increasing number of available genome sequences. LGT is largely due to the transfer and recombination activities of mobile genetic elements (MGEs). Bacterial and archaeal genomes are mosaics of vertically and horizontally transmitted DNA segments. This generates reticulate relationships between members of the prokaryotic world that are better represented by networks than by "classical" phylogenetic trees. In this review we summarize the nature and activities of MGEs, and the problems that presently limit their analysis on a large scale. We propose routes to improve their annotation in the flow of genomic and metagenomic sequences that currently exist and those that become available. We describe network analysis of evolutionary relationships among some MGE categories and sketch out possible developments of this type of approach to get more insight into the role of the mobilome in bacterial adaptation and evolution.

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

A network-based drug repositioning infrastructure for precision cancer medicine through targeting significantly mutated genes in the human cancer genomes.

Science.gov (United States)

Cheng, Feixiong; Zhao, Junfei; Fooksa, Michaela; Zhao, Zhongming

2016-07-01

Development of computational approaches and tools to effectively integrate multidomain data is urgently needed for the development of newly targeted cancer therapeutics. We proposed an integrative network-based infrastructure to identify new druggable targets and anticancer indications for existing drugs through targeting significantly mutated genes (SMGs) discovered in the human cancer genomes. The underlying assumption is that a drug would have a high potential for anticancer indication if its up-/down-regulated genes from the Connectivity Map tended to be SMGs or their neighbors in the human protein interaction network. We assembled and curated 693 SMGs in 29 cancer types and found 121 proteins currently targeted by known anticancer or noncancer (repurposed) drugs. We found that the approved or experimental cancer drugs could potentially target these SMGs in 33.3% of the mutated cancer samples, and this number increased to 68.0% by drug repositioning through surveying exome-sequencing data in approximately 5000 normal-tumor pairs from The Cancer Genome Atlas. Furthermore, we identified 284 potential new indications connecting 28 cancer types and 48 existing drugs (adjusted P < .05), with a 66.7% success rate validated by literature data. Several existing drugs (e.g., niclosamide, valproic acid, captopril, and resveratrol) were predicted to have potential indications for multiple cancer types. Finally, we used integrative analysis to showcase a potential mechanism-of-action for resveratrol in breast and lung cancer treatment whereby it targets several SMGs (ARNTL, ASPM, CTTN, EIF4G1, FOXP1, and STIP1). In summary, we demonstrated that our integrative network-based infrastructure is a promising strategy to identify potential druggable targets and uncover new indications for existing drugs to speed up molecularly targeted cancer therapeutics. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All

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.

Genomic features of lobular breast carcinoma

Science.gov (United States)

Investigators with The Cancer Genome Atlas (TCGA) Research Network have identified molecular characteristics of a type of breast cancer, invasive lobular carcinoma (ILC), that distinguishes it from invasive ductal carcinoma (IDC), the most common invasive breast cancer subtype.

Learning gene networks under SNP perturbations using eQTL datasets.

Directory of Open Access Journals (Sweden)

Lingxue Zhang

2014-02-01

Full Text Available The standard approach for identifying gene networks is based on experimental perturbations of gene regulatory systems such as gene knock-out experiments, followed by a genome-wide profiling of differential gene expressions. However, this approach is significantly limited in that it is not possible to perturb more than one or two genes simultaneously to discover complex gene interactions or to distinguish between direct and indirect downstream regulations of the differentially-expressed genes. As an alternative, genetical genomics study has been proposed to treat naturally-occurring genetic variants as potential perturbants of gene regulatory system and to recover gene networks via analysis of population gene-expression and genotype data. Despite many advantages of genetical genomics data analysis, the computational challenge that the effects of multifactorial genetic perturbations should be decoded simultaneously from data has prevented a widespread application of genetical genomics analysis. In this article, we propose a statistical framework for learning gene networks that overcomes the limitations of experimental perturbation methods and addresses the challenges of genetical genomics analysis. We introduce a new statistical model, called a sparse conditional Gaussian graphical model, and describe an efficient learning algorithm that simultaneously decodes the perturbations of gene regulatory system by a large number of SNPs to identify a gene network along with expression quantitative trait loci (eQTLs that perturb this network. While our statistical model captures direct genetic perturbations of gene network, by performing inference on the probabilistic graphical model, we obtain detailed characterizations of how the direct SNP perturbation effects propagate through the gene network to perturb other genes indirectly. We demonstrate our statistical method using HapMap-simulated and yeast eQTL datasets. In particular, the yeast gene network

An Assessment of Project Teacher Exchange for ASEAN Teachers (TEACH) Program

Science.gov (United States)

Agustin, Ma. Lourdes S.; Montebon, Darryl Roy T.

2018-01-01

Association of Southeast Asian Nations (ASEAN) integration aims to unite the South East Asian countries to promote better opportunities for the member countries in different areas such as economics and education. As a response, Philippine Normal University spearheaded the formation of the Association of Southeast Asian Teacher Education Network to…

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

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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.

The Mosaic Ancestry of the Drosophila Genetic Reference Panel and the D. melanogaster Reference Genome Reveals a Network of Epistatic Fitness Interactions.

Science.gov (United States)

Pool, John E

2015-12-01

North American populations of Drosophila melanogaster derive from both European and African source populations, but despite their importance for genetic research, patterns of ancestry along their genomes are largely undocumented. Here, I infer geographic ancestry along genomes of the Drosophila Genetic Reference Panel (DGRP) and the D. melanogaster reference genome, which may have implications for reference alignment, association mapping, and population genomic studies in Drosophila. Overall, the proportion of African ancestry was estimated to be 20% for the DGRP and 9% for the reference genome. Combining my estimate of admixture timing with historical records, I provide the first estimate of natural generation time for this species (approximately 15 generations per year). Ancestry levels were found to vary strikingly across the genome, with less African introgression on the X chromosome, in regions of high recombination, and at genes involved in specific processes (e.g., circadian rhythm). An important role for natural selection during the admixture process was further supported by evidence that many unlinked pairs of loci showed a deficiency of Africa-Europe allele combinations between them. Numerous epistatic fitness interactions may therefore exist between African and European genotypes, leading to ongoing selection against incompatible variants. By focusing on hubs in this network of fitness interactions, I identified a set of interacting loci that include genes with roles in sensation and neuropeptide/hormone reception. These findings suggest that admixed D. melanogaster samples could become an important study system for the genetics of early-stage isolation between populations. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Vocational Teacher Perceptions on the use of ICT in Learning Computer Network

Science.gov (United States)

Yannuar; Rohendi, D.; Yanti, H.; Nurhabibah; Mi'raj, Y. Z.

2018-02-01

ICT has been widely used in primary education to vocational schools, but has not been so clearly integrate ICT in the learning process. While the teacher is the key to the effective use of ICT processed. This paper reports a study of surveys that examine the perspective of vocational school teachers. Current research aims to examine a vocational school teacher knowledge about ICT and support for computer use for learning. The sample in this research group consists of 25 teachers of vocational schools. The findings of this research use descriptive method with engineering survey with sampling purposes. Resources in research is journals and book report research results. The results showed teachers have a positive outlook towards the use of ICT in learning. The conclusions resulting from this research is the use of ICT to help teachers be more effective in teaching in the classroom and can improve student learning.

Design And Planning Of E- Learning EnvironmentE-Education System On Heterogeneous Wireless Network Control System

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ThandarOo

2015-06-01

Full Text Available Abstract The purpose of this research is to provide a more efficient and effective communication method between teacher and student with the use of heterogeneous network. Moreover the effective use of heterogeneous network can be emphasized. The system of e-education can develop utilizing wireless network.The e-Education system can help students to communicate with their teacher more easily and effectively using a heterogeneous wireless network system. In this wireless network system students who are blind or dumb will also be able to communicate and learn from the teacher as normal students can do. All the devices or laptops will be connected on wireless LAN. Even when the teacher is not around he will be able to help his students with their study or give instructions easily by using the mobile phone to send text or voice signal. When the teacher sends information to the dumb student it will be converted into sign language for the student to be able to understand. When the dumb student sends the information to the teacher it will be converted into text for the teacher to understand. For the blind student text instructions from the teacher will be converted into audio signal using text-to-speech conversion.Thus the performance of heterogeneous wireless network model can evaluate by using Robust Optimization Method. Therefore the e-Education systems performance improves by evaluating Robust Optimization Method.

Use of genome-scale microbial models for metabolic engineering

DEFF Research Database (Denmark)

Patil, Kiran Raosaheb; Åkesson, M.; Nielsen, Jens

2004-01-01

Metabolic engineering serves as an integrated approach to design new cell factories by providing rational design procedures and valuable mathematical and experimental tools. Mathematical models have an important role for phenotypic analysis, but can also be used for the design of optimal metaboli...... network structures. The major challenge for metabolic engineering in the post-genomic era is to broaden its design methodologies to incorporate genome-scale biological data. Genome-scale stoichiometric models of microorganisms represent a first step in this direction....

Cyanobacterial Biofuels: Strategies and Developments on Network and Modeling.

Science.gov (United States)

Klanchui, Amornpan; Raethong, Nachon; Prommeenate, Peerada; Vongsangnak, Wanwipa; Meechai, Asawin

Cyanobacteria, the phototrophic microorganisms, have attracted much attention recently as a promising source for environmentally sustainable biofuels production. However, barriers for commercial markets of cyanobacteria-based biofuels concern the economic feasibility. Miscellaneous strategies for improving the production performance of cyanobacteria have thus been developed. Among these, the simple ad hoc strategies resulting in failure to optimize fully cell growth coupled with desired product yield are explored. With the advancement of genomics and systems biology, a new paradigm toward systems metabolic engineering has been recognized. In particular, a genome-scale metabolic network reconstruction and modeling is a crucial systems-based tool for whole-cell-wide investigation and prediction. In this review, the cyanobacterial genome-scale metabolic models, which offer a system-level understanding of cyanobacterial metabolism, are described. The main process of metabolic network reconstruction and modeling of cyanobacteria are summarized. Strategies and developments on genome-scale network and modeling through the systems metabolic engineering approach are advanced and employed for efficient cyanobacterial-based biofuels production.

Computer Networks as a New Data Base.

Science.gov (United States)

Beals, Diane E.

1992-01-01

Discusses the use of communication on computer networks as a data source for psychological, social, and linguistic research. Differences between computer-mediated communication and face-to-face communication are described, the Beginning Teacher Computer Network is discussed, and examples of network conversations are appended. (28 references) (LRW)

TELEVISION AND THE CONTINUING EDUCATION OF TEACHERS, A FEASIBILITY STUDY OF THE POTENTIAL OF NETWORK TELEVISION FOR DISSEMINATION OF EDUCATIONAL RESEARCH INFORMATION. FINAL REPORT.

Science.gov (United States)

CRESHKOFF, LAWRENCE

THIS 3-PHASE STUDY SOUGHT TO BRIDGE THE GAP BETWEEN THE PRODUCER OF NEW EDUCATIONAL IDEAS AND THE PRACTITIONER, OR TEACHER, BY EFFECTIVE USE OF NETWORK TELEVISION. PHASE I, DATA GATHERING, INCLUDED REVIEW OF THE LITERATURE, AND IDENTIFICATION OF INNOVATIONAL PROJECTS BY CONSULTATION, FIELD VISITS, AND A QUESTIONNAIRE SENT TO MEMBERS OF 2 NATIONAL…

Qualitative exploration of centralities in municipal science education networks

DEFF Research Database (Denmark)

von der Fehr, Ane; Sølberg, Jan

2016-01-01

This article examines the social nature of educational change by conducting a social network analysis of social networks involving stakeholders of science education from teachers to political stakeholders. Social networks that comprise supportive structures for development of science education ar...... of science education, especially if they are aware of their own centrality and are able to use their position intentionally for the benefit of science education.......This article examines the social nature of educational change by conducting a social network analysis of social networks involving stakeholders of science education from teachers to political stakeholders. Social networks that comprise supportive structures for development of science education...... are diverse and in order to understand how municipal stakeholders may support such development, we explored four different municipal science education networks (MSE networks) using three different measures of centrality. The centrality measures differed in terms of what kind of stakeholder functions...

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…

Modeling Lactococcus lactis using a genome-scale flux model

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Nielsen Jens

2005-06-01

Full Text Available Abstract Background Genome-scale flux models are useful tools to represent and analyze microbial metabolism. In this work we reconstructed the metabolic network of the lactic acid bacteria Lactococcus lactis and developed a genome-scale flux model able to simulate and analyze network capabilities and whole-cell function under aerobic and anaerobic continuous cultures. Flux balance analysis (FBA and minimization of metabolic adjustment (MOMA were used as modeling frameworks. Results The metabolic network was reconstructed using the annotated genome sequence from L. lactis ssp. lactis IL1403 together with physiological and biochemical information. The established network comprised a total of 621 reactions and 509 metabolites, representing the overall metabolism of L. lactis. Experimental data reported in the literature was used to fit the model to phenotypic observations. Regulatory constraints had to be included to simulate certain metabolic features, such as the shift from homo to heterolactic fermentation. A minimal medium for in silico growth was identified, indicating the requirement of four amino acids in addition to a sugar. Remarkably, de novo biosynthesis of four other amino acids was observed even when all amino acids were supplied, which is in good agreement with experimental observations. Additionally, enhanced metabolic engineering strategies for improved diacetyl producing strains were designed. Conclusion The L. lactis metabolic network can now be used for a better understanding of lactococcal metabolic capabilities and potential, for the design of enhanced metabolic engineering strategies and for integration with other types of 'omic' data, to assist in finding new information on cellular organization and function.

When teacher clusters work: selected experiences of South African teachers with the cluster approach to professional development

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Loyiso C Jita

2014-06-01

Full Text Available Recent scholarship on teacher professional development has shown renewed interest in collaborative forms of teacher learning. Networks, communities of practice and clusters are related concepts that describe forms of collaboration between schools and/or teachers that encourage such learning. In South Africa, teacher clusters represent a relatively recent and popular experiment in teacher professional development. However, there is no verdict yet about their effectiveness. While the utility of such collaborative structures for teacher learning is fairly well established in many developed countries, we still know very little about how the intended beneficiaries (the teachers experience these non-traditional structures of professional development. Using qualitative data from a large-scale research project, we explore teachers' perspectives on what constitutes a successful clustering experience, and the kinds of professional development benefits they derive from their participation therein. Our major findings are twofold: First, clusters seem to enhance teachers' content knowledge and pedagogical content knowledge. Second, and somewhat unexpectedly, the teachers identified another set of benefits, the so-called "process benefits" that include collaboration, instructional guidance and teacher leadership. In a context where teachers have tended to work solo and insulated their classroom practices from influence, the presence of the "process benefits" represents a significant finding. We conclude the paper by exploring several possible directions for further research on these process benefits of clusters for teachers in South Africa and elsewhere.

Conceptualising Changes to Pre-Service Teachers' Knowledge of How to Best Facilitate Learning in Mathematics: A TPACK Inspired Initiative

Science.gov (United States)

Bate, Frank G.; Day, Lorraine; Macnish, Jean

2013-01-01

In 2010, the Australian Commonwealth government initiated an $8m project called Teaching Teachers for the Future. The aim of the project was to engage teacher educators in a professional learning network which focused on optimising exemplary use of information and communications technologies in teacher education. By taking part in this network,…

Proteins Encoded in Genomic Regions Associated with Immune-Mediated Disease Physically Interact and Suggest Underlying Biology

DEFF Research Database (Denmark)

Rossin, Elizabeth J.; Hansen, Kasper Lage; Raychaudhuri, Soumya

2011-01-01

Genome-wide association studies (GWAS) have defined over 150 genomic regions unequivocally containing variation predisposing to immune-mediated disease. Inferring disease biology from these observations, however, hinges on our ability to discover the molecular processes being perturbed by these r......Genome-wide association studies (GWAS) have defined over 150 genomic regions unequivocally containing variation predisposing to immune-mediated disease. Inferring disease biology from these observations, however, hinges on our ability to discover the molecular processes being perturbed...... in rheumatoid arthritis (RA) and Crohn's disease (CD) GWAS, we build protein-protein interaction (PPI) networks for genes within associated loci and find abundant physical interactions between protein products of associated genes. We apply multiple permutation approaches to show that these networks are more...... that the RA and CD networks have predictive power by demonstrating that proteins in these networks, not encoded in the confirmed list of disease associated loci, are significantly enriched for association to the phenotypes in question in extended GWAS analysis. Finally, we test our method in 3 non...

Genome-wide RNAi Screen Identifies Networks Involved in Intestinal Stem Cell Regulation in Drosophila

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Xiankun Zeng

2015-02-01

Full Text Available The intestinal epithelium is the most rapidly self-renewing tissue in adult animals and maintained by intestinal stem cells (ISCs in both Drosophila and mammals. To comprehensively identify genes and pathways that regulate ISC fates, we performed a genome-wide transgenic RNAi screen in adult Drosophila intestine and identified 405 genes that regulate ISC maintenance and lineage-specific differentiation. By integrating these genes into publicly available interaction databases, we further developed functional networks that regulate ISC self-renewal, ISC proliferation, ISC maintenance of diploid status, ISC survival, ISC-to-enterocyte (EC lineage differentiation, and ISC-to-enteroendocrine (EE lineage differentiation. By comparing regulators among ISCs, female germline stem cells, and neural stem cells, we found that factors related to basic stem cell cellular processes are commonly required in all stem cells, and stem-cell-specific, niche-related signals are required only in the unique stem cell type. Our findings provide valuable insights into stem cell maintenance and lineage-specific differentiation.

Teachers Supporting Teachers in Urban Schools: What Iterative Research Designs Can Teach Us.

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Shernoff, Elisa S; Maríñez-Lora, Ane M; Frazier, Stacy L; Jakobsons, Lara J; Atkins, Marc S; Bonner, Deborah

2011-12-01

Despite alarming rates and negative consequences associated with urban teacher attrition, mentoring programs often fail to target the strongest predictors of attrition: effectiveness around classroom management and engaging learners; and connectedness to colleagues. Using a mixed-method iterative development framework, we highlight the process of developing and evaluating the feasibility of a multi-component professional development model for urban early career teachers. The model includes linking novices with peer-nominated key opinion leader teachers and an external coach who work together to (1) provide intensive support in evidence-based practices for classroom management and engaging learners, and (2) connect new teachers with their larger network of colleagues. Fidelity measures and focus group data illustrated varying attendance rates throughout the school year and that although seminars and professional learning communities were delivered as intended, adaptations to enhance the relevance, authenticity, level, and type of instrumental support were needed. Implications for science and practice are discussed.

