DNA-PKcs, ATM, and ATR Interplay Maintains Genome Integrity during Neurogenesis.

Science.gov (United States)

Enriquez-Rios, Vanessa; Dumitrache, Lavinia C; Downing, Susanna M; Li, Yang; Brown, Eric J; Russell, Helen R; McKinnon, Peter J

2017-01-25

The DNA damage response (DDR) orchestrates a network of cellular processes that integrates cell-cycle control and DNA repair or apoptosis, which serves to maintain genome stability. DNA-PKcs (the catalytic subunit of the DNA-dependent kinase, encoded by PRKDC), ATM (ataxia telangiectasia, mutated), and ATR (ATM and Rad3-related) are related PI3K-like protein kinases and central regulators of the DDR. Defects in these kinases have been linked to neurodegenerative or neurodevelopmental syndromes. In all cases, the key neuroprotective function of these kinases is uncertain. It also remains unclear how interactions between the three DNA damage-responsive kinases coordinate genome stability, particularly in a physiological context. Here, we used a genetic approach to identify the neural function of DNA-PKcs and the interplay between ATM and ATR during neurogenesis. We found that DNA-PKcs loss in the mouse sensitized neuronal progenitors to apoptosis after ionizing radiation because of excessive DNA damage. DNA-PKcs was also required to prevent endogenous DNA damage accumulation throughout the adult brain. In contrast, ATR coordinated the DDR during neurogenesis to direct apoptosis in cycling neural progenitors, whereas ATM regulated apoptosis in both proliferative and noncycling cells. We also found that ATR controls a DNA damage-induced G 2 /M checkpoint in cortical progenitors, independent of ATM and DNA-PKcs. These nonoverlapping roles were further confirmed via sustained murine embryonic or cortical development after all three kinases were simultaneously inactivated. Thus, our results illustrate how DNA-PKcs, ATM, and ATR have unique and essential roles during the DDR, collectively ensuring comprehensive genome maintenance in the nervous system. The DNA damage response (DDR) is essential for prevention of a broad spectrum of different human neurologic diseases. However, a detailed understanding of the DDR at a physiological level is lacking. In contrast to many in

A model of interval timing by neural integration.

Science.gov (United States)

Simen, Patrick; Balci, Fuat; de Souza, Laura; Cohen, Jonathan D; Holmes, Philip

2011-06-22

We show that simple assumptions about neural processing lead to a model of interval timing as a temporal integration process, in which a noisy firing-rate representation of time rises linearly on average toward a response threshold over the course of an interval. Our assumptions include: that neural spike trains are approximately independent Poisson processes, that correlations among them can be largely cancelled by balancing excitation and inhibition, that neural populations can act as integrators, and that the objective of timed behavior is maximal accuracy and minimal variance. The model accounts for a variety of physiological and behavioral findings in rodents, monkeys, and humans, including ramping firing rates between the onset of reward-predicting cues and the receipt of delayed rewards, and universally scale-invariant response time distributions in interval timing tasks. It furthermore makes specific, well-supported predictions about the skewness of these distributions, a feature of timing data that is usually ignored. The model also incorporates a rapid (potentially one-shot) duration-learning procedure. Human behavioral data support the learning rule's predictions regarding learning speed in sequences of timed responses. These results suggest that simple, integration-based models should play as prominent a role in interval timing theory as they do in theories of perceptual decision making, and that a common neural mechanism may underlie both types of behavior.

G-InforBIO: integrated system for microbial genomics

Directory of Open Access Journals (Sweden)

Abe Takashi

2006-08-01

Full Text Available Abstract Background Genome databases contain diverse kinds of information, including gene annotations and nucleotide and amino acid sequences. It is not easy to integrate such information for genomic study. There are few tools for integrated analyses of genomic data, therefore, we developed software that enables users to handle, manipulate, and analyze genome data with a variety of sequence analysis programs. Results The G-InforBIO system is a novel tool for genome data management and sequence analysis. The system can import genome data encoded as eXtensible Markup Language documents as formatted text documents, including annotations and sequences, from DNA Data Bank of Japan and GenBank encoded as flat files. The genome database is constructed automatically after importing, and the database can be exported as documents formatted with eXtensible Markup Language or tab-deliminated text. Users can retrieve data from the database by keyword searches, edit annotation data of genes, and process data with G-InforBIO. In addition, information in the G-InforBIO database can be analyzed seamlessly with nine different software programs, including programs for clustering and homology analyses. Conclusion The G-InforBIO system simplifies genome analyses by integrating several available software programs to allow efficient handling and manipulation of genome data. G-InforBIO is freely available from the download site.

The integrated microbial genome resource of analysis.

Science.gov (United States)

Checcucci, Alice; Mengoni, Alessio

2015-01-01

Integrated Microbial Genomes and Metagenomes (IMG) is a biocomputational system that allows to provide information and support for annotation and comparative analysis of microbial genomes and metagenomes. IMG has been developed by the US Department of Energy (DOE)-Joint Genome Institute (JGI). IMG platform contains both draft and complete genomes, sequenced by Joint Genome Institute and other public and available genomes. Genomes of strains belonging to Archaea, Bacteria, and Eukarya domains are present as well as those of viruses and plasmids. Here, we provide some essential features of IMG system and case study for pangenome analysis.

Integrative Genomics Viewer (IGV) | Informatics Technology for Cancer Research (ITCR)

Science.gov (United States)

The Integrative Genomics Viewer (IGV) is a high-performance visualization tool for interactive exploration of large, integrated genomic datasets. It supports a wide variety of data types, including array-based and next-generation sequence data, and genomic annotations.

Commentary. Integrative Modeling and the Role of Neural Constraints

Czech Academy of Sciences Publication Activity Database

Bantegnie, Brice

2017-01-01

Roč. 8, SEP 5 (2017), s. 1-2, č. článku 1531. ISSN 1664-1078 Institutional support: RVO:67985955 Keywords : mechanistic explanation * functional analysis * mechanistic integration * reverse inference * neural plasticity * neural networks Subject RIV: AA - Philosophy ; Religion Impact factor: 2.323, year: 2016

The Genome-Scale Integrated Networks in Microorganisms

Directory of Open Access Journals (Sweden)

Tong Hao

2018-02-01

Full Text Available The genome-scale cellular network has become a necessary tool in the systematic analysis of microbes. In a cell, there are several layers (i.e., types of the molecular networks, for example, genome-scale metabolic network (GMN, transcriptional regulatory network (TRN, and signal transduction network (STN. It has been realized that the limitation and inaccuracy of the prediction exist just using only a single-layer network. Therefore, the integrated network constructed based on the networks of the three types attracts more interests. The function of a biological process in living cells is usually performed by the interaction of biological components. Therefore, it is necessary to integrate and analyze all the related components at the systems level for the comprehensively and correctly realizing the physiological function in living organisms. In this review, we discussed three representative genome-scale cellular networks: GMN, TRN, and STN, representing different levels (i.e., metabolism, gene regulation, and cellular signaling of a cell’s activities. Furthermore, we discussed the integration of the networks of the three types. With more understanding on the complexity of microbial cells, the development of integrated network has become an inevitable trend in analyzing genome-scale cellular networks of microorganisms.

Neural Correlates of Impaired Reward-Effort Integration in Remitted Bulimia Nervosa.

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Mueller, Stefanie Verena; Morishima, Yosuke; Schwab, Simon; Wiest, Roland; Federspiel, Andrea; Hasler, Gregor

2018-03-01

The integration of reward magnitudes and effort costs is required for an effective behavioral guidance. This reward-effort integration was reported to be dependent on dopaminergic neurotransmission. As bulimia nervosa has been associated with a dysregulated dopamine system and catecholamine depletion led to reward-processing deficits in remitted bulimia nervosa, the purpose of this study was to identify the role of catecholamine dysfunction and its relation to behavioral and neural reward-effort integration in bulimia nervosa. To investigate the interaction between catecholamine functioning and behavioral, and neural responses directly, 17 remitted bulimic (rBN) and 21 healthy individuals (HC) received alpha-methyl-paratyrosine (AMPT) over 24 h to achieve catecholamine depletion in a randomized, crossover study design. We used functional magnetic resonance imaging (fMRI) and the monetary incentive delay (MID) task to assess reward-effort integration in relation to catecholaminergic neurotransmission at the behavioral and neural level. AMPT reduced the ability to integrate rewards and efforts effectively in HC participants. In contrast, in rBN participants, the reduced reward-effort integration was associated with illness duration in the sham condition and unrelated to catecholamine depletion. Regarding neural activation, AMPT decreased the reward anticipation-related neural activation in the anteroventral striatum. This decrease was associated with the AMPT-induced reduction of monetary earning in HC in contrast to rBN participants. Our findings contributed to the theory of a desensitized dopaminergic system in bulimia nervosa. A disrupted processing of reward magnitudes and effort costs might increase the probability of maintenance of bulimic symptoms.

IMG: the integrated microbial genomes database and comparative analysis system

Science.gov (United States)

Markowitz, Victor M.; Chen, I-Min A.; Palaniappan, Krishna; Chu, Ken; Szeto, Ernest; Grechkin, Yuri; Ratner, Anna; Jacob, Biju; Huang, Jinghua; Williams, Peter; Huntemann, Marcel; Anderson, Iain; Mavromatis, Konstantinos; Ivanova, Natalia N.; Kyrpides, Nikos C.

2012-01-01

The Integrated Microbial Genomes (IMG) system serves as a community resource for comparative analysis of publicly available genomes in a comprehensive integrated context. IMG integrates publicly available draft and complete genomes from all three domains of life with a large number of plasmids and viruses. IMG provides tools and viewers for analyzing and reviewing the annotations of genes and genomes in a comparative context. IMG's data content and analytical capabilities have been continuously extended through regular updates since its first release in March 2005. IMG is available at http://img.jgi.doe.gov. Companion IMG systems provide support for expert review of genome annotations (IMG/ER: http://img.jgi.doe.gov/er), teaching courses and training in microbial genome analysis (IMG/EDU: http://img.jgi.doe.gov/edu) and analysis of genomes related to the Human Microbiome Project (IMG/HMP: http://www.hmpdacc-resources.org/img_hmp). PMID:22194640

Thermal photovoltaic solar integrated system analysis using neural networks

Energy Technology Data Exchange (ETDEWEB)

Ashhab, S. [Hashemite Univ., Zarqa (Jordan). Dept. of Mechanical Engineering

2007-07-01

The energy demand in Jordan is primarily met by petroleum products. As such, the development of renewable energy systems is quite attractive. In particular, solar energy is a promising renewable energy source in Jordan and has been used for food canning, paper production, air-conditioning and sterilization. Artificial neural networks (ANNs) have received significant attention due to their capabilities in forecasting, modelling of complex nonlinear systems and control. ANNs have been used for forecasting solar energy. This paper presented a study that examined a thermal photovoltaic solar integrated system that was built in Jordan. Historical input-output system data that was collected experimentally was used to train an ANN that predicted the collector, PV module, pump and total efficiencies. The model predicted the efficiencies well and can therefore be utilized to find the operating conditions of the system that will produce the maximum system efficiencies. The paper provided a description of the photovoltaic solar system including equations for PV module efficiency; pump efficiency; and total efficiency. The paper also presented data relevant to the system performance and neural networks. The results of a neural net model were also presented based on the thermal PV solar integrated system data that was collected. It was concluded that the neural net model of the thermal photovoltaic solar integrated system set the background for achieving the best system performance. 10 refs., 6 figs.

VERSE: a novel approach to detect virus integration in host genomes through reference genome customization.

Science.gov (United States)

Wang, Qingguo; Jia, Peilin; Zhao, Zhongming

2015-01-01

Fueled by widespread applications of high-throughput next generation sequencing (NGS) technologies and urgent need to counter threats of pathogenic viruses, large-scale studies were conducted recently to investigate virus integration in host genomes (for example, human tumor genomes) that may cause carcinogenesis or other diseases. A limiting factor in these studies, however, is rapid virus evolution and resulting polymorphisms, which prevent reads from aligning readily to commonly used virus reference genomes, and, accordingly, make virus integration sites difficult to detect. Another confounding factor is host genomic instability as a result of virus insertions. To tackle these challenges and improve our capability to identify cryptic virus-host fusions, we present a new approach that detects Virus intEgration sites through iterative Reference SEquence customization (VERSE). To the best of our knowledge, VERSE is the first approach to improve detection through customizing reference genomes. Using 19 human tumors and cancer cell lines as test data, we demonstrated that VERSE substantially enhanced the sensitivity of virus integration site detection. VERSE is implemented in the open source package VirusFinder 2 that is available at http://bioinfo.mc.vanderbilt.edu/VirusFinder/.

Integrating genomics into undergraduate nursing education.

Science.gov (United States)

Daack-Hirsch, Sandra; Dieter, Carla; Quinn Griffin, Mary T

2011-09-01

To prepare the next generation of nurses, faculty are now faced with the challenge of incorporating genomics into curricula. Here we discuss how to meet this challenge. Steps to initiate curricular changes to include genomics are presented along with a discussion on creating a genomic curriculum thread versus a standalone course. Ideas for use of print material and technology on genomic topics are also presented. Information is based on review of the literature and curriculum change efforts by the authors. In recognition of advances in genomics, the nursing profession is increasing an emphasis on the integration of genomics into professional practice and educational standards. Incorporating genomics into nurses' practices begins with changes in our undergraduate curricula. Information given in didactic courses should be reinforced in clinical practica, and Internet-based tools such as WebQuest, Second Life, and wikis offer attractive, up-to-date platforms to deliver this now crucial content. To provide information that may assist faculty to prepare the next generation of nurses to practice using genomics. © 2011 Sigma Theta Tau International.

Structural reliability calculation method based on the dual neural network and direct integration method.

Science.gov (United States)

Li, Haibin; He, Yun; Nie, Xiaobo

2018-01-01

Structural reliability analysis under uncertainty is paid wide attention by engineers and scholars due to reflecting the structural characteristics and the bearing actual situation. The direct integration method, started from the definition of reliability theory, is easy to be understood, but there are still mathematics difficulties in the calculation of multiple integrals. Therefore, a dual neural network method is proposed for calculating multiple integrals in this paper. Dual neural network consists of two neural networks. The neural network A is used to learn the integrand function, and the neural network B is used to simulate the original function. According to the derivative relationships between the network output and the network input, the neural network B is derived from the neural network A. On this basis, the performance function of normalization is employed in the proposed method to overcome the difficulty of multiple integrations and to improve the accuracy for reliability calculations. The comparisons between the proposed method and Monte Carlo simulation method, Hasofer-Lind method, the mean value first-order second moment method have demonstrated that the proposed method is an efficient and accurate reliability method for structural reliability problems.

Integrating genomics into evolutionary medicine.

Science.gov (United States)

Rodríguez, Juan Antonio; Marigorta, Urko M; Navarro, Arcadi

2014-12-01

The application of the principles of evolutionary biology into medicine was suggested long ago and is already providing insight into the ultimate causes of disease. However, a full systematic integration of medical genomics and evolutionary medicine is still missing. Here, we briefly review some cases where the combination of the two fields has proven profitable and highlight two of the main issues hindering the development of evolutionary genomic medicine as a mature field, namely the dissociation between fitness and health and the still considerable difficulties in predicting phenotypes from genotypes. We use publicly available data to illustrate both problems and conclude that new approaches are needed for evolutionary genomic medicine to overcome these obstacles. Copyright © 2014 Elsevier Ltd. All rights reserved.

Characterization of Equine Infectious Anemia Virus Integration in the Horse Genome

Directory of Open Access Journals (Sweden)

Qiang Liu

2015-06-01

Full Text Available Human immunodeficiency virus (HIV-1 has a unique integration profile in the human genome relative to murine and avian retroviruses. Equine infectious anemia virus (EIAV is another well-studied lentivirus that can also be used as a promising retro-transfection vector, but its integration into its native host has not been characterized. In this study, we mapped 477 integration sites of the EIAV strain EIAVFDDV13 in fetal equine dermal (FED cells during in vitro infection. Published integration sites of EIAV and HIV-1 in the human genome were also analyzed as references. Our results demonstrated that EIAVFDDV13 tended to integrate into genes and AT-rich regions, and it avoided integrating into transcription start sites (TSS, which is consistent with EIAV and HIV-1 integration in the human genome. Notably, the integration of EIAVFDDV13 favored long interspersed elements (LINEs and DNA transposons in the horse genome, whereas the integration of HIV-1 favored short interspersed elements (SINEs in the human genome. The chromosomal environment near LINEs or DNA transposons potentially influences viral transcription and may be related to the unique EIAV latency states in equids. The data on EIAV integration in its natural host will facilitate studies on lentiviral infection and lentivirus-based therapeutic vectors.

IMG 4 version of the integrated microbial genomes comparative analysis system

Science.gov (United States)

Markowitz, Victor M.; Chen, I-Min A.; Palaniappan, Krishna; Chu, Ken; Szeto, Ernest; Pillay, Manoj; Ratner, Anna; Huang, Jinghua; Woyke, Tanja; Huntemann, Marcel; Anderson, Iain; Billis, Konstantinos; Varghese, Neha; Mavromatis, Konstantinos; Pati, Amrita; Ivanova, Natalia N.; Kyrpides, Nikos C.

2014-01-01

The Integrated Microbial Genomes (IMG) data warehouse integrates genomes from all three domains of life, as well as plasmids, viruses and genome fragments. IMG provides tools for analyzing and reviewing the structural and functional annotations of genomes in a comparative context. IMG’s data content and analytical capabilities have increased continuously since its first version released in 2005. Since the last report published in the 2012 NAR Database Issue, IMG’s annotation and data integration pipelines have evolved while new tools have been added for recording and analyzing single cell genomes, RNA Seq and biosynthetic cluster data. Different IMG datamarts provide support for the analysis of publicly available genomes (IMG/W: http://img.jgi.doe.gov/w), expert review of genome annotations (IMG/ER: http://img.jgi.doe.gov/er) and teaching and training in the area of microbial genome analysis (IMG/EDU: http://img.jgi.doe.gov/edu). PMID:24165883

IMG 4 version of the integrated microbial genomes comparative analysis system

Energy Technology Data Exchange (ETDEWEB)

Markowitz, Victor M. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Biological Data Management and Technology Center. Computational Research Division; Chen, I-Min A. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Biological Data Management and Technology Center. Computational Research Division; Palaniappan, Krishna [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Biological Data Management and Technology Center. Computational Research Division; Chu, Ken [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Biological Data Management and Technology Center. Computational Research Division; Szeto, Ernest [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Biological Data Management and Technology Center. Computational Research Division; Pillay, Manoj [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Biological Data Management and Technology Center. Computational Research Division; Ratner, Anna [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Biological Data Management and Technology Center. Computational Research Division; Huang, Jinghua [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). Biological Data Management and Technology Center. Computational Research Division; Woyke, Tanja [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States). Microbial Genome and Metagenome Program; Huntemann, Marcel [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States). Microbial Genome and Metagenome Program; Anderson, Iain [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States). Microbial Genome and Metagenome Program; Billis, Konstantinos [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States). Microbial Genome and Metagenome Program; Varghese, Neha [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States). Microbial Genome and Metagenome Program; Mavromatis, Konstantinos [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States). Microbial Genome and Metagenome Program; Pati, Amrita [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States). Microbial Genome and Metagenome Program; Ivanova, Natalia N. [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States). Microbial Genome and Metagenome Program; Kyrpides, Nikos C. [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States). Microbial Genome and Metagenome Program

2013-10-27

The Integrated Microbial Genomes (IMG) data warehouse integrates genomes from all three domains of life, as well as plasmids, viruses and genome fragments. IMG provides tools for analyzing and reviewing the structural and functional annotations of genomes in a comparative context. IMG’s data content and analytical capabilities have increased continuously since its first version released in 2005. Since the last report published in the 2012 NAR Database Issue, IMG’s annotation and data integration pipelines have evolved while new tools have been added for recording and analyzing single cell genomes, RNA Seq and biosynthetic cluster data. Finally, different IMG datamarts provide support for the analysis of publicly available genomes (IMG/W: http://img.jgi.doe.gov/w), expert review of genome annotations (IMG/ER: http://img.jgi.doe.gov/er) and teaching and training in the area of microbial genome analysis (IMG/EDU: http://img.jgi.doe.gov/edu).

The Integrated Microbial Genomes (IMG) System: An Expanding Comparative Analysis Resource

Energy Technology Data Exchange (ETDEWEB)

Markowitz, Victor M.; Chen, I-Min A.; Palaniappan, Krishna; Chu, Ken; Szeto, Ernest; Grechkin, Yuri; Ratner, Anna; Anderson, Iain; Lykidis, Athanasios; Mavromatis, Konstantinos; Ivanova, Natalia N.; Kyrpides, Nikos C.

2009-09-13

The integrated microbial genomes (IMG) system serves as a community resource for comparative analysis of publicly available genomes in a comprehensive integrated context. IMG contains both draft and complete microbial genomes integrated with other publicly available genomes from all three domains of life, together with a large number of plasmids and viruses. IMG provides tools and viewers for analyzing and reviewing the annotations of genes and genomes in a comparative context. Since its first release in 2005, IMG's data content and analytical capabilities have been constantly expanded through regular releases. Several companion IMG systems have been set up in order to serve domain specific needs, such as expert review of genome annotations. IMG is available at .

Accelerated DNA Methylation Age: Associations with PTSD and Neural Integrity

Science.gov (United States)

Wolf, Erika J.; Logue, Mark W.; Hayes, Jasmeet P.; Sadeh, Naomi; Schichman, Steven A.; Stone, Annjanette; Salat, David H.; Milberg, William; McGlinchey, Regina; Miller, Mark W.

2015-01-01

Background Accumulating evidence suggests that post traumatic stress disorder (PTSD) may accelerate cellular aging and lead to premature morbidity and neurocognitive decline. Methods This study evaluated associations between PTSD and DNA methylation (DNAm) age using recently developed algorithms of cellular age by Horvath (2013) and Hannum et al. (2013). These estimates reflect accelerated aging when they exceed chronological age. We also examined if accelerated cellular age manifested in degraded neural integrity, indexed via diffusion tensor imaging. Results Among 281 male and female veterans of the conflicts in Iraq and Afghanistan, DNAm age was strongly related to chronological age (rs ~.88). Lifetime PTSD severity was associated with Hannum DNAm age estimates residualized for chronological age (β = .13, p= .032). Advanced DNAm age was associated with reduced integrity in the genu of the corpus callosum (β = −.17, p= .009) and indirectly linked to poorer working memory performance via this region (indirect β = − .05, p= .029). Horvath DNAm age estimates were not associated with PTSD or neural integrity. Conclusions Results provide novel support for PTSD-related accelerated aging in DNAm and extend the evidence base of known DNAm age correlates to the domains of neural integrity and cognition. PMID:26447678

The Plant Genome Integrative Explorer Resource: PlantGenIE.org.

Science.gov (United States)

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.

FUZZY NEURAL NETWORK FOR OBJECT IDENTIFICATION ON INTEGRATED CIRCUIT LAYOUTS

Directory of Open Access Journals (Sweden)

A. A. Doudkin

2015-01-01

Full Text Available Fuzzy neural network model based on neocognitron is proposed to identify layout objects on images of topological layers of integrated circuits. Testing of the model on images of real chip layouts was showed a highеr degree of identification of the proposed neural network in comparison to base neocognitron.

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

CERN Document Server

Baianu, I C

2004-01-01

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

The three-dimensional genome organization of Drosophila melanogaster through data integration.

Science.gov (United States)

Li, Qingjiao; Tjong, Harianto; Li, Xiao; Gong, Ke; Zhou, Xianghong Jasmine; Chiolo, Irene; Alber, Frank

2017-07-31

Genome structures are dynamic and non-randomly organized in the nucleus of higher eukaryotes. To maximize the accuracy and coverage of three-dimensional genome structural models, it is important to integrate all available sources of experimental information about a genome's organization. It remains a major challenge to integrate such data from various complementary experimental methods. Here, we present an approach for data integration to determine a population of complete three-dimensional genome structures that are statistically consistent with data from both genome-wide chromosome conformation capture (Hi-C) and lamina-DamID experiments. Our structures resolve the genome at the resolution of topological domains, and reproduce simultaneously both sets of experimental data. Importantly, this data deconvolution framework allows for structural heterogeneity between cells, and hence accounts for the expected plasticity of genome structures. As a case study we choose Drosophila melanogaster embryonic cells, for which both data types are available. Our three-dimensional genome structures have strong predictive power for structural features not directly visible in the initial data sets, and reproduce experimental hallmarks of the D. melanogaster genome organization from independent and our own imaging experiments. Also they reveal a number of new insights about genome organization and its functional relevance, including the preferred locations of heterochromatic satellites of different chromosomes, and observations about homologous pairing that cannot be directly observed in the original Hi-C or lamina-DamID data. Our approach allows systematic integration of Hi-C and lamina-DamID data for complete three-dimensional genome structure calculation, while also explicitly considering genome structural variability.

Genome-wide profiling of HPV integration in cervical cancer identifies clustered genomic hot spots and a potential microhomology-mediated integration mechanism

DEFF Research Database (Denmark)

Hu, Zheng; Zhu, Da; Wang, Wei

2015-01-01

Human papillomavirus (HPV) integration is a key genetic event in cervical carcinogenesis1. By conducting whole-genome sequencing and high-throughput viral integration detection, we identified 3,667 HPV integration breakpoints in 26 cervical intraepithelial neoplasias, 104 cervical carcinomas and ...

GAPIT: genome association and prediction integrated tool.

Science.gov (United States)

Lipka, Alexander E; Tian, Feng; Wang, Qishan; Peiffer, Jason; Li, Meng; Bradbury, Peter J; Gore, Michael A; Buckler, Edward S; Zhang, Zhiwu

2012-09-15

Software programs that conduct genome-wide association studies and genomic prediction and selection need to use methodologies that maximize statistical power, provide high prediction accuracy and run in a computationally efficient manner. We developed an R package called Genome Association and Prediction Integrated Tool (GAPIT) that implements advanced statistical methods including the compressed mixed linear model (CMLM) and CMLM-based genomic prediction and selection. The GAPIT package can handle large datasets in excess of 10 000 individuals and 1 million single-nucleotide polymorphisms with minimal computational time, while providing user-friendly access and concise tables and graphs to interpret results. http://www.maizegenetics.net/GAPIT. zhiwu.zhang@cornell.edu Supplementary data are available at Bioinformatics online.