LASSIM-A network inference toolbox for genome-wide mechanistic modeling.

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Rasmus Magnusson

2017-06-01

Full Text Available Recent technological advancements have made time-resolved, quantitative, multi-omics data available for many model systems, which could be integrated for systems pharmacokinetic use. Here, we present large-scale simulation modeling (LASSIM, which is a novel mathematical tool for performing large-scale inference using mechanistically defined ordinary differential equations (ODE for gene regulatory networks (GRNs. LASSIM integrates structural knowledge about regulatory interactions and non-linear equations with multiple steady state and dynamic response expression datasets. The rationale behind LASSIM is that biological GRNs can be simplified using a limited subset of core genes that are assumed to regulate all other gene transcription events in the network. The LASSIM method is implemented as a general-purpose toolbox using the PyGMO Python package to make the most of multicore computers and high performance clusters, and is available at https://gitlab.com/Gustafsson-lab/lassim. As a method, LASSIM works in two steps, where it first infers a non-linear ODE system of the pre-specified core gene expression. Second, LASSIM in parallel optimizes the parameters that model the regulation of peripheral genes by core system genes. We showed the usefulness of this method by applying LASSIM to infer a large-scale non-linear model of naïve Th2 cell differentiation, made possible by integrating Th2 specific bindings, time-series together with six public and six novel siRNA-mediated knock-down experiments. ChIP-seq showed significant overlap for all tested transcription factors. Next, we performed novel time-series measurements of total T-cells during differentiation towards Th2 and verified that our LASSIM model could monitor those data significantly better than comparable models that used the same Th2 bindings. In summary, the LASSIM toolbox opens the door to a new type of model-based data analysis that combines the strengths of reliable mechanistic models

Teacher Tweets Improve Achievement for Eighth Grade Science Students

OpenAIRE

Carol Van Vooren; Corey Bess

2013-01-01

In the Digital Age teachers have fallen far behind the technical skills of their "digital native" students. The implementation of technology as a tool for classroom communication is foreign for most teachers, but highly preferred by students. While teenagers are using Facebook, Twitter, and other social networks to communicate, teachers continue to respond through face-to-face conversations, telephone calls, and email messaging. Twitter, a platform for short message service text, is an online...

Genome-wide profiling of the PIWI-interacting RNA-mRNA regulatory networks in epithelial ovarian cancers.

Science.gov (United States)

Singh, Garima; Roy, Jyoti; Rout, Pratiti; Mallick, Bibekanand

2018-01-01

PIWI-interacting (piRNAs), ~23-36 nucleotide-long small non-coding RNAs (sncRNAs), earlier believed to be germline-specific, have now been identified in somatic cells, including cancer cells. These sncRNAs impact critical biological processes by fine-tuning gene expression at post-transcriptional and epigenetic levels. The expression of piRNAs in ovarian cancer, the most lethal gynecologic cancer is largely uncharted. In this study, we investigated the expression of PIWILs by qRT-PCR and western blotting and then identified piRNA transcriptomes in tissues of normal ovary and two most prevalent epithelial ovarian cancer subtypes, serous and endometrioid by small RNA sequencing. We detected 219, 256 and 234 piRNAs in normal ovary, endometrioid and serous ovarian cancer samples respectively. We observed piRNAs are encoded from various genomic regions, among which introns harbor the majority of them. Surprisingly, piRNAs originated from different genomic contexts showed the varied level of conservations across vertebrates. The functional analysis of predicted targets of differentially expressed piRNAs revealed these could modulate key processes and pathways involved in ovarian oncogenesis. Our study provides the first comprehensive piRNA landscape in these samples and a useful resource for further functional studies to decipher new mechanistic views of piRNA-mediated gene regulatory networks affecting ovarian oncogenesis. The RNA-seq data is submitted to GEO database (GSE83794).

Qualifying in-service education of Science Teachers (QUEST)

DEFF Research Database (Denmark)

Nielsen, Keld; Nielsen, Birgitte Lund; Pontoppidan, Birgitte

The Danish QUEST-project is a large-scale (450 teachers), long-term (4 years) professional development project for science teachers. The project aims at closing the gap between the present inconsequential practice in in-service education and recent research results documenting conditions for effe......The Danish QUEST-project is a large-scale (450 teachers), long-term (4 years) professional development project for science teachers. The project aims at closing the gap between the present inconsequential practice in in-service education and recent research results documenting conditions...... and peer involvement in collaborative practices in the school science teacher group is specifically addressed and targeted throughout the project. A special way of working (the QUEST-Rhythm) has been developed to increase the degree of teacher collaboration and networking over the 4 years. The accompanying...

QuIN: A Web Server for Querying and Visualizing Chromatin Interaction Networks.

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Asa Thibodeau

2016-06-01

Full Text Available Recent studies of the human genome have indicated that regulatory elements (e.g. promoters and enhancers at distal genomic locations can interact with each other via chromatin folding and affect gene expression levels. Genomic technologies for mapping interactions between DNA regions, e.g., ChIA-PET and HiC, can generate genome-wide maps of interactions between regulatory elements. These interaction datasets are important resources to infer distal gene targets of non-coding regulatory elements and to facilitate prioritization of critical loci for important cellular functions. With the increasing diversity and complexity of genomic information and public ontologies, making sense of these datasets demands integrative and easy-to-use software tools. Moreover, network representation of chromatin interaction maps enables effective data visualization, integration, and mining. Currently, there is no software that can take full advantage of network theory approaches for the analysis of chromatin interaction datasets. To fill this gap, we developed a web-based application, QuIN, which enables: 1 building and visualizing chromatin interaction networks, 2 annotating networks with user-provided private and publicly available functional genomics and interaction datasets, 3 querying network components based on gene name or chromosome location, and 4 utilizing network based measures to identify and prioritize critical regulatory targets and their direct and indirect interactions.QuIN's web server is available at http://quin.jax.org QuIN is developed in Java and JavaScript, utilizing an Apache Tomcat web server and MySQL database and the source code is available under the GPLV3 license available on GitHub: https://github.com/UcarLab/QuIN/.

QuIN: A Web Server for Querying and Visualizing Chromatin Interaction Networks.

Science.gov (United States)

Thibodeau, Asa; Márquez, Eladio J; Luo, Oscar; Ruan, Yijun; Menghi, Francesca; Shin, Dong-Guk; Stitzel, Michael L; Vera-Licona, Paola; Ucar, Duygu

2016-06-01

Recent studies of the human genome have indicated that regulatory elements (e.g. promoters and enhancers) at distal genomic locations can interact with each other via chromatin folding and affect gene expression levels. Genomic technologies for mapping interactions between DNA regions, e.g., ChIA-PET and HiC, can generate genome-wide maps of interactions between regulatory elements. These interaction datasets are important resources to infer distal gene targets of non-coding regulatory elements and to facilitate prioritization of critical loci for important cellular functions. With the increasing diversity and complexity of genomic information and public ontologies, making sense of these datasets demands integrative and easy-to-use software tools. Moreover, network representation of chromatin interaction maps enables effective data visualization, integration, and mining. Currently, there is no software that can take full advantage of network theory approaches for the analysis of chromatin interaction datasets. To fill this gap, we developed a web-based application, QuIN, which enables: 1) building and visualizing chromatin interaction networks, 2) annotating networks with user-provided private and publicly available functional genomics and interaction datasets, 3) querying network components based on gene name or chromosome location, and 4) utilizing network based measures to identify and prioritize critical regulatory targets and their direct and indirect interactions. QuIN's web server is available at http://quin.jax.org QuIN is developed in Java and JavaScript, utilizing an Apache Tomcat web server and MySQL database and the source code is available under the GPLV3 license available on GitHub: https://github.com/UcarLab/QuIN/.

Can a student learn optimally from two different teachers?

International Nuclear Information System (INIS)

Neirotti, J P

2010-01-01

We explore the effects of over-specificity in learning algorithms by investigating the behavior of a student, suited to learn optimally from a teacher B, learning from a teacher B' ≠ B. We only considered the supervised, on-line learning scenario with teachers selected from a particular family. We found that, in the general case, the application of the optimal algorithm to the wrong teacher produces a residual generalization error, even if the right teacher is harder. By imposing mild conditions to the learning algorithm form, we obtained an approximation for the residual generalization error. Simulations carried out in finite networks validate the estimate found.

A consensus yeast metabolic network reconstruction obtained from a community approach to systems biology

NARCIS (Netherlands)

Herrgård, Markus J.; Swainston, Neil; Dobson, Paul; Dunn, Warwick B.; Arga, K. Yalçin; Arvas, Mikko; Blüthgen, Nils; Borger, Simon; Costenoble, Roeland; Heinemann, Matthias; Hucka, Michael; Novère, Nicolas Le; Li, Peter; Liebermeister, Wolfram; Mo, Monica L.; Oliveira, Ana Paula; Petranovic, Dina; Pettifer, Stephen; Simeonidis, Evangelos; Smallbone, Kieran; Spasić, Irena; Weichart, Dieter; Brent, Roger; Broomhead, David S.; Westerhoff, Hans V.; Kırdar, Betül; Penttilä, Merja; Klipp, Edda; Palsson, Bernhard Ø.; Sauer, Uwe; Oliver, Stephen G.; Mendes, Pedro; Nielsen, Jens; Kell, Douglas B.

2008-01-01

Genomic data allow the large-scale manual or semi-automated assembly of metabolic network reconstructions, which provide highly curated organism-specific knowledge bases. Although several genome-scale network reconstructions describe Saccharomyces cerevisiae metabolism, they differ in scope and

Imputation and quality control steps for combining multiple genome-wide datasets

Directory of Open Access Journals (Sweden)

Shefali S Verma

2014-12-01

Full Text Available The electronic MEdical Records and GEnomics (eMERGE network brings together DNA biobanks linked to electronic health records (EHRs from multiple institutions. Approximately 52,000 DNA samples from distinct individuals have been genotyped using genome-wide SNP arrays across the nine sites of the network. The eMERGE Coordinating Center and the Genomics Workgroup developed a pipeline to impute and merge genomic data across the different SNP arrays to maximize sample size and power to detect associations with a variety of clinical endpoints. The 1000 Genomes cosmopolitan reference panel was used for imputation. Imputation results were evaluated using the following metrics: accuracy of imputation, allelic R2 (estimated correlation between the imputed and true genotypes, and the relationship between allelic R2 and minor allele frequency. Computation time and memory resources required by two different software packages (BEAGLE and IMPUTE2 were also evaluated. A number of challenges were encountered due to the complexity of using two different imputation software packages, multiple ancestral populations, and many different genotyping platforms. We present lessons learned and describe the pipeline implemented here to impute and merge genomic data sets. The eMERGE imputed dataset will serve as a valuable resource for discovery, leveraging the clinical data that can be mined from the EHR.

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

International Nuclear Information System (INIS)

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

2014-01-01

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. (paper)

FORMATION OF TEACHERS-TUTOR ICT COMPETENCE OF DISTANCE EDUCATION RESOURCE CENTER

Directory of Open Access Journals (Sweden)

Olga E. Konevchshynska

2014-09-01

Full Text Available The paper analyzes the main approaches to the definition of ICT competence of professionals who provide training and methodological support of distance learning. There is highlighted the level of scientific development of the problem, identified and proved the essence of teacher’s ICT competence, overviewed the international and domestic experience of teacher training in the the sphere of information technologies. It is indicated that one of the main tasks of resource centers for distance education is the provision of an appropriate level of qualification of teacher-tutor working in a network of resource centers. Also it is pointed out the levels of ICT competencies necessary for successful professional activity of network teachers.

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.

Research study on analysis/use technologies of genome information; Genome joho kaidoku riyo gijutsu no chosa kenkyu

Energy Technology Data Exchange (ETDEWEB)

NONE

1997-03-01

For wide use of genome information in the industrial field, the required R and D was surveyed from the standpoints of biology and information science. To clarify the present state and issues of the international research on genome analysis, the genome map as well as sequence and function information are first surveyed. The current analysis/use technologies of genome information are analyzed, and the following are summarized: prediction and identification of gene regions in genome sequences, techniques for searching and selecting useful genes, and techniques for predicting the expression of gene functions and the gene-product structure and functions. It is recommended that R and D and data collection/interpretation necessary to clarify inter-gene interactions and information networks should be promoted by integrating Japanese advanced know-how and technologies. As examples of the impact of the research results on industry and society, the present state and future expected effect are summarized for medicines, diagnosis/analysis instruments, chemicals, foods, agriculture, fishery, animal husbandry, electronics, environment and information. 278 refs., 42 figs., 5 tabs.

An expanding universe of the non-coding genome in cancer biology.

Science.gov (United States)

Xue, Bin; He, Lin

2014-06-01

Neoplastic transformation is caused by accumulation of genetic and epigenetic alterations that ultimately convert normal cells into tumor cells with uncontrolled proliferation and survival, unlimited replicative potential and invasive growth [Hanahan,D. et al. (2011) Hallmarks of cancer: the next generation. Cell, 144, 646-674]. Although the majority of the cancer studies have focused on the functions of protein-coding genes, emerging evidence has started to reveal the importance of the vast non-coding genome, which constitutes more than 98% of the human genome. A number of non-coding RNAs (ncRNAs) derived from the 'dark matter' of the human genome exhibit cancer-specific differential expression and/or genomic alterations, and it is increasingly clear that ncRNAs, including small ncRNAs and long ncRNAs (lncRNAs), play an important role in cancer development by regulating protein-coding gene expression through diverse mechanisms. In addition to ncRNAs, nearly half of the mammalian genomes consist of transposable elements, particularly retrotransposons. Once depicted as selfish genomic parasites that propagate at the expense of host fitness, retrotransposon elements could also confer regulatory complexity to the host genomes during development and disease. Reactivation of retrotransposons in cancer, while capable of causing insertional mutagenesis and genome rearrangements to promote oncogenesis, could also alter host gene expression networks to favor tumor development. Taken together, the functional significance of non-coding genome in tumorigenesis has been previously underestimated, and diverse transcripts derived from the non-coding genome could act as integral functional components of the oncogene and tumor suppressor network. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Know How? Show How: Experienced Teachers Share Best Practices through Ontario Program

Science.gov (United States)

Amato, Lindy; Anthony, Paul; Strachan, Jim

2014-01-01

Launched in 2007, the Teacher Learning and Leadership Program, out of Ontario, Canada, operates on the belief that classroom teachers know their learning needs and the needs of their students best. Additionally, the program assumes teachers have the greatest knowledge of how to build and foster multiple learning networks in order to share their…

The application of network teaching in applied optics teaching

Science.gov (United States)

Zhao, Huifu; Piao, Mingxu; Li, Lin; Liu, Dongmei

2017-08-01

Network technology has become a creative tool of changing human productivity, the rapid development of it has brought profound changes to our learning, working and life. Network technology has many advantages such as rich contents, various forms, convenient retrieval, timely communication and efficient combination of resources. Network information resources have become the new education resources, get more and more application in the education, has now become the teaching and learning tools. Network teaching enriches the teaching contents, changes teaching process from the traditional knowledge explanation into the new teaching process by establishing situation, independence and cooperation in the network technology platform. The teacher's role has shifted from teaching in classroom to how to guide students to learn better. Network environment only provides a good platform for the teaching, we can get a better teaching effect only by constantly improve the teaching content. Changchun university of science and technology introduced a BB teaching platform, on the platform, the whole optical classroom teaching and the classroom teaching can be improved. Teachers make assignments online, students learn independently offline or the group learned cooperatively, this expands the time and space of teaching. Teachers use hypertext form related knowledge of applied optics, rich cases and learning resources, set up the network interactive platform, homework submission system, message board, etc. The teaching platform simulated the learning interest of students and strengthens the interaction in the teaching.

Development and application of Human Genome Epidemiology

Science.gov (United States)

Xu, Jingwen

2017-12-01

Epidemiology is a science that studies distribution of diseases and health in population and its influencing factors, it also studies how to prevent and cure disease and promote health strategies and measures. Epidemiology has developed rapidly in recent years and it is an intercross subject with various other disciplines to form a series of branch disciplines such as Genetic epidemiology, molecular epidemiology, drug epidemiology and tumor epidemiology. With the implementation and completion of Human Genome Project (HGP), Human Genome Epidemiology (HuGE) has emerged at this historic moment. In this review, the development of Human Genome Epidemiology, research content, the construction and structure of relevant network, research standards, as well as the existing results and problems are briefly outlined.

Municipal consultants’ participation in building networks to support science teachers’ work

DEFF Research Database (Denmark)

Sillasen, Martin Krabbe; Valero, Paola

2013-01-01

This paper focuses particularly on the role of municipal science consultants in developing and maintaining network activities and connections among primary school science teachers. The hypothesis is that consultants play a crucial role in supporting strategic planning, and sustaining contacts...... and activities within professional learning networks. The research is framed by a project that involved 80 primary science teachers in 20 schools. The aim of the project was to develop network activities that facilitate sustainable change of the participating schools’ collective culture and practice of science...... science consultants’ participation in supporting network activities enable the participants to share and develop teaching activities....

CoryneRegNet: an ontology-based data warehouse of corynebacterial transcription factors and regulatory networks.

Science.gov (United States)

Baumbach, Jan; Brinkrolf, Karina; Czaja, Lisa F; Rahmann, Sven; Tauch, Andreas

2006-02-14

The application of DNA microarray technology in post-genomic analysis of bacterial genome sequences has allowed the generation of huge amounts of data related to regulatory networks. This data along with literature-derived knowledge on regulation of gene expression has opened the way for genome-wide reconstruction of transcriptional regulatory networks. These large-scale reconstructions can be converted into in silico models of bacterial cells that allow a systematic analysis of network behavior in response to changing environmental conditions. CoryneRegNet was designed to facilitate the genome-wide reconstruction of transcriptional regulatory networks of corynebacteria relevant in biotechnology and human medicine. During the import and integration process of data derived from experimental studies or literature knowledge CoryneRegNet generates links to genome annotations, to identified transcription factors and to the corresponding cis-regulatory elements. CoryneRegNet is based on a multi-layered, hierarchical and modular concept of transcriptional regulation and was implemented by using the relational database management system MySQL and an ontology-based data structure. Reconstructed regulatory networks can be visualized by using the yFiles JAVA graph library. As an application example of CoryneRegNet, we have reconstructed the global transcriptional regulation of a cellular module involved in SOS and stress response of corynebacteria. CoryneRegNet is an ontology-based data warehouse that allows a pertinent data management of regulatory interactions along with the genome-scale reconstruction of transcriptional regulatory networks. These models can further be combined with metabolic networks to build integrated models of cellular function including both metabolism and its transcriptional regulation.

Connectivity in the yeast cell cycle transcription network: inferences from neural networks.

Directory of Open Access Journals (Sweden)

Christopher E Hart

2006-12-01

Full Text Available A current challenge is to develop computational approaches to infer gene network regulatory relationships based on multiple types of large-scale functional genomic data. We find that single-layer feed-forward artificial neural network (ANN models can effectively discover gene network structure by integrating global in vivo protein:DNA interaction data (ChIP/Array with genome-wide microarray RNA data. We test this on the yeast cell cycle transcription network, which is composed of several hundred genes with phase-specific RNA outputs. These ANNs were robust to noise in data and to a variety of perturbations. They reliably identified and ranked 10 of 12 known major cell cycle factors at the top of a set of 204, based on a sum-of-squared weights metric. Comparative analysis of motif occurrences among multiple yeast species independently confirmed relationships inferred from ANN weights analysis. ANN models can capitalize on properties of biological gene networks that other kinds of models do not. ANNs naturally take advantage of patterns of absence, as well as presence, of factor binding associated with specific expression output; they are easily subjected to in silico "mutation" to uncover biological redundancies; and they can use the full range of factor binding values. A prominent feature of cell cycle ANNs suggested an analogous property might exist in the biological network. This postulated that "network-local discrimination" occurs when regulatory connections (here between MBF and target genes are explicitly disfavored in one network module (G2, relative to others and to the class of genes outside the mitotic network. If correct, this predicts that MBF motifs will be significantly depleted from the discriminated class and that the discrimination will persist through evolution. Analysis of distantly related Schizosaccharomyces pombe confirmed this, suggesting that network-local discrimination is real and complements well-known enrichment of

Codon based co-occurrence network motifs in human mitochondria

Directory of Open Access Journals (Sweden)

Pramod Shinde

2017-10-01

Full Text Available The nucleotide polymorphism in human mitochondrial genome (mtDNA tolled by codon position bias plays an indispensable role in human population dispersion and expansion. Herein, we constructed genome-wide nucleotide co-occurrence networks using a massive data consisting of five different geographical regions and around 3000 samples for each region. We developed a powerful network model to describe complex mitochondrial evolutionary patterns between codon and non-codon positions. It was interesting to report a different evolution of Asian genomes than those of the rest which is divulged by network motifs. We found evidence that mtDNA undergoes substantial amounts of adaptive evolution, a finding which was supported by a number of previous studies. The dominance of higher order motifs indicated the importance of long-range nucleotide co-occurrence in genomic diversity. Most notably, codon motifs apparently underpinned the preferences among codon positions for co-evolution which is probably highly biased during the origin of the genetic code. Our analyses manifested that codon position co-evolution is very well conserved across human sub-populations and independently maintained within human sub-populations implying the selective role of evolutionary processes on codon position co-evolution. Ergo, this study provided a framework to investigate cooperative genomic interactions which are critical in underlying complex mitochondrial evolution.

Simultaneous genome-wide inference of physical, genetic, regulatory, and functional pathway components.

Directory of Open Access Journals (Sweden)

Christopher Y Park

2010-11-01

Full Text Available Biomolecular pathways are built from diverse types of pairwise interactions, ranging from physical protein-protein interactions and modifications to indirect regulatory relationships. One goal of systems biology is to bridge three aspects of this complexity: the growing body of high-throughput data assaying these interactions; the specific interactions in which individual genes participate; and the genome-wide patterns of interactions in a system of interest. Here, we describe methodology for simultaneously predicting specific types of biomolecular interactions using high-throughput genomic data. This results in a comprehensive compendium of whole-genome networks for yeast, derived from ∼3,500 experimental conditions and describing 30 interaction types, which range from general (e.g. physical or regulatory to specific (e.g. phosphorylation or transcriptional regulation. We used these networks to investigate molecular pathways in carbon metabolism and cellular transport, proposing a novel connection between glycogen breakdown and glucose utilization supported by recent publications. Additionally, 14 specific predicted interactions in DNA topological change and protein biosynthesis were experimentally validated. We analyzed the systems-level network features within all interactomes, verifying the presence of small-world properties and enrichment for recurring network motifs. This compendium of physical, synthetic, regulatory, and functional interaction networks has been made publicly available through an interactive web interface for investigators to utilize in future research at http://function.princeton.edu/bioweaver/.

Meta genome-wide network from functional linkages of genes in human gut microbial ecosystems.

Science.gov (United States)

Ji, Yan; Shi, Yixiang; Wang, Chuan; Dai, Jianliang; Li, Yixue

2013-03-01

The human gut microbial ecosystem (HGME) exerts an important influence on the human health. In recent researches, meta-genomics provided deep insights into the HGME in terms of gene contents, metabolic processes and genome constitutions of meta-genome. Here we present a novel methodology to investigate the HGME on the basis of a set of functionally coupled genes regardless of their genome origins when considering the co-evolution properties of genes. By analyzing these coupled genes, we showed some basic properties of HGME significantly associated with each other, and further constructed a protein interaction map of human gut meta-genome to discover some functional modules that may relate with essential metabolic processes. Compared with other studies, our method provides a new idea to extract basic function elements from meta-genome systems and investigate complex microbial environment by associating its biological traits with co-evolutionary fingerprints encoded in it.

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.

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…

Network clustering coefficient approach to DNA sequence analysis

Energy Technology Data Exchange (ETDEWEB)

Gerhardt, Guenther J.L. [Universidade Federal do Rio Grande do Sul-Hospital de Clinicas de Porto Alegre, Rua Ramiro Barcelos 2350/sala 2040/90035-003 Porto Alegre (Brazil); Departamento de Fisica e Quimica da Universidade de Caxias do Sul, Rua Francisco Getulio Vargas 1130, 95001-970 Caxias do Sul (Brazil); Lemke, Ney [Programa Interdisciplinar em Computacao Aplicada, Unisinos, Av. Unisinos, 950, 93022-000 Sao Leopoldo, RS (Brazil); Corso, Gilberto [Departamento de Biofisica e Farmacologia, Centro de Biociencias, Universidade Federal do Rio Grande do Norte, Campus Universitario, 59072 970 Natal, RN (Brazil)]. E-mail: corso@dfte.ufrn.br

2006-05-15

In this work we propose an alternative DNA sequence analysis tool based on graph theoretical concepts. The methodology investigates the path topology of an organism genome through a triplet network. In this network, triplets in DNA sequence are vertices and two vertices are connected if they occur juxtaposed on the genome. We characterize this network topology by measuring the clustering coefficient. We test our methodology against two main bias: the guanine-cytosine (GC) content and 3-bp (base pairs) periodicity of DNA sequence. We perform the test constructing random networks with variable GC content and imposed 3-bp periodicity. A test group of some organisms is constructed and we investigate the methodology in the light of the constructed random networks. We conclude that the clustering coefficient is a valuable tool since it gives information that is not trivially contained in 3-bp periodicity neither in the variable GC content.

Teacher-student Relationship and SNS-mediated Communication: Perceptions of both role-players

Directory of Open Access Journals (Sweden)

Arnon Hershkovitz

2015-12-01

Full Text Available Teacher-student relationships are vital for academic and social development of students, for teachers’ professional and personal development, and for having a supportive learning environment. In the digital age, these relationships can extend beyond bricks and mortar and beyond school hours. Specifically, these relationships are extended today while teachers and students communicate via social networking sites (SNS. This paper characterizes differences between teachers (N=160 and students (N=587 who are willing to connect with their students/teachers via Facebook and those who do not wish to connect. The quantitative research reported here within is based on data collection of personal characteristics, attitudes towards Facebook, and perceptions of teacher-student relationship. Findings suggest differences in characteristics of the two groups (willing to connect vs. not willing to connect within both populations (teachers and students. Also, in both populations, those who were willing to connect, compared to those who were not willing to connect, present more positive attitudes towards using Facebook for teaching/learning and are more opposed to a banning policy of student-teacher SNS-based communication. We also found that students who were willing to connect showed a greater degree of closeness with their teachers compared to those who were not willing to connect. This study may assist policymakers when setting up regulations regarding teacher-student communication via social networking sites.

Dimensions of social learning in teacher education: an exemplary case study

NARCIS (Netherlands)

Van den Beemt, Antoine; Vrieling, Emmy

2016-01-01

Growing attention can be noticed for social learning in teacher groups as a stimulus for teachers’ professional development. Research shows the importance of understanding the role and impact of informal social networks on teacher professional development. This paper describes a rich case study of

The Influence of Teachers' Career Guidance Profiles on Students' Career Competencies

Science.gov (United States)

Mittendorff, Kariene; Beijaard, Douwe; den Brok, Perry; Koopman, Maaike

2012-01-01

In this article, we examine the relationship between different career guidance styles of vocational education teachers and vocational education students' career competencies (i.e. career reflection, career exploration and networking). Questionnaires on students' perceptions of the career guidance of their teachers during career conversations, and…

Genomic Perturbations Reveal Distinct Regulatory Networks in Intrahepatic Cholangiocarcinoma

DEFF Research Database (Denmark)

Nepal, Chirag; O'Rourke, Colm J; Oliveira, Douglas Vnp

2018-01-01

Intrahepatic cholangiocarcinoma (iCCA) remains a highly heterogeneous malignancy that has eluded effective patient stratification to date. The extent to which such heterogeneity can be influenced by individual driver mutations remains to be evaluated. Here, we analyzed genomic (whole-exome sequen...

Teacher Formation in the Mathematical Thinking through Problem Solving in the Second Phase of the CCyM Network of Reading Comprehension and Mathematics

Directory of Open Access Journals (Sweden)

LUZ STELLA LÓPEZ

2008-12-01

Full Text Available This article shares the design, implementation, and evaluation of theLesson Study process used for the professional development of teachers of mathematics, through the Red de Comprensión Lectora y Matemáticas – CCyM Network, in ways to teach mathematics through problem solving. The program began with a course on the implementation of the Thinking Classroom, followed by the semi-presencial Lesson Study process. An analysis of teacher interactions during the Lesson Study process yielded these categories of study: Group Collective Thinking, Mathematical Pedagogical Content Knowledge, Subject Matter Knowledge, Knowledge about Technology, and Expert Support. The analysis reflected variations in group interactions, in the command of concepts, in reflective practice, in the ability to make arguments and to propose changes in practice, and in the ability to self-regulate.

Teacher Tweets Improve Achievement for Eighth Grade Science Students

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Carol Van Vooren

2013-02-01

Full Text Available In the Digital Age teachers have fallen far behind the technical skills of their "digital native" students. The implementation of technology as a tool for classroom communication is foreign for most teachers, but highly preferred by students. While teenagers are using Facebook, Twitter, and other social networks to communicate, teachers continue to respond through face-to-face conversations, telephone calls, and email messaging. Twitter, a platform for short message service text, is an online social network site that allows users to send and receive messages using 140 characters or less called Tweets. To analyze the relationship of the teacher's use of Twitter with student academic achievement, a correlation study conducted by Bess collected data from two matched samples of eighth grade science students: one utilizing Twitter and one not utilizing Twitter to reinforce classroom instruction. Two tests matching the science standards were given to both samples of students. The results of the tests were used as primary data. The findings suggested a positive correlation between the use of Twitter and student performance on the standardized tests. Implications for this study indicate that young teenagers may prefer Twitter as a mode of communication with their teacher, resulting in higher academic achievement in a middle school science class.

Biobanking and translation of human genetics and genomics for infectious diseases

Directory of Open Access Journals (Sweden)

Ivan Branković

2014-06-01

Full Text Available Biobanks are invaluable resources in genomic research of both the infectious diseases and their hosts. This article examines the role of biobanks in basic research of infectious disease genomics, as well as the relevance and applicability of biobanks in the translation of impending knowledge and the clinical uptake of knowledge of infectious diseases. Our research identifies potential fields of interaction between infectious disease genomics and biobanks, in line with global trends in the integration of genome-based knowledge into clinical practice. It also examines various networks and biobanks that specialize in infectious diseases (including HIV, HPV and Chlamydia trachomatis, and provides examples of successful research and clinical uptake stemming from these biobanks. Finally, it outlines key issues with respect to data privacy in infectious disease genomics, as well as the utility of adequately designed and maintained electronic health records. We maintain that the public should be able to easily access a clear and detailed outline of regulations and procedures for sample and data utilization by academic or commercial investigators, and also should be able to understand the precise roles of relevant governing bodies. This would ultimately facilitate uptake by researchers and clinics. As a result of the efforts and resources invested by several networks and consortia, there is an increasing awareness of the prospective uses of biobanks in advancing infectious disease genomic research, diagnostics and their clinical management.

Biobanking and translation of human genetics and genomics for infectious diseases.

Science.gov (United States)

Branković, Ivan; Malogajski, Jelena; Morré, Servaas A

2014-06-01

Biobanks are invaluable resources in genomic research of both the infectious diseases and their hosts. This article examines the role of biobanks in basic research of infectious disease genomics, as well as the relevance and applicability of biobanks in the translation of impending knowledge and the clinical uptake of knowledge of infectious diseases. Our research identifies potential fields of interaction between infectious disease genomics and biobanks, in line with global trends in the integration of genome-based knowledge into clinical practice. It also examines various networks and biobanks that specialize in infectious diseases (including HIV, HPV and Chlamydia trachomatis), and provides examples of successful research and clinical uptake stemming from these biobanks. Finally, it outlines key issues with respect to data privacy in infectious disease genomics, as well as the utility of adequately designed and maintained electronic health records. We maintain that the public should be able to easily access a clear and detailed outline of regulations and procedures for sample and data utilization by academic or commercial investigators, and also should be able to understand the precise roles of relevant governing bodies. This would ultimately facilitate uptake by researchers and clinics. As a result of the efforts and resources invested by several networks and consortia, there is an increasing awareness of the prospective uses of biobanks in advancing infectious disease genomic research, diagnostics and their clinical management.

Professional Online Presence and Learning Networks: Educating for Ethical Use of Social Media

Science.gov (United States)

Forbes, Dianne

2017-01-01

In a teacher education context, this study considers the use of social media for building a professional online presence and learning network. This article provides an overview of uses of social media in teacher education, presents a case study of key processes in relation to professional online presence and learning networks, and highlights…

Teachers’ motives for learning in networks : costs, rewards and community interest

NARCIS (Netherlands)

van den Beemt, A.A.J.; Ketelaar, E.; Diepstraten, I.; de Laat, M.

2018-01-01

Background: This paper discusses teachers’ perspectives on learning networks and their motives for participating in these networks. Although it is widely held that teachers’ learning may be developed through learning networks, not all teachers participate in such networks. Purpose: The theme of

Signaling Network Assessment of Mutations and Copy Number Variations Predict Breast Cancer Subtype-Specific Drug Targets

Directory of Open Access Journals (Sweden)

Naif Zaman

2013-10-01

Full Text Available Individual cancer cells carry a bewildering number of distinct genomic alterations (e.g., copy number variations and mutations, making it a challenge to uncover genomic-driven mechanisms governing tumorigenesis. Here, we performed exome sequencing on several breast cancer cell lines that represent two subtypes, luminal and basal. We integrated these sequencing data and functional RNAi screening data (for the identification of genes that are essential for cell proliferation and survival onto a human signaling network. Two subtype-specific networks that potentially represent core-signaling mechanisms underlying tumorigenesis were identified. Within both networks, we found that genes were differentially affected in different cell lines; i.e., in some cell lines a gene was identified through RNAi screening, whereas in others it was genomically altered. Interestingly, we found that highly connected network genes could be used to correctly classify breast tumors into subtypes on the basis of genomic alterations. Further, the networks effectively predicted subtype-specific drug targets, which were experimentally validated.

SINEs as driving forces in genome evolution.

Science.gov (United States)

Schmitz, J

2012-01-01

SINEs are short interspersed elements derived from cellular RNAs that repetitively retropose via RNA intermediates and integrate more or less randomly back into the genome. SINEs propagate almost entirely vertically within their host cells and, once established in the germline, are passed on from generation to generation. As non-autonomous elements, their reverse transcription (from RNA to cDNA) and genomic integration depends on the activity of the enzymatic machinery of autonomous retrotransposons, such as long interspersed elements (LINEs). SINEs are widely distributed in eukaryotes, but are especially effectively propagated in mammalian species. For example, more than a million Alu-SINE copies populate the human genome (approximately 13% of genomic space), and few master copies of them are still active. In the organisms where they occur, SINEs are a challenge to genomic integrity, but in the long term also can serve as beneficial building blocks for evolution, contributing to phenotypic heterogeneity and modifying gene regulatory networks. They substantially expand the genomic space and introduce structural variation to the genome. SINEs have the potential to mutate genes, to alter gene expression, and to generate new parts of genes. A balanced distribution and controlled activity of such properties is crucial to maintaining the organism's dynamic and thriving evolution. Copyright © 2012 S. Karger AG, Basel.