Integrated Markov-neural reliability computation method: A case for multiple automated guided vehicle system

International Nuclear Information System (INIS)

Fazlollahtabar, Hamed; Saidi-Mehrabad, Mohammad; Balakrishnan, Jaydeep

2015-01-01

This paper proposes an integrated Markovian and back propagation neural network approaches to compute reliability of a system. While states of failure occurrences are significant elements for accurate reliability computation, Markovian based reliability assessment method is designed. Due to drawbacks shown by Markovian model for steady state reliability computations and neural network for initial training pattern, integration being called Markov-neural is developed and evaluated. To show efficiency of the proposed approach comparative analyses are performed. Also, for managerial implication purpose an application case for multiple automated guided vehicles (AGVs) in manufacturing networks is conducted. - Highlights: • Integrated Markovian and back propagation neural network approach to compute reliability. • Markovian based reliability assessment method. • Managerial implication is shown in an application case for multiple automated guided vehicles (AGVs) in manufacturing networks

Application of Integrated Neural Network Method to Fault Diagnosis of Nuclear Steam Generator

International Nuclear Information System (INIS)

Zhou Gang; Yang Li

2009-01-01

A new fault diagnosis method based on integrated neural networks for nuclear steam generator (SG) was proposed in view of the shortcoming of the conventional fault monitoring and diagnosis method. In the method, two neural networks (ANNs) were employed for the fault diagnosis of steam generator. A neural network, which was used for predicting the values of steam generator operation parameters, was taken as the dynamics model of steam generator. The principle of fault monitoring method using the neural network model is to detect the deviations between process signals measured from an operating steam generator and corresponding output signals from the neural network model of steam generator. When the deviation exceeds the limit set in advance, the abnormal event is thought to occur. The other neural network as a fault classifier conducts the fault classification of steam generator. So, the fault types of steam generator are given by the fault classifier. The clear information on steam generator faults was obtained by fusing the monitoring and diagnosis results of two neural networks. The simulation results indicate that employing integrated neural networks can improve the capacity of fault monitoring and diagnosis for the steam generator. (authors)

Assembly and Multiplex Genome Integration of Metabolic Pathways in Yeast Using CasEMBLR

DEFF Research Database (Denmark)

Jakočiūnas, Tadas; Jensen, Emil D.; Jensen, Michael Krogh

2018-01-01

and marker-free integration of the carotenoid pathway from 15 exogenously supplied DNA parts into three targeted genomic loci. As a second proof-of-principle, a total of ten DNA parts were assembled and integrated in two genomic loci to construct a tyrosine production strain, and at the same time knocking......Genome integration is a vital step for implementing large biochemical pathways to build a stable microbial cell factory. Although traditional strain construction strategies are well established for the model organism Saccharomyces cerevisiae, recent advances in CRISPR/Cas9-mediated genome...... engineering allow much higher throughput and robustness in terms of strain construction. In this chapter, we describe CasEMBLR, a highly efficient and marker-free genome engineering method for one-step integration of in vivo assembled expression cassettes in multiple genomic sites simultaneously. Cas...

Optimal multiple-information integration inherent in a ring neural network

International Nuclear Information System (INIS)

Takiyama, Ken

2017-01-01

Although several behavioral experiments have suggested that our neural system integrates multiple sources of information based on the certainty of each type of information in the manner of maximum-likelihood estimation, it is unclear how the maximum-likelihood estimation is implemented in our neural system. Here, I investigate the relationship between maximum-likelihood estimation and a widely used ring-type neural network model that is used as a model of visual, motor, or prefrontal cortices. Without any approximation or ansatz, I analytically demonstrate that the equilibrium of an order parameter in the neural network model exactly corresponds to the maximum-likelihood estimation when the strength of the symmetrical recurrent synaptic connectivity within a neural population is appropriately stronger than that of asymmetrical connectivity, that of local and external inputs, and that of symmetrical or asymmetrical connectivity between different neural populations. In this case, strengths of local and external inputs or those of symmetrical connectivity between different neural populations exactly correspond to the input certainty in maximum-likelihood estimation. Thus, my analysis suggests appropriately strong symmetrical recurrent connectivity as a possible candidate for implementing the maximum-likelihood estimation within our neural system. (paper)

Functional Stem Cell Integration into Neural Networks Assessed by Organotypic Slice Cultures.

Science.gov (United States)

Forsberg, David; Thonabulsombat, Charoensri; Jäderstad, Johan; Jäderstad, Linda Maria; Olivius, Petri; Herlenius, Eric

2017-08-14

Re-formation or preservation of functional, electrically active neural networks has been proffered as one of the goals of stem cell-mediated neural therapeutics. A primary issue for a cell therapy approach is the formation of functional contacts between the implanted cells and the host tissue. Therefore, it is of fundamental interest to establish protocols that allow us to delineate a detailed time course of grafted stem cell survival, migration, differentiation, integration, and functional interaction with the host. One option for in vitro studies is to examine the integration of exogenous stem cells into an existing active neural network in ex vivo organotypic cultures. Organotypic cultures leave the structural integrity essentially intact while still allowing the microenvironment to be carefully controlled. This allows detailed studies over time of cellular responses and cell-cell interactions, which are not readily performed in vivo. This unit describes procedures for using organotypic slice cultures as ex vivo model systems for studying neural stem cell and embryonic stem cell engraftment and communication with CNS host tissue. © 2017 by John Wiley & Sons, Inc. Copyright © 2017 John Wiley & Sons, Inc.

Forecasting SPEI and SPI Drought Indices Using the Integrated Artificial Neural Networks

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Petr Maca

2016-01-01

Full Text Available The presented paper compares forecast of drought indices based on two different models of artificial neural networks. The first model is based on feedforward multilayer perceptron, sANN, and the second one is the integrated neural network model, hANN. The analyzed drought indices are the standardized precipitation index (SPI and the standardized precipitation evaporation index (SPEI and were derived for the period of 1948–2002 on two US catchments. The meteorological and hydrological data were obtained from MOPEX experiment. The training of both neural network models was made by the adaptive version of differential evolution, JADE. The comparison of models was based on six model performance measures. The results of drought indices forecast, explained by the values of four model performance indices, show that the integrated neural network model was superior to the feedforward multilayer perceptron with one hidden layer of neurons.

Transcription as a Threat to Genome Integrity.

Science.gov (United States)

Gaillard, Hélène; Aguilera, Andrés

2016-06-02

Genomes undergo different types of sporadic alterations, including DNA damage, point mutations, and genome rearrangements, that constitute the basis for evolution. However, these changes may occur at high levels as a result of cell pathology and trigger genome instability, a hallmark of cancer and a number of genetic diseases. In the last two decades, evidence has accumulated that transcription constitutes an important natural source of DNA metabolic errors that can compromise the integrity of the genome. Transcription can create the conditions for high levels of mutations and recombination by its ability to open the DNA structure and remodel chromatin, making it more accessible to DNA insulting agents, and by its ability to become a barrier to DNA replication. Here we review the molecular basis of such events from a mechanistic perspective with particular emphasis on the role of transcription as a genome instability determinant.

Human Papillomavirus Genome Integration and Head and Neck Cancer.

Science.gov (United States)

Pinatti, L M; Walline, H M; Carey, T E

2018-06-01

We conducted a critical review of human papillomavirus (HPV) integration into the host genome in oral/oropharyngeal cancer, reviewed the literature for HPV-induced cancers, and obtained current data for HPV-related oral and oropharyngeal cancers. In addition, we performed studies to identify HPV integration sites and the relationship of integration to viral-host fusion transcripts and whether integration is required for HPV-associated oncogenesis. Viral integration of HPV into the host genome is not required for the viral life cycle and might not be necessary for cellular transformation, yet HPV integration is frequently reported in cervical and head and neck cancer specimens. Studies of large numbers of early cervical lesions revealed frequent viral integration into gene-poor regions of the host genome with comparatively rare integration into cellular genes, suggesting that integration is a stochastic event and that site of integration may be largely a function of chance. However, more recent studies of head and neck squamous cell carcinomas (HNSCCs) suggest that integration may represent an additional oncogenic mechanism through direct effects on cancer-related gene expression and generation of hybrid viral-host fusion transcripts. In HNSCC cell lines as well as primary tumors, integration into cancer-related genes leading to gene disruption has been reported. The studies have shown that integration-induced altered gene expression may be associated with tumor recurrence. Evidence from several studies indicates that viral integration into genic regions is accompanied by local amplification, increased expression in some cases, interruption of gene expression, and likely additional oncogenic effects. Similarly, reported examples of viral integration near microRNAs suggest that altered expression of these regulatory molecules may also contribute to oncogenesis. Future work is indicated to identify the mechanisms of these events on cancer cell behavior.

Perspectives of Integrative Cancer Genomics in Next Generation Sequencing Era

Directory of Open Access Journals (Sweden)

So Mee Kwon

2012-06-01

Full Text Available The explosive development of genomics technologies including microarrays and next generation sequencing (NGS has provided comprehensive maps of cancer genomes, including the expression of mRNAs and microRNAs, DNA copy numbers, sequence variations, and epigenetic changes. These genome-wide profiles of the genetic aberrations could reveal the candidates for diagnostic and/or prognostic biomarkers as well as mechanistic insights into tumor development and progression. Recent efforts to establish the huge cancer genome compendium and integrative omics analyses, so-called "integromics", have extended our understanding on the cancer genome, showing its daunting complexity and heterogeneity. However, the challenges of the structured integration, sharing, and interpretation of the big omics data still remain to be resolved. Here, we review several issues raised in cancer omics data analysis, including NGS, focusing particularly on the study design and analysis strategies. This might be helpful to understand the current trends and strategies of the rapidly evolving cancer genomics research.

Assembly and Multiplex Genome Integration of Metabolic Pathways in Yeast Using CasEMBLR.

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Jakočiūnas, Tadas; Jensen, Emil D; Jensen, Michael K; Keasling, Jay D

2018-01-01

Genome integration is a vital step for implementing large biochemical pathways to build a stable microbial cell factory. Although traditional strain construction strategies are well established for the model organism Saccharomyces cerevisiae, recent advances in CRISPR/Cas9-mediated genome engineering allow much higher throughput and robustness in terms of strain construction. In this chapter, we describe CasEMBLR, a highly efficient and marker-free genome engineering method for one-step integration of in vivo assembled expression cassettes in multiple genomic sites simultaneously. CasEMBLR capitalizes on the CRISPR/Cas9 technology to generate double-strand breaks in genomic loci, thus prompting native homologous recombination (HR) machinery to integrate exogenously derived homology templates. As proof-of-principle for microbial cell factory development, CasEMBLR was used for one-step assembly and marker-free integration of the carotenoid pathway from 15 exogenously supplied DNA parts into three targeted genomic loci. As a second proof-of-principle, a total of ten DNA parts were assembled and integrated in two genomic loci to construct a tyrosine production strain, and at the same time knocking out two genes. This new method complements and improves the field of genome engineering in S. cerevisiae by providing a more flexible platform for rapid and precise strain building.

GDR (Genome Database for Rosaceae: integrated web resources for Rosaceae genomics and genetics research

Directory of Open Access Journals (Sweden)

Ficklin Stephen

2004-09-01

Full Text Available Abstract Background Peach is being developed as a model organism for Rosaceae, an economically important family that includes fruits and ornamental plants such as apple, pear, strawberry, cherry, almond and rose. The genomics and genetics data of peach can play a significant role in the gene discovery and the genetic understanding of related species. The effective utilization of these peach resources, however, requires the development of an integrated and centralized database with associated analysis tools. Description The Genome Database for Rosaceae (GDR is a curated and integrated web-based relational database. GDR contains comprehensive data of the genetically anchored peach physical map, an annotated peach EST database, Rosaceae maps and markers and all publicly available Rosaceae sequences. Annotations of ESTs include contig assembly, putative function, simple sequence repeats, and anchored position to the peach physical map where applicable. Our integrated map viewer provides graphical interface to the genetic, transcriptome and physical mapping information. ESTs, BACs and markers can be queried by various categories and the search result sites are linked to the integrated map viewer or to the WebFPC physical map sites. In addition to browsing and querying the database, users can compare their sequences with the annotated GDR sequences via a dedicated sequence similarity server running either the BLAST or FASTA algorithm. To demonstrate the utility of the integrated and fully annotated database and analysis tools, we describe a case study where we anchored Rosaceae sequences to the peach physical and genetic map by sequence similarity. Conclusions The GDR has been initiated to meet the major deficiency in Rosaceae genomics and genetics research, namely a centralized web database and bioinformatics tools for data storage, analysis and exchange. GDR can be accessed at http://www.genome.clemson.edu/gdr/.

GDR (Genome Database for Rosaceae): integrated web resources for Rosaceae genomics and genetics research.

Science.gov (United States)

Jung, Sook; Jesudurai, Christopher; Staton, Margaret; Du, Zhidian; Ficklin, Stephen; Cho, Ilhyung; Abbott, Albert; Tomkins, Jeffrey; Main, Dorrie

2004-09-09

Peach is being developed as a model organism for Rosaceae, an economically important family that includes fruits and ornamental plants such as apple, pear, strawberry, cherry, almond and rose. The genomics and genetics data of peach can play a significant role in the gene discovery and the genetic understanding of related species. The effective utilization of these peach resources, however, requires the development of an integrated and centralized database with associated analysis tools. The Genome Database for Rosaceae (GDR) is a curated and integrated web-based relational database. GDR contains comprehensive data of the genetically anchored peach physical map, an annotated peach EST database, Rosaceae maps and markers and all publicly available Rosaceae sequences. Annotations of ESTs include contig assembly, putative function, simple sequence repeats, and anchored position to the peach physical map where applicable. Our integrated map viewer provides graphical interface to the genetic, transcriptome and physical mapping information. ESTs, BACs and markers can be queried by various categories and the search result sites are linked to the integrated map viewer or to the WebFPC physical map sites. In addition to browsing and querying the database, users can compare their sequences with the annotated GDR sequences via a dedicated sequence similarity server running either the BLAST or FASTA algorithm. To demonstrate the utility of the integrated and fully annotated database and analysis tools, we describe a case study where we anchored Rosaceae sequences to the peach physical and genetic map by sequence similarity. The GDR has been initiated to meet the major deficiency in Rosaceae genomics and genetics research, namely a centralized web database and bioinformatics tools for data storage, analysis and exchange. GDR can be accessed at http://www.genome.clemson.edu/gdr/.

An integrative neural model of social perception, action observation, and theory of mind

Science.gov (United States)

Yang, Daniel Y.-J.; Rosenblau, Gabriela; Keifer, Cara; Pelphrey, Kevin A.

2016-01-01

In the field of social neuroscience, major branches of research have been instrumental in describing independent components of typical and aberrant social information processing, but the field as a whole lacks a comprehensive model that integrates different branches. We review existing research related to the neural basis of three key neural systems underlying social information processing: social perception, action observation, and theory of mind. We propose an integrative model that unites these three processes and highlights the posterior superior temporal sulcus (pSTS), which plays a central role in all three systems. Furthermore, we integrate these neural systems with the dual system account of implicit and explicit social information processing. Large-scale meta-analyses based on Neurosynth confirmed that the pSTS is at the intersection of the three neural systems. Resting-state functional connectivity analysis with 1000 subjects confirmed that the pSTS is connected to all other regions in these systems. The findings presented in this review are specifically relevant for psychiatric research especially disorders characterized by social deficits such as autism spectrum disorder. PMID:25660957

Ensembl Genomes: an integrative resource for genome-scale data from non-vertebrate species.

Science.gov (United States)

Kersey, Paul J; Staines, Daniel M; Lawson, Daniel; Kulesha, Eugene; Derwent, Paul; Humphrey, Jay C; Hughes, Daniel S T; Keenan, Stephan; Kerhornou, Arnaud; Koscielny, Gautier; Langridge, Nicholas; McDowall, Mark D; Megy, Karine; Maheswari, Uma; Nuhn, Michael; Paulini, Michael; Pedro, Helder; Toneva, Iliana; Wilson, Derek; Yates, Andrew; Birney, Ewan

2012-01-01

Ensembl Genomes (http://www.ensemblgenomes.org) is an integrative resource for genome-scale data from non-vertebrate species. The project exploits and extends technology (for genome annotation, analysis and dissemination) developed in the context of the (vertebrate-focused) Ensembl project and provides a complementary set of resources for non-vertebrate species through a consistent set of programmatic and interactive interfaces. These provide access to data including reference sequence, gene models, transcriptional data, polymorphisms and comparative analysis. Since its launch in 2009, Ensembl Genomes has undergone rapid expansion, with the goal of providing coverage of all major experimental organisms, and additionally including taxonomic reference points to provide the evolutionary context in which genes can be understood. Against the backdrop of a continuing increase in genome sequencing activities in all parts of the tree of life, we seek to work, wherever possible, with the communities actively generating and using data, and are participants in a growing range of collaborations involved in the annotation and analysis of genomes.

Integrated Genome-Based Studies of Shewanella Ecophysiology

Energy Technology Data Exchange (ETDEWEB)

Zhou, Jizhong [Univ. of Oklahoma, Norman, OK (United States); He, Zhili [Univ. of Oklahoma, Norman, OK (United States)

2014-04-08

As a part of the Shewanella Federation project, we have used integrated genomic, proteomic and computational technologies to study various aspects of energy metabolism of two Shewanella strains from a systems-level perspective.

Integrative Genome Comparison of Primary and Metastatic Melanomas

Science.gov (United States)

Feng, Bin; Nazarian, Rosalynn M.; Bosenberg, Marcus; Wu, Min; Scott, Kenneth L.; Kwong, Lawrence N.; Xiao, Yonghong; Cordon-Cardo, Carlos; Granter, Scott R.; Ramaswamy, Sridhar; Golub, Todd; Duncan, Lyn M.; Wagner, Stephan N.; Brennan, Cameron; Chin, Lynda

2010-01-01

A cardinal feature of malignant melanoma is its metastatic propensity. An incomplete view of the genetic events driving metastatic progression has been a major barrier to rational development of effective therapeutics and prognostic diagnostics for melanoma patients. In this study, we conducted global genomic characterization of primary and metastatic melanomas to examine the genomic landscape associated with metastatic progression. In addition to uncovering three genomic subclasses of metastastic melanomas, we delineated 39 focal and recurrent regions of amplification and deletions, many of which encompassed resident genes that have not been implicated in cancer or metastasis. To identify progression-associated metastasis gene candidates, we applied a statistical approach, Integrative Genome Comparison (IGC), to define 32 genomic regions of interest that were significantly altered in metastatic relative to primary melanomas, encompassing 30 resident genes with statistically significant expression deregulation. Functional assays on a subset of these candidates, including MET, ASPM, AKAP9, IMP3, PRKCA, RPA3, and SCAP2, validated their pro-invasion activities in human melanoma cells. Validity of the IGC approach was further reinforced by tissue microarray analysis of Survivin showing significant increased protein expression in thick versus thin primary cutaneous melanomas, and a progression correlation with lymph node metastases. Together, these functional validation results and correlative analysis of human tissues support the thesis that integrated genomic and pathological analyses of staged melanomas provide a productive entry point for discovery of melanoma metastases genes. PMID:20520718

INE: a rice genome database with an integrated map view.

Science.gov (United States)

Sakata, K; Antonio, B A; Mukai, Y; Nagasaki, H; Sakai, Y; Makino, K; Sasaki, T

2000-01-01

The Rice Genome Research Program (RGP) launched a large-scale rice genome sequencing in 1998 aimed at decoding all genetic information in rice. A new genome database called INE (INtegrated rice genome Explorer) has been developed in order to integrate all the genomic information that has been accumulated so far and to correlate these data with the genome sequence. A web interface based on Java applet provides a rapid viewing capability in the database. The first operational version of the database has been completed which includes a genetic map, a physical map using YAC (Yeast Artificial Chromosome) clones and PAC (P1-derived Artificial Chromosome) contigs. These maps are displayed graphically so that the positional relationships among the mapped markers on each chromosome can be easily resolved. INE incorporates the sequences and annotations of the PAC contig. A site on low quality information ensures that all submitted sequence data comply with the standard for accuracy. As a repository of rice genome sequence, INE will also serve as a common database of all sequence data obtained by collaborating members of the International Rice Genome Sequencing Project (IRGSP). The database can be accessed at http://www. dna.affrc.go.jp:82/giot/INE. html or its mirror site at http://www.staff.or.jp/giot/INE.html

Crossmodal integration enhances neural representation of task-relevant features in audiovisual face perception.

Science.gov (United States)

Li, Yuanqing; Long, Jinyi; Huang, Biao; Yu, Tianyou; Wu, Wei; Liu, Yongjian; Liang, Changhong; Sun, Pei

2015-02-01

Previous studies have shown that audiovisual integration improves identification performance and enhances neural activity in heteromodal brain areas, for example, the posterior superior temporal sulcus/middle temporal gyrus (pSTS/MTG). Furthermore, it has also been demonstrated that attention plays an important role in crossmodal integration. In this study, we considered crossmodal integration in audiovisual facial perception and explored its effect on the neural representation of features. The audiovisual stimuli in the experiment consisted of facial movie clips that could be classified into 2 gender categories (male vs. female) or 2 emotion categories (crying vs. laughing). The visual/auditory-only stimuli were created from these movie clips by removing the auditory/visual contents. The subjects needed to make a judgment about the gender/emotion category for each movie clip in the audiovisual, visual-only, or auditory-only stimulus condition as functional magnetic resonance imaging (fMRI) signals were recorded. The neural representation of the gender/emotion feature was assessed using the decoding accuracy and the brain pattern-related reproducibility indices, obtained by a multivariate pattern analysis method from the fMRI data. In comparison to the visual-only and auditory-only stimulus conditions, we found that audiovisual integration enhanced the neural representation of task-relevant features and that feature-selective attention might play a role of modulation in the audiovisual integration. © The Author 2013. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Integrated evolutionary computation neural network quality controller for automated systems

Energy Technology Data Exchange (ETDEWEB)

Patro, S.; Kolarik, W.J. [Texas Tech Univ., Lubbock, TX (United States). Dept. of Industrial Engineering

1999-06-01

With increasing competition in the global market, more and more stringent quality standards and specifications are being demands at lower costs. Manufacturing applications of computing power are becoming more common. The application of neural networks to identification and control of dynamic processes has been discussed. The limitations of using neural networks for control purposes has been pointed out and a different technique, evolutionary computation, has been discussed. The results of identifying and controlling an unstable, dynamic process using evolutionary computation methods has been presented. A framework for an integrated system, using both neural networks and evolutionary computation, has been proposed to identify the process and then control the product quality, in a dynamic, multivariable system, in real-time.

Securing Digital Images Integrity using Artificial Neural Networks

Science.gov (United States)

Hajji, Tarik; Itahriouan, Zakaria; Ouazzani Jamil, Mohammed

2018-05-01

Digital image signature is a technique used to protect the image integrity. The application of this technique can serve several areas of imaging applied to smart cities. The objective of this work is to propose two methods to protect digital image integrity. We present a description of two approaches using artificial neural networks (ANN) to digitally sign an image. The first one is “Direct Signature without learning” and the second is “Direct Signature with learning”. This paper presents the theory of proposed approaches and an experimental study to test their effectiveness.

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

Science.gov (United States)

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.

An integrative neural model of social perception, action observation, and theory of mind.

Science.gov (United States)

Yang, Daniel Y-J; Rosenblau, Gabriela; Keifer, Cara; Pelphrey, Kevin A

2015-04-01

In the field of social neuroscience, major branches of research have been instrumental in describing independent components of typical and aberrant social information processing, but the field as a whole lacks a comprehensive model that integrates different branches. We review existing research related to the neural basis of three key neural systems underlying social information processing: social perception, action observation, and theory of mind. We propose an integrative model that unites these three processes and highlights the posterior superior temporal sulcus (pSTS), which plays a central role in all three systems. Furthermore, we integrate these neural systems with the dual system account of implicit and explicit social information processing. Large-scale meta-analyses based on Neurosynth confirmed that the pSTS is at the intersection of the three neural systems. Resting-state functional connectivity analysis with 1000 subjects confirmed that the pSTS is connected to all other regions in these systems. The findings presented in this review are specifically relevant for psychiatric research especially disorders characterized by social deficits such as autism spectrum disorder. Copyright © 2015 Elsevier Ltd. All rights reserved.

KAIKObase: An integrated silkworm genome database and data mining tool

Directory of Open Access Journals (Sweden)

Nagaraju Javaregowda

2009-10-01

Full Text Available Abstract Background The silkworm, Bombyx mori, is one of the most economically important insects in many developing countries owing to its large-scale cultivation for silk production. With the development of genomic and biotechnological tools, B. mori has also become an important bioreactor for production of various recombinant proteins of biomedical interest. In 2004, two genome sequencing projects for B. mori were reported independently by Chinese and Japanese teams; however, the datasets were insufficient for building long genomic scaffolds which are essential for unambiguous annotation of the genome. Now, both the datasets have been merged and assembled through a joint collaboration between the two groups. Description Integration of the two data sets of silkworm whole-genome-shotgun sequencing by the Japanese and Chinese groups together with newly obtained fosmid- and BAC-end sequences produced the best continuity (~3.7 Mb in N50 scaffold size among the sequenced insect genomes and provided a high degree of nucleotide coverage (88% of all 28 chromosomes. In addition, a physical map of BAC contigs constructed by fingerprinting BAC clones and a SNP linkage map constructed using BAC-end sequences were available. In parallel, proteomic data from two-dimensional polyacrylamide gel electrophoresis in various tissues and developmental stages were compiled into a silkworm proteome database. Finally, a Bombyx trap database was constructed for documenting insertion positions and expression data of transposon insertion lines. Conclusion For efficient usage of genome information for functional studies, genomic sequences, physical and genetic map information and EST data were compiled into KAIKObase, an integrated silkworm genome database which consists of 4 map viewers, a gene viewer, and sequence, keyword and position search systems to display results and data at the level of nucleotide sequence, gene, scaffold and chromosome. Integration of the

3D silicon neural probe with integrated optical fibers for optogenetic modulation.

Science.gov (United States)

Kim, Eric G R; Tu, Hongen; Luo, Hao; Liu, Bin; Bao, Shaowen; Zhang, Jinsheng; Xu, Yong

2015-07-21

Optogenetics is a powerful modality for neural modulation that can be useful for a wide array of biomedical studies. Penetrating microelectrode arrays provide a means of recording neural signals with high spatial resolution. It is highly desirable to integrate optics with neural probes to allow for functional study of neural tissue by optogenetics. In this paper, we report the development of a novel 3D neural probe coupled simply and robustly to optical fibers using a hollow parylene tube structure. The device shanks are hollow tubes with rigid silicon tips, allowing the insertion and encasement of optical fibers within the shanks. The position of the fiber tip can be precisely controlled relative to the electrodes on the shank by inherent design features. Preliminary in vivo rat studies indicate that these devices are capable of optogenetic modulation simultaneously with 3D neural signal recording.

Integrated analysis of whole genome and transcriptome sequencing reveals diverse transcriptomic aberrations driven by somatic genomic changes in liver cancers.

Directory of Open Access Journals (Sweden)

Yuichi Shiraishi

Full Text Available Recent studies applying high-throughput sequencing technologies have identified several recurrently mutated genes and pathways in multiple cancer genomes. However, transcriptional consequences from these genomic alterations in cancer genome remain unclear. In this study, we performed integrated and comparative analyses of whole genomes and transcriptomes of 22 hepatitis B virus (HBV-related hepatocellular carcinomas (HCCs and their matched controls. Comparison of whole genome sequence (WGS and RNA-Seq revealed much evidence that various types of genomic mutations triggered diverse transcriptional changes. Not only splice-site mutations, but also silent mutations in coding regions, deep intronic mutations and structural changes caused splicing aberrations. HBV integrations generated diverse patterns of virus-human fusion transcripts depending on affected gene, such as TERT, CDK15, FN1 and MLL4. Structural variations could drive over-expression of genes such as WNT ligands, with/without creating gene fusions. Furthermore, by taking account of genomic mutations causing transcriptional aberrations, we could improve the sensitivity of deleterious mutation detection in known cancer driver genes (TP53, AXIN1, ARID2, RPS6KA3, and identified recurrent disruptions in putative cancer driver genes such as HNF4A, CPS1, TSC1 and THRAP3 in HCCs. These findings indicate genomic alterations in cancer genome have diverse transcriptomic effects, and integrated analysis of WGS and RNA-Seq can facilitate the interpretation of a large number of genomic alterations detected in cancer genome.

Soft computing integrating evolutionary, neural, and fuzzy systems

CERN Document Server

Tettamanzi, Andrea

2001-01-01

Soft computing encompasses various computational methodologies, which, unlike conventional algorithms, are tolerant of imprecision, uncertainty, and partial truth. Soft computing technologies offer adaptability as a characteristic feature and thus permit the tracking of a problem through a changing environment. Besides some recent developments in areas like rough sets and probabilistic networks, fuzzy logic, evolutionary algorithms, and artificial neural networks are core ingredients of soft computing, which are all bio-inspired and can easily be combined synergetically. This book presents a well-balanced integration of fuzzy logic, evolutionary computing, and neural information processing. The three constituents are introduced to the reader systematically and brought together in differentiated combinations step by step. The text was developed from courses given by the authors and offers numerous illustrations as

PGSB/MIPS PlantsDB Database Framework for the Integration and Analysis of Plant Genome Data.