CoryneRegNet: An ontology-based data warehouse of corynebacterial transcription factors and regulatory networks

Directory of Open Access Journals (Sweden)

Czaja Lisa F

2006-02-01

Full Text Available Abstract Background The application of DNA microarray technology in post-genomic analysis of bacterial genome sequences has allowed the generation of huge amounts of data related to regulatory networks. This data along with literature-derived knowledge on regulation of gene expression has opened the way for genome-wide reconstruction of transcriptional regulatory networks. These large-scale reconstructions can be converted into in silico models of bacterial cells that allow a systematic analysis of network behavior in response to changing environmental conditions. Description CoryneRegNet was designed to facilitate the genome-wide reconstruction of transcriptional regulatory networks of corynebacteria relevant in biotechnology and human medicine. During the import and integration process of data derived from experimental studies or literature knowledge CoryneRegNet generates links to genome annotations, to identified transcription factors and to the corresponding cis-regulatory elements. CoryneRegNet is based on a multi-layered, hierarchical and modular concept of transcriptional regulation and was implemented by using the relational database management system MySQL and an ontology-based data structure. Reconstructed regulatory networks can be visualized by using the yFiles JAVA graph library. As an application example of CoryneRegNet, we have reconstructed the global transcriptional regulation of a cellular module involved in SOS and stress response of corynebacteria. Conclusion CoryneRegNet is an ontology-based data warehouse that allows a pertinent data management of regulatory interactions along with the genome-scale reconstruction of transcriptional regulatory networks. These models can further be combined with metabolic networks to build integrated models of cellular function including both metabolism and its transcriptional regulation.

Teacher Unions' Participation in Policy Making: A South African Case Study

Science.gov (United States)

Govender, Logan

2015-01-01

This article contends that teacher unions' participation in policy making during South Africa's political transition was characterised by assertion of ideological identity (unionism and professionalism) and the cultivation of policy networks and alliances. It is argued that, historically, while teacher unions were divided along political and…

What Is Popular Is Not Always Right--Measuring Teacher Professional Behaviour

Science.gov (United States)

Morris, Zoe A.; Richardson, Paul W.; Watt, Helen M.G.

2012-01-01

Teaching is considered one of the most trusted professions, yet literature evaluating teachers' understanding of professional behaviour is scarce. Recently, technological advancements such as Social Networking Sites (SNS; e.g. Facebook) have created fresh debate about appropriate behaviour for teachers: in school and online. The "Professional…

[Teacher enhancement at Supercomputing `96

Energy Technology Data Exchange (ETDEWEB)

NONE

1998-02-13

The SC`96 Education Program provided a three-day professional development experience for middle and high school science, mathematics, and computer technology teachers. The program theme was Computers at Work in the Classroom, and a majority of the sessions were presented by classroom teachers who have had several years experience in using these technologies with their students. The teachers who attended the program were introduced to classroom applications of computing and networking technologies and were provided to the greatest extent possible with lesson plans, sample problems, and other resources that could immediately be used in their own classrooms. The attached At a Glance Schedule and Session Abstracts describes in detail the three-day SC`96 Education Program. Also included is the SC`96 Education Program evaluation report and the financial report.

Support, Inclusion, and Special Education Teachers' Attitudes toward the Education of Students with Autism Spectrum Disorders

Science.gov (United States)

Rodríguez, Isabel R.; Saldaña, David; Moreno, F. Javier

2012-01-01

This study is aimed at assessing special education teachers' attitudes toward teaching pupils with autism spectrum disorders (ASDs) and at determining the role of variables associated with a positive attitude towards the children and their education. Sixty-nine special education teachers were interviewed. The interview included two multiple-choice Likert-type questionnaires, one about teachers' attitude, and another about teachers' perceived needs in relation to the specific education of the pupil with ASD. The study shows a positive view of teachers' expectations regarding the education of pupils with ASD. A direct logistic regression analysis was performed testing for experience with the child, school relationship with an ASD network and type of school (mainstream or special) as potential predictors. Although all three variables are useful in predicting special education teachers' attitudes, the most relevant was the relationship with an ASD network. Need for information and social support are the relatively highest needs expressed by teachers. PMID:22934171

A complex regulatory network coordinating cell cycles during C. elegans development is revealed by a genome-wide RNAi screen.

Science.gov (United States)

Roy, Sarah H; Tobin, David V; Memar, Nadin; Beltz, Eleanor; Holmen, Jenna; Clayton, Joseph E; Chiu, Daniel J; Young, Laura D; Green, Travis H; Lubin, Isabella; Liu, Yuying; Conradt, Barbara; Saito, R Mako

2014-02-28

The development and homeostasis of multicellular animals requires precise coordination of cell division and differentiation. We performed a genome-wide RNA interference screen in Caenorhabditis elegans to reveal the components of a regulatory network that promotes developmentally programmed cell-cycle quiescence. The 107 identified genes are predicted to constitute regulatory networks that are conserved among higher animals because almost half of the genes are represented by clear human orthologs. Using a series of mutant backgrounds to assess their genetic activities, the RNA interference clones displaying similar properties were clustered to establish potential regulatory relationships within the network. This approach uncovered four distinct genetic pathways controlling cell-cycle entry during intestinal organogenesis. The enhanced phenotypes observed for animals carrying compound mutations attest to the collaboration between distinct mechanisms to ensure strict developmental regulation of cell cycles. Moreover, we characterized ubc-25, a gene encoding an E2 ubiquitin-conjugating enzyme whose human ortholog, UBE2Q2, is deregulated in several cancers. Our genetic analyses suggested that ubc-25 acts in a linear pathway with cul-1/Cul1, in parallel to pathways employing cki-1/p27 and lin-35/pRb to promote cell-cycle quiescence. Further investigation of the potential regulatory mechanism demonstrated that ubc-25 activity negatively regulates CYE-1/cyclin E protein abundance in vivo. Together, our results show that the ubc-25-mediated pathway acts within a complex network that integrates the actions of multiple molecular mechanisms to control cell cycles during development. Copyright © 2014 Roy et al.

Constructing an integrated gene similarity network for the identification of disease genes.

Science.gov (United States)

Tian, Zhen; Guo, Maozu; Wang, Chunyu; Xing, LinLin; Wang, Lei; Zhang, Yin

2017-09-20

Discovering novel genes that are involved human diseases is a challenging task in biomedical research. In recent years, several computational approaches have been proposed to prioritize candidate disease genes. Most of these methods are mainly based on protein-protein interaction (PPI) networks. However, since these PPI networks contain false positives and only cover less half of known human genes, their reliability and coverage are very low. Therefore, it is highly necessary to fuse multiple genomic data to construct a credible gene similarity network and then infer disease genes on the whole genomic scale. We proposed a novel method, named RWRB, to infer causal genes of interested diseases. First, we construct five individual gene (protein) similarity networks based on multiple genomic data of human genes. Then, an integrated gene similarity network (IGSN) is reconstructed based on similarity network fusion (SNF) method. Finally, we employee the random walk with restart algorithm on the phenotype-gene bilayer network, which combines phenotype similarity network, IGSN as well as phenotype-gene association network, to prioritize candidate disease genes. We investigate the effectiveness of RWRB through leave-one-out cross-validation methods in inferring phenotype-gene relationships. Results show that RWRB is more accurate than state-of-the-art methods on most evaluation metrics. Further analysis shows that the success of RWRB is benefited from IGSN which has a wider coverage and higher reliability comparing with current PPI networks. Moreover, we conduct a comprehensive case study for Alzheimer's disease and predict some novel disease genes that supported by literature. RWRB is an effective and reliable algorithm in prioritizing candidate disease genes on the genomic scale. Software and supplementary information are available at http://nclab.hit.edu.cn/~tianzhen/RWRB/ .

Social Network Methods for the Educational and Psychological Sciences

Science.gov (United States)

Sweet, Tracy M.

2016-01-01

Social networks are especially applicable in educational and psychological studies involving social interactions. A social network is defined as a specific relationship among a group of individuals. Social networks arise in a variety of situations such as friendships among children, collaboration and advice seeking among teachers, and coauthorship…

Smart Social Networking: 21st Century Teaching and Learning Skills

Directory of Open Access Journals (Sweden)

Helen B. Boholano

2017-06-01

Full Text Available Education in the 21st century highlights globalization and internationalization. Preservice teachers in the 21st century are technology savvy. To effectively engage and teach generation Z students, preservice teachers will help the educational system meet this requirement. The educational systems must be outfitted with a prerequisite of ICT resources both hardware and software, and curricula must be designed to promote a collaborative learner-centered environment to which students will relate and respond. This study determines the 21st century skills possessed by the pre-service teachers in terms of social networking. Pre-service teachers use computers in very advanced ways, but educators must remember that they still need guidance to use technology safely and effectively. Through social media the pre-service teachers can use a multitude of applications, including Web 2.0, for their projects. Smart social networking requires critical-thinking skills and the ability to integrate and evaluate real-world scenarios and authentic learning skills for validation.

Annotation of loci from genome-wide association studies using tissue-specific quantitative interaction proteomics

DEFF Research Database (Denmark)

Lundby, Alicia; Rossin, Elizabeth J.; Steffensen, Annette B.

2014-01-01

Genome-wide association studies (GWAS) have identified thousands of loci associated with complex traits, but it is challenging to pinpoint causal genes in these loci and to exploit subtle association signals. We used tissue-specific quantitative interaction proteomics to map a network of five genes...... involved in the Mendelian disorder long QT syndrome (LOTS). We integrated the LOTS network with GWAS loci from the corresponding common complex trait, QT-interval variation, to identify candidate genes that were subsequently confirmed in Xenopus laevis oocytes and zebrafish. We used the LOTS protein...... network to filter weak GWAS signals by identifying single-nucleotide polymorphisms (SNPs) in proximity to genes in the network supported by strong proteomic evidence. Three SNPs passing this filter reached genome-wide significance after replication genotyping. Overall, we present a general strategy...

KnowEnG: a knowledge engine for genomics.

Science.gov (United States)

Sinha, Saurabh; Song, Jun; Weinshilboum, Richard; Jongeneel, Victor; Han, Jiawei

2015-11-01

We describe here the vision, motivations, and research plans of the National Institutes of Health Center for Excellence in Big Data Computing at the University of Illinois, Urbana-Champaign. The Center is organized around the construction of "Knowledge Engine for Genomics" (KnowEnG), an E-science framework for genomics where biomedical scientists will have access to powerful methods of data mining, network mining, and machine learning to extract knowledge out of genomics data. The scientist will come to KnowEnG with their own data sets in the form of spreadsheets and ask KnowEnG to analyze those data sets in the light of a massive knowledge base of community data sets called the "Knowledge Network" that will be at the heart of the system. The Center is undertaking discovery projects aimed at testing the utility of KnowEnG for transforming big data to knowledge. These projects span a broad range of biological enquiry, from pharmacogenomics (in collaboration with Mayo Clinic) to transcriptomics of human behavior. © The Author 2015. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

MIPS: a database for genomes and protein sequences.

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Mewes, H W; Frishman, D; Güldener, U; Mannhaupt, G; Mayer, K; Mokrejs, M; Morgenstern, B; Münsterkötter, M; Rudd, S; Weil, B

2002-01-01

The Munich Information Center for Protein Sequences (MIPS-GSF, Neuherberg, Germany) continues to provide genome-related information in a systematic way. MIPS supports both national and European sequencing and functional analysis projects, develops and maintains automatically generated and manually annotated genome-specific databases, develops systematic classification schemes for the functional annotation of protein sequences, and provides tools for the comprehensive analysis of protein sequences. This report updates the information on the yeast genome (CYGD), the Neurospora crassa genome (MNCDB), the databases for the comprehensive set of genomes (PEDANT genomes), the database of annotated human EST clusters (HIB), the database of complete cDNAs from the DHGP (German Human Genome Project), as well as the project specific databases for the GABI (Genome Analysis in Plants) and HNB (Helmholtz-Netzwerk Bioinformatik) networks. The Arabidospsis thaliana database (MATDB), the database of mitochondrial proteins (MITOP) and our contribution to the PIR International Protein Sequence Database have been described elsewhere [Schoof et al. (2002) Nucleic Acids Res., 30, 91-93; Scharfe et al. (2000) Nucleic Acids Res., 28, 155-158; Barker et al. (2001) Nucleic Acids Res., 29, 29-32]. All databases described, the protein analysis tools provided and the detailed descriptions of our projects can be accessed through the MIPS World Wide Web server (http://mips.gsf.de).

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

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......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....... RESULTS: In this study, we report genome-scale transcript response diversity of 10 A. thaliana ecotypes originating from different geographical locations to non-freezing cold stress (10°C). To analyze the transcriptional response diversity, we initially compared transcriptome changes in all 10 ecotypes...

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. © 2010 American Society for Bone and Mineral Research.

In Silico Genome-Scale Reconstruction and Validation of the Staphylococcus aureus Metabolic Network

NARCIS (Netherlands)

Heinemann, Matthias; Kümmel, Anne; Ruinatscha, Reto; Panke, Sven

2005-01-01

A genome-scale metabolic model of the Gram-positive, facultative anaerobic opportunistic pathogen Staphylococcus aureus N315 was constructed based on current genomic data, literature, and physiological information. The model comprises 774 metabolic processes representing approximately 23% of all

Structure of the human chromosome interaction network.

Directory of Open Access Journals (Sweden)

Sergio Sarnataro

Full Text Available New Hi-C technologies have revealed that chromosomes have a complex network of spatial contacts in the cell nucleus of higher organisms, whose organisation is only partially understood. Here, we investigate the structure of such a network in human GM12878 cells, to derive a large scale picture of nuclear architecture. We find that the intensity of intra-chromosomal interactions is power-law distributed. Inter-chromosomal interactions are two orders of magnitude weaker and exponentially distributed, yet they are not randomly arranged along the genomic sequence. Intra-chromosomal contacts broadly occur between epigenomically homologous regions, whereas inter-chromosomal contacts are especially associated with regions rich in highly expressed genes. Overall, genomic contacts in the nucleus appear to be structured as a network of networks where a set of strongly individual chromosomal units, as envisaged in the 'chromosomal territory' scenario derived from microscopy, interact with each other via on average weaker, yet far from random and functionally important interactions.

A Study of Teacher-Mediated Enhancement of Students' Organization of Earth Science Knowledge Using Web Diagrams as a Teaching Device

Science.gov (United States)

Anderson, O. Roger; Contino, Julie

2010-10-01

Current research indicates that students with enhanced knowledge networks are more effective in learning science content and applying higher order thinking skills in open-ended inquiry learning. This research examined teacher implementation of a novel teaching strategy called “web diagramming,” a form of network mapping, in a secondary school earth science class. We report evidence for student improvement in knowledge networking, questionnaire-based reports by the students on the merits of web diagramming in terms of interest and usefulness, and information on the collaborating teacher’s perceptions of the process of implementation, including implications for teacher education. This is among the first reports that teachers can be provided with strategies to enhance student knowledge networking capacity, especially for those students whose initial networking scores are among the lowest.

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)

Garcillán-Barcia, M. Pilar; Mora, Azucena; Blanco, Jorge; Coque, Teresa M.; de la Cruz, Fernando

2014-01-01

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. PMID:25522143

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.

Students' Informal Peer Feedback Networks

Science.gov (United States)

Headington, Rita

2018-01-01

The nature and significance of students' informal peer feedback networks is an under-explored area. This paper offers the findings of a longitudinal investigation of the informal peer feedback networks of a cohort of student teachers [n = 105] across the three years of a UK primary education degree programme. It tracked the dynamic nature of these…

Is There a Teacher in This Class? Information Processing, Multimedia and Education

Science.gov (United States)

Muralikrishnan, T. R.; Sanjayan, T. S.

2009-01-01

This paper proposes to discuss the concept of multimedia using information processing theory in ICT enabled teacher education in the context of a knowledge society. The Information and communication technology (ICT) competencies required of teachers related to content, pedagogy, technical issues, social issues, collaboration and networking remain…

A Snapshot of the Emerging Tomato Genome Sequence

Directory of Open Access Journals (Sweden)

Lukas A. Mueller

2009-03-01

Full Text Available The genome of tomato ( L. is being sequenced by an international consortium of 10 countries (Korea, China, the United Kingdom, India, the Netherlands, France, Japan, Spain, Italy, and the United States as part of the larger “International Solanaceae Genome Project (SOL: Systems Approach to Diversity and Adaptation” initiative. The tomato genome sequencing project uses an ordered bacterial artificial chromosome (BAC approach to generate a high-quality tomato euchromatic genome sequence for use as a reference genome for the Solanaceae and euasterids. Sequence is deposited at GenBank and at the SOL Genomics Network (SGN. Currently, there are around 1000 BACs finished or in progress, representing more than a third of the projected euchromatic portion of the genome. An annotation effort is also underway by the International Tomato Annotation Group. The expected number of genes in the euchromatin is ∼40,000, based on an estimate from a preliminary annotation of 11% of finished sequence. Here, we present this first snapshot of the emerging tomato genome and its annotation, a short comparison with potato ( L. sequence data, and the tools available for the researchers to exploit this new resource are also presented. In the future, whole-genome shotgun techniques will be combined with the BAC-by-BAC approach to cover the entire tomato genome. The high-quality reference euchromatic tomato sequence is expected to be near completion by 2010.

Evaluation of Twitter Users Writings about Teachers in Turkey

Science.gov (United States)

Yavuz, Mustafa

2014-01-01

As a social sharing network whose number of users worldwide continues to rapidly increase, Twitter has become an active network for individuals to share their thoughts and feelings at any given time. The purpose of this work, then, is to evaluate Twitter users of Turkey in terms of how they write about their teachers on Twitter. In order to…

Network-Based Integration of GWAS and Gene Expression Identifies a HOX-Centric Network Associated with Serous Ovarian Cancer Risk.

Science.gov (United States)

Kar, Siddhartha P; Tyrer, Jonathan P; Li, Qiyuan; Lawrenson, Kate; Aben, Katja K H; Anton-Culver, Hoda; Antonenkova, Natalia; Chenevix-Trench, Georgia; Baker, Helen; Bandera, Elisa V; Bean, Yukie T; Beckmann, Matthias W; Berchuck, Andrew; Bisogna, Maria; Bjørge, Line; Bogdanova, Natalia; Brinton, Louise; Brooks-Wilson, Angela; Butzow, Ralf; Campbell, Ian; Carty, Karen; Chang-Claude, Jenny; Chen, Yian Ann; Chen, Zhihua; Cook, Linda S; Cramer, Daniel; Cunningham, Julie M; Cybulski, Cezary; Dansonka-Mieszkowska, Agnieszka; Dennis, Joe; Dicks, Ed; Doherty, Jennifer A; Dörk, Thilo; du Bois, Andreas; Dürst, Matthias; Eccles, Diana; Easton, Douglas F; Edwards, Robert P; Ekici, Arif B; Fasching, Peter A; Fridley, Brooke L; Gao, Yu-Tang; Gentry-Maharaj, Aleksandra; Giles, Graham G; Glasspool, Rosalind; Goode, Ellen L; Goodman, Marc T; Grownwald, Jacek; Harrington, Patricia; Harter, Philipp; Hein, Alexander; Heitz, Florian; Hildebrandt, Michelle A T; Hillemanns, Peter; Hogdall, Estrid; Hogdall, Claus K; Hosono, Satoyo; Iversen, Edwin S; Jakubowska, Anna; Paul, James; Jensen, Allan; Ji, Bu-Tian; Karlan, Beth Y; Kjaer, Susanne K; Kelemen, Linda E; Kellar, Melissa; Kelley, Joseph; Kiemeney, Lambertus A; Krakstad, Camilla; Kupryjanczyk, Jolanta; Lambrechts, Diether; Lambrechts, Sandrina; Le, Nhu D; Lee, Alice W; Lele, Shashi; Leminen, Arto; Lester, Jenny; Levine, Douglas A; Liang, Dong; Lissowska, Jolanta; Lu, Karen; Lubinski, Jan; Lundvall, Lene; Massuger, Leon; Matsuo, Keitaro; McGuire, Valerie; McLaughlin, John R; McNeish, Iain A; Menon, Usha; Modugno, Francesmary; Moysich, Kirsten B; Narod, Steven A; Nedergaard, Lotte; Ness, Roberta B; Nevanlinna, Heli; Odunsi, Kunle; Olson, Sara H; Orlow, Irene; Orsulic, Sandra; Weber, Rachel Palmieri; Pearce, Celeste Leigh; Pejovic, Tanja; Pelttari, Liisa M; Permuth-Wey, Jennifer; Phelan, Catherine M; Pike, Malcolm C; Poole, Elizabeth M; Ramus, Susan J; Risch, Harvey A; Rosen, Barry; Rossing, Mary Anne; Rothstein, Joseph H; Rudolph, Anja; Runnebaum, Ingo B; Rzepecka, Iwona K; Salvesen, Helga B; Schildkraut, Joellen M; Schwaab, Ira; Shu, Xiao-Ou; Shvetsov, Yurii B; Siddiqui, Nadeem; Sieh, Weiva; Song, Honglin; Southey, Melissa C; Sucheston-Campbell, Lara E; Tangen, Ingvild L; Teo, Soo-Hwang; Terry, Kathryn L; Thompson, Pamela J; Timorek, Agnieszka; Tsai, Ya-Yu; Tworoger, Shelley S; van Altena, Anne M; Van Nieuwenhuysen, Els; Vergote, Ignace; Vierkant, Robert A; Wang-Gohrke, Shan; Walsh, Christine; Wentzensen, Nicolas; Whittemore, Alice S; Wicklund, Kristine G; Wilkens, Lynne R; Woo, Yin-Ling; Wu, Xifeng; Wu, Anna; Yang, Hannah; Zheng, Wei; Ziogas, Argyrios; Sellers, Thomas A; Monteiro, Alvaro N A; Freedman, Matthew L; Gayther, Simon A; Pharoah, Paul D P

2015-10-01

Genome-wide association studies (GWAS) have so far reported 12 loci associated with serous epithelial ovarian cancer (EOC) risk. We hypothesized that some of these loci function through nearby transcription factor (TF) genes and that putative target genes of these TFs as identified by coexpression may also be enriched for additional EOC risk associations. We selected TF genes within 1 Mb of the top signal at the 12 genome-wide significant risk loci. Mutual information, a form of correlation, was used to build networks of genes strongly coexpressed with each selected TF gene in the unified microarray dataset of 489 serous EOC tumors from The Cancer Genome Atlas. Genes represented in this dataset were subsequently ranked using a gene-level test based on results for germline SNPs from a serous EOC GWAS meta-analysis (2,196 cases/4,396 controls). Gene set enrichment analysis identified six networks centered on TF genes (HOXB2, HOXB5, HOXB6, HOXB7 at 17q21.32 and HOXD1, HOXD3 at 2q31) that were significantly enriched for genes from the risk-associated end of the ranked list (P < 0.05 and FDR < 0.05). These results were replicated (P < 0.05) using an independent association study (7,035 cases/21,693 controls). Genes underlying enrichment in the six networks were pooled into a combined network. We identified a HOX-centric network associated with serous EOC risk containing several genes with known or emerging roles in serous EOC development. Network analysis integrating large, context-specific datasets has the potential to offer mechanistic insights into cancer susceptibility and prioritize genes for experimental characterization. ©2015 American Association for Cancer Research.

JAIF's teacher support activity on radiation education

International Nuclear Information System (INIS)

Kito, K.; Kudo, K.

2016-01-01

Japan Atomic Industrial Forum (JAIF) has been conducting science teacher support activities on radiation education since 2011, after the Fukushima NPP Accident, in cooperation with member organizations of the Japan Nuclear Human Resource Development Network (JN-HRD Net). (author)

Bioinformatics for genetical genomics : novel experimental design and algorithms

NARCIS (Netherlands)

Fu, Jingyuan

2007-01-01

Jingyuan Fu promoveert op een onderzoek naar genetische analyses. Onder andere werkte ze aan een nieuw softwarepakket MetaNetwork, dat hulp biedt bij het zoeken naar een optimaal ontwerp van experimenten op het gebied van genetical genomics.

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…

Latina Spanish High School Teachers' Negotiation of Capital in New Latino Communities

Science.gov (United States)

Colomer, Soria Elizabeth

2014-01-01

Based on a qualitative study documenting how Spanish teachers bear an especially heavy burden as unofficial translators, interpreters, and school representatives, this article documents how some Latina high school Spanish teachers struggle to form social networks with Latino students in new Latino school communities. Employing social frameworks,…

Transposable element activity, genome regulation and human health.

Science.gov (United States)

Wang, Lu; Jordan, I King

2018-03-02

A convergence of novel genome analysis technologies is enabling population genomic studies of human transposable elements (TEs). Population surveys of human genome sequences have uncovered thousands of individual TE insertions that segregate as common genetic variants, i.e. TE polymorphisms. These recent TE insertions provide an important source of naturally occurring human genetic variation. Investigators are beginning to leverage population genomic data sets to execute genome-scale association studies for assessing the phenotypic impact of human TE polymorphisms. For example, the expression quantitative trait loci (eQTL) analytical paradigm has recently been used to uncover hundreds of associations between human TE insertion variants and gene expression levels. These include population-specific gene regulatory effects as well as coordinated changes to gene regulatory networks. In addition, analyses of linkage disequilibrium patterns with previously characterized genome-wide association study (GWAS) trait variants have uncovered TE insertion polymorphisms that are likely causal variants for a variety of common complex diseases. Gene regulatory mechanisms that underlie specific disease phenotypes have been proposed for a number of these trait associated TE polymorphisms. These new population genomic approaches hold great promise for understanding how ongoing TE activity contributes to functionally relevant genetic variation within and between human populations. Copyright © 2018 Elsevier Ltd. All rights reserved.

Prospective English Language Teachers' Experiences in Facebook: Adoption, Use and Educational Use in Turkish Context

Science.gov (United States)

Balcikanli, Cem

2015-01-01

There has been an increasing attention given to the role of social networking in educational settings. Teacher education is not an exception to this, for teacher education is approaching social media on two fronts: a) application to enhance learning in the process of teacher preparation or professional development b) applications in classrooms…

Tissue-specific functional networks for prioritizing phenotype and disease genes.

Directory of Open Access Journals (Sweden)

Yuanfang Guan

Full Text Available Integrated analyses of functional genomics data have enormous potential for identifying phenotype-associated genes. Tissue-specificity is an important aspect of many genetic diseases, reflecting the potentially different roles of proteins and pathways in diverse cell lineages. Accounting for tissue specificity in global integration of functional genomics data is challenging, as "functionality" and "functional relationships" are often not resolved for specific tissue types. We address this challenge by generating tissue-specific functional networks, which can effectively represent the diversity of protein function for more accurate identification of phenotype-associated genes in the laboratory mouse. Specifically, we created 107 tissue-specific functional relationship networks through integration of genomic data utilizing knowledge of tissue-specific gene expression patterns. Cross-network comparison revealed significantly changed genes enriched for functions related to specific tissue development. We then utilized these tissue-specific networks to predict genes associated with different phenotypes. Our results demonstrate that prediction performance is significantly improved through using the tissue-specific networks as compared to the global functional network. We used a testis-specific functional relationship network to predict genes associated with male fertility and spermatogenesis phenotypes, and experimentally confirmed one top prediction, Mbyl1. We then focused on a less-common genetic disease, ataxia, and identified candidates uniquely predicted by the cerebellum network, which are supported by both literature and experimental evidence. Our systems-level, tissue-specific scheme advances over traditional global integration and analyses and establishes a prototype to address the tissue-specific effects of genetic perturbations, diseases and drugs.

Twitter: A Professional Development and Community of Practice Tool for Teachers

Science.gov (United States)

Rosell-Aguilar, Fernando

2018-01-01

This article shows how a group of language teachers use Twitter as a tool for continuous professional development through the #MFLtwitterati hashtag. Based on data collected through a survey (n = 116) and interviews (n = 11), it describes how this collective of teachers use the hashtag and evaluates the impact of their Twitter network on their…

Integrated Genomics Reveals Convergent Transcriptomic Networks Underlying Chronic Obstructive Pulmonary Disease and Idiopathic Pulmonary Fibrosis.

Science.gov (United States)

Kusko, Rebecca L; Brothers, John F; Tedrow, John; Pandit, Kusum; Huleihel, Luai; Perdomo, Catalina; Liu, Gang; Juan-Guardela, Brenda; Kass, Daniel; Zhang, Sherry; Lenburg, Marc; Martinez, Fernando; Quackenbush, John; Sciurba, Frank; Limper, Andrew; Geraci, Mark; Yang, Ivana; Schwartz, David A; Beane, Jennifer; Spira, Avrum; Kaminski, Naftali

2016-10-15

Despite shared environmental exposures, idiopathic pulmonary fibrosis (IPF) and chronic obstructive pulmonary disease are usually studied in isolation, and the presence of shared molecular mechanisms is unknown. We applied an integrative genomic approach to identify convergent transcriptomic pathways in emphysema and IPF. We defined the transcriptional repertoire of chronic obstructive pulmonary disease, IPF, or normal histology lungs using RNA-seq (n = 87). Genes increased in both emphysema and IPF relative to control were enriched for the p53/hypoxia pathway, a finding confirmed in an independent cohort using both gene expression arrays and the nCounter Analysis System (n = 193). Immunohistochemistry confirmed overexpression of HIF1A, MDM2, and NFKBIB members of this pathway in tissues from patients with emphysema or IPF. Using reads aligned across splice junctions, we determined that alternative splicing of p53/hypoxia pathway-associated molecules NUMB and PDGFA occurred more frequently in IPF or emphysema compared with control and validated these findings by quantitative polymerase chain reaction and the nCounter Analysis System on an independent sample set (n = 193). Finally, by integrating parallel microRNA and mRNA-Seq data on the same samples, we identified MIR96 as a key novel regulatory hub in the p53/hypoxia gene-expression network and confirmed that modulation of MIR96 in vitro recapitulates the disease-associated gene-expression network. Our results suggest convergent transcriptional regulatory hubs in diseases as varied phenotypically as chronic obstructive pulmonary disease and IPF and suggest that these hubs may represent shared key responses of the lung to environmental stresses.

A Gene Gravity Model for the Evolution of Cancer Genomes: A Study of 3,000 Cancer Genomes across 9 Cancer Types

Science.gov (United States)

Lin, Chen-Ching; Zhao, Junfei; Jia, Peilin; Li, Wen-Hsiung; Zhao, Zhongming

2015-01-01

Cancer development and progression result from somatic evolution by an accumulation of genomic alterations. The effects of those alterations on the fitness of somatic cells lead to evolutionary adaptations such as increased cell proliferation, angiogenesis, and altered anticancer drug responses. However, there are few general mathematical models to quantitatively examine how perturbations of a single gene shape subsequent evolution of the cancer genome. In this study, we proposed the gene gravity model to study the evolution of cancer genomes by incorporating the genome-wide transcription and somatic mutation profiles of ~3,000 tumors across 9 cancer types from The Cancer Genome Atlas into a broad gene network. We found that somatic mutations of a cancer driver gene may drive cancer genome evolution by inducing mutations in other genes. This functional consequence is often generated by the combined effect of genetic and epigenetic (e.g., chromatin regulation) alterations. By quantifying cancer genome evolution using the gene gravity model, we identified six putative cancer genes (AHNAK, COL11A1, DDX3X, FAT4, STAG2, and SYNE1). The tumor genomes harboring the nonsynonymous somatic mutations in these genes had a higher mutation density at the genome level compared to the wild-type groups. Furthermore, we provided statistical evidence that hypermutation of cancer driver genes on inactive X chromosomes is a general feature in female cancer genomes. In summary, this study sheds light on the functional consequences and evolutionary characteristics of somatic mutations during tumorigenesis by propelling adaptive cancer genome evolution, which would provide new perspectives for cancer research and therapeutics. PMID:26352260

CoryneCenter – An online resource for the integrated analysis of corynebacterial genome and transcriptome data

Directory of Open Access Journals (Sweden)

Hüser Andrea T

2007-11-01

Full Text Available Abstract Background The introduction of high-throughput genome sequencing and post-genome analysis technologies, e.g. DNA microarray approaches, has created the potential to unravel and scrutinize complex gene-regulatory networks on a large scale. The discovery of transcriptional regulatory interactions has become a major topic in modern functional genomics. Results To facilitate the analysis of gene-regulatory networks, we have developed CoryneCenter, a web-based resource for the systematic integration and analysis of genome, transcriptome, and gene regulatory information for prokaryotes, especially corynebacteria. For this purpose, we extended and combined the following systems into a common platform: (1 GenDB, an open source genome annotation system, (2 EMMA, a MAGE compliant application for high-throughput transcriptome data storage and analysis, and (3 CoryneRegNet, an ontology-based data warehouse designed to facilitate the reconstruction and analysis of gene regulatory interactions. We demonstrate the potential of CoryneCenter by means of an application example. Using microarray hybridization data, we compare the gene expression of Corynebacterium glutamicum under acetate and glucose feeding conditions: Known regulatory networks are confirmed, but moreover CoryneCenter points out additional regulatory interactions. Conclusion CoryneCenter provides more than the sum of its parts. Its novel analysis and visualization features significantly simplify the process of obtaining new biological insights into complex regulatory systems. Although the platform currently focusses on corynebacteria, the integrated tools are by no means restricted to these species, and the presented approach offers a general strategy for the analysis and verification of gene regulatory networks. CoryneCenter provides freely accessible projects with the underlying genome annotation, gene expression, and gene regulation data. The system is publicly available at http://www.CoryneCenter.de.

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…

Current approaches to gene regulatory network modelling

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Brazma Alvis

2007-09-01

Full Text Available Abstract Many different approaches have been developed to model and simulate gene regulatory networks. We proposed the following categories for gene regulatory network models: network parts lists, network topology models, network control logic models, and dynamic models. Here we will describe some examples for each of these categories. We will study the topology of gene regulatory networks in yeast in more detail, comparing a direct network derived from transcription factor binding data and an indirect network derived from genome-wide expression data in mutants. Regarding the network dynamics we briefly describe discrete and continuous approaches to network modelling, then describe a hybrid model called Finite State Linear Model and demonstrate that some simple network dynamics can be simulated in this model.

Networked elearning and collaborative knowledge building

DEFF Research Database (Denmark)

Sorensen, Elsebeth Korsgaard

2005-01-01

This paper addresses the core goals for educators to stimulate participation across diversity (including life trajectories and culture) and motivate learners to engage in negotiation of meaning and knowledge building dialogue in the processes of networked learning. The paper reports on a Danish...... masters online course on networked learning for educators that attempted to realize these goals. The participating teacher learned important methods, including moderation, through experience, guided by a teacher educator whose instructional design was based on communities of practice for participants...... with different backgrounds, cultures, age, and prerequisites in a shared learning endeavor on the Web. The experience supports a twofold foundation for instructional design: the learning theoretical concept of Etienne Wenger (1998) and an orientation toward participant cultures in terms of experiences...

Nitrogen fixation and molecular oxygen: comparative genomic reconstruction of transcription regulation in Alphaproteobacteria

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Olga V Tsoy

2016-08-01

Full Text Available Biological nitrogen fixation plays a crucial role in the nitrogen cycle. An ability to fix atmospheric nitrogen, reducing it to ammonium, was described for multiple species of Bacteria and Archaea. Being a complex and sensitive process, nitrogen fixation requires a complicated regulatory system, also, on the level of transcription. The transcriptional regulatory network for nitrogen fixation was extensively studied in several representatives of the class Alphaproteobacteria. This regulatory network includes the activator of nitrogen fixation NifA, working in tandem with the alternative sigma-factor RpoN as well as oxygen-responsive regulatory systems, one-component regulators FnrN/FixK and two-component system FixLJ. Here we used a comparative genomics analysis for in silico study of the transcriptional regulatory network in 50 genomes of Alphaproteobacteria. We extended the known regulons and proposed the scenario for the evolution of the nitrogen fixation transcriptional network. The reconstructed network substantially expands the existing knowledge of transcriptional regulation in nitrogen-fixing microorganisms and can be used for genetic experiments, metabolic reconstruction, and evolutionary analysis.