Science.gov (United States)

Spannagl, Manuel; Nussbaumer, Thomas; Bader, Kai; Gundlach, Heidrun; Mayer, Klaus F X

2017-01-01

Plant Genome and Systems Biology (PGSB), formerly Munich Institute for Protein Sequences (MIPS) PlantsDB, is a database framework for the integration and analysis of plant genome data, developed and maintained for more than a decade now. Major components of that framework are genome databases and analysis resources focusing on individual (reference) genomes providing flexible and intuitive access to data. Another main focus is the integration of genomes from both model and crop plants to form a scaffold for comparative genomics, assisted by specialized tools such as the CrowsNest viewer to explore conserved gene order (synteny). Data exchange and integrated search functionality with/over many plant genome databases is provided within the transPLANT project.

Toward integration of genomic selection with crop modelling: the development of an integrated approach to predicting rice heading dates.

Science.gov (United States)

Onogi, Akio; Watanabe, Maya; Mochizuki, Toshihiro; Hayashi, Takeshi; Nakagawa, Hiroshi; Hasegawa, Toshihiro; Iwata, Hiroyoshi

2016-04-01

It is suggested that accuracy in predicting plant phenotypes can be improved by integrating genomic prediction with crop modelling in a single hierarchical model. Accurate prediction of phenotypes is important for plant breeding and management. Although genomic prediction/selection aims to predict phenotypes on the basis of whole-genome marker information, it is often difficult to predict phenotypes of complex traits in diverse environments, because plant phenotypes are often influenced by genotype-environment interaction. A possible remedy is to integrate genomic prediction with crop/ecophysiological modelling, which enables us to predict plant phenotypes using environmental and management information. To this end, in the present study, we developed a novel method for integrating genomic prediction with phenological modelling of Asian rice (Oryza sativa, L.), allowing the heading date of untested genotypes in untested environments to be predicted. The method simultaneously infers the phenological model parameters and whole-genome marker effects on the parameters in a Bayesian framework. By cultivating backcross inbred lines of Koshihikari × Kasalath in nine environments, we evaluated the potential of the proposed method in comparison with conventional genomic prediction, phenological modelling, and two-step methods that applied genomic prediction to phenological model parameters inferred from Nelder-Mead or Markov chain Monte Carlo algorithms. In predicting heading dates of untested lines in untested environments, the proposed and two-step methods tended to provide more accurate predictions than the conventional genomic prediction methods, particularly in environments where phenotypes from environments similar to the target environment were unavailable for training genomic prediction. The proposed method showed greater accuracy in prediction than the two-step methods in all cross-validation schemes tested, suggesting the potential of the integrated approach in

GIGGLE: a search engine for large-scale integrated genome analysis.

Science.gov (United States)

Layer, Ryan M; Pedersen, Brent S; DiSera, Tonya; Marth, Gabor T; Gertz, Jason; Quinlan, Aaron R

2018-02-01

GIGGLE is a genomics search engine that identifies and ranks the significance of genomic loci shared between query features and thousands of genome interval files. GIGGLE (https://github.com/ryanlayer/giggle) scales to billions of intervals and is over three orders of magnitude faster than existing methods. Its speed extends the accessibility and utility of resources such as ENCODE, Roadmap Epigenomics, and GTEx by facilitating data integration and hypothesis generation.

Ultra low-power integrated circuit design for wireless neural interfaces

CERN Document Server

Holleman, Jeremy; Otis, Brian

2014-01-01

Presenting results from real prototype systems, this volume provides an overview of ultra low-power integrated circuits and systems for neural signal processing and wireless communication. Topics include analog, radio, and signal processing theory and design for ultra low-power circuits.

Integrating genomic selection into dairy cattle breeding programmes: a review.

Science.gov (United States)

Bouquet, A; Juga, J

2013-05-01

Extensive genetic progress has been achieved in dairy cattle populations on many traits of economic importance because of efficient breeding programmes. Success of these programmes has relied on progeny testing of the best young males to accurately assess their genetic merit and hence their potential for breeding. Over the last few years, the integration of dense genomic information into statistical tools used to make selection decisions, commonly referred to as genomic selection, has enabled gains in predicting accuracy of breeding values for young animals without own performance. The possibility to select animals at an early stage allows defining new breeding strategies aimed at boosting genetic progress while reducing costs. The first objective of this article was to review methods used to model and optimize breeding schemes integrating genomic selection and to discuss their relative advantages and limitations. The second objective was to summarize the main results and perspectives on the use of genomic selection in practical breeding schemes, on the basis of the example of dairy cattle populations. Two main designs of breeding programmes integrating genomic selection were studied in dairy cattle. Genomic selection can be used either for pre-selecting males to be progeny tested or for selecting males to be used as active sires in the population. The first option produces moderate genetic gains without changing the structure of breeding programmes. The second option leads to large genetic gains, up to double those of conventional schemes because of a major reduction in the mean generation interval, but it requires greater changes in breeding programme structure. The literature suggests that genomic selection becomes more attractive when it is coupled with embryo transfer technologies to further increase selection intensity on the dam-to-sire pathway. The use of genomic information also offers new opportunities to improve preservation of genetic variation. However

Integrated Genome-Based Studies of Shewanella Ecophysiology

Energy Technology Data Exchange (ETDEWEB)

Andrei L. Osterman, Ph.D.

2012-12-17

Integration of bioinformatics and experimental techniques was applied to mapping and characterization of the key components (pathways, enzymes, transporters, regulators) of the core metabolic machinery in Shewanella oneidensis and related species with main focus was on metabolic and regulatory pathways involved in utilization of various carbon and energy sources. Among the main accomplishments reflected in ten joint publications with other participants of Shewanella Federation are: (i) A systems-level reconstruction of carbohydrate utilization pathways in the genus of Shewanella (19 species). This analysis yielded reconstruction of 18 sugar utilization pathways including 10 novel pathway variants and prediction of > 60 novel protein families of enzymes, transporters and regulators involved in these pathways. Selected functional predictions were verified by focused biochemical and genetic experiments. Observed growth phenotypes were consistent with bioinformatic predictions providing strong validation of the technology and (ii) Global genomic reconstruction of transcriptional regulons in 16 Shewanella genomes. The inferred regulatory network includes 82 transcription factors, 8 riboswitches and 6 translational attenuators. Of those, 45 regulons were inferred directly from the genome context analysis, whereas others were propagated from previously characterized regulons in other species. Selected regulatory predictions were experimentally tested. Integration of this analysis with microarray data revealed overall consistency and provided additional layer of interactions between regulons. All the results were captured in the new database RegPrecise, which is a joint development with the LBNL team. A more detailed analysis of the individual subsystems, pathways and regulons in Shewanella spp included bioinfiormatics-based prediction and experimental characterization of: (i) N-Acetylglucosamine catabolic pathway; (ii)Lactate utilization machinery; (iii) Novel Nrt

Simulation of sensory integration dysfunction in autism with dynamic neural fields model

NARCIS (Netherlands)

Chonnaparamutt, W.; Barakova, E.I.; Rutkowski, L.; Taseusiewicz, R.

2008-01-01

This paper applies dynamic neural fields model [1,23,7] to multimodal interaction of sensory cues obtained from a mobile robot, and shows the impact of different temporal aspects of the integration to the precision of movements. We speculate that temporally uncoordinated sensory integration might be

INDIGO - INtegrated data warehouse of microbial genomes with examples from the red sea extremophiles.

KAUST Repository

Alam, Intikhab

2013-12-06

The next generation sequencing technologies substantially increased the throughput of microbial genome sequencing. To functionally annotate newly sequenced microbial genomes, a variety of experimental and computational methods are used. Integration of information from different sources is a powerful approach to enhance such annotation. Functional analysis of microbial genomes, necessary for downstream experiments, crucially depends on this annotation but it is hampered by the current lack of suitable information integration and exploration systems for microbial genomes.

INDIGO - INtegrated data warehouse of microbial genomes with examples from the red sea extremophiles.

KAUST Repository

Alam, Intikhab; Antunes, André ; Kamau, Allan; Ba Alawi, Wail; Kalkatawi, Manal M.; Stingl, Ulrich; Bajic, Vladimir B.

2013-01-01

The next generation sequencing technologies substantially increased the throughput of microbial genome sequencing. To functionally annotate newly sequenced microbial genomes, a variety of experimental and computational methods are used. Integration of information from different sources is a powerful approach to enhance such annotation. Functional analysis of microbial genomes, necessary for downstream experiments, crucially depends on this annotation but it is hampered by the current lack of suitable information integration and exploration systems for microbial genomes.

GIGGLE: a search engine for large-scale integrated genome analysis

Science.gov (United States)

Layer, Ryan M; Pedersen, Brent S; DiSera, Tonya; Marth, Gabor T; Gertz, Jason; Quinlan, Aaron R

2018-01-01

GIGGLE is a genomics search engine that identifies and ranks the significance of genomic loci shared between query features and thousands of genome interval files. GIGGLE (https://github.com/ryanlayer/giggle) scales to billions of intervals and is over three orders of magnitude faster than existing methods. Its speed extends the accessibility and utility of resources such as ENCODE, Roadmap Epigenomics, and GTEx by facilitating data integration and hypothesis generation. PMID:29309061

Structured Matrix Completion with Applications to Genomic Data Integration.

Science.gov (United States)

Cai, Tianxi; Cai, T Tony; Zhang, Anru

2016-01-01

Matrix completion has attracted significant recent attention in many fields including statistics, applied mathematics and electrical engineering. Current literature on matrix completion focuses primarily on independent sampling models under which the individual observed entries are sampled independently. Motivated by applications in genomic data integration, we propose a new framework of structured matrix completion (SMC) to treat structured missingness by design. Specifically, our proposed method aims at efficient matrix recovery when a subset of the rows and columns of an approximately low-rank matrix are observed. We provide theoretical justification for the proposed SMC method and derive lower bound for the estimation errors, which together establish the optimal rate of recovery over certain classes of approximately low-rank matrices. Simulation studies show that the method performs well in finite sample under a variety of configurations. The method is applied to integrate several ovarian cancer genomic studies with different extent of genomic measurements, which enables us to construct more accurate prediction rules for ovarian cancer survival.

Integrated proteomic and genomic analysis of colorectal cancer

Science.gov (United States)

Investigators who analyzed 95 human colorectal tumor samples have determined how gene alterations identified in previous analyses of the same samples are expressed at the protein level. The integration of proteomic and genomic data, or proteogenomics, pro

The modulation of neural gain facilitates a transition between functional segregation and integration in the brain.

Science.gov (United States)

Shine, James M; Aburn, Matthew J; Breakspear, Michael; Poldrack, Russell A

2018-01-29

Cognitive function relies on a dynamic, context-sensitive balance between functional integration and segregation in the brain. Previous work has proposed that this balance is mediated by global fluctuations in neural gain by projections from ascending neuromodulatory nuclei. To test this hypothesis in silico, we studied the effects of neural gain on network dynamics in a model of large-scale neuronal dynamics. We found that increases in neural gain directed the network through an abrupt dynamical transition, leading to an integrated network topology that was maximal in frontoparietal 'rich club' regions. This gain-mediated transition was also associated with increased topological complexity, as well as increased variability in time-resolved topological structure, further highlighting the potential computational benefits of the gain-mediated network transition. These results support the hypothesis that neural gain modulation has the computational capacity to mediate the balance between integration and segregation in the brain. © 2018, Shine et al.

Integration of expression data in genome-scale metabolic network reconstructions

Directory of Open Access Journals (Sweden)

Anna S. Blazier

2012-08-01

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

Involvement of Atm and Trp53 in neural cell loss due to Terf2 inactivation during mouse brain development.

Science.gov (United States)

Kim, Jusik; Choi, Inseo; Lee, Youngsoo

2017-11-01

Maintenance of genomic integrity is one of the critical features for proper neurodevelopment and inhibition of neurological diseases. The signals from both ATM and ATR to TP53 are well-known mechanisms to remove neural cells with DNA damage during neurogenesis. Here we examined the involvement of Atm and Atr in genomic instability due to Terf2 inactivation during mouse brain development. Selective inactivation of Terf2 in neural progenitors induced apoptosis, resulting in a complete loss of the brain structure. This neural loss was rescued partially in both Atm and Trp53 deficiency, but not in an Atr-deficient background in the mouse. Atm inactivation resulted in incomplete brain structures, whereas p53 deficiency led to the formation of multinucleated giant neural cells and the disruption of the brain structure. These giant neural cells disappeared in Lig4 deficiency. These data demonstrate ATM and TP53 are important for the maintenance of telomere homeostasis and the surveillance of telomere dysfunction during neurogenesis.

A model for integrating elementary neural functions into delayed-response behavior.

Directory of Open Access Journals (Sweden)

Thomas Gisiger

2006-04-01

Full Text Available It is well established that various cortical regions can implement a wide array of neural processes, yet the mechanisms which integrate these processes into behavior-producing, brain-scale activity remain elusive. We propose that an important role in this respect might be played by executive structures controlling the traffic of information between the cortical regions involved. To illustrate this hypothesis, we present a neural network model comprising a set of interconnected structures harboring stimulus-related activity (visual representation, working memory, and planning, and a group of executive units with task-related activity patterns that manage the information flowing between them. The resulting dynamics allows the network to perform the dual task of either retaining an image during a delay (delayed-matching to sample task, or recalling from this image another one that has been associated with it during training (delayed-pair association task. The model reproduces behavioral and electrophysiological data gathered on the inferior temporal and prefrontal cortices of primates performing these same tasks. It also makes predictions on how neural activity coding for the recall of the image associated with the sample emerges and becomes prospective during the training phase. The network dynamics proves to be very stable against perturbations, and it exhibits signs of scale-invariant organization and cooperativity. The present network represents a possible neural implementation for active, top-down, prospective memory retrieval in primates. The model suggests that brain activity leading to performance of cognitive tasks might be organized in modular fashion, simple neural functions becoming integrated into more complex behavior by executive structures harbored in prefrontal cortex and/or basal ganglia.

A model for integrating elementary neural functions into delayed-response behavior.

Science.gov (United States)

Gisiger, Thomas; Kerszberg, Michel

2006-04-01

It is well established that various cortical regions can implement a wide array of neural processes, yet the mechanisms which integrate these processes into behavior-producing, brain-scale activity remain elusive. We propose that an important role in this respect might be played by executive structures controlling the traffic of information between the cortical regions involved. To illustrate this hypothesis, we present a neural network model comprising a set of interconnected structures harboring stimulus-related activity (visual representation, working memory, and planning), and a group of executive units with task-related activity patterns that manage the information flowing between them. The resulting dynamics allows the network to perform the dual task of either retaining an image during a delay (delayed-matching to sample task), or recalling from this image another one that has been associated with it during training (delayed-pair association task). The model reproduces behavioral and electrophysiological data gathered on the inferior temporal and prefrontal cortices of primates performing these same tasks. It also makes predictions on how neural activity coding for the recall of the image associated with the sample emerges and becomes prospective during the training phase. The network dynamics proves to be very stable against perturbations, and it exhibits signs of scale-invariant organization and cooperativity. The present network represents a possible neural implementation for active, top-down, prospective memory retrieval in primates. The model suggests that brain activity leading to performance of cognitive tasks might be organized in modular fashion, simple neural functions becoming integrated into more complex behavior by executive structures harbored in prefrontal cortex and/or basal ganglia.

High throughput platforms for structural genomics of integral membrane proteins.

Science.gov (United States)

Mancia, Filippo; Love, James

2011-08-01

Structural genomics approaches on integral membrane proteins have been postulated for over a decade, yet specific efforts are lagging years behind their soluble counterparts. Indeed, high throughput methodologies for production and characterization of prokaryotic integral membrane proteins are only now emerging, while large-scale efforts for eukaryotic ones are still in their infancy. Presented here is a review of recent literature on actively ongoing structural genomics of membrane protein initiatives, with a focus on those aimed at implementing interesting techniques aimed at increasing our rate of success for this class of macromolecules. Copyright © 2011 Elsevier Ltd. All rights reserved.

Improving Microbial Genome Annotations in an Integrated Database Context

Science.gov (United States)

Chen, I-Min A.; Markowitz, Victor M.; Chu, Ken; Anderson, Iain; Mavromatis, Konstantinos; Kyrpides, Nikos C.; Ivanova, Natalia N.

2013-01-01

Effective comparative analysis of microbial genomes requires a consistent and complete view of biological data. Consistency regards the biological coherence of annotations, while completeness regards the extent and coverage of functional characterization for genomes. We have developed tools that allow scientists to assess and improve the consistency and completeness of microbial genome annotations in the context of the Integrated Microbial Genomes (IMG) family of systems. All publicly available microbial genomes are characterized in IMG using different functional annotation and pathway resources, thus providing a comprehensive framework for identifying and resolving annotation discrepancies. A rule based system for predicting phenotypes in IMG provides a powerful mechanism for validating functional annotations, whereby the phenotypic traits of an organism are inferred based on the presence of certain metabolic reactions and pathways and compared to experimentally observed phenotypes. The IMG family of systems are available at http://img.jgi.doe.gov/. PMID:23424620

Improving microbial genome annotations in an integrated database context.

Directory of Open Access Journals (Sweden)

I-Min A Chen

Full Text Available Effective comparative analysis of microbial genomes requires a consistent and complete view of biological data. Consistency regards the biological coherence of annotations, while completeness regards the extent and coverage of functional characterization for genomes. We have developed tools that allow scientists to assess and improve the consistency and completeness of microbial genome annotations in the context of the Integrated Microbial Genomes (IMG family of systems. All publicly available microbial genomes are characterized in IMG using different functional annotation and pathway resources, thus providing a comprehensive framework for identifying and resolving annotation discrepancies. A rule based system for predicting phenotypes in IMG provides a powerful mechanism for validating functional annotations, whereby the phenotypic traits of an organism are inferred based on the presence of certain metabolic reactions and pathways and compared to experimentally observed phenotypes. The IMG family of systems are available at http://img.jgi.doe.gov/.

INDIGO - INtegrated data warehouse of microbial genomes with examples from the red sea extremophiles.

Science.gov (United States)

Alam, Intikhab; Antunes, André; Kamau, Allan Anthony; Ba Alawi, Wail; Kalkatawi, Manal; Stingl, Ulrich; Bajic, Vladimir B

2013-01-01

The next generation sequencing technologies substantially increased the throughput of microbial genome sequencing. To functionally annotate newly sequenced microbial genomes, a variety of experimental and computational methods are used. Integration of information from different sources is a powerful approach to enhance such annotation. Functional analysis of microbial genomes, necessary for downstream experiments, crucially depends on this annotation but it is hampered by the current lack of suitable information integration and exploration systems for microbial genomes. We developed a data warehouse system (INDIGO) that enables the integration of annotations for exploration and analysis of newly sequenced microbial genomes. INDIGO offers an opportunity to construct complex queries and combine annotations from multiple sources starting from genomic sequence to protein domain, gene ontology and pathway levels. This data warehouse is aimed at being populated with information from genomes of pure cultures and uncultured single cells of Red Sea bacteria and Archaea. Currently, INDIGO contains information from Salinisphaera shabanensis, Haloplasma contractile, and Halorhabdus tiamatea - extremophiles isolated from deep-sea anoxic brine lakes of the Red Sea. We provide examples of utilizing the system to gain new insights into specific aspects on the unique lifestyle and adaptations of these organisms to extreme environments. We developed a data warehouse system, INDIGO, which enables comprehensive integration of information from various resources to be used for annotation, exploration and analysis of microbial genomes. It will be regularly updated and extended with new genomes. It is aimed to serve as a resource dedicated to the Red Sea microbes. In addition, through INDIGO, we provide our Automatic Annotation of Microbial Genomes (AAMG) pipeline. The INDIGO web server is freely available at http://www.cbrc.kaust.edu.sa/indigo.

Evolution of endogenous non-retroviral genes integrated into plant genomes

Directory of Open Access Journals (Sweden)

Hyosub Chu

2014-08-01

Full Text Available Numerous comparative genome analyses have revealed the wide extent of horizontal gene transfer (HGT in living organisms, which contributes to their evolution and genetic diversity. Viruses play important roles in HGT. Endogenous viral elements (EVEs are defined as viral DNA sequences present within the genomes of non-viral organisms. In eukaryotic cells, the majority of EVEs are derived from RNA viruses using reverse transcription. In contrast, endogenous non-retroviral elements (ENREs are poorly studied. However, the increasing availability of genomic data and the rapid development of bioinformatics tools have enabled the identification of several ENREs in various eukaryotic organisms. To date, a small number of ENREs integrated into plant genomes have been identified. Of the known non-retroviruses, most identified ENREs are derived from double-strand (ds RNA viruses, followed by single-strand (ss DNA and ssRNA viruses. At least eight virus families have been identified. Of these, viruses in the family Partitiviridae are dominant, followed by viruses of the families Chrysoviridae and Geminiviridae. The identified ENREs have been primarily identified in eudicots, followed by monocots. In this review, we briefly discuss the current view on non-retroviral sequences integrated into plant genomes that are associated with plant-virus evolution and their possible roles in antiviral resistance.

The octopus genome and the evolution of cephalopod neural and morphological novelties.

Science.gov (United States)

Albertin, Caroline B; Simakov, Oleg; Mitros, Therese; Wang, Z Yan; Pungor, Judit R; Edsinger-Gonzales, Eric; Brenner, Sydney; Ragsdale, Clifton W; Rokhsar, Daniel S

2015-08-13

Coleoid cephalopods (octopus, squid and cuttlefish) are active, resourceful predators with a rich behavioural repertoire. They have the largest nervous systems among the invertebrates and present other striking morphological innovations including camera-like eyes, prehensile arms, a highly derived early embryogenesis and a remarkably sophisticated adaptive colouration system. To investigate the molecular bases of cephalopod brain and body innovations, we sequenced the genome and multiple transcriptomes of the California two-spot octopus, Octopus bimaculoides. We found no evidence for hypothesized whole-genome duplications in the octopus lineage. The core developmental and neuronal gene repertoire of the octopus is broadly similar to that found across invertebrate bilaterians, except for massive expansions in two gene families previously thought to be uniquely enlarged in vertebrates: the protocadherins, which regulate neuronal development, and the C2H2 superfamily of zinc-finger transcription factors. Extensive messenger RNA editing generates transcript and protein diversity in genes involved in neural excitability, as previously described, as well as in genes participating in a broad range of other cellular functions. We identified hundreds of cephalopod-specific genes, many of which showed elevated expression levels in such specialized structures as the skin, the suckers and the nervous system. Finally, we found evidence for large-scale genomic rearrangements that are closely associated with transposable element expansions. Our analysis suggests that substantial expansion of a handful of gene families, along with extensive remodelling of genome linkage and repetitive content, played a critical role in the evolution of cephalopod morphological innovations, including their large and complex nervous systems.

Genome-Wide Analysis of Transposon and Retroviral Insertions Reveals Preferential Integrations in Regions of DNA Flexibility.

Science.gov (United States)

Vrljicak, Pavle; Tao, Shijie; Varshney, Gaurav K; Quach, Helen Ngoc Bao; Joshi, Adita; LaFave, Matthew C; Burgess, Shawn M; Sampath, Karuna

2016-04-07

DNA transposons and retroviruses are important transgenic tools for genome engineering. An important consideration affecting the choice of transgenic vector is their insertion site preferences. Previous large-scale analyses of Ds transposon integration sites in plants were done on the basis of reporter gene expression or germ-line transmission, making it difficult to discern vertebrate integration preferences. Here, we compare over 1300 Ds transposon integration sites in zebrafish with Tol2 transposon and retroviral integration sites. Genome-wide analysis shows that Ds integration sites in the presence or absence of marker selection are remarkably similar and distributed throughout the genome. No strict motif was found, but a preference for structural features in the target DNA associated with DNA flexibility (Twist, Tilt, Rise, Roll, Shift, and Slide) was observed. Remarkably, this feature is also found in transposon and retroviral integrations in maize and mouse cells. Our findings show that structural features influence the integration of heterologous DNA in genomes, and have implications for targeted genome engineering. Copyright © 2016 Vrljicak et al.

Genome-wide survey of recurrent HBV integration in hepatocellular carcinoma

DEFF Research Database (Denmark)

Sung, Wing-Kin; Zheng, Hancheng; Li, Shuyu

2012-01-01

To survey hepatitis B virus (HBV) integration in liver cancer genomes, we conducted massively parallel sequencing of 81 HBV-positive and 7 HBV-negative hepatocellular carcinomas (HCCs) and adjacent normal tissues. We found that HBV integration is observed more frequently in the tumors (86.4%) than...

DO DYNAMIC NEURAL NETWORKS STAND A BETTER CHANCE IN FRACTIONALLY INTEGRATED PROCESS FORECASTING?

Directory of Open Access Journals (Sweden)

Majid Delavari

2013-04-01

Full Text Available The main purpose of the present study was to investigate the capabilities of two generations of models such as those based on dynamic neural network (e.g., Nonlinear Neural network Auto Regressive or NNAR model and a regressive (Auto Regressive Fractionally Integrated Moving Average model which is based on Fractional Integration Approach in forecasting daily data related to the return index of Tehran Stock Exchange (TSE. In order to compare these models under similar conditions, Mean Square Error (MSE and also Root Mean Square Error (RMSE were selected as criteria for the models’ simulated out-of-sample forecasting performance. Besides, fractal markets hypothesis was examined and according to the findings, fractal structure was confirmed to exist in the time series under investigation. Another finding of the study was that dynamic artificial neural network model had the best performance in out-of-sample forecasting based on the criteria introduced for calculating forecasting error in comparison with the ARFIMA model.

INDIGO - INtegrated data warehouse of microbial genomes with examples from the red sea extremophiles.

Directory of Open Access Journals (Sweden)

Intikhab Alam

Full Text Available The next generation sequencing technologies substantially increased the throughput of microbial genome sequencing. To functionally annotate newly sequenced microbial genomes, a variety of experimental and computational methods are used. Integration of information from different sources is a powerful approach to enhance such annotation. Functional analysis of microbial genomes, necessary for downstream experiments, crucially depends on this annotation but it is hampered by the current lack of suitable information integration and exploration systems for microbial genomes.We developed a data warehouse system (INDIGO that enables the integration of annotations for exploration and analysis of newly sequenced microbial genomes. INDIGO offers an opportunity to construct complex queries and combine annotations from multiple sources starting from genomic sequence to protein domain, gene ontology and pathway levels. This data warehouse is aimed at being populated with information from genomes of pure cultures and uncultured single cells of Red Sea bacteria and Archaea. Currently, INDIGO contains information from Salinisphaera shabanensis, Haloplasma contractile, and Halorhabdus tiamatea - extremophiles isolated from deep-sea anoxic brine lakes of the Red Sea. We provide examples of utilizing the system to gain new insights into specific aspects on the unique lifestyle and adaptations of these organisms to extreme environments.We developed a data warehouse system, INDIGO, which enables comprehensive integration of information from various resources to be used for annotation, exploration and analysis of microbial genomes. It will be regularly updated and extended with new genomes. It is aimed to serve as a resource dedicated to the Red Sea microbes. In addition, through INDIGO, we provide our Automatic Annotation of Microbial Genomes (AAMG pipeline. The INDIGO web server is freely available at http://www.cbrc.kaust.edu.sa/indigo.

Wireless neural recording with single low-power integrated circuit.