Technologies and techniques for analysis and use of genome information, 1997; Genome joho kaidoku riyo gijutsu no chosa kenkyu

Energy Technology Data Exchange (ETDEWEB)

NONE

1998-03-01

The paper clarified the whole image of cell functions by elucidating the function and manifestation control mechanism of genes existing in genomes, and the network of their interactions, and surveyed applicability of the useful functions obtained of cells and proteins to the industrial field. The survey was made from a viewpoint of the fields of both biology and information science. Especially, based on the function-known DNA base sequence database, the following technologies were surveyed: technology to predict the function of the function-unknown DNA base sequence, search/separation technology to acquire the genes to be functionally elucidated in a state of being suitable for manifestation, technology to get perfect proteins by effectively manifesting the genes to be functionally elucidated, and technology to analyze the function of the proteins obtained by manifestation of genes. Further, the International Symposium was held which is titled `Genome Research Opens a New World to Bioindustry (New Developments in Genome Informatics Technologies). With the future progress of technology to decipher and use genome information, the construction of much newer genome industry is anticipated. 165 refs., 44 figs., 10 tabs.

Reframing Teachers' Work for Educational Innovation

Science.gov (United States)

Kunnari, Irma; Ilomäki, Liisa

2016-01-01

The universities of applied sciences in Finland aim to support students in achieving work life competences by integrating authentic research, development and innovation (RDI) practices into learning. However, pursuing an educational change from a traditional higher education culture to a networked model of working is challenging for teachers. This…

Nuclear routing networks span between nuclear pore complexes and genomic DNA to guide nucleoplasmic trafficking of biomolecules

Science.gov (United States)

Malecki, Marek; Malecki, Bianca

2012-01-01

In health and disease, biomolecules, which are involved in gene expression, recombination, or reprogramming have to traffic through the nucleoplasm, between nuclear pore complexes (NPCs) and genomic DNA (gDNA). This trafficking is guided by the recently revealed nuclear routing networks (NRNs). In this study, we aimed to investigate, if the NRNs have established associations with the genomic DNA in situ and if the NRNs have capabilities to bind the DNA de novo. Moreover, we aimed to study further, if nucleoplasmic trafficking of the histones, rRNA, and transgenes’ vectors, between the NPCs and gDNA, is guided by the NRNs. We used Xenopus laevis oocytes as the model system. We engineered the transgenes’ DNA vectors equipped with the SV40 LTA nuclear localization signals (NLS) and/or HIV Rev nuclear export signals (NES). We purified histones, 5S rRNA, and gDNA. We rendered all these molecules superparamagnetic and fluorescent for detection with nuclear magnetic resonance (NMR), total reflection x-ray fluorescence (TXRF), energy dispersive x-ray spectroscopy (EDXS), and electron energy loss spectroscopy (EELS). The NRNs span between the NPCs and genomic DNA. They form firm bonds with the gDNA in situ. After complete digestion of the nucleic acids with the RNases and DNases, the newly added DNA - modified with the dNTP analogs, bonds firmly to the NRNs. Moreover, the NRNs guide the trafficking of the DNA transgenes’ vectors - modified with the SV40 LTA NLS, following their import into the nuclei through the NPCs. The pathway is identical to that of histones. The NRNs also guide the trafficking of the DNA transgenes’ vectors, modified with the HIV Rev NES, to the NPCs, followed by their export out of the nuclei. Ribosomal RNAs follow the same pathway. To summarize, the NRNs are the structures connecting the NPCs and the gDNA. They guide the trafficking of the biomolecules between the NPCs and the gDNA. PMID:23275893

Genomic and Epigenomic Alterations in Cancer.

Science.gov (United States)

Chakravarthi, Balabhadrapatruni V S K; Nepal, Saroj; Varambally, Sooryanarayana

2016-07-01

Multiple genetic and epigenetic events characterize tumor progression and define the identity of the tumors. Advances in high-throughput technologies, like gene expression profiling, next-generation sequencing, proteomics, and metabolomics, have enabled detailed molecular characterization of various tumors. The integration and analyses of these high-throughput data have unraveled many novel molecular aberrations and network alterations in tumors. These molecular alterations include multiple cancer-driving mutations, gene fusions, amplification, deletion, and post-translational modifications, among others. Many of these genomic events are being used in cancer diagnosis, whereas others are therapeutically targeted with small-molecule inhibitors. Multiple genes/enzymes that play a role in DNA and histone modifications are also altered in various cancers, changing the epigenomic landscape during cancer initiation and progression. Apart from protein-coding genes, studies are uncovering the critical regulatory roles played by noncoding RNAs and noncoding regions of the genome during cancer progression. Many of these genomic and epigenetic events function in tandem to drive tumor development and metastasis. Concurrent advances in genome-modulating technologies, like gene silencing and genome editing, are providing ability to understand in detail the process of cancer initiation, progression, and signaling as well as opening up avenues for therapeutic targeting. In this review, we discuss some of the recent advances in cancer genomic and epigenomic research. Copyright © 2016 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

Network-Guided Key Gene Discovery for a Given Cellular Process

DEFF Research Database (Denmark)

He, Feng Q; Ollert, Markus

2018-01-01

Identification of key genes for a given physiological or pathological process is an essential but still very challenging task for the entire biomedical research community. Statistics-based approaches, such as genome-wide association study (GWAS)- or quantitative trait locus (QTL)-related analysis...... have already made enormous contributions to identifying key genes associated with a given disease or phenotype, the success of which is however very much dependent on a huge number of samples. Recent advances in network biology, especially network inference directly from genome-scale data...

Students’ voice: The hopes and fears of student-teacher candidates

Directory of Open Access Journals (Sweden)

Shirli Shoyer

2016-12-01

Full Text Available It is widely claimed that learners interpret new information and experiences through their existing network of knowledge, experience, and beliefs. Research on professional identities of teachers highlight the impact of biographical factors such as teachers schooling experiences, motivations for entering teacher education programs, their initial teacher education experiences and contexts of professional practice, as influential of “construction, deconstruction and reconstruction” of teachers’ professional identities and the kind of teachers they become. The study investigates teacher education candidates’ hopes and fears concerning their future career as teachers. An open-ended questionnaire was distributed to 90 candidates in a teacher education college. The qualitative analysis identifies the domains of candidates’ hope and fears. The findings reveal that candidates expressed more hopes then fears. Their hopes and fears correspond with qualities of the “good teacher” and effective teaching. The study can support the development of prospective teachers towards expertise in teaching and assist program designers and educators in strengthening education programs by catering for students’ needs, taking into consideration their hopes and concerns.

Using Epistemic Network Analysis to understand core topics as planned learning objectives

DEFF Research Database (Denmark)

Allsopp, Benjamin Brink; Dreyøe, Jonas; Misfeldt, Morten

Epistemic Network Analysis is a tool developed by the epistemic games group at the University of Wisconsin Madison for tracking the relations between concepts in students discourse (Shaffer 2017). In our current work we are applying this tool to learning objectives in teachers digital preparation....... The danish mathematics curriculum is organised in six competencies and three topics. In the recently implemented learning platforms teacher choose which of the mathematical competencies that serves as objective for a specific lesson or teaching sequence. Hence learning objectives for lessons and teaching...... sequences are defining a network of competencies, where two competencies are closely related of they often are part of the same learning objective or teaching sequence. We are currently using Epistemic Network Analysis to study these networks. In the poster we will include examples of different networks...

Prospective teachers information and communication technology metaphors

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Ömür Akdemir

2015-04-01

Full Text Available Determination of the perceptions of the prospective teachers for the Information and Communications Technology (ICT terms have a remarkable potential to provide input for technology integration plans and ICT trainings. Within this context, the purpose of this study is to discover the metaphors constructed by prospective teachers for the ICT terms. Data were gathered from 180 prospective teachers through survey. 977 valid metaphors constructed by the participants were grouped into conceptual categories for the six ICT terms. The most common conceptual categories are “developing and changing” for technology, “making life easy” for computers and search engines, “limitless and endless” for the Internet, “means of communication” for social networks, and “addictive items” for video games. Future research should concentrate on investigating the match and mismatches between intended use of the ICT tools and the perception of the prospective teachers.

A Methodological Framework for Studying Policy-Oriented Teacher Inquiry in Qualitative Research Contexts

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Koro-Ljungberg, Mirka

2014-01-01

System-based and collaborative teacher inquiry has unexplored potential that can impact educational policy in numerous ways. This impact can be increased when teacher inquiry builds momentum from classrooms and teaching practices and simultaneously addresses district, state, and national discourses and networks. In this conceptual paper, I…

A protocol for generating a high-quality genome-scale metabolic reconstruction.

Science.gov (United States)

Thiele, Ines; Palsson, Bernhard Ø

2010-01-01

Network reconstructions are a common denominator in systems biology. Bottom-up metabolic network reconstructions have been developed over the last 10 years. These reconstructions represent structured knowledge bases that abstract pertinent information on the biochemical transformations taking place within specific target organisms. The conversion of a reconstruction into a mathematical format facilitates a myriad of computational biological studies, including evaluation of network content, hypothesis testing and generation, analysis of phenotypic characteristics and metabolic engineering. To date, genome-scale metabolic reconstructions for more than 30 organisms have been published and this number is expected to increase rapidly. However, these reconstructions differ in quality and coverage that may minimize their predictive potential and use as knowledge bases. Here we present a comprehensive protocol describing each step necessary to build a high-quality genome-scale metabolic reconstruction, as well as the common trials and tribulations. Therefore, this protocol provides a helpful manual for all stages of the reconstruction process.

Generalizing genetical genomics : getting added value from environmental perturbation

NARCIS (Netherlands)

Li, Yang; Breitling, Rainer; Jansen, Ritsert C.

2008-01-01

Genetical genomics is a useful approach for studying the effect of genetic perturbations on biological systems at the molecular level. However, molecular networks depend on the environmental conditions and, thus, a comprehensive understanding of biological systems requires studying them across

Nothing in Evolution Makes Sense Except in the Light of Genomics: Read–Write Genome Evolution as an Active Biological Process

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James A. Shapiro

2016-06-01

Full Text Available The 21st century genomics-based analysis of evolutionary variation reveals a number of novel features impossible to predict when Dobzhansky and other evolutionary biologists formulated the neo-Darwinian Modern Synthesis in the middle of the last century. These include three distinct realms of cell evolution; symbiogenetic fusions forming eukaryotic cells with multiple genome compartments; horizontal organelle, virus and DNA transfers; functional organization of proteins as systems of interacting domains subject to rapid evolution by exon shuffling and exonization; distributed genome networks integrated by mobile repetitive regulatory signals; and regulation of multicellular development by non-coding lncRNAs containing repetitive sequence components. Rather than single gene traits, all phenotypes involve coordinated activity by multiple interacting cell molecules. Genomes contain abundant and functional repetitive components in addition to the unique coding sequences envisaged in the early days of molecular biology. Combinatorial coding, plus the biochemical abilities cells possess to rearrange DNA molecules, constitute a powerful toolbox for adaptive genome rewriting. That is, cells possess “Read–Write Genomes” they alter by numerous biochemical processes capable of rapidly restructuring cellular DNA molecules. Rather than viewing genome evolution as a series of accidental modifications, we can now study it as a complex biological process of active self-modification.

Aftermath of bustamante attack on genomic beacon service.

Science.gov (United States)

Aziz, Md Momin Al; Ghasemi, Reza; Waliullah, Md; Mohammed, Noman

2017-07-26

With the enormous need for federated eco-system for holding global genomic and clinical data, Global Alliance for Genomic and Health (GA4GH) has created an international website called beacon service which allows a researcher to find out whether a specific dataset can be utilized to his or her research beforehand. This simple webservice is quite useful as it allows queries like whether a certain position of a target chromosome has a specific nucleotide. However, the increased integration of individuals genomic data into clinical practice and research raised serious privacy concern. Though the answer of such queries are yes or no in Bacon network, it results in serious privacy implication as demonstrated in a recent work from Shringarpure and Bustamante. In their attack model, the authors demonstrated that with a limited number of queries, presence of an individual in any dataset can be determined. We propose two lightweight algorithms (based on randomized response) which captures the efficacy while preserving the privacy of the participants in a genomic beacon service. We also elaborate the strength and weakness of the attack by explaining some of their statistical and mathematical models using real world genomic database. We extend their experimental simulations for different adversarial assumptions and parameters. We experimentally evaluated the solutions on the original attack model with different parameters for better understanding of the privacy and utility tradeoffs provided by these two methods. Also, the statistical analysis further elaborates the different aspects of the prior attack which leads to a better risk management for the participants in a beacon service. The differentially private and lightweight solutions discussed here will make the attack much difficult to succeed while maintaining the fundamental motivation of beacon database network.

A Bayesian approach to the evolution of metabolic networks on a phylogeny.

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Aziz Mithani

2010-08-01

Full Text Available The availability of genomes of many closely related bacteria with diverse metabolic capabilities offers the possibility of tracing metabolic evolution on a phylogeny relating the genomes to understand the evolutionary processes and constraints that affect the evolution of metabolic networks. Using simple (independent loss/gain of reactions or complex (incorporating dependencies among reactions stochastic models of metabolic evolution, it is possible to study how metabolic networks evolve over time. Here, we describe a model that takes the reaction neighborhood into account when modeling metabolic evolution. The model also allows estimation of the strength of the neighborhood effect during the course of evolution. We present Gibbs samplers for sampling networks at the internal node of a phylogeny and for estimating the parameters of evolution over a phylogeny without exploring the whole search space by iteratively sampling from the conditional distributions of the internal networks and parameters. The samplers are used to estimate the parameters of evolution of metabolic networks of bacteria in the genus Pseudomonas and to infer the metabolic networks of the ancestral pseudomonads. The results suggest that pathway maps that are conserved across the Pseudomonas phylogeny have a stronger neighborhood structure than those which have a variable distribution of reactions across the phylogeny, and that some Pseudomonas lineages are going through genome reduction resulting in the loss of a number of reactions from their metabolic networks.

Genomic minimalism in the early diverging intestinal parasite Giardia lamblia.

Science.gov (United States)

Morrison, Hilary G; McArthur, Andrew G; Gillin, Frances D; Aley, Stephen B; Adam, Rodney D; Olsen, Gary J; Best, Aaron A; Cande, W Zacheus; Chen, Feng; Cipriano, Michael J; Davids, Barbara J; Dawson, Scott C; Elmendorf, Heidi G; Hehl, Adrian B; Holder, Michael E; Huse, Susan M; Kim, Ulandt U; Lasek-Nesselquist, Erica; Manning, Gerard; Nigam, Anuranjini; Nixon, Julie E J; Palm, Daniel; Passamaneck, Nora E; Prabhu, Anjali; Reich, Claudia I; Reiner, David S; Samuelson, John; Svard, Staffan G; Sogin, Mitchell L

2007-09-28

The genome of the eukaryotic protist Giardia lamblia, an important human intestinal parasite, is compact in structure and content, contains few introns or mitochondrial relics, and has simplified machinery for DNA replication, transcription, RNA processing, and most metabolic pathways. Protein kinases comprise the single largest protein class and reflect Giardia's requirement for a complex signal transduction network for coordinating differentiation. Lateral gene transfer from bacterial and archaeal donors has shaped Giardia's genome, and previously unknown gene families, for example, cysteine-rich structural proteins, have been discovered. Unexpectedly, the genome shows little evidence of heterozygosity, supporting recent speculations that this organism is sexual. This genome sequence will not only be valuable for investigating the evolution of eukaryotes, but will also be applied to the search for new therapeutics for this parasite.

SUPPORTING TEACHERS IN IMPLEMENTING FORMATIVE ASSESSMENT PRACTICES IN EARTH SYSTEMS SCIENCE

Science.gov (United States)

Harris, C. J.; Penuel, W. R.; Haydel Debarger, A.; Blank, J. G.

2009-12-01

An important purpose of formative assessment is to elicit student thinking to use in instruction to help all students learn and inform next steps in teaching. However, formative assessment practices are difficult to implement and thus present a formidable challenge for many science teachers. A critical need in geoscience education is a framework for providing teachers with real-time assessment tools as well as professional development to learn how to use formative assessment to improve instruction. Here, we describe a comprehensive support system, developed for our NSF-funded Contingent Pedagogies project, for addressing the challenge of helping teachers to use formative assessment to enhance student learning in middle school Earth Systems science. Our support system is designed to improve student understanding about the geosphere by integrating classroom network technology, interactive formative assessments, and contingent curricular activities to guide teachers from formative assessment to instructional decision-making and improved student learning. To accomplish this, we are using a new classroom network technology, Group Scribbles, in the context of an innovative middle-grades Earth Science curriculum called Investigating Earth Systems (IES). Group Scribbles, developed at SRI International, is a collaborative software tool that allows individual students to compose “scribbles” (i.e., drawings and notes), on “post-it” notes in a private workspace (a notebook computer) in response to a public task. They can post these notes anonymously to a shared, public workspace (a teacher-controlled large screen monitor) that becomes the centerpiece of group and class discussion. To help teachers implement formative assessment practices, we have introduced a key resource, called a teaching routine, to help teachers take advantage of Group Scribbles for more interactive assessments. Routine refers to a sequence of repeatable interactions that, over time, become

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

Using online learning networks to promote self-regulated learning in primary teacher education

NARCIS (Netherlands)

Vrieling, Emmy; Bastiaens, Theo; Stijnen, Sjef

2017-01-01

Many recent studies have stressed the importance of students’ self-regulated learning (SRL) skills for successful learning. Consequently, teacher educators have begun to increase student teachers’ SRL opportunities in educational pre-service programs. Although primary teacher educators are aware of

Anti-pairing in learning of a neural network with redundant hidden units

International Nuclear Information System (INIS)

Kwon, Chulan; Kim, Hyong Kyun

2005-01-01

We study the statistical mechanics of learning from examples between the two-layered committee machines with different numbers of hidden units using the replica theory. The number M of hidden units of the student network is larger than the number M T of those of the target network called the teacher. We choose the networks to have binary synaptic weights, ±1, which makes it possible to compare the calculation with the Monte Carlo simulation. We propose an effective teacher as a virtual target network which has the same M hidden units as the student and gives identical outputs with those of the original teacher. This is a way of making a conjecture for a ground state of a thermodynamic system, given by the weights of the effective teacher in our study. We suppose that the weights on M T hidden units of the effective teacher are the same as those of the original teacher while those on M - M T redundant hidden units are composed of anti-pairs, {1, - 1}, with probability 1 - p in the limit p → 0. For p = 0 exact, there are no terms related to the effective teacher in the calculation, for the contributions of anti-pairs to outputs are exactly cancelled. In the limit p → 0, however, we find that the learnt weights of the student are actually equivalent to those of the suggested effective teacher, which is not possible from the calculation for p = 0. p plays the role of a symmetry breaking parameter for anti-pairing ordering, which is analogous to the magnetic field for the Ising model. A first-order phase transition is found to be signalled by breaking of symmetry in permuting hidden units. Above a critical number of examples, the student is shown to learn perfectly the effective teacher. Anti-pairing can be measured by a set of order parameters; zero in the permutation-symmetric phase and nonzero in the permutation symmetry breaking phase. Results from the Monte Carlo simulation are shown to be in good agreement with those from the replica calculation

Development of neural network for analysis of local power distributions in BWR fuel bundles

International Nuclear Information System (INIS)

Tanabe, Akira; Yamamoto, Toru; Shinfuku, Kimihiro; Nakamae, Takuji.