Science.gov (United States)

Harrison, Reid R; Kier, Ryan J; Chestek, Cynthia A; Gilja, Vikash; Nuyujukian, Paul; Ryu, Stephen; Greger, Bradley; Solzbacher, Florian; Shenoy, Krishna V

2009-08-01

We present benchtop and in vivo experimental results from an integrated circuit designed for wireless implantable neural recording applications. The chip, which was fabricated in a commercially available 0.6- mum 2P3M BiCMOS process, contains 100 amplifiers, a 10-bit analog-to-digital converter (ADC), 100 threshold-based spike detectors, and a 902-928 MHz frequency-shift-keying (FSK) transmitter. Neural signals from a selected amplifier are sampled by the ADC at 15.7 kSps and telemetered over the FSK wireless data link. Power, clock, and command signals are sent to the chip wirelessly over a 2.765-MHz inductive (coil-to-coil) link. The chip is capable of operating with only two off-chip components: a power/command receiving coil and a 100-nF capacitor.

Integrated Genome-Based Studies of Shewanella Echophysiology

Energy Technology Data Exchange (ETDEWEB)

Margrethe H. Serres

2012-06-29

Shewanella oneidensis MR-1 is a motile, facultative {gamma}-Proteobacterium with remarkable respiratory versatility; it can utilize a range of organic and inorganic compounds as terminal electronacceptors for anaerobic metabolism. The ability to effectively reduce nitrate, S0, polyvalent metals andradionuclides has established MR-1 as an important model dissimilatory metal-reducing microorganism for genome-based investigations of biogeochemical transformation of metals and radionuclides that are of concern to the U.S. Department of Energy (DOE) sites nationwide. Metal-reducing bacteria such as Shewanella also have a highly developed capacity for extracellular transfer of respiratory electrons to solid phase Fe and Mn oxides as well as directly to anode surfaces in microbial fuel cells. More broadly, Shewanellae are recognized free-living microorganisms and members of microbial communities involved in the decomposition of organic matter and the cycling of elements in aquatic and sedimentary systems. To function and compete in environments that are subject to spatial and temporal environmental change, Shewanella must be able to sense and respond to such changes and therefore require relatively robust sensing and regulation systems. The overall goal of this project is to apply the tools of genomics, leveraging the availability of genome sequence for 18 additional strains of Shewanella, to better understand the ecophysiology and speciation of respiratory-versatile members of this important genus. To understand these systems we propose to use genome-based approaches to investigate Shewanella as a system of integrated networks; first describing key cellular subsystems - those involved in signal transduction, regulation, and metabolism - then building towards understanding the function of whole cells and, eventually, cells within populations. As a general approach, this project will employ complimentary "top-down" - bioinformatics-based genome functional predictions, high

Site-Specific Integration of Exogenous Genes Using Genome Editing Technologies in Zebrafish

Directory of Open Access Journals (Sweden)

Atsuo Kawahara

2016-05-01

Full Text Available The zebrafish (Danio rerio is an ideal vertebrate model to investigate the developmental molecular mechanism of organogenesis and regeneration. Recent innovation in genome editing technologies, such as zinc finger nucleases (ZFNs, transcription activator-like effector nucleases (TALENs and the clustered regularly interspaced short palindromic repeats (CRISPR/CRISPR associated protein 9 (Cas9 system, have allowed researchers to generate diverse genomic modifications in whole animals and in cultured cells. The CRISPR/Cas9 and TALEN techniques frequently induce DNA double-strand breaks (DSBs at the targeted gene, resulting in frameshift-mediated gene disruption. As a useful application of genome editing technology, several groups have recently reported efficient site-specific integration of exogenous genes into targeted genomic loci. In this review, we provide an overview of TALEN- and CRISPR/Cas9-mediated site-specific integration of exogenous genes in zebrafish.

Genomic integrity and the ageing brain.

Science.gov (United States)

Chow, Hei-man; Herrup, Karl

2015-11-01

DNA damage is correlated with and may drive the ageing process. Neurons in the brain are postmitotic and are excluded from many forms of DNA repair; therefore, neurons are vulnerable to various neurodegenerative diseases. The challenges facing the field are to understand how and when neuronal DNA damage accumulates, how this loss of genomic integrity might serve as a 'time keeper' of nerve cell ageing and why this process manifests itself as different diseases in different individuals.

Brassica database (BRAD) version 2.0: integrating and mining Brassicaceae species genomic resources.

Science.gov (United States)

Wang, Xiaobo; Wu, Jian; Liang, Jianli; Cheng, Feng; Wang, Xiaowu

2015-01-01

The Brassica database (BRAD) was built initially to assist users apply Brassica rapa and Arabidopsis thaliana genomic data efficiently to their research. However, many Brassicaceae genomes have been sequenced and released after its construction. These genomes are rich resources for comparative genomics, gene annotation and functional evolutionary studies of Brassica crops. Therefore, we have updated BRAD to version 2.0 (V2.0). In BRAD V2.0, 11 more Brassicaceae genomes have been integrated into the database, namely those of Arabidopsis lyrata, Aethionema arabicum, Brassica oleracea, Brassica napus, Camelina sativa, Capsella rubella, Leavenworthia alabamica, Sisymbrium irio and three extremophiles Schrenkiella parvula, Thellungiella halophila and Thellungiella salsuginea. BRAD V2.0 provides plots of syntenic genomic fragments between pairs of Brassicaceae species, from the level of chromosomes to genomic blocks. The Generic Synteny Browser (GBrowse_syn), a module of the Genome Browser (GBrowse), is used to show syntenic relationships between multiple genomes. Search functions for retrieving syntenic and non-syntenic orthologs, as well as their annotation and sequences are also provided. Furthermore, genome and annotation information have been imported into GBrowse so that all functional elements can be visualized in one frame. We plan to continually update BRAD by integrating more Brassicaceae genomes into the database. Database URL: http://brassicadb.org/brad/. © The Author(s) 2015. Published by Oxford University Press.

Improved bacteriophage genome data is necessary for integrating viral and bacterial ecology.

Science.gov (United States)

Bibby, Kyle

2014-02-01

The recent rise in "omics"-enabled approaches has lead to improved understanding in many areas of microbial ecology. However, despite the importance that viruses play in a broad microbial ecology context, viral ecology remains largely not integrated into high-throughput microbial ecology studies. A fundamental hindrance to the integration of viral ecology into omics-enabled microbial ecology studies is the lack of suitable reference bacteriophage genomes in reference databases-currently, only 0.001% of bacteriophage diversity is represented in genome sequence databases. This commentary serves to highlight this issue and to promote bacteriophage genome sequencing as a valuable scientific undertaking to both better understand bacteriophage diversity and move towards a more holistic view of microbial ecology.

Impulsive synchronization of Markovian jumping randomly coupled neural networks with partly unknown transition probabilities via multiple integral approach.

Science.gov (United States)

Chandrasekar, A; Rakkiyappan, R; Cao, Jinde

2015-10-01

This paper studies the impulsive synchronization of Markovian jumping randomly coupled neural networks with partly unknown transition probabilities via multiple integral approach. The array of neural networks are coupled in a random fashion which is governed by Bernoulli random variable. The aim of this paper is to obtain the synchronization criteria, which is suitable for both exactly known and partly unknown transition probabilities such that the coupled neural network is synchronized with mixed time-delay. The considered impulsive effects can be synchronized at partly unknown transition probabilities. Besides, a multiple integral approach is also proposed to strengthen the Markovian jumping randomly coupled neural networks with partly unknown transition probabilities. By making use of Kronecker product and some useful integral inequalities, a novel Lyapunov-Krasovskii functional was designed for handling the coupled neural network with mixed delay and then impulsive synchronization criteria are solvable in a set of linear matrix inequalities. Finally, numerical examples are presented to illustrate the effectiveness and advantages of the theoretical results. Copyright © 2015 Elsevier Ltd. All rights reserved.

Simulation electromagnetic scattering on bodies through integral equation and neural networks methods

Science.gov (United States)

Lvovich, I. Ya; Preobrazhenskiy, A. P.; Choporov, O. N.

2018-05-01

The paper deals with the issue of electromagnetic scattering on a perfectly conducting diffractive body of a complex shape. Performance calculation of the body scattering is carried out through the integral equation method. Fredholm equation of the second time was used for calculating electric current density. While solving the integral equation through the moments method, the authors have properly described the core singularity. The authors determined piecewise constant functions as basic functions. The chosen equation was solved through the moments method. Within the Kirchhoff integral approach it is possible to define the scattered electromagnetic field, in some way related to obtained electrical currents. The observation angles sector belongs to the area of the front hemisphere of the diffractive body. To improve characteristics of the diffractive body, the authors used a neural network. All the neurons contained a logsigmoid activation function and weighted sums as discriminant functions. The paper presents the matrix of weighting factors of the connectionist model, as well as the results of the optimized dimensions of the diffractive body. The paper also presents some basic steps in calculation technique of the diffractive bodies, based on the combination of integral equation and neural networks methods.

Modeling the integration of bacterial rRNA fragments into the human cancer genome.

Science.gov (United States)

Sieber, Karsten B; Gajer, Pawel; Dunning Hotopp, Julie C

2016-03-21

Cancer is a disease driven by the accumulation of genomic alterations, including the integration of exogenous DNA into the human somatic genome. We previously identified in silico evidence of DNA fragments from a Pseudomonas-like bacteria integrating into the 5'-UTR of four proto-oncogenes in stomach cancer sequencing data. The functional and biological consequences of these bacterial DNA integrations remain unknown. Modeling of these integrations suggests that the previously identified sequences cover most of the sequence flanking the junction between the bacterial and human DNA. Further examination of these reads reveals that these integrations are rich in guanine nucleotides and the integrated bacterial DNA may have complex transcript secondary structures. The models presented here lay the foundation for future experiments to test if bacterial DNA integrations alter the transcription of the human genes.

Influence of neural adaptation on dynamics and equilibrium state of neural activities in a ring neural network

Science.gov (United States)

Takiyama, Ken

2017-12-01

How neural adaptation affects neural information processing (i.e. the dynamics and equilibrium state of neural activities) is a central question in computational neuroscience. In my previous works, I analytically clarified the dynamics and equilibrium state of neural activities in a ring-type neural network model that is widely used to model the visual cortex, motor cortex, and several other brain regions. The neural dynamics and the equilibrium state in the neural network model corresponded to a Bayesian computation and statistically optimal multiple information integration, respectively, under a biologically inspired condition. These results were revealed in an analytically tractable manner; however, adaptation effects were not considered. Here, I analytically reveal how the dynamics and equilibrium state of neural activities in a ring neural network are influenced by spike-frequency adaptation (SFA). SFA is an adaptation that causes gradual inhibition of neural activity when a sustained stimulus is applied, and the strength of this inhibition depends on neural activities. I reveal that SFA plays three roles: (1) SFA amplifies the influence of external input in neural dynamics; (2) SFA allows the history of the external input to affect neural dynamics; and (3) the equilibrium state corresponds to the statistically optimal multiple information integration independent of the existence of SFA. In addition, the equilibrium state in a ring neural network model corresponds to the statistically optimal integration of multiple information sources under biologically inspired conditions, independent of the existence of SFA.

An integrated semiconductor device enabling non-optical genome sequencing.

Science.gov (United States)

Rothberg, Jonathan M; Hinz, Wolfgang; Rearick, Todd M; Schultz, Jonathan; Mileski, William; Davey, Mel; Leamon, John H; Johnson, Kim; Milgrew, Mark J; Edwards, Matthew; Hoon, Jeremy; Simons, Jan F; Marran, David; Myers, Jason W; Davidson, John F; Branting, Annika; Nobile, John R; Puc, Bernard P; Light, David; Clark, Travis A; Huber, Martin; Branciforte, Jeffrey T; Stoner, Isaac B; Cawley, Simon E; Lyons, Michael; Fu, Yutao; Homer, Nils; Sedova, Marina; Miao, Xin; Reed, Brian; Sabina, Jeffrey; Feierstein, Erika; Schorn, Michelle; Alanjary, Mohammad; Dimalanta, Eileen; Dressman, Devin; Kasinskas, Rachel; Sokolsky, Tanya; Fidanza, Jacqueline A; Namsaraev, Eugeni; McKernan, Kevin J; Williams, Alan; Roth, G Thomas; Bustillo, James

2011-07-20

The seminal importance of DNA sequencing to the life sciences, biotechnology and medicine has driven the search for more scalable and lower-cost solutions. Here we describe a DNA sequencing technology in which scalable, low-cost semiconductor manufacturing techniques are used to make an integrated circuit able to directly perform non-optical DNA sequencing of genomes. Sequence data are obtained by directly sensing the ions produced by template-directed DNA polymerase synthesis using all-natural nucleotides on this massively parallel semiconductor-sensing device or ion chip. The ion chip contains ion-sensitive, field-effect transistor-based sensors in perfect register with 1.2 million wells, which provide confinement and allow parallel, simultaneous detection of independent sequencing reactions. Use of the most widely used technology for constructing integrated circuits, the complementary metal-oxide semiconductor (CMOS) process, allows for low-cost, large-scale production and scaling of the device to higher densities and larger array sizes. We show the performance of the system by sequencing three bacterial genomes, its robustness and scalability by producing ion chips with up to 10 times as many sensors and sequencing a human genome.

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.

Wireless Neural Recording With Single Low-Power Integrated Circuit

Science.gov (United States)

Harrison, Reid R.; Kier, Ryan J.; Chestek, Cynthia A.; Gilja, Vikash; Nuyujukian, Paul; Ryu, Stephen; Greger, Bradley; Solzbacher, Florian; Shenoy, Krishna V.

2010-01-01

We present benchtop and in vivo experimental results from an integrated circuit designed for wireless implantable neural recording applications. The chip, which was fabricated in a commercially available 0.6-μm 2P3M BiCMOS process, contains 100 amplifiers, a 10-bit analog-to-digital converter (ADC), 100 threshold-based spike detectors, and a 902–928 MHz frequency-shift-keying (FSK) transmitter. Neural signals from a selected amplifier are sampled by the ADC at 15.7 kSps and telemetered over the FSK wireless data link. Power, clock, and command signals are sent to the chip wirelessly over a 2.765-MHz inductive (coil-to-coil) link. The chip is capable of operating with only two off-chip components: a power/command receiving coil and a 100-nF capacitor. PMID:19497825

An analog integrated front-end amplifier for neural applications

OpenAIRE

Zhou, Zhijun; Warr, Paul

2017-01-01

The front-end amplifier forms the critical element for signal detection and pre-processing within neural monitoring systems. It determines not only the fidelity of the biosignal, but also impacts power consumption and detector size. In this paper, a combined feedback loop-controlled approach is proposed to neutralize for the input leakage currents generated by low noise amplifiers when in integrated circuit form, alongside signal leakage into the input bias network. Significantly, this loop t...

Classical Conditioning with Pulsed Integrated Neural Networks: Circuits and System

DEFF Research Database (Denmark)

Lehmann, Torsten

1998-01-01

In this paper we investigate on-chip learning for pulsed, integrated neural networks. We discuss the implementational problems the technology imposes on learning systems and we find that abiologically inspired approach using simple circuit structures is most likely to bring success. We develop a ...... chip to solve simple classical conditioning tasks, thus verifying the design methodologies put forward in the paper....

Neurogenomics: An opportunity to integrate neuroscience, genomics and bioinformatics research in Africa

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Thomas K. Karikari

2015-06-01

Full Text Available Modern genomic approaches have made enormous contributions to improving our understanding of the function, development and evolution of the nervous system, and the diversity within and between species. However, most of these research advances have been recorded in countries with advanced scientific resources and funding support systems. On the contrary, little is known about, for example, the possible interplay between different genes, non-coding elements and environmental factors in modulating neurological diseases among populations in low-income countries, including many African countries. The unique ancestry of African populations suggests that improved inclusion of these populations in neuroscience-related genomic studies would significantly help to identify novel factors that might shape the future of neuroscience research and neurological healthcare. This perspective is strongly supported by the recent identification that diseased individuals and their kindred from specific sub-Saharan African populations lack common neurological disease-associated genetic mutations. This indicates that there may be population-specific causes of neurological diseases, necessitating further investigations into the contribution of additional, presently-unknown genomic factors. Here, we discuss how the development of neurogenomics research in Africa would help to elucidate disease-related genomic variants, and also provide a good basis to develop more effective therapies. Furthermore, neurogenomics would harness African scientists' expertise in neuroscience, genomics and bioinformatics to extend our understanding of the neural basis of behaviour, development and evolution.

Efficient genome-wide genotyping strategies and data integration in crop plants.

Science.gov (United States)

Torkamaneh, Davoud; Boyle, Brian; Belzile, François

2018-03-01

Next-generation sequencing (NGS) has revolutionized plant and animal research by providing powerful genotyping methods. This review describes and discusses the advantages, challenges and, most importantly, solutions to facilitate data processing, the handling of missing data, and cross-platform data integration. Next-generation sequencing technologies provide powerful and flexible genotyping methods to plant breeders and researchers. These methods offer a wide range of applications from genome-wide analysis to routine screening with a high level of accuracy and reproducibility. Furthermore, they provide a straightforward workflow to identify, validate, and screen genetic variants in a short time with a low cost. NGS-based genotyping methods include whole-genome re-sequencing, SNP arrays, and reduced representation sequencing, which are widely applied in crops. The main challenges facing breeders and geneticists today is how to choose an appropriate genotyping method and how to integrate genotyping data sets obtained from various sources. Here, we review and discuss the advantages and challenges of several NGS methods for genome-wide genetic marker development and genotyping in crop plants. We also discuss how imputation methods can be used to both fill in missing data in genotypic data sets and to integrate data sets obtained using different genotyping tools. It is our hope that this synthetic view of genotyping methods will help geneticists and breeders to integrate these NGS-based methods in crop plant breeding and research.

Neural Networks Integrated Circuit for Biomimetics MEMS Microrobot

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Ken Saito

2014-06-01

Full Text Available In this paper, we will propose the neural networks integrated circuit (NNIC which is the driving waveform generator of the 4.0, 2.7, 2.5 mm, width, length, height in size biomimetics microelectromechanical systems (MEMS microrobot. The microrobot was made from silicon wafer fabricated by micro fabrication technology. The mechanical system of the robot was equipped with small size rotary type actuators, link mechanisms and six legs to realize the ant-like switching behavior. The NNIC generates the driving waveform using synchronization phenomena such as biological neural networks. The driving waveform can operate the actuators of the MEMS microrobot directly. Therefore, the NNIC bare chip realizes the robot control without using any software programs or A/D converters. The microrobot performed forward and backward locomotion, and also changes direction by inputting an external single trigger pulse. The locomotion speed of the microrobot was 26.4 mm/min when the step width was 0.88 mm. The power consumption of the system was 250 mWh when the room temperature was 298 K.

Human neural progenitors derived from integration-free iPSCs for SCI therapy

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Ying Liu

2017-03-01

Full Text Available As a potentially unlimited autologous cell source, patient induced pluripotent stem cells (iPSCs provide great capability for tissue regeneration, particularly in spinal cord injury (SCI. However, despite significant progress made in translation of iPSC-derived neural progenitor cells (NPCs to clinical settings, a few hurdles remain. Among them, non-invasive approach to obtain source cells in a timely manner, safer integration-free delivery of reprogramming factors, and purification of NPCs before transplantation are top priorities to overcome. In this study, we developed a safe and cost-effective pipeline to generate clinically relevant NPCs. We first isolated cells from patients' urine and reprogrammed them into iPSCs by non-integrating Sendai viral vectors, and carried out experiments on neural differentiation. NPCs were purified by A2B5, an antibody specifically recognizing a glycoganglioside on the cell surface of neural lineage cells, via fluorescence activated cell sorting. Upon further in vitro induction, NPCs were able to give rise to neurons, oligodendrocytes and astrocytes. To test the functionality of the A2B5+ NPCs, we grafted them into the contused mouse thoracic spinal cord. Eight weeks after transplantation, the grafted cells survived, integrated into the injured spinal cord, and differentiated into neurons and glia. Our specific focus on cell source, reprogramming, differentiation and purification method purposely addresses timing and safety issues of transplantation to SCI models. It is our belief that this work takes one step closer on using human iPSC derivatives to SCI clinical settings.

A biologically inspired neural model for visual and proprioceptive integration including sensory training.

Science.gov (United States)

Saidi, Maryam; Towhidkhah, Farzad; Gharibzadeh, Shahriar; Lari, Abdolaziz Azizi

2013-12-01

Humans perceive the surrounding world by integration of information through different sensory modalities. Earlier models of multisensory integration rely mainly on traditional Bayesian and causal Bayesian inferences for single causal (source) and two causal (for two senses such as visual and auditory systems), respectively. In this paper a new recurrent neural model is presented for integration of visual and proprioceptive information. This model is based on population coding which is able to mimic multisensory integration of neural centers in the human brain. The simulation results agree with those achieved by casual Bayesian inference. The model can also simulate the sensory training process of visual and proprioceptive information in human. Training process in multisensory integration is a point with less attention in the literature before. The effect of proprioceptive training on multisensory perception was investigated through a set of experiments in our previous study. The current study, evaluates the effect of both modalities, i.e., visual and proprioceptive training and compares them with each other through a set of new experiments. In these experiments, the subject was asked to move his/her hand in a circle and estimate its position. The experiments were performed on eight subjects with proprioception training and eight subjects with visual training. Results of the experiments show three important points: (1) visual learning rate is significantly more than that of proprioception; (2) means of visual and proprioceptive errors are decreased by training but statistical analysis shows that this decrement is significant for proprioceptive error and non-significant for visual error, and (3) visual errors in training phase even in the beginning of it, is much less than errors of the main test stage because in the main test, the subject has to focus on two senses. The results of the experiments in this paper is in agreement with the results of the neural model

Variant Review with the Integrative Genomics Viewer.

Science.gov (United States)

Robinson, James T; Thorvaldsdóttir, Helga; Wenger, Aaron M; Zehir, Ahmet; Mesirov, Jill P

2017-11-01

Manual review of aligned reads for confirmation and interpretation of variant calls is an important step in many variant calling pipelines for next-generation sequencing (NGS) data. Visual inspection can greatly increase the confidence in calls, reduce the risk of false positives, and help characterize complex events. The Integrative Genomics Viewer (IGV) was one of the first tools to provide NGS data visualization, and it currently provides a rich set of tools for inspection, validation, and interpretation of NGS datasets, as well as other types of genomic data. Here, we present a short overview of IGV's variant review features for both single-nucleotide variants and structural variants, with examples from both cancer and germline datasets. IGV is freely available at https://www.igv.org Cancer Res; 77(21); e31-34. ©2017 AACR . ©2017 American Association for Cancer Research.

Integrated Eye Tracking and Neural Monitoring for Enhanced Assessment of Mild TBI

Science.gov (United States)

2017-06-01

working memory load effects after mild traumatic brain injury. Neuroimage, 2001. 14(5): p. 1004-12. 2. Chen, J.K., et al., Functional abnormalities in...report. 10 Supporting Data None. Integrated Eye Tracking and Neural Monitoring for Enhanced Assessment of Mild TBI Psychological Health

Neural basis of limb ownership in individuals with body integrity identity disorder

NARCIS (Netherlands)

van Dijk, Milenna T.; van Wingen, Guido A.; van Lammeren, Anouk; Blom, Rianne M.; de Kwaasteniet, Bart P.; Scholte, H. Steven; Denys, Damiaan

2013-01-01

Our body feels like it is ours. However, individuals with body integrity identity disorder (BIID) lack this feeling of ownership for distinct limbs and desire amputation of perfectly healthy body parts. This extremely rare condition provides us with an opportunity to study the neural basis

Dynamic stability analysis of fractional order leaky integrator echo state neural networks

Science.gov (United States)

Pahnehkolaei, Seyed Mehdi Abedi; Alfi, Alireza; Tenreiro Machado, J. A.

2017-06-01

The Leaky integrator echo state neural network (Leaky-ESN) is an improved model of the recurrent neural network (RNN) and adopts an interconnected recurrent grid of processing neurons. This paper presents a new proof for the convergence of a Lyapunov candidate function to zero when time tends to infinity by means of the Caputo fractional derivative with order lying in the range (0, 1). The stability of Fractional-Order Leaky-ESN (FO Leaky-ESN) is then analyzed, and the existence, uniqueness and stability of the equilibrium point are provided. A numerical example demonstrates the feasibility of the proposed method.

Concept of neural genoarchitecture and its genomic fundament.

Directory of Open Access Journals (Sweden)

Luis ePuelles

2012-11-01

Full Text Available The recent concept of neural genoarchitecture (or genoarchitectonics is examined from several angles, aiming to clarify the rationale for this new approach in causal and descriptive neuroanatomy. Gene expression patterns can be used as topographic stains revealing architectonic borders that may clarify, dispute or complicate existing brain anatomical subdivisions based on other methods, while increasing our understanding of how they arise in ontogenesis and evolution. A section of the text deals with differential regulation of gene expression in an ontogenetic causal network, attending to the structure of the genome and the functional peculiarities of enhancer and repressor regulatory regions that modulate gene transcription. The emergence of regionally characteristic sets of active transcription factors represents a critical concept, molecular identity, which can be applied to discrete brain territories and neuronal populations. Gene regulation is tied to positional effects, that is, topologically invariant domains of gene expression and natural boundaries, which can be correlated with anatomic ones. The large-scale stability of these patterns among vertebrates underpins molecularly the structural brain Bauplan, and is the fundament of field homology. The study of genoarchitectonic boundaries is presented as a crucial objective of modern neuroanatomic research. At most brain regions, new neuronal populations are being detected thanks to their differential genoarchitectonic features.

Unexpected inheritance: multiple integrations of ancient bornavirus and ebolavirus/marburgvirus sequences in vertebrate genomes.

Science.gov (United States)

Belyi, Vladimir A; Levine, Arnold J; Skalka, Anna Marie

2010-07-29

Vertebrate genomes contain numerous copies of retroviral sequences, acquired over the course of evolution. Until recently they were thought to be the only type of RNA viruses to be so represented, because integration of a DNA copy of their genome is required for their replication. In this study, an extensive sequence comparison was conducted in which 5,666 viral genes from all known non-retroviral families with single-stranded RNA genomes were matched against the germline genomes of 48 vertebrate species, to determine if such viruses could also contribute to the vertebrate genetic heritage. In 19 of the tested vertebrate species, we discovered as many as 80 high-confidence examples of genomic DNA sequences that appear to be derived, as long ago as 40 million years, from ancestral members of 4 currently circulating virus families with single strand RNA genomes. Surprisingly, almost all of the sequences are related to only two families in the Order Mononegavirales: the Bornaviruses and the Filoviruses, which cause lethal neurological disease and hemorrhagic fevers, respectively. Based on signature landmarks some, and perhaps all, of the endogenous virus-like DNA sequences appear to be LINE element-facilitated integrations derived from viral mRNAs. The integrations represent genes that encode viral nucleocapsid, RNA-dependent-RNA-polymerase, matrix and, possibly, glycoproteins. Integrations are generally limited to one or very few copies of a related viral gene per species, suggesting that once the initial germline integration was obtained (or selected), later integrations failed or provided little advantage to the host. The conservation of relatively long open reading frames for several of the endogenous sequences, the virus-like protein regions represented, and a potential correlation between their presence and a species' resistance to the diseases caused by these pathogens, are consistent with the notion that their products provide some important biological

Unexpected inheritance: multiple integrations of ancient bornavirus and ebolavirus/marburgvirus sequences in vertebrate genomes.

Directory of Open Access Journals (Sweden)

Vladimir A Belyi

2010-07-01

Full Text Available Vertebrate genomes contain numerous copies of retroviral sequences, acquired over the course of evolution. Until recently they were thought to be the only type of RNA viruses to be so represented, because integration of a DNA copy of their genome is required for their replication. In this study, an extensive sequence comparison was conducted in which 5,666 viral genes from all known non-retroviral families with single-stranded RNA genomes were matched against the germline genomes of 48 vertebrate species, to determine if such viruses could also contribute to the vertebrate genetic heritage. In 19 of the tested vertebrate species, we discovered as many as 80 high-confidence examples of genomic DNA sequences that appear to be derived, as long ago as 40 million years, from ancestral members of 4 currently circulating virus families with single strand RNA genomes. Surprisingly, almost all of the sequences are related to only two families in the Order Mononegavirales: the Bornaviruses and the Filoviruses, which cause lethal neurological disease and hemorrhagic fevers, respectively. Based on signature landmarks some, and perhaps all, of the endogenous virus-like DNA sequences appear to be LINE element-facilitated integrations derived from viral mRNAs. The integrations represent genes that encode viral nucleocapsid, RNA-dependent-RNA-polymerase, matrix and, possibly, glycoproteins. Integrations are generally limited to one or very few copies of a related viral gene per species, suggesting that once the initial germline integration was obtained (or selected, later integrations failed or provided little advantage to the host. The conservation of relatively long open reading frames for several of the endogenous sequences, the virus-like protein regions represented, and a potential correlation between their presence and a species' resistance to the diseases caused by these pathogens, are consistent with the notion that their products provide some important

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.

An integrated artificial neural networks approach for predicting global radiation

International Nuclear Information System (INIS)

Azadeh, A.; Maghsoudi, A.; Sohrabkhani, S.

2009-01-01

This article presents an integrated artificial neural network (ANN) approach for predicting solar global radiation by climatological variables. The integrated ANN trains and tests data with multi layer perceptron (MLP) approach which has the lowest mean absolute percentage error (MAPE). The proposed approach is particularly useful for locations where no available measurement equipment. Also, it considers all related climatological and meteorological parameters as input variables. To show the applicability and superiority of the integrated ANN approach, monthly data were collected for 6 years (1995-2000) in six nominal cities in Iran. Separate model for each city is considered and the quantity of solar global radiation in each city is calculated. Furthermore an integrated ANN model has been introduced for prediction of solar global radiation. The acquired results of the integrated model have shown high accuracy of about 94%. The results of the integrated model have been compared with traditional angstrom's model to show its considerable accuracy. Therefore, the proposed approach can be used as an efficient tool for prediction of solar radiation in the remote and rural locations with no direct measurement equipment.

Integration sites of Epstein-Barr virus genome on chromosomes of human lymphoblastoid cell lines

Energy Technology Data Exchange (ETDEWEB)

Wuu, K.D.; Chen, Y.J.; Wang-Wuu, S. [Institute of Genetics, Taipei (Taiwan, Province of China)

1994-09-01

Epstein-Barr virus (EBV) is the pathogen of infectious mononucleosis. The viral genome is present in more than 95% of the African cases of Burkitt lymphoma and it is usually maintained in episomal form in the tumor cells. Viral integration has been described only for Nanalwa which is a Burkitt lymphoma cell line lacking episomes. In order to examine the role of EBV in the immortalization of human Blymphocytes, we investigated whether the EBV integration into the human genome is essential. If the integration does occur, we would like to know whether the integration is randomly distributed or whether the viral DNA integrates preferentially at certain sites. Fourteen in vitro immortalized human lymphoblastoid cell lines (LCLs) were examined by fluorescence in situ hybridization (FISH) with a biotinylated EBV BamHI w DNA fragment as probe. The episomal form of EBV DNA was found in all cells of these cell lines, while only about 65% of the cells have the integrated viral DNA. This might suggest that integration is not a pre-requisite for cell immortalization. Although all chromosomes, except Y, have been found with integrated viral genome, chromsomes 1 and 5 are the most frequent EBV DNA carrier (p<0.05). Nine chromosome bands, namely, 1p31, 1q31, 2q32, 3q13, 3q26, 5q14, 6q24, 7q31 and 12q21, are preferential targets for EBV integration (p<0.001). Eighty percent of the total 938 EBV hybridization signals were found to be at G-band-positive area. This suggests that the mechanism of EBV integration might be different from that of the retroviruses, which specifically integrate to G-band-negative areas. Thus, we conclude that the integration of EBV to host genome is non-random and it may have something to do with the structure of chromosome and DNA sequences.

INDIGO – INtegrated Data Warehouse of MIcrobial GenOmes with Examples from the Red Sea Extremophiles

Science.gov (United States)

Alam, Intikhab; Antunes, André; Kamau, Allan Anthony; Ba alawi, Wail; Kalkatawi, Manal; Stingl, Ulrich; Bajic, Vladimir B.

2013-01-01

Background The next generation sequencing technologies substantially increased the throughput of microbial genome sequencing. To functionally annotate newly sequenced microbial genomes, a variety of experimental and computational methods are used. Integration of information from different sources is a powerful approach to enhance such annotation. Functional analysis of microbial genomes, necessary for downstream experiments, crucially depends on this annotation but it is hampered by the current lack of suitable information integration and exploration systems for microbial genomes. Results We developed a data warehouse system (INDIGO) that enables the integration of annotations for exploration and analysis of newly sequenced microbial genomes. INDIGO offers an opportunity to construct complex queries and combine annotations from multiple sources starting from genomic sequence to protein domain, gene ontology and pathway levels. This data warehouse is aimed at being populated with information from genomes of pure cultures and uncultured single cells of Red Sea bacteria and Archaea. Currently, INDIGO contains information from Salinisphaera shabanensis, Haloplasma contractile, and Halorhabdus tiamatea - extremophiles isolated from deep-sea anoxic brine lakes of the Red Sea. We provide examples of utilizing the system to gain new insights into specific aspects on the unique lifestyle and adaptations of these organisms to extreme environments. Conclusions We developed a data warehouse system, INDIGO, which enables comprehensive integration of information from various resources to be used for annotation, exploration and analysis of microbial genomes. It will be regularly updated and extended with new genomes. It is aimed to serve as a resource dedicated to the Red Sea microbes. In addition, through INDIGO, we provide our Automatic Annotation of Microbial Genomes (AAMG) pipeline. The INDIGO web server is freely available at http://www.cbrc.kaust.edu.sa/indigo. PMID

A scalable neural chip with synaptic electronics using CMOS integrated memristors

International Nuclear Information System (INIS)

Cruz-Albrecht, Jose M; Derosier, Timothy; Srinivasa, Narayan

2013-01-01

The design and simulation of a scalable neural chip with synaptic electronics using nanoscale memristors fully integrated with complementary metal–oxide–semiconductor (CMOS) is presented. The circuit consists of integrate-and-fire neurons and synapses with spike-timing dependent plasticity (STDP). The synaptic conductance values can be stored in memristors with eight levels, and the topology of connections between neurons is reconfigurable. The circuit has been designed using a 90 nm CMOS process with via connections to on-chip post-processed memristor arrays. The design has about 16 million CMOS transistors and 73 728 integrated memristors. We provide circuit level simulations of the entire chip performing neuronal and synaptic computations that result in biologically realistic functional behavior. (paper)

A Fully Integrated Wireless Compressed Sensing Neural Signal Acquisition System for Chronic Recording and Brain Machine Interface.

Science.gov (United States)

Liu, Xilin; Zhang, Milin; Xiong, Tao; Richardson, Andrew G; Lucas, Timothy H; Chin, Peter S; Etienne-Cummings, Ralph; Tran, Trac D; Van der Spiegel, Jan

2016-07-18

Reliable, multi-channel neural recording is critical to the neuroscience research and clinical treatment. However, most hardware development of fully integrated, multi-channel wireless neural recorders to-date, is still in the proof-of-concept stage. To be ready for practical use, the trade-offs between performance, power consumption, device size, robustness, and compatibility need to be carefully taken into account. This paper presents an optimized wireless compressed sensing neural signal recording system. The system takes advantages of both custom integrated circuits and universal compatible wireless solutions. The proposed system includes an implantable wireless system-on-chip (SoC) and an external wireless relay. The SoC integrates 16-channel low-noise neural amplifiers, programmable filters and gain stages, a SAR ADC, a real-time compressed sensing module, and a near field wireless power and data transmission link. The external relay integrates a 32 bit low-power microcontroller with Bluetooth 4.0 wireless module, a programming interface, and an inductive charging unit. The SoC achieves high signal recording quality with minimized power consumption, while reducing the risk of infection from through-skin connectors. The external relay maximizes the compatibility and programmability. The proposed compressed sensing module is highly configurable, featuring a SNDR of 9.78 dB with a compression ratio of 8×. The SoC has been fabricated in a 180 nm standard CMOS technology, occupying 2.1 mm × 0.6 mm silicon area. A pre-implantable system has been assembled to demonstrate the proposed paradigm. The developed system has been successfully used for long-term wireless neural recording in freely behaving rhesus monkey.

Genome-wide conserved non-coding microsatellite (CNMS) marker-based integrative genetical genomics for quantitative dissection of seed weight in chickpea.

Science.gov (United States)

Bajaj, Deepak; Saxena, Maneesha S; Kujur, Alice; Das, Shouvik; Badoni, Saurabh; Tripathi, Shailesh; Upadhyaya, Hari D; Gowda, C L L; Sharma, Shivali; Singh, Sube; Tyagi, Akhilesh K; Parida, Swarup K

2015-03-01

Phylogenetic footprinting identified 666 genome-wide paralogous and orthologous CNMS (conserved non-coding microsatellite) markers from 5'-untranslated and regulatory regions (URRs) of 603 protein-coding chickpea genes. The (CT)n and (GA)n CNMS carrying CTRMCAMV35S and GAGA8BKN3 regulatory elements, respectively, are abundant in the chickpea genome. The mapped genic CNMS markers with robust amplification efficiencies (94.7%) detected higher intraspecific polymorphic potential (37.6%) among genotypes, implying their immense utility in chickpea breeding and genetic analyses. Seventeen differentially expressed CNMS marker-associated genes showing strong preferential and seed tissue/developmental stage-specific expression in contrasting genotypes were selected to narrow down the gene targets underlying seed weight quantitative trait loci (QTLs)/eQTLs (expression QTLs) through integrative genetical genomics. The integration of transcript profiling with seed weight QTL/eQTL mapping, molecular haplotyping, and association analyses identified potential molecular tags (GAGA8BKN3 and RAV1AAT regulatory elements and alleles/haplotypes) in the LOB-domain-containing protein- and KANADI protein-encoding transcription factor genes controlling the cis-regulated expression for seed weight in the chickpea. This emphasizes the potential of CNMS marker-based integrative genetical genomics for the quantitative genetic dissection of complex seed weight in chickpea. © The Author 2014. Published by Oxford University Press on behalf of the Society for Experimental Biology.

Genome-wide analysis reveals the extent of EAV-HP integration in domestic chicken.

Science.gov (United States)

Wragg, David; Mason, Andrew S; Yu, Le; Kuo, Richard; Lawal, Raman A; Desta, Takele Taye; Mwacharo, Joram M; Cho, Chang-Yeon; Kemp, Steve; Burt, David W; Hanotte, Olivier

2015-10-14

EAV-HP is an ancient retrovirus pre-dating Gallus speciation, which continues to circulate in modern chicken populations, and led to the emergence of avian leukosis virus subgroup J causing significant economic losses to the poultry industry. We mapped EAV-HP integration sites in Ethiopian village chickens, a Silkie, Taiwan Country chicken, red junglefowl Gallus gallus and several inbred experimental lines using whole-genome sequence data. An average of 75.22 ± 9.52 integration sites per bird were identified, which collectively group into 279 intervals of which 5 % are common to 90 % of the genomes analysed and are suggestive of pre-domestication integration events. More than a third of intervals are specific to individual genomes, supporting active circulation of EAV-HP in modern chickens. Interval density is correlated with chromosome length (P < 2.31(-6)), and 27 % of intervals are located within 5 kb of a transcript. Functional annotation clustering of genes reveals enrichment for immune-related functions (P < 0.05). Our results illustrate a non-random distribution of EAV-HP in the genome, emphasising the importance it may have played in the adaptation of the species, and provide a platform from which to extend investigations on the co-evolutionary significance of endogenous retroviral genera with their hosts.

LocusTrack: Integrated visualization of GWAS results and genomic annotation.

Science.gov (United States)

Cuellar-Partida, Gabriel; Renteria, Miguel E; MacGregor, Stuart

2015-01-01

Genome-wide association studies (GWAS) are an important tool for the mapping of complex traits and diseases. Visual inspection of genomic annotations may be used to generate insights into the biological mechanisms underlying GWAS-identified loci. We developed LocusTrack, a web-based application that annotates and creates plots of regional GWAS results and incorporates user-specified tracks that display annotations such as linkage disequilibrium (LD), phylogenetic conservation, chromatin state, and other genomic and regulatory elements. Currently, LocusTrack can integrate annotation tracks from the UCSC genome-browser as well as from any tracks provided by the user. LocusTrack is an easy-to-use application and can be accessed at the following URL: http://gump.qimr.edu.au/general/gabrieC/LocusTrack/. Users can upload and manage GWAS results and select from and/or provide annotation tracks using simple and intuitive menus. LocusTrack scripts and associated data can be downloaded from the website and run locally.

MicroScope in 2017: an expanding and evolving integrated resource for community expertise of microbial genomes.

Science.gov (United States)

Vallenet, David; Calteau, Alexandra; Cruveiller, Stéphane; Gachet, Mathieu; Lajus, Aurélie; Josso, Adrien; Mercier, Jonathan; Renaux, Alexandre; Rollin, Johan; Rouy, Zoe; Roche, David; Scarpelli, Claude; Médigue, Claudine

2017-01-04

The annotation of genomes from NGS platforms needs to be automated and fully integrated. However, maintaining consistency and accuracy in genome annotation is a challenging problem because millions of protein database entries are not assigned reliable functions. This shortcoming limits the knowledge that can be extracted from genomes and metabolic models. Launched in 2005, the MicroScope platform (http://www.genoscope.cns.fr/agc/microscope) is an integrative resource that supports systematic and efficient revision of microbial genome annotation, data management and comparative analysis. Effective comparative analysis requires a consistent and complete view of biological data, and therefore, support for reviewing the quality of functional annotation is critical. MicroScope allows users to analyze microbial (meta)genomes together with post-genomic experiment results if any (i.e. transcriptomics, re-sequencing of evolved strains, mutant collections, phenotype data). It combines tools and graphical interfaces to analyze genomes and to perform the expert curation of gene functions in a comparative context. Starting with a short overview of the MicroScope system, this paper focuses on some major improvements of the Web interface, mainly for the submission of genomic data and on original tools and pipelines that have been developed and integrated in the platform: computation of pan-genomes and prediction of biosynthetic gene clusters. Today the resource contains data for more than 6000 microbial genomes, and among the 2700 personal accounts (65% of which are now from foreign countries), 14% of the users are performing expert annotations, on at least a weekly basis, contributing to improve the quality of microbial genome annotations. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Integration of active devices on smart polymers for neural interfaces

Science.gov (United States)

Avendano-Bolivar, Adrian Emmanuel

The increasing ability to ever more precisely identify and measure neural interactions and other phenomena in the central and peripheral nervous systems is revolutionizing our understanding of the human body and brain. To facilitate further understanding, more sophisticated neural devices, perhaps using microelectronics processing, must be fabricated. Materials often used in these neural interfaces, while compatible with these fabrication processes, are not optimized for long-term use in the body and are often orders of magnitude stiffer than the tissue with which they interact. Using the smart polymer substrates described in this work, suitability for processing as well as chronic implantation is demonstrated. We explore how to integrate reliable circuitry onto these flexible, biocompatible substrates that can withstand the aggressive environment of the body. To increase the capabilities of these devices beyond individual channel sensing and stimulation, active electronics must also be included onto our systems. In order to add this functionality to these substrates and explore the limits of these devices, we developed a process to fabricate single organic thin film transistors with mobilities up to 0.4 cm2/Vs and threshold voltages close to 0V. A process for fabricating organic light emitting diodes on flexible substrates is also addressed. We have set a foundation and demonstrated initial feasibility for integrating multiple transistors onto thin-film flexible devices to create new applications, such as matrix addressable functionalized electrodes and organic light emitting diodes. A brief description on how to integrate waveguides for their use in optogenetics is addressed. We have built understanding about device constraints on mechanical, electrical and in vivo reliability and how various conditions affect the electronics' lifetime. We use a bi-layer gate dielectric using an inorganic material such as HfO 2 combined with organic Parylene-c. A study of

Human papillomavirus genome integration in squamous carcinogenesis: what have next-generation sequencing studies taught us?

Science.gov (United States)

Groves, Ian J; Coleman, Nicholas

2018-05-01

Human papillomavirus (HPV) infection is associated with ∼5% of all human cancers, including a range of squamous cell carcinomas. Persistent infection by high-risk HPVs (HRHPVs) is associated with the integration of virus genomes (which are usually stably maintained as extrachromosomal episomes) into host chromosomes. Although HRHPV integration rates differ across human sites of infection, this process appears to be an important event in HPV-associated neoplastic progression, leading to deregulation of virus oncogene expression, host gene expression modulation, and further genomic instability. However, the mechanisms by which HRHPV integration occur and by which the subsequent gene expression changes take place are incompletely understood. The advent of next-generation sequencing (NGS) of both RNA and DNA has allowed powerful interrogation of the association of HRHPVs with human disease, including precise determination of the sites of integration and the genomic rearrangements at integration loci. In turn, these data have indicated that integration occurs through two main mechanisms: looping integration and direct insertion. Improved understanding of integration sites is allowing further investigation of the factors that provide a competitive advantage to some integrants during disease progression. Furthermore, advanced approaches to the generation of genome-wide samples have given novel insights into the three-dimensional interactions within the nucleus, which could act as another layer of epigenetic control of both virus and host transcription. It is hoped that further advances in NGS techniques and analysis will not only allow the examination of further unanswered questions regarding HPV infection, but also direct new approaches to treating HPV-associated human disease. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John

Neural Network Control for the Probe Landing Based on Proportional Integral Observer

Directory of Open Access Journals (Sweden)

Yuanchun Li

2015-01-01

Full Text Available For the probe descending and landing safely, a neural network control method based on proportional integral observer (PIO is proposed. First, the dynamics equation of the probe under the landing site coordinate system is deduced and the nominal trajectory meeting the constraints in advance on three axes is preplanned. Then the PIO designed by using LMI technique is employed in the control law to compensate the effect of the disturbance. At last, the neural network control algorithm is used to guarantee the double zero control of the probe and ensure the probe can land safely. An illustrative design example is employed to demonstrate the effectiveness of the proposed control approach.

An integrative and applicable phylogenetic footprinting framework for cis-regulatory motifs identification in prokaryotic genomes.

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Liu, Bingqiang; Zhang, Hanyuan; Zhou, Chuan; Li, Guojun; Fennell, Anne; Wang, Guanghui; Kang, Yu; Liu, Qi; Ma, Qin

2016-08-09

Phylogenetic footprinting is an important computational technique for identifying cis-regulatory motifs in orthologous regulatory regions from multiple genomes, as motifs tend to evolve slower than their surrounding non-functional sequences. Its application, however, has several difficulties for optimizing the selection of orthologous data and reducing the false positives in motif prediction. Here we present an integrative phylogenetic footprinting framework for accurate motif predictions in prokaryotic genomes (MP(3)). The framework includes a new orthologous data preparation procedure, an additional promoter scoring and pruning method and an integration of six existing motif finding algorithms as basic motif search engines. Specifically, we collected orthologous genes from available prokaryotic genomes and built the orthologous regulatory regions based on sequence similarity of promoter regions. This procedure made full use of the large-scale genomic data and taxonomy information and filtered out the promoters with limited contribution to produce a high quality orthologous promoter set. The promoter scoring and pruning is implemented through motif voting by a set of complementary predicting tools that mine as many motif candidates as possible and simultaneously eliminate the effect of random noise. We have applied the framework to Escherichia coli k12 genome and evaluated the prediction performance through comparison with seven existing programs. This evaluation was systematically carried out at the nucleotide and binding site level, and the results showed that MP(3) consistently outperformed other popular motif finding tools. We have integrated MP(3) into our motif identification and analysis server DMINDA, allowing users to efficiently identify and analyze motifs in 2,072 completely sequenced prokaryotic genomes. The performance evaluation indicated that MP(3) is effective for predicting regulatory motifs in prokaryotic genomes. Its application may enhance

Genome scale models of yeast: towards standardized evaluation and consistent omic integration

DEFF Research Database (Denmark)

Sanchez, Benjamin J.; Nielsen, Jens

2015-01-01

Genome scale models (GEMs) have enabled remarkable advances in systems biology, acting as functional databases of metabolism, and as scaffolds for the contextualization of high-throughput data. In the case of Saccharomyces cerevisiae (budding yeast), several GEMs have been published and are curre......Genome scale models (GEMs) have enabled remarkable advances in systems biology, acting as functional databases of metabolism, and as scaffolds for the contextualization of high-throughput data. In the case of Saccharomyces cerevisiae (budding yeast), several GEMs have been published...... in which all levels of omics data (from gene expression to flux) have been integrated in yeast GEMs. Relevant conclusions and current challenges for both GEM evaluation and omic integration are highlighted....

Integration of neural networks with fuzzy reasoning for measuring operational parameters in a nuclear reactor

International Nuclear Information System (INIS)

Ikonomopoulos, A.; Tsoukalas, L.H.

1993-01-01

A novel approach is described for measuring variables with operational significance in a complex system such as a nuclear reactor. The methodology is based on the integration of artificial neural networks with fuzzy reasoning. Neural networks are used to map dynamic time series to a set of user-defined linguistic labels called fuzzy values. The process takes place in a manner analogous to that of measurement. Hence, the entire procedure is referred to as virtual measurement and its software implementation as a virtual measuring device. An optimization algorithm based on information criteria and fuzzy algebra augments the process and assists in the identification of different states of the monitored parameter. The proposed technique is applied for monitoring parameters such as performance, valve position, transient type, and reactivity. The results obtained from the application of the neural network-fuzzy reasoning integration in a high power research reactor clearly demonstrate the excellent tolerance of the virtual measuring device to faulty signals as well as its ability to accommodate noisy inputs

Decoding the genome with an integrative analysis tool: combinatorial CRM Decoder.

Science.gov (United States)

Kang, Keunsoo; Kim, Joomyeong; Chung, Jae Hoon; Lee, Daeyoup

2011-09-01

The identification of genome-wide cis-regulatory modules (CRMs) and characterization of their associated epigenetic features are fundamental steps toward the understanding of gene regulatory networks. Although integrative analysis of available genome-wide information can provide new biological insights, the lack of novel methodologies has become a major bottleneck. Here, we present a comprehensive analysis tool called combinatorial CRM decoder (CCD), which utilizes the publicly available information to identify and characterize genome-wide CRMs in a species of interest. CCD first defines a set of the epigenetic features which is significantly associated with a set of known CRMs as a code called 'trace code', and subsequently uses the trace code to pinpoint putative CRMs throughout the genome. Using 61 genome-wide data sets obtained from 17 independent mouse studies, CCD successfully catalogued ∼12 600 CRMs (five distinct classes) including polycomb repressive complex 2 target sites as well as imprinting control regions. Interestingly, we discovered that ∼4% of the identified CRMs belong to at least two different classes named 'multi-functional CRM', suggesting their functional importance for regulating spatiotemporal gene expression. From these examples, we show that CCD can be applied to any potential genome-wide datasets and therefore will shed light on unveiling genome-wide CRMs in various species.

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.

An integrated clinical and genomic information system for cancer precision medicine.

Science.gov (United States)

Jang, Yeongjun; Choi, Taekjin; Kim, Jongho; Park, Jisub; Seo, Jihae; Kim, Sangok; Kwon, Yeajee; Lee, Seungjae; Lee, Sanghyuk

2018-04-20

Increasing affordability of next-generation sequencing (NGS) has created an opportunity for realizing genomically-informed personalized cancer therapy as a path to precision oncology. However, the complex nature of genomic information presents a huge challenge for clinicians in interpreting the patient's genomic alterations and selecting the optimum approved or investigational therapy. An elaborate and practical information system is urgently needed to support clinical decision as well as to test clinical hypotheses quickly. Here, we present an integrated clinical and genomic information system (CGIS) based on NGS data analyses. Major components include modules for handling clinical data, NGS data processing, variant annotation and prioritization, drug-target-pathway analysis, and population cohort explorer. We built a comprehensive knowledgebase of genes, variants, drugs by collecting annotated information from public and in-house resources. Structured reports for molecular pathology are generated using standardized terminology in order to help clinicians interpret genomic variants and utilize them for targeted cancer therapy. We also implemented many features useful for testing hypotheses to develop prognostic markers from mutation and gene expression data. Our CGIS software is an attempt to provide useful information for both clinicians and scientists who want to explore genomic information for precision oncology.

Adaptive Moving Object Tracking Integrating Neural Networks And Intelligent Processing

Science.gov (United States)

Lee, James S. J.; Nguyen, Dziem D.; Lin, C.

1989-03-01

A real-time adaptive scheme is introduced to detect and track moving objects under noisy, dynamic conditions including moving sensors. This approach integrates the adaptiveness and incremental learning characteristics of neural networks with intelligent reasoning and process control. Spatiotemporal filtering is used to detect and analyze motion, exploiting the speed and accuracy of multiresolution processing. A neural network algorithm constitutes the basic computational structure for classification. A recognition and learning controller guides the on-line training of the network, and invokes pattern recognition to determine processing parameters dynamically and to verify detection results. A tracking controller acts as the central control unit, so that tracking goals direct the over-all system. Performance is benchmarked against the Widrow-Hoff algorithm, for target detection scenarios presented in diverse FLIR image sequences. Efficient algorithm design ensures that this recognition and control scheme, implemented in software and commercially available image processing hardware, meets the real-time requirements of tracking applications.

GDR (Genome Database for Rosaceae): integrated web-database for Rosaceae genomics and genetics data.

Science.gov (United States)

Jung, Sook; Staton, Margaret; Lee, Taein; Blenda, Anna; Svancara, Randall; Abbott, Albert; Main, Dorrie

2008-01-01

The Genome Database for Rosaceae (GDR) is a central repository of curated and integrated genetics and genomics data of Rosaceae, an economically important family which includes apple, cherry, peach, pear, raspberry, rose and strawberry. GDR contains annotated databases of all publicly available Rosaceae ESTs, the genetically anchored peach physical map, Rosaceae genetic maps and comprehensively annotated markers and traits. The ESTs are assembled to produce unigene sets of each genus and the entire Rosaceae. Other annotations include putative function, microsatellites, open reading frames, single nucleotide polymorphisms, gene ontology terms and anchored map position where applicable. Most of the published Rosaceae genetic maps can be viewed and compared through CMap, the comparative map viewer. The peach physical map can be viewed using WebFPC/WebChrom, and also through our integrated GDR map viewer, which serves as a portal to the combined genetic, transcriptome and physical mapping information. ESTs, BACs, markers and traits can be queried by various categories and the search result sites are linked to the mapping visualization tools. GDR also provides online analysis tools such as a batch BLAST/FASTA server for the GDR datasets, a sequence assembly server and microsatellite and primer detection tools. GDR is available at http://www.rosaceae.org.

CTDB: An Integrated Chickpea Transcriptome Database for Functional and Applied Genomics.