1993-01-01

A neural network model has been developed to learn the local power distributions in a BWR fuel bundle. A two layers neural network with total 128 elements is used for this model. The neural network learns 33 cases of local power peaking factors of fuel rods with given enrichment distribution as the teacher signals, which were calculated by a fuel bundle nuclear analysis code based on precise physical models. This neural network model studied well the teacher signals within 1 % error. It is also able to calculate the local power distributions within several % error for the different enrichment distributions from the teacher signals when the average enrichment is close to 2 %. This neural network is simple and the computing speed of this model is 300 times faster than that of the precise nuclear analysis code. This model was applied to survey the enrichment distribution to meet a target local power distribution in a fuel bundle, and the enrichment distribution with flat power shape are obtained within short computing time. (author)

Genome and metabolic network of Candidatus Phaeomarinobacter ectocarpi Ec32, a new candidate genus of Alphaproteobacteria frequently associated with brown algae

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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.

A program for verification of phylogenetic network models.

Science.gov (United States)

Gunawan, Andreas D M; Lu, Bingxin; Zhang, Louxin

2016-09-01

Genetic material is transferred in a non-reproductive manner across species more frequently than commonly thought, particularly in the bacteria kingdom. On one hand, extant genomes are thus more properly considered as a fusion product of both reproductive and non-reproductive genetic transfers. This has motivated researchers to adopt phylogenetic networks to study genome evolution. On the other hand, a gene's evolution is usually tree-like and has been studied for over half a century. Accordingly, the relationships between phylogenetic trees and networks are the basis for the reconstruction and verification of phylogenetic networks. One important problem in verifying a network model is determining whether or not certain existing phylogenetic trees are displayed in a phylogenetic network. This problem is formally called the tree containment problem. It is NP-complete even for binary phylogenetic networks. We design an exponential time but efficient method for determining whether or not a phylogenetic tree is displayed in an arbitrary phylogenetic network. It is developed on the basis of the so-called reticulation-visible property of phylogenetic networks. A C-program is available for download on http://www.math.nus.edu.sg/∼matzlx/tcp_package matzlx@nus.edu.sg Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Dynamics of the cell-cycle network under genome-rewiring perturbations

International Nuclear Information System (INIS)

Katzir, Yair; Elhanati, Yuval; Braun, Erez; Averbukh, Inna

2013-01-01

The cell-cycle progression is regulated by a specific network enabling its ordered dynamics. Recent experiments supported by computational models have shown that a core of genes ensures this robust cycle dynamics. However, much less is known about the direct interaction of the cell-cycle regulators with genes outside of the cell-cycle network, in particular those of the metabolic system. Following our recent experimental work, we present here a model focusing on the dynamics of the cell-cycle core network under rewiring perturbations. Rewiring is achieved by placing an essential metabolic gene exclusively under the regulation of a cell-cycle's promoter, forcing the cell-cycle network to function under a multitasking challenging condition; operating in parallel the cell-cycle progression and a metabolic essential gene. Our model relies on simple rate equations that capture the dynamics of the relevant protein–DNA and protein–protein interactions, while making a clear distinction between these two different types of processes. In particular, we treat the cell-cycle transcription factors as limited ‘resources’ and focus on the redistribution of resources in the network during its dynamics. This elucidates the sensitivity of its various nodes to rewiring interactions. The basic model produces the correct cycle dynamics for a wide range of parameters. The simplicity of the model enables us to study the interface between the cell-cycle regulation and other cellular processes. Rewiring a promoter of the network to regulate a foreign gene, forces a multitasking regulatory load. The higher the load on the promoter, the longer is the cell-cycle period. Moreover, in agreement with our experimental results, the model shows that different nodes of the network exhibit variable susceptibilities to the rewiring perturbations. Our model suggests that the topology of the cell-cycle core network ensures its plasticity and flexible interface with other cellular processes

Comprehensive reconstruction and in silico analysis of Aspergillus niger genome-scale metabolic network model that accounts for 1210 ORFs.

Science.gov (United States)

Lu, Hongzhong; Cao, Weiqiang; Ouyang, Liming; Xia, Jianye; Huang, Mingzhi; Chu, Ju; Zhuang, Yingping; Zhang, Siliang; Noorman, Henk

2017-03-01

Aspergillus niger is one of the most important cell factories for industrial enzymes and organic acids production. A comprehensive genome-scale metabolic network model (GSMM) with high quality is crucial for efficient strain improvement and process optimization. The lack of accurate reaction equations and gene-protein-reaction associations (GPRs) in the current best model of A. niger named GSMM iMA871, however, limits its application scope. To overcome these limitations, we updated the A. niger GSMM by combining the latest genome annotation and literature mining technology. Compared with iMA871, the number of reactions in iHL1210 was increased from 1,380 to 1,764, and the number of unique ORFs from 871 to 1,210. With the aid of our transcriptomics analysis, the existence of 63% ORFs and 68% reactions in iHL1210 can be verified when glucose was used as the only carbon source. Physiological data from chemostat cultivations, 13 C-labeled and molecular experiments from the published literature were further used to check the performance of iHL1210. The average correlation coefficients between the predicted fluxes and estimated fluxes from 13 C-labeling data were sufficiently high (above 0.89) and the prediction of cell growth on most of the reported carbon and nitrogen sources was consistent. Using the updated genome-scale model, we evaluated gene essentiality on synthetic and yeast extract medium, as well as the effects of NADPH supply on glucoamylase production in A. niger. In summary, the new A. niger GSMM iHL1210 contains significant improvements with respect to the metabolic coverage and prediction performance, which paves the way for systematic metabolic engineering of A. niger. Biotechnol. Bioeng. 2017;114: 685-695. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Exploration of plant genomes in the FLAGdb++ environment

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Leplé Jean-Charles

2011-03-01

Full Text Available Abstract Background In the contexts of genomics, post-genomics and systems biology approaches, data integration presents a major concern. Databases provide crucial solutions: they store, organize and allow information to be queried, they enhance the visibility of newly produced data by comparing them with previously published results, and facilitate the exploration and development of both existing hypotheses and new ideas. Results The FLAGdb++ information system was developed with the aim of using whole plant genomes as physical references in order to gather and merge available genomic data from in silico or experimental approaches. Available through a JAVA application, original interfaces and tools assist the functional study of plant genes by considering them in their specific context: chromosome, gene family, orthology group, co-expression cluster and functional network. FLAGdb++ is mainly dedicated to the exploration of large gene groups in order to decipher functional connections, to highlight shared or specific structural or functional features, and to facilitate translational tasks between plant species (Arabidopsis thaliana, Oryza sativa, Populus trichocarpa and Vitis vinifera. Conclusion Combining original data with the output of experts and graphical displays that differ from classical plant genome browsers, FLAGdb++ presents a powerful complementary tool for exploring plant genomes and exploiting structural and functional resources, without the need for computer programming knowledge. First launched in 2002, a 15th version of FLAGdb++ is now available and comprises four model plant genomes and over eight million genomic features.

Functional enrichment analyses and construction of functional similarity networks with high confidence function prediction by PFP

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Kihara Daisuke

2010-05-01

Full Text Available Abstract Background A new paradigm of biological investigation takes advantage of technologies that produce large high throughput datasets, including genome sequences, interactions of proteins, and gene expression. The ability of biologists to analyze and interpret such data relies on functional annotation of the included proteins, but even in highly characterized organisms many proteins can lack the functional evidence necessary to infer their biological relevance. Results Here we have applied high confidence function predictions from our automated prediction system, PFP, to three genome sequences, Escherichia coli, Saccharomyces cerevisiae, and Plasmodium falciparum (malaria. The number of annotated genes is increased by PFP to over 90% for all of the genomes. Using the large coverage of the function annotation, we introduced the functional similarity networks which represent the functional space of the proteomes. Four different functional similarity networks are constructed for each proteome, one each by considering similarity in a single Gene Ontology (GO category, i.e. Biological Process, Cellular Component, and Molecular Function, and another one by considering overall similarity with the funSim score. The functional similarity networks are shown to have higher modularity than the protein-protein interaction network. Moreover, the funSim score network is distinct from the single GO-score networks by showing a higher clustering degree exponent value and thus has a higher tendency to be hierarchical. In addition, examining function assignments to the protein-protein interaction network and local regions of genomes has identified numerous cases where subnetworks or local regions have functionally coherent proteins. These results will help interpreting interactions of proteins and gene orders in a genome. Several examples of both analyses are highlighted. Conclusion The analyses demonstrate that applying high confidence predictions from PFP

[Development of Plant Metabolomics and Medicinal Plant Genomics].

Science.gov (United States)

Saito, Kazuki

2018-01-01

 A variety of chemicals produced by plants, often referred to as 'phytochemicals', have been used as medicines, food, fuels and industrial raw materials. Recent advances in the study of genomics and metabolomics in plant science have accelerated our understanding of the mechanisms, regulation and evolution of the biosynthesis of specialized plant products. We can now address such questions as how the metabolomic diversity of plants is originated at the levels of genome, and how we should apply this knowledge to drug discovery, industry and agriculture. Our research group has focused on metabolomics-based functional genomics over the last 15 years and we have developed a new research area called 'Phytochemical Genomics'. In this review, the development of a research platform for plant metabolomics is discussed first, to provide a better understanding of the chemical diversity of plants. Then, representative applications of metabolomics to functional genomics in a model plant, Arabidopsis thaliana, are described. The extension of integrated multi-omics analyses to non-model specialized plants, e.g., medicinal plants, is presented, including the identification of novel genes, metabolites and networks for the biosynthesis of flavonoids, alkaloids, sulfur-containing metabolites and terpenoids. Further, functional genomics studies on a variety of medicinal plants is presented. I also discuss future trends in pharmacognosy and related sciences.

Review of Biological Network Data and Its Applications

Directory of Open Access Journals (Sweden)

Donghyeon Yu

2013-12-01

Full Text Available Studying biological networks, such as protein-protein interactions, is key to understanding complex biological activities. Various types of large-scale biological datasets have been collected and analyzed with high-throughput technologies, including DNA microarray, next-generation sequencing, and the two-hybrid screening system, for this purpose. In this review, we focus on network-based approaches that help in understanding biological systems and identifying biological functions. Accordingly, this paper covers two major topics in network biology: reconstruction of gene regulatory networks and network-based applications, including protein function prediction, disease gene prioritization, and network-based genome-wide association study.

Functional RNA structures throughout the Hepatitis C Virus genome.

Science.gov (United States)

Adams, Rebecca L; Pirakitikulr, Nathan; Pyle, Anna Marie

2017-06-01

The single-stranded Hepatitis C Virus (HCV) genome adopts a set of elaborate RNA structures that are involved in every stage of the viral lifecycle. Recent advances in chemical probing, sequencing, and structural biology have facilitated analysis of RNA folding on a genome-wide scale, revealing novel structures and networks of interactions. These studies have underscored the active role played by RNA in every function of HCV and they open the door to new types of RNA-targeted therapeutics. Copyright © 2017 Elsevier B.V. All rights reserved.

HKC: An Algorithm to Predict Protein Complexes in Protein-Protein Interaction Networks

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Xiaomin Wang

2011-01-01

Full Text Available With the availability of more and more genome-scale protein-protein interaction (PPI networks, research interests gradually shift to Systematic Analysis on these large data sets. A key topic is to predict protein complexes in PPI networks by identifying clusters that are densely connected within themselves but sparsely connected with the rest of the network. In this paper, we present a new topology-based algorithm, HKC, to detect protein complexes in genome-scale PPI networks. HKC mainly uses the concepts of highest k-core and cohesion to predict protein complexes by identifying overlapping clusters. The experiments on two data sets and two benchmarks show that our algorithm has relatively high F-measure and exhibits better performance compared with some other methods.

Integrated genomic and interfacility patient-transfer data reveal the transmission pathways of multidrug-resistant Klebsiella pneumoniae in a regional outbreak.

Science.gov (United States)

Snitkin, Evan S; Won, Sarah; Pirani, Ali; Lapp, Zena; Weinstein, Robert A; Lolans, Karen; Hayden, Mary K

2017-11-22

Development of effective strategies to limit the proliferation of multidrug-resistant organisms requires a thorough understanding of how such organisms spread among health care facilities. We sought to uncover the chains of transmission underlying a 2008 U.S. regional outbreak of carbapenem-resistant Klebsiella pneumoniae by performing an integrated analysis of genomic and interfacility patient-transfer data. Genomic analysis yielded a high-resolution transmission network that assigned directionality to regional transmission events and discriminated between intra- and interfacility transmission when epidemiologic data were ambiguous or misleading. Examining the genomic transmission network in the context of interfacility patient transfers (patient-sharing networks) supported the role of patient transfers in driving the outbreak, with genomic analysis revealing that a small subset of patient-transfer events was sufficient to explain regional spread. Further integration of the genomic and patient-sharing networks identified one nursing home as an important bridge facility early in the outbreak-a role that was not apparent from analysis of genomic or patient-transfer data alone. Last, we found that when simulating a real-time regional outbreak, our methodology was able to accurately infer the facility at which patients acquired their infections. This approach has the potential to identify facilities with high rates of intra- or interfacility transmission, data that will be useful for triggering targeted interventions to prevent further spread of multidrug-resistant organisms. Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

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…

Improving Teachers' Teaching with Communication Technology

Science.gov (United States)

Chen, Li-Ling

2012-01-01

With the growing needs to address the challenges that new teachers face and the popularity of social networking technology, this study explores how to increase the effectives of teaching through the use of such technology, and how the technology may serve to promote collaboration and open new resources of support in public education. In this…

Computer Networking Strategies for Building Collaboration among Science Educators.

Science.gov (United States)

Aust, Ronald

The development and dissemination of science materials can be associated with technical delivery systems such as the Unified Network for Informatics in Teacher Education (UNITE). The UNITE project was designed to investigate ways for using computer networking to improve communications and collaboration among university schools of education and…

Social Network Analysis in E-Learning Environments: A Preliminary Systematic Review

Science.gov (United States)

Cela, Karina L.; Sicilia, Miguel Ángel; Sánchez, Salvador

2015-01-01

E-learning occupies an increasingly prominent place in education. It provides the learner with a rich virtual network where he or she can exchange ideas and information and create synergies through interactions with other members of the network, whether fellow learners or teachers. Social network analysis (SNA) has proven extremely powerful at…

Genome-Wide Approaches to Drosophila Heart Development

Directory of Open Access Journals (Sweden)

Manfred Frasch

2016-05-01

Full Text Available The development of the dorsal vessel in Drosophila is one of the first systems in which key mechanisms regulating cardiogenesis have been defined in great detail at the genetic and molecular level. Due to evolutionary conservation, these findings have also provided major inputs into studies of cardiogenesis in vertebrates. Many of the major components that control Drosophila cardiogenesis were discovered based on candidate gene approaches and their functions were defined by employing the outstanding genetic tools and molecular techniques available in this system. More recently, approaches have been taken that aim to interrogate the entire genome in order to identify novel components and describe genomic features that are pertinent to the regulation of heart development. Apart from classical forward genetic screens, the availability of the thoroughly annotated Drosophila genome sequence made new genome-wide approaches possible, which include the generation of massive numbers of RNA interference (RNAi reagents that were used in forward genetic screens, as well as studies of the transcriptomes and proteomes of the developing heart under normal and experimentally manipulated conditions. Moreover, genome-wide chromatin immunoprecipitation experiments have been performed with the aim to define the full set of genomic binding sites of the major cardiogenic transcription factors, their relevant target genes, and a more complete picture of the regulatory network that drives cardiogenesis. This review will give an overview on these genome-wide approaches to Drosophila heart development and on computational analyses of the obtained information that ultimately aim to provide a description of this process at the systems level.

Histone chaperone networks shaping chromatin function

DEFF Research Database (Denmark)

Hammond, Colin; Strømme, Caroline Bianchi; Huang, Hongda

2017-01-01

and fate, which affects all chromosomal processes, including gene expression, chromosome segregation and genome replication and repair. Here, we review the distinct structural and functional properties of the expanding network of histone chaperones. We emphasize how chaperones cooperate in the histone...... chaperone network and via co-chaperone complexes to match histone supply with demand, thereby promoting proper nucleosome assembly and maintaining epigenetic information by recycling modified histones evicted from chromatin....

Tracking of time-varying genomic regulatory networks with a LASSO-Kalman smoother

OpenAIRE

Khan, Jehandad; Bouaynaya, Nidhal; Fathallah-Shaykh, Hassan M

2014-01-01

It is widely accepted that cellular requirements and environmental conditions dictate the architecture of genetic regulatory networks. Nonetheless, the status quo in regulatory network modeling and analysis assumes an invariant network topology over time. In this paper, we refocus on a dynamic perspective of genetic networks, one that can uncover substantial topological changes in network structure during biological processes such as developmental growth. We propose a novel outlook on the inf...

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

OpenAIRE

Titus, Tom A.; Yan, Yi-Lin; Wilson, Catherine; Starks, Amber M.; Frohnmayer, Jonathan D.; Canestro, Cristian; Rodriguez-Mari, Adriana; He, Xinjun; Postlethwait, John H.

2008-01-01

Fanconi anemia (FA) is a genic 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 expresse...

A Culture of High Expectations: Teacher Leadership at Pritzker College Prep

Science.gov (United States)

Aspen Institute, 2014

2014-01-01

Relying on teachers as culture leaders is a solution embraced by many high-performing charter schools. This profile focuses on the design of the Grade Level Lead roles at Pritzker College Prep, a member of the Noble Network of Schools in Chicago. The successes of this school and network are well-documented: Of non-selective public high schools in…

Development of Bioinformatics Infrastructure for Genomics Research.