Directory of Open Access Journals (Sweden)

Mohit Verma

Full Text Available Chickpea is an important grain legume used as a rich source of protein in human diet. The narrow genetic diversity and limited availability of genomic resources are the major constraints in implementing breeding strategies and biotechnological interventions for genetic enhancement of chickpea. We developed an integrated Chickpea Transcriptome Database (CTDB, which provides the comprehensive web interface for visualization and easy retrieval of transcriptome data in chickpea. The database features many tools for similarity search, functional annotation (putative function, PFAM domain and gene ontology search and comparative gene expression analysis. The current release of CTDB (v2.0 hosts transcriptome datasets with high quality functional annotation from cultivated (desi and kabuli types and wild chickpea. A catalog of transcription factor families and their expression profiles in chickpea are available in the database. The gene expression data have been integrated to study the expression profiles of chickpea transcripts in major tissues/organs and various stages of flower development. The utilities, such as similarity search, ortholog identification and comparative gene expression have also been implemented in the database to facilitate comparative genomic studies among different legumes and Arabidopsis. Furthermore, the CTDB represents a resource for the discovery of functional molecular markers (microsatellites and single nucleotide polymorphisms between different chickpea types. We anticipate that integrated information content of this database will accelerate the functional and applied genomic research for improvement of chickpea. The CTDB web service is freely available at http://nipgr.res.in/ctdb.html.

STINGRAY: system for integrated genomic resources and analysis.

Science.gov (United States)

Wagner, Glauber; Jardim, Rodrigo; Tschoeke, Diogo A; Loureiro, Daniel R; Ocaña, Kary A C S; Ribeiro, Antonio C B; Emmel, Vanessa E; Probst, Christian M; Pitaluga, André N; Grisard, Edmundo C; Cavalcanti, Maria C; Campos, Maria L M; Mattoso, Marta; Dávila, Alberto M R

2014-03-07

The STINGRAY system has been conceived to ease the tasks of integrating, analyzing, annotating and presenting genomic and expression data from Sanger and Next Generation Sequencing (NGS) platforms. STINGRAY includes: (a) a complete and integrated workflow (more than 20 bioinformatics tools) ranging from functional annotation to phylogeny; (b) a MySQL database schema, suitable for data integration and user access control; and (c) a user-friendly graphical web-based interface that makes the system intuitive, facilitating the tasks of data analysis and annotation. STINGRAY showed to be an easy to use and complete system for analyzing sequencing data. While both Sanger and NGS platforms are supported, the system could be faster using Sanger data, since the large NGS datasets could potentially slow down the MySQL database usage. STINGRAY is available at http://stingray.biowebdb.org and the open source code at http://sourceforge.net/projects/stingray-biowebdb/.

MicroScope-an integrated resource for community expertise of gene functions and comparative analysis of microbial genomic and metabolic data.

Science.gov (United States)

Médigue, Claudine; Calteau, Alexandra; Cruveiller, Stéphane; Gachet, Mathieu; Gautreau, Guillaume; Josso, Adrien; Lajus, Aurélie; Langlois, Jordan; Pereira, Hugo; Planel, Rémi; Roche, David; Rollin, Johan; Rouy, Zoe; Vallenet, David

2017-09-12

The overwhelming list of new bacterial genomes becoming available on a daily basis makes accurate genome annotation an essential step that ultimately determines the relevance of thousands of genomes stored in public databanks. The MicroScope platform (http://www.genoscope.cns.fr/agc/microscope) is an integrative resource that supports systematic and efficient revision of microbial genome annotation, data management and comparative analysis. Starting from the results of our syntactic, functional and relational annotation pipelines, MicroScope provides an integrated environment for the expert annotation and comparative analysis of prokaryotic genomes. It combines tools and graphical interfaces to analyze genomes and to perform the manual curation of gene function in a comparative genomics and metabolic context. In this article, we describe the free-of-charge MicroScope services for the annotation and analysis of microbial (meta)genomes, transcriptomic and re-sequencing data. Then, the functionalities of the platform are presented in a way providing practical guidance and help to the nonspecialists in bioinformatics. Newly integrated analysis tools (i.e. prediction of virulence and resistance genes in bacterial genomes) and original method recently developed (the pan-genome graph representation) are also described. Integrated environments such as MicroScope clearly contribute, through the user community, to help maintaining accurate resources. © The Author 2017. Published by Oxford University Press.

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.

Integration of Online Parameter Identification and Neural Network for In-Flight Adaptive Control

Science.gov (United States)

Hageman, Jacob J.; Smith, Mark S.; Stachowiak, Susan

2003-01-01

An indirect adaptive system has been constructed for robust control of an aircraft with uncertain aerodynamic characteristics. This system consists of a multilayer perceptron pre-trained neural network, online stability and control derivative identification, a dynamic cell structure online learning neural network, and a model following control system based on the stochastic optimal feedforward and feedback technique. The pre-trained neural network and model following control system have been flight-tested, but the online parameter identification and online learning neural network are new additions used for in-flight adaptation of the control system model. A description of the modification and integration of these two stand-alone software packages into the complete system in preparation for initial flight tests is presented. Open-loop results using both simulation and flight data, as well as closed-loop performance of the complete system in a nonlinear, six-degree-of-freedom, flight validated simulation, are analyzed. Results show that this online learning system, in contrast to the nonlearning system, has the ability to adapt to changes in aerodynamic characteristics in a real-time, closed-loop, piloted simulation, resulting in improved flying qualities.

NGS-based approach to determine the presence of HPV and their sites of integration in human cancer genome.

Science.gov (United States)

Chandrani, P; Kulkarni, V; Iyer, P; Upadhyay, P; Chaubal, R; Das, P; Mulherkar, R; Singh, R; Dutt, A

2015-06-09

Human papilloma virus (HPV) accounts for the most common cause of all virus-associated human cancers. Here, we describe the first graphic user interface (GUI)-based automated tool 'HPVDetector', for non-computational biologists, exclusively for detection and annotation of the HPV genome based on next-generation sequencing data sets. We developed a custom-made reference genome that comprises of human chromosomes along with annotated genome of 143 HPV types as pseudochromosomes. The tool runs on a dual mode as defined by the user: a 'quick mode' to identify presence of HPV types and an 'integration mode' to determine genomic location for the site of integration. The input data can be a paired-end whole-exome, whole-genome or whole-transcriptome data set. The HPVDetector is available in public domain for download: http://www.actrec.gov.in/pi-webpages/AmitDutt/HPVdetector/HPVDetector.html. On the basis of our evaluation of 116 whole-exome, 23 whole-transcriptome and 2 whole-genome data, we were able to identify presence of HPV in 20 exomes and 4 transcriptomes of cervical and head and neck cancer tumour samples. Using the inbuilt annotation module of HPVDetector, we found predominant integration of viral gene E7, a known oncogene, at known 17q21, 3q27, 7q35, Xq28 and novel sites of integration in the human genome. Furthermore, co-infection with high-risk HPVs such as 16 and 31 were found to be mutually exclusive compared with low-risk HPV71. HPVDetector is a simple yet precise and robust tool for detecting HPV from tumour samples using variety of next-generation sequencing platforms including whole genome, whole exome and transcriptome. Two different modes (quick detection and integration mode) along with a GUI widen the usability of HPVDetector for biologists and clinicians with minimal computational knowledge.

Prolonged Integration Site Selection of a Lentiviral Vector in the Genome of Human Keratinocytes.

Science.gov (United States)

Qian, Wei; Wang, Yong; Li, Rui-Fu; Zhou, Xin; Liu, Jing; Peng, Dai-Zhi

2017-03-03

BACKGROUND Lentiviral vectors have been successfully used for human skin cell gene transfer studies. Defining the selection of integration sites for retroviral vectors in the host genome is crucial in risk assessment analysis of gene therapy. However, genome-wide analyses of lentiviral integration sites in human keratinocytes, especially after prolonged growth, are poorly understood. MATERIAL AND METHODS In this study, 874 unique lentiviral vector integration sites in human HaCaT keratinocytes after long-term culture were identified and analyzed with the online tool GTSG-QuickMap and SPSS software. RESULTS The data indicated that lentiviral vectors showed integration site preferences for genes and gene-rich regions. CONCLUSIONS This study will likely assist in determining the relative risks of the lentiviral vector system and in the design of a safe lentiviral vector system in the gene therapy of skin diseases.

Molecular Assemblies, Genes and Genomics Integrated Efficiently (MAGGIE)

Energy Technology Data Exchange (ETDEWEB)

Baliga, Nitin S

2011-05-26

when applied to the manually curated training set. Applying this method to the data representing around a quarter of the fraction space for water soluble proteins in D. vulgaris, we obtained 854 reliable pair wise interactions. Further, we have developed algorithms to analyze and assign significance to protein interaction data from bait pull-down experiments and integrate these data with other systems biology data through associative biclustering in a parallel computing environment. We will 'fill-in' missing information in these interaction data using a 'Transitive Closure' algorithm and subsequently use 'Between Commonality Decomposition' algorithm to discover complexes within these large graphs of protein interactions. To characterize the metabolic activities of proteins and their complexes we are developing algorithms to deconvolute pure mass spectra, estimate chemical formula for m/z values, and fit isotopic fine structure to metabolomics data. We have discovered that in comparison to isotopic pattern fitting methods restricting the chemical formula by these two dimensions actually facilitates unique solutions for chemical formula generators. To understand how microbial functions are regulated we have developed complementary algorithms for reconstructing gene regulatory networks (GRNs). Whereas the network inference algorithms cMonkey and Inferelator developed enable de novo reconstruction of predictive models for GRNs from diverse systems biology data, the RegPrecise and RegPredict framework developed uses evolutionary comparisons of genomes from closely related organisms to reconstruct conserved regulons. We have integrated the two complementary algorithms to rapidly generate comprehensive models for gene regulation of understudied organisms. Our preliminary analyses of these reconstructed GRNs have revealed novel regulatory mechanisms and cis-regulatory motifs, as well asothers that are conserved across species. Finally, we are

Neural substrates of reliability-weighted visual-tactile multisensory integration

Directory of Open Access Journals (Sweden)

Michael S Beauchamp

2010-06-01

Full Text Available As sensory systems deteriorate in aging or disease, the brain must relearn the appropriate weights to assign each modality during multisensory integration. Using blood-oxygen level dependent functional magnetic resonance imaging (BOLD fMRI of human subjects, we tested a model for the neural mechanisms of sensory weighting, termed “weighted connections”. This model holds that the connection weights between early and late areas vary depending on the reliability of the modality, independent of the level of early sensory cortex activity. When subjects detected viewed and felt touches to the hand, a network of brain areas was active, including visual areas in lateral occipital cortex, somatosensory areas in inferior parietal lobe, and multisensory areas in the intraparietal sulcus (IPS. In agreement with the weighted connection model, the connection weight measured with structural equation modeling between somatosensory cortex and IPS increased for somatosensory-reliable stimuli, and the connection weight between visual cortex and IPS increased for visual-reliable stimuli. This double dissociation of connection strengths was similar to the pattern of behavioral responses during incongruent multisensory stimulation, suggesting that weighted connections may be a neural mechanism for behavioral reliability weighting.for behavioral reliability weighting.

Construction of an integrated database to support genomic sequence analysis

Energy Technology Data Exchange (ETDEWEB)

Gilbert, W.; Overbeek, R.

1994-11-01

The central goal of this project is to develop an integrated database to support comparative analysis of genomes including DNA sequence data, protein sequence data, gene expression data and metabolism data. In developing the logic-based system GenoBase, a broader integration of available data was achieved due to assistance from collaborators. Current goals are to easily include new forms of data as they become available and to easily navigate through the ensemble of objects described within the database. This report comments on progress made in these areas.

INTEGRATION OF FRACTAL AND NEURAL NETWORK TECHNOLOGIES IN PEDAGOGICAL MONITORING AND ASSESSMENT OF KNOWLEDGE OF TRAINEES

Directory of Open Access Journals (Sweden)

Svetlana N Dvoryatkina

2017-12-01

Full Text Available The possibility of statement and solution of the problem of searching of theoretical justification and development of efficient didactic mechanisms of the organization of process of pedagogical monitoring and assessment of level of knowledge of trainees can be based on convergence of the leading psychological and pedagogical, mathematical, and informational technologies with accounting of the modern achievements in science. In the article, the pedagogical expediency of realization of opportunities of means of informational technologies in monitoring and assessment of the composite mathematical knowledge, in the management of cognitive activity of students is proved. The ability to integrate fractal methods and neural network technologies in perfecting of a system of pedagogical monitoring of mathematical knowledge of trainees as a part of the automated training systems (ATS is investigated and realized in practice. It is proved that fractal methods increase the accuracy and depth of estimation of the level of proficiency of students and also complexes of intellectual operations of the integrative qualities allowing to master and apply cross-disciplinary knowledge and abilities in professional activity. Neural network technologies solve a problem of realization of the personal focused tutoring from positions of optimum individualization of mathematical education and self-realization of the person. The technology of projection of integrative system of pedagogical monitoring of knowledge of students includes the following stages: establishment of the required tutoring parameters; definition and preparation of input data for realization of integration of fractal and neural network technologies; development of the diagnostic module as a part of the block of an artificial intelligence of ATS, filling of the databases structured by system; start of system for obtaining the forecast. In development of the integrative automated system of pedagogical

The RNAPII-CTD Maintains Genome Integrity through Inhibition of Retrotransposon Gene Expression and Transposition.

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Maria J Aristizabal

2015-10-01

Full Text Available RNA polymerase II (RNAPII contains a unique C-terminal domain that is composed of heptapeptide repeats and which plays important regulatory roles during gene expression. RNAPII is responsible for the transcription of most protein-coding genes, a subset of non-coding genes, and retrotransposons. Retrotransposon transcription is the first step in their multiplication cycle, given that the RNA intermediate is required for the synthesis of cDNA, the material that is ultimately incorporated into a new genomic location. Retrotransposition can have grave consequences to genome integrity, as integration events can change the gene expression landscape or lead to alteration or loss of genetic information. Given that RNAPII transcribes retrotransposons, we sought to investigate if the RNAPII-CTD played a role in the regulation of retrotransposon gene expression. Importantly, we found that the RNAPII-CTD functioned to maintaining genome integrity through inhibition of retrotransposon gene expression, as reducing CTD length significantly increased expression and transposition rates of Ty1 elements. Mechanistically, the increased Ty1 mRNA levels in the rpb1-CTD11 mutant were partly due to Cdk8-dependent alterations to the RNAPII-CTD phosphorylation status. In addition, Cdk8 alone contributed to Ty1 gene expression regulation by altering the occupancy of the gene-specific transcription factor Ste12. Loss of STE12 and TEC1 suppressed growth phenotypes of the RNAPII-CTD truncation mutant. Collectively, our results implicate Ste12 and Tec1 as general and important contributors to the Cdk8, RNAPII-CTD regulatory circuitry as it relates to the maintenance of genome integrity.

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.

MicrobesOnline: an integrated portal for comparative and functional genomics

Energy Technology Data Exchange (ETDEWEB)

Dehal, Paramvir S.; Joachimiak, Marcin P.; Price, Morgan N.; Bates, John T.; Baumohl, Jason K.; Chivian, Dylan; Friedland, Greg D.; Huang, Katherine H.; Keller, Keith; Novichkov, Pavel S.; Dubchak, Inna L.; Alm, Eric J.; Arkin, Adam P.

2009-09-17

Since 2003, MicrobesOnline (http://www.microbesonline.org) has been providing a community resource for comparative and functional genome analysis. The portal includes over 1000 complete genomes of bacteria, archaea and fungi and thousands of expression microarrays from diverse organisms ranging from model organisms such as Escherichia coli and Saccharomyces cerevisiae to environmental microbes such as Desulfovibrio vulgaris and Shewanella oneidensis. To assist in annotating genes and in reconstructing their evolutionary history, MicrobesOnline includes a comparative genome browser based on phylogenetic trees for every gene family as well as a species tree. To identify co-regulated genes, MicrobesOnline can search for genes based on their expression profile, and provides tools for identifying regulatory motifs and seeing if they are conserved. MicrobesOnline also includes fast phylogenetic profile searches, comparative views of metabolic pathways, operon predictions, a workbench for sequence analysis and integration with RegTransBase and other microbial genome resources. The next update of MicrobesOnline will contain significant new functionality, including comparative analysis of metagenomic sequence data. Programmatic access to the database, along with source code and documentation, is available at http://microbesonline.org/programmers.html.

MicrobesOnline: an integrated portal for comparative and functional genomics

Energy Technology Data Exchange (ETDEWEB)

Dehal, Paramvir; Joachimiak, Marcin; Price, Morgan; Bates, John; Baumohl, Jason; Chivian, Dylan; Friedland, Greg; Huang, Kathleen; Keller, Keith; Novichkov, Pavel; Dubchak, Inna; Alm, Eric; Arkin, Adam

2011-07-14

Since 2003, MicrobesOnline (http://www.microbesonline.org) has been providing a community resource for comparative and functional genome analysis. The portal includes over 1000 complete genomes of bacteria, archaea and fungi and thousands of expression microarrays from diverse organisms ranging from model organisms such as Escherichia coli and Saccharomyces cerevisiae to environmental microbes such as Desulfovibrio vulgaris and Shewanella oneidensis. To assist in annotating genes and in reconstructing their evolutionary history, MicrobesOnline includes a comparative genome browser based on phylogenetic trees for every gene family as well as a species tree. To identify co-regulated genes, MicrobesOnline can search for genes based on their expression profile, and provides tools for identifying regulatory motifs and seeing if they are conserved. MicrobesOnline also includes fast phylogenetic profile searches, comparative views of metabolic pathways, operon predictions, a workbench for sequence analysis and integration with RegTransBase and other microbial genome resources. The next update of MicrobesOnline will contain significant new functionality, including comparative analysis of metagenomic sequence data. Programmatic access to the database, along with source code and documentation, is available at http://microbesonline.org/programmers.html.

Integrative Genomic Analysis of Cholangiocarcinoma Identifies Distinct IDH-Mutant Molecular Profiles

DEFF Research Database (Denmark)

Farshidfar, Farshad; Zheng, Siyuan; Gingras, Marie-Claude

2017-01-01

Cholangiocarcinoma (CCA) is an aggressive malignancy of the bile ducts, with poor prognosis and limited treatment options. Here, we describe the integrated analysis of somatic mutations, RNA expression, copy number, and DNA methylation by The Cancer Genome Atlas of a set of predominantly intrahep...

Enhanced biocompatibility of neural probes by integrating microstructures and delivering anti-inflammatory agents via microfluidic channels

Science.gov (United States)

Liu, Bin; Kim, Eric; Meggo, Anika; Gandhi, Sachin; Luo, Hao; Kallakuri, Srinivas; Xu, Yong; Zhang, Jinsheng

2017-04-01

Objective. Biocompatibility is a major issue for chronic neural implants, involving inflammatory and wound healing responses of neurons and glial cells. To enhance biocompatibility, we developed silicon-parylene hybrid neural probes with open architecture electrodes, microfluidic channels and a reservoir for drug delivery to suppress tissue responses. Approach. We chronically implanted our neural probes in the rat auditory cortex and investigated (1) whether open architecture electrode reduces inflammatory reaction by measuring glial responses; and (2) whether delivery of antibiotic minocycline reduces inflammatory and tissue reaction. Four weeks after implantation, immunostaining for glial fibrillary acid protein (astrocyte marker) and ionizing calcium-binding adaptor molecule 1 (macrophages/microglia cell marker) were conducted to identify immunoreactive astrocyte and microglial cells, and to determine the extent of astrocytes and microglial cell reaction/activation. A comparison was made between using traditional solid-surface electrodes and newly-designed electrodes with open architecture, as well as between deliveries of minocycline and artificial cerebral-spinal fluid diffused through microfluidic channels. Main results. The new probes with integrated micro-structures induced minimal tissue reaction compared to traditional electrodes at 4 weeks after implantation. Microcycline delivered through integrated microfluidic channels reduced tissue response as indicated by decreased microglial reaction around the neural probes implanted. Significance. The new design will help enhance the long-term stability of the implantable devices.

Neural initialization of audiovisual integration in prereaders at varying risk for developmental dyslexia.

Science.gov (United States)

I Karipidis, Iliana; Pleisch, Georgette; Röthlisberger, Martina; Hofstetter, Christoph; Dornbierer, Dario; Stämpfli, Philipp; Brem, Silvia

2017-02-01

Learning letter-speech sound correspondences is a major step in reading acquisition and is severely impaired in children with dyslexia. Up to now, it remains largely unknown how quickly neural networks adopt specific functions during audiovisual integration of linguistic information when prereading children learn letter-speech sound correspondences. Here, we simulated the process of learning letter-speech sound correspondences in 20 prereading children (6.13-7.17 years) at varying risk for dyslexia by training artificial letter-speech sound correspondences within a single experimental session. Subsequently, we acquired simultaneously event-related potentials (ERP) and functional magnetic resonance imaging (fMRI) scans during implicit audiovisual presentation of trained and untrained pairs. Audiovisual integration of trained pairs correlated with individual learning rates in right superior temporal, left inferior temporal, and bilateral parietal areas and with phonological awareness in left temporal areas. In correspondence, a differential left-lateralized parietooccipitotemporal ERP at 400 ms for trained pairs correlated with learning achievement and familial risk. Finally, a late (650 ms) posterior negativity indicating audiovisual congruency of trained pairs was associated with increased fMRI activation in the left occipital cortex. Taken together, a short (audiovisual integration in neural systems that are responsible for processing linguistic information in proficient readers. To conclude, the ability to learn grapheme-phoneme correspondences, the familial history of reading disability, and phonological awareness of prereading children account for the degree of audiovisual integration in a distributed brain network. Such findings on emerging linguistic audiovisual integration could allow for distinguishing between children with typical and atypical reading development. Hum Brain Mapp 38:1038-1055, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals

Data integration to prioritize drugs using genomics and curated data.

Science.gov (United States)

Louhimo, Riku; Laakso, Marko; Belitskin, Denis; Klefström, Juha; Lehtonen, Rainer; Hautaniemi, Sampsa

2016-01-01

Genomic alterations affecting drug target proteins occur in several tumor types and are prime candidates for patient-specific tailored treatments. Increasingly, patients likely to benefit from targeted cancer therapy are selected based on molecular alterations. The selection of a precision therapy benefiting most patients is challenging but can be enhanced with integration of multiple types of molecular data. Data integration approaches for drug prioritization have successfully integrated diverse molecular data but do not take full advantage of existing data and literature. We have built a knowledge-base which connects data from public databases with molecular results from over 2200 tumors, signaling pathways and drug-target databases. Moreover, we have developed a data mining algorithm to effectively utilize this heterogeneous knowledge-base. Our algorithm is designed to facilitate retargeting of existing drugs by stratifying samples and prioritizing drug targets. We analyzed 797 primary tumors from The Cancer Genome Atlas breast and ovarian cancer cohorts using our framework. FGFR, CDK and HER2 inhibitors were prioritized in breast and ovarian data sets. Estrogen receptor positive breast tumors showed potential sensitivity to targeted inhibitors of FGFR due to activation of FGFR3. Our results suggest that computational sample stratification selects potentially sensitive samples for targeted therapies and can aid in precision medicine drug repositioning. Source code is available from http://csblcanges.fimm.fi/GOPredict/.

Crossmodal deficit in dyslexic children: practice affects the neural timing of letter-speech sound integration

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Gojko eŽarić

2015-06-01

Full Text Available A failure to build solid letter-speech sound associations may contribute to reading impairments in developmental dyslexia. Whether this reduced neural integration of letters and speech sounds changes over time within individual children and how this relates to behavioral gains in reading skills remains unknown. In this research, we examined changes in event-related potential (ERP measures of letter-speech sound integration over a 6-month period during which 9-year-old dyslexic readers (n=17 followed a training in letter-speech sound coupling next to their regular reading curriculum. We presented the Dutch spoken vowels /a/ and /o/ as standard and deviant stimuli in one auditory and two audiovisual oddball conditions. In one audiovisual condition (AV0, the letter ‘a’ was presented simultaneously with the vowels, while in the other (AV200 it was preceding vowel onset for 200 ms. Prior to the training (T1, dyslexic readers showed the expected pattern of typical auditory mismatch responses, together with the absence of letter-speech sound effects in a late negativity (LN window. After the training (T2, our results showed earlier (and enhanced crossmodal effects in the LN window. Most interestingly, earlier LN latency at T2 was significantly related to higher behavioral accuracy in letter-speech sound coupling. On a more general level, the timing of the earlier mismatch negativity (MMN in the simultaneous condition (AV0 measured at T1, significantly related to reading fluency at both T1 and T2 as well as with reading gains. Our findings suggest that the reduced neural integration of letters and speech sounds in dyslexic children may show moderate improvement with reading instruction and training and that behavioral improvements relate especially to individual differences in the timing of this neural integration.

CMOS On-Chip Optoelectronic Neural Interface Device with Integrated Light Source for Optogenetics

International Nuclear Information System (INIS)

Sawadsaringkarn, Y; Kimura, H; Maezawa, Y; Nakajima, A; Kobayashi, T; Sasagawa, K; Noda, T; Tokuda, T; Ohta, J

2012-01-01

A novel optoelectronic neural interface device is proposed for target applications in optogenetics for neural science. The device consists of a light emitting diode (LED) array implemented on a CMOS image sensor for on-chip local light stimulation. In this study, we designed a suitable CMOS image sensor equipped with on-chip electrodes to drive the LEDs, and developed a device structure and packaging process for LED integration. The prototype device produced an illumination intensity of approximately 1 mW with a driving current of 2.0 mA, which is expected to be sufficient to activate channelrhodopsin (ChR2). We also demonstrated the functions of light stimulation and on-chip imaging using a brain slice from a mouse as a target sample.

Stress affects the neural ensemble for integrating new information and prior knowledge.

Science.gov (United States)

Vogel, Susanne; Kluen, Lisa Marieke; Fernández, Guillén; Schwabe, Lars

2018-06-01

Prior knowledge, represented as a schema, facilitates memory encoding. This schema-related learning is assumed to rely on the medial prefrontal cortex (mPFC) that rapidly integrates new information into the schema, whereas schema-incongruent or novel information is encoded by the hippocampus. Stress is a powerful modulator of prefrontal and hippocampal functioning and first studies suggest a stress-induced deficit of schema-related learning. However, the underlying neural mechanism is currently unknown. To investigate the neural basis of a stress-induced schema-related learning impairment, participants first acquired a schema. One day later, they underwent a stress induction or a control procedure before learning schema-related and novel information in the MRI scanner. In line with previous studies, learning schema-related compared to novel information activated the mPFC, angular gyrus, and precuneus. Stress, however, affected the neural ensemble activated during learning. Whereas the control group distinguished between sets of brain regions for related and novel information, stressed individuals engaged the hippocampus even when a relevant schema was present. Additionally, stressed participants displayed aberrant functional connectivity between brain regions involved in schema processing when encoding novel information. The failure to segregate functional connectivity patterns depending on the presence of prior knowledge was linked to impaired performance after stress. Our results show that stress affects the neural ensemble underlying the efficient use of schemas during learning. These findings may have relevant implications for clinical and educational settings. Copyright © 2018 Elsevier Inc. All rights reserved.

Imaging Genetics and Genomics in Psychiatry: A Critical Review of Progress and Potential.

Science.gov (United States)

Bogdan, Ryan; Salmeron, Betty Jo; Carey, Caitlin E; Agrawal, Arpana; Calhoun, Vince D; Garavan, Hugh; Hariri, Ahmad R; Heinz, Andreas; Hill, Matthew N; Holmes, Andrew; Kalin, Ned H; Goldman, David

2017-08-01

Imaging genetics and genomics research has begun to provide insight into the molecular and genetic architecture of neural phenotypes and the neural mechanisms through which genetic risk for psychopathology may emerge. As it approaches its third decade, imaging genetics is confronted by many challenges, including the proliferation of studies using small sample sizes and diverse designs, limited replication, problems with harmonization of neural phenotypes for meta-analysis, unclear mechanisms, and evidence that effect sizes may be more modest than originally posited, with increasing evidence of polygenicity. These concerns have encouraged the field to grow in many new directions, including the development of consortia and large-scale data collection projects and the use of novel methods (e.g., polygenic approaches, machine learning) that enhance the quality of imaging genetic studies but also introduce new challenges. We critically review progress in imaging genetics and offer suggestions and highlight potential pitfalls of novel approaches. Ultimately, the strength of imaging genetics and genomics lies in their translational and integrative potential with other research approaches (e.g., nonhuman animal models, psychiatric genetics, pharmacologic challenge) to elucidate brain-based pathways that give rise to the vast individual differences in behavior as well as risk for psychopathology. Copyright © 2017 Society of Biological Psychiatry. All rights reserved.

From behavior to neural dynamics: An integrated theory of attention

Science.gov (United States)

Buschman, Timothy J.; Kastner, Sabine

2015-01-01

The brain has a limited capacity and therefore needs mechanisms to selectively enhance the information most relevant to one’s current behavior. We refer to these mechanisms as ‘attention’. Attention acts by increasing the strength of selected neural representations and preferentially routing them through the brain’s large-scale network. This is a critical component of cognition and therefore has been a central topic in cognitive neuroscience. Here we review a diverse literature that has studied attention at the level of behavior, networks, circuits and neurons. We then integrate these disparate results into a unified theory of attention. PMID:26447577

Visualization of RNA structure models within the Integrative Genomics Viewer.

Science.gov (United States)

Busan, Steven; Weeks, Kevin M

2017-07-01

Analyses of the interrelationships between RNA structure and function are increasingly important components of genomic studies. The SHAPE-MaP strategy enables accurate RNA structure probing and realistic structure modeling of kilobase-length noncoding RNAs and mRNAs. Existing tools for visualizing RNA structure models are not suitable for efficient analysis of long, structurally heterogeneous RNAs. In addition, structure models are often advantageously interpreted in the context of other experimental data and gene annotation information, for which few tools currently exist. We have developed a module within the widely used and well supported open-source Integrative Genomics Viewer (IGV) that allows visualization of SHAPE and other chemical probing data, including raw reactivities, data-driven structural entropies, and data-constrained base-pair secondary structure models, in context with linear genomic data tracks. We illustrate the usefulness of visualizing RNA structure in the IGV by exploring structure models for a large viral RNA genome, comparing bacterial mRNA structure in cells with its structure under cell- and protein-free conditions, and comparing a noncoding RNA structure modeled using SHAPE data with a base-pairing model inferred through sequence covariation analysis. © 2017 Busan and Weeks; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

International regulatory landscape and integration of corrective genome editing into in vitro fertilization.

Science.gov (United States)

Araki, Motoko; Ishii, Tetsuya

2014-11-24

Genome editing technology, including zinc finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs), and clustered regularly interspaced short palindromic repeat (CRISPR)/Cas, has enabled far more efficient genetic engineering even in non-human primates. This biotechnology is more likely to develop into medicine for preventing a genetic disease if corrective genome editing is integrated into assisted reproductive technology, represented by in vitro fertilization. Although rapid advances in genome editing are expected to make germline gene correction feasible in a clinical setting, there are many issues that still need to be addressed before this could occur. We herein examine current status of genome editing in mammalian embryonic stem cells and zygotes and discuss potential issues in the international regulatory landscape regarding human germline gene modification. Moreover, we address some ethical and social issues that would be raised when each country considers whether genome editing-mediated germline gene correction for preventive medicine should be permitted.

An integrated CRISPR Bombyx mori genome editing system with improved efficiency and expanded target sites.

Science.gov (United States)

Ma, Sanyuan; Liu, Yue; Liu, Yuanyuan; Chang, Jiasong; Zhang, Tong; Wang, Xiaogang; Shi, Run; Lu, Wei; Xia, Xiaojuan; Zhao, Ping; Xia, Qingyou

2017-04-01

Genome editing enabled unprecedented new opportunities for targeted genomic engineering of a wide variety of organisms ranging from microbes, plants, animals and even human embryos. The serial establishing and rapid applications of genome editing tools significantly accelerated Bombyx mori (B. mori) research during the past years. However, the only CRISPR system in B. mori was the commonly used SpCas9, which only recognize target sites containing NGG PAM sequence. In the present study, we first improve the efficiency of our previous established SpCas9 system by 3.5 folds. The improved high efficiency was also observed at several loci in both BmNs cells and B. mori embryos. Then to expand the target sites, we showed that two newly discovered CRISPR system, SaCas9 and AsCpf1, could also induce highly efficient site-specific genome editing in BmNs cells, and constructed an integrated CRISPR system. Genome-wide analysis of targetable sites was further conducted and showed that the integrated system cover 69,144,399 sites in B. mori genome, and one site could be found in every 6.5 bp. The efficiency and resolution of this CRISPR platform will probably accelerate both fundamental researches and applicable studies in B. mori, and perhaps other insects. Copyright © 2017 Elsevier Ltd. All rights reserved.

Attention Modulates the Neural Processes Underlying Multisensory Integration of Emotion

Directory of Open Access Journals (Sweden)

Hao Tam Ho

2011-10-01

Full Text Available Integrating emotional information from multiple sensory modalities is generally assumed to be a pre-attentive process (de Gelder et al., 1999. This assumption, however, presupposes that the integrative process occurs independent of attention. Using event-potentials (ERP the present study investigated whether the neural processes underlying the integration of dynamic facial expression and emotional prosody is indeed unaffected by attentional manipulations. To this end, participants were presented with congruent and incongruent face-voice combinations (eg, an angry face combined with a neutral voice and performed different two-choice tasks in four consecutive blocks. Three of the tasks directed the participants' attention to emotion expressions in the face, the voice or both. The fourth task required participants to attend to the synchronicity between voice and lip movements. The results show divergent modulations of early ERP components by the different attentional manipulations. For example, when attention was directed to the face (or the voice, incongruent stimuli elicited a reduced N1 as compared to congruent stimuli. This effect was absent, when attention was diverted away from the emotionality in both face and voice suggesting that the detection of emotional incongruence already requires attention. Based on these findings, we question whether multisensory integration of emotion occurs indeed pre-attentively.

The Conjugative Relaxase TrwC Promotes Integration of Foreign DNA in the Human Genome.

Science.gov (United States)

González-Prieto, Coral; Gabriel, Richard; Dehio, Christoph; Schmidt, Manfred; Llosa, Matxalen

2017-06-15

Bacterial conjugation is a mechanism of horizontal DNA transfer. The relaxase TrwC of the conjugative plasmid R388 cleaves one strand of the transferred DNA at the oriT gene, covalently attaches to it, and leads the single-stranded DNA (ssDNA) into the recipient cell. In addition, TrwC catalyzes site-specific integration of the transferred DNA into its target sequence present in the genome of the recipient bacterium. Here, we report the analysis of the efficiency and specificity of the integrase activity of TrwC in human cells, using the type IV secretion system of the human pathogen Bartonella henselae to introduce relaxase-DNA complexes. Compared to Mob relaxase from plasmid pBGR1, we found that TrwC mediated a 10-fold increase in the rate of plasmid DNA transfer to human cells and a 100-fold increase in the rate of chromosomal integration of the transferred DNA. We used linear amplification-mediated PCR and plasmid rescue to characterize the integration pattern in the human genome. DNA sequence analysis revealed mostly reconstituted oriT sequences, indicating that TrwC is active and recircularizes transferred DNA in human cells. One TrwC-mediated site-specific integration event was detected, proving that TrwC is capable of mediating site-specific integration in the human genome, albeit with very low efficiency compared to the rate of random integration. Our results suggest that TrwC may stabilize the plasmid DNA molecules in the nucleus of the human cell, probably by recircularization of the transferred DNA strand. This stabilization would increase the opportunities for integration of the DNA by the host machinery. IMPORTANCE Different biotechnological applications, including gene therapy strategies, require permanent modification of target cells. Long-term expression is achieved either by extrachromosomal persistence or by integration of the introduced DNA. Here, we studied the utility of conjugative relaxase TrwC, a bacterial protein with site

Nucleotide excision repair : a multi-step mechanism required to maintain genome integrity

NARCIS (Netherlands)

Moser, Jill

2010-01-01

DNA is continuously exposed to exogenous and genotoxic insults including ionizing and ultraviolet radiation as well as chemical agents. DNA damage can compromise the integrity of the genome and have potentially deleterious effects. Ultraviolet light (UV) can induce the formation of helix distorting

Chromosomally Integrated Human Herpesvirus 6: Models of Viral Genome Release from the Telomere and Impacts on Human Health.

Science.gov (United States)

Wood, Michael L; Royle, Nicola J

2017-07-12

Human herpesvirus 6A and 6B, alongside some other herpesviruses, have the striking capacity to integrate into telomeres, the terminal repeated regions of chromosomes. The chromosomally integrated forms, ciHHV-6A and ciHHV-6B, are proposed to be a state of latency and it has been shown that they can both be inherited if integration occurs in the germ line. The first step in full viral reactivation must be the release of the integrated viral genome from the telomere and here we propose various models of this release involving transcription of the viral genome, replication fork collapse, and t-circle mediated release. In this review, we also discuss the relationship between ciHHV-6 and the telomere carrying the insertion, particularly how the presence and subsequent partial or complete release of the ciHHV-6 genome may affect telomere dynamics and the risk of disease.

Integration and long distance axonal regeneration in the central nervous system from transplanted primitive neural stem cells.

Science.gov (United States)

Zhao, Jiagang; Sun, Woong; Cho, Hyo Min; Ouyang, Hong; Li, Wenlin; Lin, Ying; Do, Jiun; Zhang, Liangfang; Ding, Sheng; Liu, Yizhi; Lu, Paul; Zhang, Kang

2013-01-04

Spinal cord injury (SCI) results in devastating motor and sensory deficits secondary to disrupted neuronal circuits and poor regenerative potential. Efforts to promote regeneration through cell extrinsic and intrinsic manipulations have met with limited success. Stem cells represent an as yet unrealized therapy in SCI. Recently, we identified novel culture methods to induce and maintain primitive neural stem cells (pNSCs) from human embryonic stem cells. We tested whether transplanted human pNSCs can integrate into the CNS of the developing chick neural tube and injured adult rat spinal cord. Following injection of pNSCs into the developing chick CNS, pNSCs integrated into the dorsal aspects of the neural tube, forming cell clusters that spontaneously differentiated into neurons. Furthermore, following transplantation of pNSCs into the lesioned rat spinal cord, grafted pNSCs survived, differentiated into neurons, and extended long distance axons through the scar tissue at the graft-host interface and into the host spinal cord to form terminal-like structures near host spinal neurons. Together, these findings suggest that pNSCs derived from human embryonic stem cells differentiate into neuronal cell types with the potential to extend axons that associate with circuits of the CNS and, more importantly, provide new insights into CNS integration and axonal regeneration, offering hope for repair in SCI.

GenomeCAT: a versatile tool for the analysis and integrative visualization of DNA copy number variants.

Science.gov (United States)

Tebel, Katrin; Boldt, Vivien; Steininger, Anne; Port, Matthias; Ebert, Grit; Ullmann, Reinhard

2017-01-06

The analysis of DNA copy number variants (CNV) has increasing impact in the field of genetic diagnostics and research. However, the interpretation of CNV data derived from high resolution array CGH or NGS platforms is complicated by the considerable variability of the human genome. Therefore, tools for multidimensional data analysis and comparison of patient cohorts are needed to assist in the discrimination of clinically relevant CNVs from others. We developed GenomeCAT, a standalone Java application for the analysis and integrative visualization of CNVs. GenomeCAT is composed of three modules dedicated to the inspection of single cases, comparative analysis of multidimensional data and group comparisons aiming at the identification of recurrent aberrations in patients sharing the same phenotype, respectively. Its flexible import options ease the comparative analysis of own results derived from microarray or NGS platforms with data from literature or public depositories. Multidimensional data obtained from different experiment types can be merged into a common data matrix to enable common visualization and analysis. All results are stored in the integrated MySQL database, but can also be exported as tab delimited files for further statistical calculations in external programs. GenomeCAT offers a broad spectrum of visualization and analysis tools that assist in the evaluation of CNVs in the context of other experiment data and annotations. The use of GenomeCAT does not require any specialized computer skills. The various R packages implemented for data analysis are fully integrated into GenomeCATs graphical user interface and the installation process is supported by a wizard. The flexibility in terms of data import and export in combination with the ability to create a common data matrix makes the program also well suited as an interface between genomic data from heterogeneous sources and external software tools. Due to the modular architecture the functionality of

Neural Basis of Limb Ownership in Individuals with Body Integrity Identity Disorder

OpenAIRE

van Dijk, Milenna T.; van Wingen, Guido A.; van Lammeren, Anouk; Blom, Rianne M.; de Kwaasteniet, Bart P.; Scholte, H. Steven; Denys, Damiaan

2013-01-01

Our body feels like it is ours. However, individuals with body integrity identity disorder (BIID) lack this feeling of ownership for distinct limbs and desire amputation of perfectly healthy body parts. This extremely rare condition provides us with an opportunity to study the neural basis underlying the feeling of limb ownership, since these individuals have a feeling of disownership for a limb in the absence of apparent brain damage. Here we directly compared brain activation between limbs ...

The 128-channel fully differential digital integrated neural recording and stimulation interface.

Science.gov (United States)

Shahrokhi, Farzaneh; Abdelhalim, Karim; Serletis, Demitre; Carlen, Peter L; Genov, Roman

2010-06-01

We present a fully differential 128-channel integrated neural interface. It consists of an array of 8 X 16 low-power low-noise signal-recording and generation circuits for electrical neural activity monitoring and stimulation, respectively. The recording channel has two stages of signal amplification and conditioning with and a fully differential 8-b column-parallel successive approximation (SAR) analog-to-digital converter (ADC). The total measured power consumption of each recording channel, including the SAR ADC, is 15.5 ¿W. The measured input-referred noise is 6.08 ¿ Vrms over a 5-kHz bandwidth, resulting in a noise efficiency factor of 5.6. The stimulation channel performs monophasic or biphasic voltage-mode stimulation, with a maximum stimulation current of 5 mA and a quiescent power dissipation of 51.5 ¿W. The design is implemented in 0.35-¿m complementary metal-oxide semiconductor technology with the channel pitch of 200 ¿m for a total die size of 3.4 mm × 2.5 mm and a total power consumption of 9.33 mW. The neural interface was validated in in vitro recording of a low-Mg(2+)/high-K(+) epileptic seizure model in an intact hippocampus of a mouse.

The CanOE strategy: integrating genomic and metabolic contexts across multiple prokaryote genomes to find candidate genes for orphan enzymes.

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Adam Alexander Thil Smith

2012-05-01

Full Text Available Of all biochemically characterized metabolic reactions formalized by the IUBMB, over one out of four have yet to be associated with a nucleic or protein sequence, i.e. are sequence-orphan enzymatic activities. Few bioinformatics annotation tools are able to propose candidate genes for such activities by exploiting context-dependent rather than sequence-dependent data, and none are readily accessible and propose result integration across multiple genomes. Here, we present CanOE (Candidate genes for Orphan Enzymes, a four-step bioinformatics strategy that proposes ranked candidate genes for sequence-orphan enzymatic activities (or orphan enzymes for short. The first step locates "genomic metabolons", i.e. groups of co-localized genes coding proteins catalyzing reactions linked by shared metabolites, in one genome at a time. These metabolons can be particularly helpful for aiding bioanalysts to visualize relevant metabolic data. In the second step, they are used to generate candidate associations between un-annotated genes and gene-less reactions. The third step integrates these gene-reaction associations over several genomes using gene families, and summarizes the strength of family-reaction associations by several scores. In the final step, these scores are used to rank members of gene families which are proposed for metabolic reactions. These associations are of particular interest when the metabolic reaction is a sequence-orphan enzymatic activity. Our strategy found over 60,000 genomic metabolons in more than 1,000 prokaryote organisms from the MicroScope platform, generating candidate genes for many metabolic reactions, of which more than 70 distinct orphan reactions. A computational validation of the approach is discussed. Finally, we present a case study on the anaerobic allantoin degradation pathway in Escherichia coli K-12.

RGmatch: matching genomic regions to proximal genes in omics data integration

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Pedro Furió-Tarí

2016-11-01

Full Text Available Abstract Background The integrative analysis of multiple genomics data often requires that genome coordinates-based signals have to be associated with proximal genes. The relative location of a genomic region with respect to the gene (gene area is important for functional data interpretation; hence algorithms that match regions to genes should be able to deliver insight into this information. Results In this work we review the tools that are publicly available for making region-to-gene associations. We also present a novel method, RGmatch, a flexible and easy-to-use Python tool that computes associations either at the gene, transcript, or exon level, applying a set of rules to annotate each region-gene association with the region location within the gene. RGmatch can be applied to any organism as long as genome annotation is available. Furthermore, we qualitatively and quantitatively compare RGmatch to other tools. Conclusions RGmatch simplifies the association of a genomic region with its closest gene. At the same time, it is a powerful tool because the rules used to annotate these associations are very easy to modify according to the researcher’s specific interests. Some important differences between RGmatch and other similar tools already in existence are RGmatch’s flexibility, its wide range of user options, compatibility with any annotatable organism, and its comprehensive and user-friendly output.

Ensembl Genomes 2016: more genomes, more complexity.

Science.gov (United States)

Kersey, Paul Julian; Allen, James E; Armean, Irina; Boddu, Sanjay; Bolt, Bruce J; Carvalho-Silva, Denise; Christensen, Mikkel; Davis, Paul; Falin, Lee J; Grabmueller, Christoph; Humphrey, Jay; Kerhornou, Arnaud; Khobova, Julia; Aranganathan, Naveen K; Langridge, Nicholas; Lowy, Ernesto; McDowall, Mark D; Maheswari, Uma; Nuhn, Michael; Ong, Chuang Kee; Overduin, Bert; Paulini, Michael; Pedro, Helder; Perry, Emily; Spudich, Giulietta; Tapanari, Electra; Walts, Brandon; Williams, Gareth; Tello-Ruiz, Marcela; Stein, Joshua; Wei, Sharon; Ware, Doreen; Bolser, Daniel M; Howe, Kevin L; Kulesha, Eugene; Lawson, Daniel; Maslen, Gareth; Staines, Daniel M

2016-01-04

Ensembl Genomes (http://www.ensemblgenomes.org) is an integrating resource for genome-scale data from non-vertebrate species, complementing the resources for vertebrate genomics developed in the context of the Ensembl project (http://www.ensembl.org). Together, the two resources provide a consistent set of programmatic and interactive interfaces to a rich range of data including reference sequence, gene models, transcriptional data, genetic variation and comparative analysis. This paper provides an update to the previous publications about the resource, with a focus on recent developments. These include the development of new analyses and views to represent polyploid genomes (of which bread wheat is the primary exemplar); and the continued up-scaling of the resource, which now includes over 23 000 bacterial genomes, 400 fungal genomes and 100 protist genomes, in addition to 55 genomes from invertebrate metazoa and 39 genomes from plants. This dramatic increase in the number of included genomes is one part of a broader effort to automate the integration of archival data (genome sequence, but also associated RNA sequence data and variant calls) within the context of reference genomes and make it available through the Ensembl user interfaces. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

In vitro analysis of integrated global high-resolution DNA methylation profiling with genomic imbalance and gene expression in osteosarcoma.

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Bekim Sadikovic

Full Text Available Genetic and epigenetic changes contribute to deregulation of gene expression and development of human cancer. Changes in DNA methylation are key epigenetic factors regulating gene expression and genomic stability. Recent progress in microarray technologies resulted in developments of high resolution platforms for profiling of genetic, epigenetic and gene expression changes. OS is a pediatric bone tumor with characteristically high level of numerical and structural chromosomal changes. Furthermore, little is known about DNA methylation changes in OS. Our objective was to develop an integrative approach for analysis of high-resolution epigenomic, genomic, and gene expression profiles in order to identify functional epi/genomic differences between OS cell lines and normal human osteoblasts. A combination of Affymetrix Promoter Tilling Arrays for DNA methylation, Agilent array-CGH platform for genomic imbalance and Affymetrix Gene 1.0 platform for gene expression analysis was used. As a result, an integrative high-resolution approach for interrogation of genome-wide tumour-specific changes in DNA methylation was developed. This approach was used to provide the first genomic DNA methylation maps, and to identify and validate genes with aberrant DNA methylation in OS cell lines. This first integrative analysis of global cancer-related changes in DNA methylation, genomic imbalance, and gene expression has provided comprehensive evidence of the cumulative roles of epigenetic and genetic mechanisms in deregulation of gene expression networks.

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.

EasyCloneMulti: A Set of Vectors for Simultaneous and Multiple Genomic Integrations in Saccharomyces cerevisiae

DEFF Research Database (Denmark)

Maury, Jerome; Germann, Susanne Manuela; Jacobsen, Simo Abdessamad

2016-01-01

Saccharomyces cerevisiae is widely used in the biotechnology industry for production of ethanol, recombinant proteins, food ingredients and other chemicals. In order to generate highly producing and stable strains, genome integration of genes encoding metabolic pathway enzymes is the preferred...... of integrative vectors, EasyCloneMulti, that enables multiple and simultaneous integration of genes in S. cerevisiae. By creating vector backbones that combine consensus sequences that aim at targeting subsets of Ty sequences and a quickly degrading selective marker, integrations at multiple genomic loci...... and a range of expression levels were obtained, as assessed with the green fluorescent protein (GFP) reporter system. The EasyCloneMulti vector set was applied to balance the expression of the rate-controlling step in the β-alanine pathway for biosynthesis of 3-hydroxypropionic acid (3HP). The best 3HP...

Integrative Functional Genomics for Systems Genetics in GeneWeaver.org.

Science.gov (United States)

Bubier, Jason A; Langston, Michael A; Baker, Erich J; Chesler, Elissa J

2017-01-01

The abundance of existing functional genomics studies permits an integrative approach to interpreting and resolving the results of diverse systems genetics studies. However, a major challenge lies in assembling and harmonizing heterogeneous data sets across species for facile comparison to the positional candidate genes and coexpression networks that come from systems genetic studies. GeneWeaver is an online database and suite of tools at www.geneweaver.org that allows for fast aggregation and analysis of gene set-centric data. GeneWeaver contains curated experimental data together with resource-level data such as GO annotations, MP annotations, and KEGG pathways, along with persistent stores of user entered data sets. These can be entered directly into GeneWeaver or transferred from widely used resources such as GeneNetwork.org. Data are analyzed using statistical tools and advanced graph algorithms to discover new relations, prioritize candidate genes, and generate function hypotheses. Here we use GeneWeaver to find genes common to multiple gene sets, prioritize candidate genes from a quantitative trait locus, and characterize a set of differentially expressed genes. Coupling a large multispecies repository curated and empirical functional genomics data to fast computational tools allows for the rapid integrative analysis of heterogeneous data for interpreting and extrapolating systems genetics results.

In Vivo Transplantation of Enteric Neural Crest Cells into Mouse Gut; Engraftment, Functional Integration and Long-Term Safety.

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Julie E Cooper

Full Text Available Enteric neuropathies are severe gastrointestinal disorders with unsatisfactory outcomes. We aimed to investigate the potential of enteric neural stem cell therapy approaches for such disorders by transplanting mouse enteric neural crest cells (ENCCs into ganglionic and aganglionic mouse gut in vivo and analysing functional integration and long-term safety.Neurospheres generated from yellow fluorescent protein (YFP expressing ENCCs selected from postnatal Wnt1-cre;R26R-YFP/YFP murine gut were transplanted into ganglionic hindgut of wild-type littermates or aganglionic hindgut of Ednrbtm1Ywa mice (lacking functional endothelin receptor type-B. Intestines were then assessed for ENCC integration and differentiation using immunohistochemistry, cell function using calcium imaging, and long-term safety using PCR to detect off-target YFP expression.YFP+ ENCCs engrafted, proliferated and differentiated into enteric neurons and glia within recipient ganglionic gut. Transplanted cells and their projections spread along the endogenous myenteric plexus to form branching networks. Electrical point stimulation of endogenous nerve fibres resulted in calcium transients (F/F0 = 1.16 ± 0.01;43 cells, n = 6 in YFP+ transplanted ENCCs (abolished with TTX. Long-term follow-up (24 months showed transplanted ENCCs did not give rise to tumours or spread to other organs (PCR negative in extraintestinal sites. In aganglionic gut ENCCs similarly spread and differentiated to form neuronal and glial networks with projections closely associated with endogenous neural networks of the transition zone.Transplanted ENCCs successfully engrafted into recipient ganglionic and aganglionic gut showing appropriate spread, localisation and, importantly, functional integration without any long-term safety issues. This study provides key support for the development and use of enteric neural stem cell therapies.

A DNMT3A2-HDAC2 Complex Is Essential for Genomic Imprinting and Genome Integrity in Mouse Oocytes

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Pengpeng Ma

2015-11-01

Full Text Available Maternal genomic imprints are established during oogenesis. Histone deacetylases (HDACs 1 and 2 are required for oocyte development in mouse, but their role in genomic imprinting is unknown. We find that Hdac1:Hdac2−/− double-mutant growing oocytes exhibit global DNA hypomethylation and fail to establish imprinting marks for Igf2r, Peg3, and Srnpn. Global hypomethylation correlates with increased retrotransposon expression and double-strand DNA breaks. Nuclear-associated DNMT3A2 is reduced in double-mutant oocytes, and injecting these oocytes with Hdac2 partially restores DNMT3A2 nuclear staining. DNMT3A2 co-immunoprecipitates with HDAC2 in mouse embryonic stem cells. Partial loss of nuclear DNMT3A2 and HDAC2 occurs in Sin3a−/− oocytes, which exhibit decreased DNA methylation of imprinting control regions for Igf2r and Srnpn, but not Peg3. These results suggest seminal roles of HDAC1/2 in establishing maternal genomic imprints and maintaining genomic integrity in oocytes mediated in part through a SIN3A complex that interacts with DNMT3A2.

Neural Integration of Information Specifying Human Structure from Form, Motion, and Depth

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Jackson, Stuart; Blake, Randolph

2010-01-01

Recent computational models of biological motion perception operate on ambiguous two-dimensional representations of the body (e.g., snapshots, posture templates) and contain no explicit means for disambiguating the three-dimensional orientation of a perceived human figure. Are there neural mechanisms in the visual system that represent a moving human figure’s orientation in three dimensions? To isolate and characterize the neural mechanisms mediating perception of biological motion, we used an adaptation paradigm together with bistable point-light (PL) animations whose perceived direction of heading fluctuates over time. After exposure to a PL walker with a particular stereoscopically defined heading direction, observers experienced a consistent aftereffect: a bistable PL walker, which could be perceived in the adapted orientation or reversed in depth, was perceived predominantly reversed in depth. A phase-scrambled adaptor produced no aftereffect, yet when adapting and test walkers differed in size or appeared on opposite sides of fixation aftereffects did occur. Thus, this heading direction aftereffect cannot be explained by local, disparity-specific motion adaptation, and the properties of scale and position invariance imply higher-level origins of neural adaptation. Nor is disparity essential for producing adaptation: when suspended on top of a stereoscopically defined, rotating globe, a context-disambiguated “globetrotter” was sufficient to bias the bistable walker’s direction, as were full-body adaptors. In sum, these results imply that the neural signals supporting biomotion perception integrate information on the form, motion, and three-dimensional depth orientation of the moving human figure. Models of biomotion perception should incorporate mechanisms to disambiguate depth ambiguities in two-dimensional body representations. PMID:20089892

MIPS Arabidopsis thaliana Database (MAtDB): an integrated biological knowledge resource based on the first complete plant genome

Science.gov (United States)

Schoof, Heiko; Zaccaria, Paolo; Gundlach, Heidrun; Lemcke, Kai; Rudd, Stephen; Kolesov, Grigory; Arnold, Roland; Mewes, H. W.; Mayer, Klaus F. X.