Science.gov (United States)

Mulder, Nicola J; Adebiyi, Ezekiel; Adebiyi, Marion; Adeyemi, Seun; Ahmed, Azza; Ahmed, Rehab; Akanle, Bola; Alibi, Mohamed; Armstrong, Don L; Aron, Shaun; Ashano, Efejiro; Baichoo, Shakuntala; Benkahla, Alia; Brown, David K; Chimusa, Emile R; Fadlelmola, Faisal M; Falola, Dare; Fatumo, Segun; Ghedira, Kais; Ghouila, Amel; Hazelhurst, Scott; Isewon, Itunuoluwa; Jung, Segun; Kassim, Samar Kamal; Kayondo, Jonathan K; Mbiyavanga, Mamana; Meintjes, Ayton; Mohammed, Somia; Mosaku, Abayomi; Moussa, Ahmed; Muhammd, Mustafa; Mungloo-Dilmohamud, Zahra; Nashiru, Oyekanmi; Odia, Trust; Okafor, Adaobi; Oladipo, Olaleye; Osamor, Victor; Oyelade, Jellili; Sadki, Khalid; Salifu, Samson Pandam; Soyemi, Jumoke; Panji, Sumir; Radouani, Fouzia; Souiai, Oussama; Tastan Bishop, Özlem

2017-06-01

Although pockets of bioinformatics excellence have developed in Africa, generally, large-scale genomic data analysis has been limited by the availability of expertise and infrastructure. H3ABioNet, a pan-African bioinformatics network, was established to build capacity specifically to enable H3Africa (Human Heredity and Health in Africa) researchers to analyze their data in Africa. Since the inception of the H3Africa initiative, H3ABioNet's role has evolved in response to changing needs from the consortium and the African bioinformatics community. H3ABioNet set out to develop core bioinformatics infrastructure and capacity for genomics research in various aspects of data collection, transfer, storage, and analysis. Various resources have been developed to address genomic data management and analysis needs of H3Africa researchers and other scientific communities on the continent. NetMap was developed and used to build an accurate picture of network performance within Africa and between Africa and the rest of the world, and Globus Online has been rolled out to facilitate data transfer. A participant recruitment database was developed to monitor participant enrollment, and data is being harmonized through the use of ontologies and controlled vocabularies. The standardized metadata will be integrated to provide a search facility for H3Africa data and biospecimens. Because H3Africa projects are generating large-scale genomic data, facilities for analysis and interpretation are critical. H3ABioNet is implementing several data analysis platforms that provide a large range of bioinformatics tools or workflows, such as Galaxy, the Job Management System, and eBiokits. A set of reproducible, portable, and cloud-scalable pipelines to support the multiple H3Africa data types are also being developed and dockerized to enable execution on multiple computing infrastructures. In addition, new tools have been developed for analysis of the uniquely divergent African data and for

1997 NASA/MSFC Summer Teacher Enrichment Program

Science.gov (United States)

1999-01-01

This is a report on the follow-up activities conducted for the 1997 NASA Summer Teacher Enrichment Program (STEP), which was held at the George C. Marshall Space Flight Center (MSFC) for the seventh consecutive year. The program was conducted as a six-week session with 17 sixth through twelfth grade math and science teachers from a six-state region (Alabama, Arkansas, Iowa, Louisiana, Mississippi and Missouri). The program began on June 8, 1997, and ended on July 25, 1997. The long-term objectives of the program are to: increase the nation's scientific and technical talent pool with a special emphasis on underrepresented groups, improve the quality of pre-college math and science education, improve math and science literacy, and improve NASA's and pre-college education's understandings of each other's operating environments and needs. Short-term measurable objectives for the MSFC STEP are to: improve the teachers' content and pedagogy knowledge in science and/or mathematics, integrate applications from the teachers' STEP laboratory experiences into science and math curricula, increase the teachers' use of instructional technology, enhance the teachers' leadership skills by requiring them to present workshops and/or inservice programs for other teachers, require the support of the participating teacher(s) by the local school administration through a written commitment, and create networks and partnerships within the education community, both pre-college and college. The follow-up activities for the 1997 STEP included the following: academic-year questionnaire, site visits, academic-year workshop, verification of commitment of support, and additional NASA support.

Integrated genomic and gene expression profiling identifies two major genomic circuits in urothelial carcinoma.

Directory of Open Access Journals (Sweden)

David Lindgren

Full Text Available Similar to other malignancies, urothelial carcinoma (UC is characterized by specific recurrent chromosomal aberrations and gene mutations. However, the interconnection between specific genomic alterations, and how patterns of chromosomal alterations adhere to different molecular subgroups of UC, is less clear. We applied tiling resolution array CGH to 146 cases of UC and identified a number of regions harboring recurrent focal genomic amplifications and deletions. Several potential oncogenes were included in the amplified regions, including known oncogenes like E2F3, CCND1, and CCNE1, as well as new candidate genes, such as SETDB1 (1q21, and BCL2L1 (20q11. We next combined genome profiling with global gene expression, gene mutation, and protein expression data and identified two major genomic circuits operating in urothelial carcinoma. The first circuit was characterized by FGFR3 alterations, overexpression of CCND1, and 9q and CDKN2A deletions. The second circuit was defined by E3F3 amplifications and RB1 deletions, as well as gains of 5p, deletions at PTEN and 2q36, 16q, 20q, and elevated CDKN2A levels. TP53/MDM2 alterations were common for advanced tumors within the two circuits. Our data also suggest a possible RAS/RAF circuit. The tumors with worst prognosis showed a gene expression profile that indicated a keratinized phenotype. Taken together, our integrative approach revealed at least two separate networks of genomic alterations linked to the molecular diversity seen in UC, and that these circuits may reflect distinct pathways of tumor development.

Investigating core genetic-and-epigenetic cell cycle networks for stemness and carcinogenic mechanisms, and cancer drug design using big database mining and genome-wide next-generation sequencing data.

Science.gov (United States)

Li, Cheng-Wei; Chen, Bor-Sen

2016-10-01

Recent studies have demonstrated that cell cycle plays a central role in development and carcinogenesis. Thus, the use of big databases and genome-wide high-throughput data to unravel the genetic and epigenetic mechanisms underlying cell cycle progression in stem cells and cancer cells is a matter of considerable interest. Real genetic-and-epigenetic cell cycle networks (GECNs) of embryonic stem cells (ESCs) and HeLa cancer cells were constructed by applying system modeling, system identification, and big database mining to genome-wide next-generation sequencing data. Real GECNs were then reduced to core GECNs of HeLa cells and ESCs by applying principal genome-wide network projection. In this study, we investigated potential carcinogenic and stemness mechanisms for systems cancer drug design by identifying common core and specific GECNs between HeLa cells and ESCs. Integrating drug database information with the specific GECNs of HeLa cells could lead to identification of multiple drugs for cervical cancer treatment with minimal side-effects on the genes in the common core. We found that dysregulation of miR-29C, miR-34A, miR-98, and miR-215; and methylation of ANKRD1, ARID5B, CDCA2, PIF1, STAMBPL1, TROAP, ZNF165, and HIST1H2AJ in HeLa cells could result in cell proliferation and anti-apoptosis through NFκB, TGF-β, and PI3K pathways. We also identified 3 drugs, methotrexate, quercetin, and mimosine, which repressed the activated cell cycle genes, ARID5B, STK17B, and CCL2, in HeLa cells with minimal side-effects.

Integrated Network Analysis and Effective Tools in Plant Systems Biology

Directory of Open Access Journals (Sweden)

Atsushi eFukushima

2014-11-01

Full Text Available One of the ultimate goals in plant systems biology is to elucidate the genotype-phenotype relationship in plant cellular systems. Integrated network analysis that combines omics data with mathematical models has received particular attention. Here we focus on the latest cutting-edge computational advances that facilitate their combination. We highlight (1 network visualization tools, (2 pathway analyses, (3 genome-scale metabolic reconstruction, and (4 the integration of high-throughput experimental data and mathematical models. Multi-omics data that contain the genome, transcriptome, proteome, and metabolome and mathematical models are expected to integrate and expand our knowledge of complex plant metabolisms.

Semantic prioritization of novel causative genomic variants

KAUST Repository

Boudellioua, Imene

2017-04-17

Discriminating the causative disease variant(s) for individuals with inherited or de novo mutations presents one of the main challenges faced by the clinical genetics community today. Computational approaches for variant prioritization include machine learning methods utilizing a large number of features, including molecular information, interaction networks, or phenotypes. Here, we demonstrate the PhenomeNET Variant Predictor (PVP) system that exploits semantic technologies and automated reasoning over genotype-phenotype relations to filter and prioritize variants in whole exome and whole genome sequencing datasets. We demonstrate the performance of PVP in identifying causative variants on a large number of synthetic whole exome and whole genome sequences, covering a wide range of diseases and syndromes. In a retrospective study, we further illustrate the application of PVP for the interpretation of whole exome sequencing data in patients suffering from congenital hypothyroidism. We find that PVP accurately identifies causative variants in whole exome and whole genome sequencing datasets and provides a powerful resource for the discovery of causal variants.

Semantic prioritization of novel causative genomic variants

KAUST Repository

Boudellioua, Imene; Mohamad Razali, Rozaimi; Kulmanov, Maxat; Hashish, Yasmeen; Bajic, Vladimir B.; Goncalves-Serra, Eva; Schoenmakers, Nadia; Gkoutos, Georgios V.; Schofield, Paul N.; Hoehndorf, Robert

2017-01-01

Discriminating the causative disease variant(s) for individuals with inherited or de novo mutations presents one of the main challenges faced by the clinical genetics community today. Computational approaches for variant prioritization include machine learning methods utilizing a large number of features, including molecular information, interaction networks, or phenotypes. Here, we demonstrate the PhenomeNET Variant Predictor (PVP) system that exploits semantic technologies and automated reasoning over genotype-phenotype relations to filter and prioritize variants in whole exome and whole genome sequencing datasets. We demonstrate the performance of PVP in identifying causative variants on a large number of synthetic whole exome and whole genome sequences, covering a wide range of diseases and syndromes. In a retrospective study, we further illustrate the application of PVP for the interpretation of whole exome sequencing data in patients suffering from congenital hypothyroidism. We find that PVP accurately identifies causative variants in whole exome and whole genome sequencing datasets and provides a powerful resource for the discovery of causal variants.

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

Genome scale metabolic network reconstruction of Spirochaeta cellobiosiphila

Directory of Open Access Journals (Sweden)

Bharat Manna

2017-10-01

Full Text Available Substantial rise in the global energy demand is one of the biggest challenges in this century. Environmental pollution due to rapid depletion of the fossil fuel resources and its alarming impact on the climate change and Global Warming have motivated researchers to look for non-petroleum-based sustainable, eco-friendly, renewable, low-cost energy alternatives, such as biofuel. Lignocellulosic biomass is one of the most promising bio-resources with huge potential to contribute to this worldwide energy demand. However, the complex organization of the Cellulose, Hemicellulose and Lignin in the Lignocellulosic biomass requires extensive pre-treatment and enzymatic hydrolysis followed by fermentation, raising overall production cost of biofuel. This encourages researchers to design cost-effective approaches for the production of second generation biofuels. The products from enzymatic hydrolysis of cellulose are mostly glucose monomer or cellobiose unit that are subjected to fermentation. Spirochaeta genus is a well-known group of obligate or facultative anaerobes, living primarily on carbohydrate metabolism. Spirochaeta cellobiosiphila sp. is a facultative anaerobe under this genus, which uses a variety of monosaccharides and disaccharides as energy sources. However, most rapid growth occurs on cellobiose and fermentation yields significant amount of ethanol, acetate, CO2, H2 and small amounts of formate. It is predicted to be promising microbial machinery for industrial fermentation processes for biofuel production. The metabolic pathways that govern cellobiose metabolism in Spirochaeta cellobiosiphila are yet to be explored. The function annotation of the genome sequence of Spirochaeta cellobiosiphila is in progress. In this work we aim to map all the metabolic activities for reconstruction of genome-scale metabolic model of Spirochaeta cellobiosiphila.

MIPS: analysis and annotation of proteins from whole genomes in 2005.

Science.gov (United States)

Mewes, H W; Frishman, D; Mayer, K F X; Münsterkötter, M; Noubibou, O; Pagel, P; Rattei, T; Oesterheld, M; Ruepp, A; Stümpflen, V

2006-01-01

The Munich Information Center for Protein Sequences (MIPS at the GSF), Neuherberg, Germany, provides resources related to genome information. Manually curated databases for several reference organisms are maintained. Several of these databases are described elsewhere in this and other recent NAR database issues. In a complementary effort, a comprehensive set of >400 genomes automatically annotated with the PEDANT system are maintained. The main goal of our current work on creating and maintaining genome databases is to extend gene centered information to information on interactions within a generic comprehensive framework. We have concentrated our efforts along three lines (i) the development of suitable comprehensive data structures and database technology, communication and query tools to include a wide range of different types of information enabling the representation of complex information such as functional modules or networks Genome Research Environment System, (ii) the development of databases covering computable information such as the basic evolutionary relations among all genes, namely SIMAP, the sequence similarity matrix and the CABiNet network analysis framework and (iii) the compilation and manual annotation of information related to interactions such as protein-protein interactions or other types of relations (e.g. MPCDB, MPPI, CYGD). All databases described and the detailed descriptions of our projects can be accessed through the MIPS WWW server (http://mips.gsf.de).

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

Science.gov (United States)

Boldogköi, Zsolt

2012-01-01

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 organization, 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 neighboring 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 synchronized 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 organisms too.

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

Teacher and student reflections on ICT-rich science inquiry

DEFF Research Database (Denmark)

Williams, John; Otrel-Cass, Kathrin

2017-01-01

and different ways for students to engage with, explore and communicate science ideas within inquiry. Sample: This project developed case studies with 6 science teachers of year 9 and 10 students, with an average age of 13 and 14 years in three New Zealand high schools. Teacher participants in the project had...... varying levels of understanding and experience with inquiry learning in science. Teacher knowledge and experience with ICT were equally diverse. Design and Methods: Teachers and researchers developed initially in a joint workshop a shared understanding of inquiry, and how this could be enacted. During......Background: Inquiry learning in science provides authentic and relevant contexts in which students can create knowledge to solve problems, make decisions and find solutions to issues in today’s world. The use of electronic networks can facilitate this interaction, dialogue and sharing, and adds...

Genomes, Proteomes and the Central Dogma

Science.gov (United States)

Franklin, Sarah; Vondriska, Thomas M.

2011-01-01

Systems biology, with its associated technologies of proteomics, genomics and metabolomics, is driving the evolution of our understanding of cardiovascular physiology. Rather than studying individual molecules or even single reactions, a systems approach allows integration of orthogonal datasets from distinct tiers of biological data, including gene, RNA, protein, metabolite and other component networks. Together these networks give rise to emergent properties of cellular function and it is their reprogramming that causes disease. We present five observations regarding how systems biology is guiding a revisiting of the central dogma: (i) de-emphasizing the unidirectional flow of information from genes to proteins; (ii) revealing the role of modules of molecules as opposed to individual proteins acting in isolation; (iii) enabling discovery of novel emergent properties; (iv) demonstrating the importance of networks in biology; and (v) adding new dimensionality to the study of biological systems. PMID:22010165

Genomes, proteomes, and the central dogma.

Science.gov (United States)

Franklin, Sarah; Vondriska, Thomas M

2011-10-01

Systems biology, with its associated technologies of proteomics, genomics, and metabolomics, is driving the evolution of our understanding of cardiovascular physiology. Rather than studying individual molecules or even single reactions, a systems approach allows integration of orthogonal data sets from distinct tiers of biological data, including gene, RNA, protein, metabolite, and other component networks. Together these networks give rise to emergent properties of cellular function, and it is their reprogramming that causes disease. We present 5 observations regarding how systems biology is guiding a revisiting of the central dogma: (1) It deemphasizes the unidirectional flow of information from genes to proteins; (2) it reveals the role of modules of molecules as opposed to individual proteins acting in isolation; (3) it enables discovery of novel emergent properties; (4) it demonstrates the importance of networks in biology; and (5) it adds new dimensionality to the study of biological systems.

Divergent and convergent modes of interaction between wheat and Puccinia graminis f. sp. tritici isolates revealed by the comparative gene co-expression network and genome analyses.

Science.gov (United States)

Rutter, William B; Salcedo, Andres; Akhunova, Alina; He, Fei; Wang, Shichen; Liang, Hanquan; Bowden, Robert L; Akhunov, Eduard

2017-04-12

Two opposing evolutionary constraints exert pressure on plant pathogens: one to diversify virulence factors in order to evade plant defenses, and the other to retain virulence factors critical for maintaining a compatible interaction with the plant host. To better understand how the diversified arsenals of fungal genes promote interaction with the same compatible wheat line, we performed a comparative genomic analysis of two North American isolates of Puccinia graminis f. sp. tritici (Pgt). The patterns of inter-isolate divergence in the secreted candidate effector genes were compared with the levels of conservation and divergence of plant-pathogen gene co-expression networks (GCN) developed for each isolate. Comprative genomic analyses revealed substantial level of interisolate divergence in effector gene complement and sequence divergence. Gene Ontology (GO) analyses of the conserved and unique parts of the isolate-specific GCNs identified a number of conserved host pathways targeted by both isolates. Interestingly, the degree of inter-isolate sub-network conservation varied widely for the different host pathways and was positively associated with the proportion of conserved effector candidates associated with each sub-network. While different Pgt isolates tended to exploit similar wheat pathways for infection, the mode of plant-pathogen interaction varied for different pathways with some pathways being associated with the conserved set of effectors and others being linked with the diverged or isolate-specific effectors. Our data suggest that at the intra-species level pathogen populations likely maintain divergent sets of effectors capable of targeting the same plant host pathways. This functional redundancy may play an important role in the dynamic of the "arms-race" between host and pathogen serving as the basis for diverse virulence strategies and creating conditions where mutations in certain effector groups will not have a major effect on the pathogen