2002-01-01

Arabidopsis thaliana is the first plant for which the complete genome has been sequenced and published. Annotation of complex eukaryotic genomes requires more than the assignment of genetic elements to the sequence. Besides completing the list of genes, we need to discover their cellular roles, their regulation and their interactions in order to understand the workings of the whole plant. The MIPS Arabidopsis thaliana Database (MAtDB; http://mips.gsf.de/proj/thal/db) started out as a repository for genome sequence data in the European Scientists Sequencing Arabidopsis (ESSA) project and the Arabidopsis Genome Initiative. Our aim is to transform MAtDB into an integrated biological knowledge resource by integrating diverse data, tools, query and visualization capabilities and by creating a comprehensive resource for Arabidopsis as a reference model for other species, including crop plants. PMID:11752263

A genome-wide analysis of lentivector integration sites using targeted sequence capture and next generation sequencing technology.

Science.gov (United States)

Ustek, Duran; Sirma, Sema; Gumus, Ergun; Arikan, Muzaffer; Cakiris, Aris; Abaci, Neslihan; Mathew, Jaicy; Emrence, Zeliha; Azakli, Hulya; Cosan, Fulya; Cakar, Atilla; Parlak, Mahmut; Kursun, Olcay

2012-10-01

One application of next-generation sequencing (NGS) is the targeted resequencing of interested genes which has not been used in viral integration site analysis of gene therapy applications. Here, we combined targeted sequence capture array and next generation sequencing to address the whole genome profiling of viral integration sites. Human 293T and K562 cells were transduced with a HIV-1 derived vector. A custom made DNA probe sets targeted pLVTHM vector used to capture lentiviral vector/human genome junctions. The captured DNA was sequenced using GS FLX platform. Seven thousand four hundred and eighty four human genome sequences flanking the long terminal repeats (LTR) of pLVTHM fragment sequences matched with an identity of at least 98% and minimum 50 bp criteria in both cells. In total, 203 unique integration sites were identified. The integrations in both cell lines were totally distant from the CpG islands and from the transcription start sites and preferentially located in introns. A comparison between the two cell lines showed that the lentiviral-transduced DNA does not have the same preferred regions in the two different cell lines. Copyright © 2012 Elsevier B.V. All rights reserved.

BiGG Models: A platform for integrating, standardizing and sharing genome-scale models

DEFF Research Database (Denmark)

King, Zachary A.; Lu, Justin; Dräger, Andreas

2016-01-01

Genome-scale metabolic models are mathematically-structured knowledge bases that can be used to predict metabolic pathway usage and growth phenotypes. Furthermore, they can generate and test hypotheses when integrated with experimental data. To maximize the value of these models, centralized repo...

IMGMD: A platform for the integration and standardisation of In silico Microbial Genome-scale Metabolic Models.

Science.gov (United States)

Ye, Chao; Xu, Nan; Dong, Chuan; Ye, Yuannong; Zou, Xuan; Chen, Xiulai; Guo, Fengbiao; Liu, Liming

2017-04-07

Genome-scale metabolic models (GSMMs) constitute a platform that combines genome sequences and detailed biochemical information to quantify microbial physiology at the system level. To improve the unity, integrity, correctness, and format of data in published GSMMs, a consensus IMGMD database was built in the LAMP (Linux + Apache + MySQL + PHP) system by integrating and standardizing 328 GSMMs constructed for 139 microorganisms. The IMGMD database can help microbial researchers download manually curated GSMMs, rapidly reconstruct standard GSMMs, design pathways, and identify metabolic targets for strategies on strain improvement. Moreover, the IMGMD database facilitates the integration of wet-lab and in silico data to gain an additional insight into microbial physiology. The IMGMD database is freely available, without any registration requirements, at http://imgmd.jiangnan.edu.cn/database.

Drosophila Sld5 is essential for normal cell cycle progression and maintenance of genomic integrity

Energy Technology Data Exchange (ETDEWEB)

Gouge, Catherine A. [Department of Biology, East Carolina University East Carolina University, Greenville, NC 27858 (United States); Christensen, Tim W., E-mail: christensent@ecu.edu [Department of Biology, East Carolina University East Carolina University, Greenville, NC 27858 (United States)

2010-09-10

Research highlights: {yields} Drosophila Sld5 interacts with Psf1, PPsf2, and Mcm10. {yields} Haploinsufficiency of Sld5 leads to M-phase delay and genomic instability. {yields} Sld5 is also required for normal S phase progression. -- Abstract: Essential for the normal functioning of a cell is the maintenance of genomic integrity. Failure in this process is often catastrophic for the organism, leading to cell death or mis-proliferation. Central to genomic integrity is the faithful replication of DNA during S phase. The GINS complex has recently come to light as a critical player in DNA replication through stabilization of MCM2-7 and Cdc45 as a member of the CMG complex which is likely responsible for the processivity of helicase activity during S phase. The GINS complex is made up of 4 members in a 1:1:1:1 ratio: Psf1, Psf2, Psf3, And Sld5. Here we present the first analysis of the function of the Sld5 subunit in a multicellular organism. We show that Drosophila Sld5 interacts with Psf1, Psf2, and Mcm10 and that mutations in Sld5 lead to M and S phase delays with chromosomes exhibiting hallmarks of genomic instability.

A Neural Systems-Based Neurobiology and Neuropsychiatry Course: Integrating Biology, Psychodynamics, and Psychology in the Psychiatric Curriculum

Science.gov (United States)

Lacy, Timothy; Hughes, John D.

2006-01-01

Objective: Psychotherapy and biological psychiatry remain divided in psychiatry residency curricula. Behavioral neurobiology and neuropsychiatry provide a systems-level framework that allows teachers to integrate biology, psychodynamics, and psychology. Method: The authors detail the underlying assumptions and outline of a neural systems-based…

IVAG: An Integrative Visualization Application for Various Types of Genomic Data Based on R-Shiny and the Docker Platform.

Science.gov (United States)

Lee, Tae-Rim; Ahn, Jin Mo; Kim, Gyuhee; Kim, Sangsoo

2017-12-01

Next-generation sequencing (NGS) technology has become a trend in the genomics research area. There are many software programs and automated pipelines to analyze NGS data, which can ease the pain for traditional scientists who are not familiar with computer programming. However, downstream analyses, such as finding differentially expressed genes or visualizing linkage disequilibrium maps and genome-wide association study (GWAS) data, still remain a challenge. Here, we introduce a dockerized web application written in R using the Shiny platform to visualize pre-analyzed RNA sequencing and GWAS data. In addition, we have integrated a genome browser based on the JBrowse platform and an automated intermediate parsing process required for custom track construction, so that users can easily build and navigate their personal genome tracks with in-house datasets. This application will help scientists perform series of downstream analyses and obtain a more integrative understanding about various types of genomic data by interactively visualizing them with customizable options.

The European Renal Genome Project: An Integrated Approach Towards Understanding the Genetics of Kidney Development and Disease

OpenAIRE

Willnow, TE; Antignac, C; Brändli, AW; Christensen, EI; Cox, RD; Davidson, D; Davies, JA; Devuyst, O; Eichele, G; Hastie, ND; Verroust, PJ; Schedl, A; Meij, IC

2005-01-01

Rapid progress in genome research creates a wealth of information on the functional annotation of mammalian genome sequences. However, as we accumulate large amounts of scientific information we are facing problems of how to integrate and relate the data produced by various genomic approaches. Here, we propose the novel concept of an organ atlas where diverse data from expression maps to histological findings to mutant phenotypes can be queried, compared and visualized in the context of a thr...

The first neural probe integrated with light source (blue laser diode) for optical stimulation and electrical recording.

Science.gov (United States)

Park, HyungDal; Shin, Hyun-Joon; Cho, Il-Joo; Yoon, Eui-sung; Suh, Jun-Kyo Francis; Im, Maesoon; Yoon, Euisik; Kim, Yong-Jun; Kim, Jinseok

2011-01-01

In this paper, we report a neural probe which can selectively stimulate target neurons optically through Si wet etched mirror surface and record extracellular neural signals in iridium oxide tetrodes. Consequently, the proposed approach provides to improve directional problem and achieve at least 150/m gap distance between stimulation and recording sites by wet etched mirror surface in V-groove. Also, we developed light source, blue laser diode (OSRAM Blue Laser Diode_PL 450), integration through simple jig for one-touch butt-coupling. Furthermore, optical power and impedance of iridium oxide tetrodes were measured as 200 μW on 5 mW from LD and 206.5 k Ω at 1 kHz and we demonstrated insertion test of probe in 0.5% agarose-gel successfully. We have successfully transmitted a light of 450 nm to optical fiber through the integrated LD using by butt-coupling method.

Application of neural network to CT

International Nuclear Information System (INIS)

Ma, Xiao-Feng; Takeda, Tatsuoki

1999-01-01

This paper presents a new method for two-dimensional image reconstruction by using a multilayer neural network. Multilayer neural networks are extensively investigated and practically applied to solution of various problems such as inverse problems or time series prediction problems. From learning an input-output mapping from a set of examples, neural networks can be regarded as synthesizing an approximation of multidimensional function (that is, solving the problem of hypersurface reconstruction, including smoothing and interpolation). From this viewpoint, neural networks are well suited to the solution of CT image reconstruction. Though a conventionally used object function of a neural network is composed of a sum of squared errors of the output data, we can define an object function composed of a sum of residue of an integral equation. By employing an appropriate line integral for this integral equation, we can construct a neural network that can be used for CT. We applied this method to some model problems and obtained satisfactory results. As it is not necessary to discretized the integral equation using this reconstruction method, therefore it is application to the problem of complicated geometrical shapes is also feasible. Moreover, in neural networks, interpolation is performed quite smoothly, as a result, inverse mapping can be achieved smoothly even in case of including experimental and numerical errors, However, use of conventional back propagation technique for optimization leads to an expensive computation cost. To overcome this drawback, 2nd order optimization methods or parallel computing will be applied in future. (J.P.N.)

RegPredict: an integrated system for regulon inference in prokaryotes by comparative genomics approach

Energy Technology Data Exchange (ETDEWEB)

Novichkov, Pavel S.; Rodionov, Dmitry A.; Stavrovskaya, Elena D.; Novichkova, Elena S.; Kazakov, Alexey E.; Gelfand, Mikhail S.; Arkin, Adam P.; Mironov, Andrey A.; Dubchak, Inna

2010-05-26

RegPredict web server is designed to provide comparative genomics tools for reconstruction and analysis of microbial regulons using comparative genomics approach. The server allows the user to rapidly generate reference sets of regulons and regulatory motif profiles in a group of prokaryotic genomes. The new concept of a cluster of co-regulated orthologous operons allows the user to distribute the analysis of large regulons and to perform the comparative analysis of multiple clusters independently. Two major workflows currently implemented in RegPredict are: (i) regulon reconstruction for a known regulatory motif and (ii) ab initio inference of a novel regulon using several scenarios for the generation of starting gene sets. RegPredict provides a comprehensive collection of manually curated positional weight matrices of regulatory motifs. It is based on genomic sequences, ortholog and operon predictions from the MicrobesOnline. An interactive web interface of RegPredict integrates and presents diverse genomic and functional information about the candidate regulon members from several web resources. RegPredict is freely accessible at http://regpredict.lbl.gov.

Neural network integration during the perception of in-group and out-group members.

Science.gov (United States)

Greven, Inez M; Ramsey, Richard

2017-11-01

Group biases guide social interactions by promoting in-group favouritism, but the neural mechanisms underpinning group biases remain unclear. While neuroscience research has shown that distributed brain circuits are associated with seeing in-group and out-group members as "us" and "them", it is less clear how these networks exchange signals. This fMRI study uses functional connectivity analyses to investigate the contribution of functional integration to group bias modulation of person perception. Participants were assigned to an arbitrary group and during scanning they observed bodies of in-group or out-group members that cued the recall of positive or negative social knowledge. The results showed that functional coupling between perceptual and cognitive neural networks is tuned to particular combinations of group membership and social knowledge valence. Specifically, coupling between body perception and theory-of-mind networks is biased towards seeing a person that had previously been paired with information consistent with group bias (positive for in-group and negative for out-group). This demonstrates how brain regions associated with visual analysis of others and belief reasoning exchange and integrate signals when evaluating in-group and out-group members. The results update models of person perception by showing how and when interplay occurs between perceptual and extended systems when developing a representation of another person. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

CTDB: An Integrated Chickpea Transcriptome Database for Functional and Applied Genomics

OpenAIRE

Verma, Mohit; Kumar, Vinay; Patel, Ravi K.; Garg, Rohini; Jain, Mukesh

2015-01-01

Chickpea is an important grain legume used as a rich source of protein in human diet. The narrow genetic diversity and limited availability of genomic resources are the major constraints in implementing breeding strategies and biotechnological interventions for genetic enhancement of chickpea. We developed an integrated Chickpea Transcriptome Database (CTDB), which provides the comprehensive web interface for visualization and easy retrieval of transcriptome data in chickpea. The database fea...

Quantitative and qualitative proteome characteristics extracted from in-depth integrated genomics and proteomics analysis

NARCIS (Netherlands)

Low, T.Y.; van Heesch, S.; van den Toorn, H.; Giansanti, P.; Cristobal, A.; Toonen, P.; Schafer, S.; Hubner, N.; van Breukelen, B.; Mohammed, S.; Cuppen, E.; Heck, A.J.R.; Guryev, V.

2013-01-01

Quantitative and qualitative protein characteristics are regulated at genomic, transcriptomic, and posttranscriptional levels. Here, we integrated in-depth transcriptome and proteome analyses of liver tissues from two rat strains to unravel the interactions within and between these layers. We

The neural crest migrating into the 21st century

Science.gov (United States)

Bronner, Marianne E.; Simões-Costa, Marcos

2016-01-01

From the initial discovery of the neural crest over 150 years ago to the seminal studies of Le Douarin and colleagues in the latter part of the 20th century, understanding of the neural crest has moved from the descriptive to the experimental. Now, in the 21st century, neural crest research has migrated into the genomic age. Here we reflect upon the major advances in neural crest biology and the open questions that will continue to make research on this incredible vertebrate cell type an important subject in developmental biology for the century to come. PMID:26970616

Integrative genome analyses identify key somatic driver mutations of small-cell lung cancer

NARCIS (Netherlands)

Peifer, Martin; Fernandez-Cuesta, Lynnette; Sos, Martin L.; George, Julie; Seidel, Danila; Kasper, Lawryn H.; Plenker, Dennis; Leenders, Frauke; Sun, Ruping; Zander, Thomas; Menon, Roopika; Koker, Mirjam; Dahmen, Ilona; Mueller, Christian; Di Cerbo, Vincenzo; Schildhaus, Hans-Ulrich; Altmueller, Janine; Baessmann, Ingelore; Becker, Christian; de Wilde, Bram; Vandesompele, Jo; Boehm, Diana; Ansen, Sascha; Gabler, Franziska; Wilkening, Ines; Heynck, Stefanie; Heuckmann, Johannes M.; Lu, Xin; Carter, Scott L.; Cibulskis, Kristian; Banerji, Shantanu; Getz, Gad; Park, Kwon-Sik; Rauh, Daniel; Gruetter, Christian; Fischer, Matthias; Pasqualucci, Laura; Wright, Gavin; Wainer, Zoe; Russell, Prudence; Petersen, Iver; Chen, Yuan; Stoelben, Erich; Ludwig, Corinna; Schnabel, Philipp; Hoffmann, Hans; Muley, Thomas; Brockmann, Michael; Engel-Riedel, Walburga; Muscarella, Lucia A.; Fazio, Vito M.; Groen, Harry; Timens, Wim; Sietsma, Hannie; Thunnissen, Erik; Smit, Egbert; Heideman, Danielle A. M.; Snijders, Peter J. F.; Cappuzzo, Federico; Ligorio, Claudia; Damiani, Stefania; Field, John; Solberg, Steinar; Brustugun, Odd Terje; Lund-Iversen, Marius; Saenger, Joerg; Clement, Joachim H.; Soltermann, Alex; Moch, Holger; Weder, Walter; Solomon, Benjamin; Soria, Jean-Charles; Validire, Pierre; Besse, Benjamin; Brambilla, Elisabeth; Brambilla, Christian; Lantuejoul, Sylvie; Lorimier, Philippe; Schneider, Peter M.; Hallek, Michael; Pao, William; Meyerson, Matthew; Sage, Julien; Shendure, Jay; Schneider, Robert; Buettner, Reinhard; Wolf, Juergen; Nuernberg, Peter; Perner, Sven; Heukamp, Lukas C.; Brindle, Paul K.; Haas, Stefan; Thomas, Roman K.

2012-01-01

Small-cell lung cancer (SCLC) is an aggressive lung tumor subtype with poor prognosis(1-3). We sequenced 29 SCLC exomes, 2 genomes and 15 transcriptomes and found an extremely high mutation rate of 7.4 +/- 1 protein-changing mutations per million base pairs. Therefore, we conducted integrated

Construction of an ortholog database using the semantic web technology for integrative analysis of genomic data.

Science.gov (United States)

Chiba, Hirokazu; Nishide, Hiroyo; Uchiyama, Ikuo

2015-01-01

Recently, various types of biological data, including genomic sequences, have been rapidly accumulating. To discover biological knowledge from such growing heterogeneous data, a flexible framework for data integration is necessary. Ortholog information is a central resource for interlinking corresponding genes among different organisms, and the Semantic Web provides a key technology for the flexible integration of heterogeneous data. We have constructed an ortholog database using the Semantic Web technology, aiming at the integration of numerous genomic data and various types of biological information. To formalize the structure of the ortholog information in the Semantic Web, we have constructed the Ortholog Ontology (OrthO). While the OrthO is a compact ontology for general use, it is designed to be extended to the description of database-specific concepts. On the basis of OrthO, we described the ortholog information from our Microbial Genome Database for Comparative Analysis (MBGD) in the form of Resource Description Framework (RDF) and made it available through the SPARQL endpoint, which accepts arbitrary queries specified by users. In this framework based on the OrthO, the biological data of different organisms can be integrated using the ortholog information as a hub. Besides, the ortholog information from different data sources can be compared with each other using the OrthO as a shared ontology. Here we show some examples demonstrating that the ortholog information described in RDF can be used to link various biological data such as taxonomy information and Gene Ontology. Thus, the ortholog database using the Semantic Web technology can contribute to biological knowledge discovery through integrative data analysis.

Induced Neural Stem Cells Achieve Long-Term Survival and Functional Integration in the Adult Mouse Brain

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Kathrin Hemmer

2014-09-01

Full Text Available Differentiated cells can be converted directly into multipotent neural stem cells (i.e., induced neural stem cells [iNSCs]. iNSCs offer an attractive alternative to induced pluripotent stem cell (iPSC technology with regard to regenerative therapies. Here, we show an in vivo long-term analysis of transplanted iNSCs in the adult mouse brain. iNSCs showed sound in vivo long-term survival rates without graft overgrowths. The cells displayed a neural multilineage potential with a clear bias toward astrocytes and a permanent downregulation of progenitor and cell-cycle markers, indicating that iNSCs are not predisposed to tumor formation. Furthermore, the formation of synaptic connections as well as neuronal and glial electrophysiological properties demonstrated that differentiated iNSCs migrated, functionally integrated, and interacted with the existing neuronal circuitry. We conclude that iNSC long-term transplantation is a safe procedure; moreover, it might represent an interesting tool for future personalized regenerative applications.

Quantitative and Qualitative Proteome Characteristics Extracted from In-Depth Integrated Genomics and Proteomics Analysis

NARCIS (Netherlands)

Low, Teck Yew; van Heesch, Sebastiaan; van den Toorn, Henk; Giansanti, Piero; Cristobal, Alba; Toonen, Pim; Schafer, Sebastian; Huebner, Norbert; van Breukelen, Bas; Mohammed, Shabaz; Cuppen, Edwin; Heck, Albert J. R.; Guryev, Victor

2013-01-01

Quantitative and qualitative protein characteristics are regulated at genomic, transcriptomic, and post-transcriptional levels. Here, we integrated in-depth transcriptome and proteome analyses of liver tissues from two rat strains to unravel the interactions within and between these layers. We

An intelligent sales forecasting system through integration of artificial neural networks and fuzzy neural networks with fuzzy weight elimination.

Science.gov (United States)

Kuo, R J; Wu, P; Wang, C P

2002-09-01

Sales forecasting plays a very prominent role in business strategy. Numerous investigations addressing this problem have generally employed statistical methods, such as regression or autoregressive and moving average (ARMA). However, sales forecasting is very complicated owing to influence by internal and external environments. Recently, artificial neural networks (ANNs) have also been applied in sales forecasting since their promising performances in the areas of control and pattern recognition. However, further improvement is still necessary since unique circumstances, e.g. promotion, cause a sudden change in the sales pattern. Thus, this study utilizes a proposed fuzzy neural network (FNN), which is able to eliminate the unimportant weights, for the sake of learning fuzzy IF-THEN rules obtained from the marketing experts with respect to promotion. The result from FNN is further integrated with the time series data through an ANN. Both the simulated and real-world problem results show that FNN with weight elimination can have lower training error compared with the regular FNN. Besides, real-world problem results also indicate that the proposed estimation system outperforms the conventional statistical method and single ANN in accuracy.

A recurrent neural model for proto-object based contour integration and figure-ground segregation.

Science.gov (United States)

Hu, Brian; Niebur, Ernst

2017-12-01

Visual processing of objects makes use of both feedforward and feedback streams of information. However, the nature of feedback signals is largely unknown, as is the identity of the neuronal populations in lower visual areas that receive them. Here, we develop a recurrent neural model to address these questions in the context of contour integration and figure-ground segregation. A key feature of our model is the use of grouping neurons whose activity represents tentative objects ("proto-objects") based on the integration of local feature information. Grouping neurons receive input from an organized set of local feature neurons, and project modulatory feedback to those same neurons. Additionally, inhibition at both the local feature level and the object representation level biases the interpretation of the visual scene in agreement with principles from Gestalt psychology. Our model explains several sets of neurophysiological results (Zhou et al. Journal of Neuroscience, 20(17), 6594-6611 2000; Qiu et al. Nature Neuroscience, 10(11), 1492-1499 2007; Chen et al. Neuron, 82(3), 682-694 2014), and makes testable predictions about the influence of neuronal feedback and attentional selection on neural responses across different visual areas. Our model also provides a framework for understanding how object-based attention is able to select both objects and the features associated with them.

MicroScope—an integrated microbial resource for the curation and comparative analysis of genomic and metabolic data

Science.gov (United States)

Vallenet, David; Belda, Eugeni; Calteau, Alexandra; Cruveiller, Stéphane; Engelen, Stefan; Lajus, Aurélie; Le Fèvre, François; Longin, Cyrille; Mornico, Damien; Roche, David; Rouy, Zoé; Salvignol, Gregory; Scarpelli, Claude; Thil Smith, Adam Alexander; Weiman, Marion; Médigue, Claudine

2013-01-01

MicroScope is an integrated platform dedicated to both the methodical updating of microbial genome annotation and to comparative analysis. The resource provides data from completed and ongoing genome projects (automatic and expert annotations), together with data sources from post-genomic experiments (i.e. transcriptomics, mutant collections) allowing users to perfect and improve the understanding of gene functions. MicroScope (http://www.genoscope.cns.fr/agc/microscope) combines tools and graphical interfaces to analyse genomes and to perform the manual curation of gene annotations in a comparative context. Since its first publication in January 2006, the system (previously named MaGe for Magnifying Genomes) has been continuously extended both in terms of data content and analysis tools. The last update of MicroScope was published in 2009 in the Database journal. Today, the resource contains data for >1600 microbial genomes, of which ∼300 are manually curated and maintained by biologists (1200 personal accounts today). Expert annotations are continuously gathered in the MicroScope database (∼50 000 a year), contributing to the improvement of the quality of microbial genomes annotations. Improved data browsing and searching tools have been added, original tools useful in the context of expert annotation have been developed and integrated and the website has been significantly redesigned to be more user-friendly. Furthermore, in the context of the European project Microme (Framework Program 7 Collaborative Project), MicroScope is becoming a resource providing for the curation and analysis of both genomic and metabolic data. An increasing number of projects are related to the study of environmental bacterial (meta)genomes that are able to metabolize a large variety of chemical compounds that may be of high industrial interest. PMID:23193269

Integrating sequencing technologies in personal genomics: optimal low cost reconstruction of structural variants.

Directory of Open Access Journals (Sweden)

Jiang Du

2009-07-01

Full Text Available The goal of human genome re-sequencing is obtaining an accurate assembly of an individual's genome. Recently, there has been great excitement in the development of many technologies for this (e.g. medium and short read sequencing from companies such as 454 and SOLiD, and high-density oligo-arrays from Affymetrix and NimbelGen, with even more expected to appear. The costs and sensitivities of these technologies differ considerably from each other. As an important goal of personal genomics is to reduce the cost of re-sequencing to an affordable point, it is worthwhile to consider optimally integrating technologies. Here, we build a simulation toolbox that will help us optimally combine different technologies for genome re-sequencing, especially in reconstructing large structural variants (SVs. SV reconstruction is considered the most challenging step in human genome re-sequencing. (It is sometimes even harder than de novo assembly of small genomes because of the duplications and repetitive sequences in the human genome. To this end, we formulate canonical problems that are representative of issues in reconstruction and are of small enough scale to be computationally tractable and simulatable. Using semi-realistic simulations, we show how we can combine different technologies to optimally solve the assembly at low cost. With mapability maps, our simulations efficiently handle the inhomogeneous repeat-containing structure of the human genome and the computational complexity of practical assembly algorithms. They quantitatively show how combining different read lengths is more cost-effective than using one length, how an optimal mixed sequencing strategy for reconstructing large novel SVs usually also gives accurate detection of SNPs/indels, how paired-end reads can improve reconstruction efficiency, and how adding in arrays is more efficient than just sequencing for disentangling some complex SVs. Our strategy should facilitate the sequencing of

Integrated genomic and BMI analysis for type 2 diabetes risk assessment.

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Dayanara eLebrón-Aldea

2015-03-01

Full Text Available Type 2 Diabetes (T2D is a chronic disease arising from the development of insulin absence or resistance within the body, and a complex interplay of environmental and genetic factors. The incidence of T2D has increased throughout the last few decades, together with the occurrence of the obesity epidemic. The consideration of variants identified by Genome Wide Association Studies (GWAS into risk assessment models for T2D could aid in the identification of at-risk patients who could benefit from preventive medicine. In this study, we build several risk assessment models, and evaluated them with two different classification approaches (Logistic Regression and Neural Networks, to measure the effect of including genetic information in the prediction of T2D. We used data from to the Original and the Offspring cohorts of the Framingham Heart Study, which provides phenotypic and genetic information for 5,245 subjects (4,306 controls and 939 cases. Models were built by using several covariates: gender, exposure time, cohort, body mass index (BMI, and 65 established T2D-associated SNPs. We fitted Logistic Regressions and Bayesian Regularized Neural Network and then assessed their predictive ability by using a ten-fold cross validation. We found that the inclusion of genetic information into the risk assessment models increased the predictive ability by 2%, when compared to the baseline model. Furthermore, the models that included BMI at the onset of diabetes as a possible effector, gave an improvement of 6% in the area under the curve derived from the ROC analysis. The highest AUC achieved (0.75 belonged to the model that included BMI, and a genetic score based on the 65 established T2D-associated SNPs. Finally, the inclusion of SNPs and BMI raised predictive ability in all models as expected; however, results from the AUC in Neural Networks and Logistic Regression did not differ significantly in their prediction accuracy.

Selective Gene Delivery for Integrating Exogenous DNA into Plastid and Mitochondrial Genomes Using Peptide-DNA Complexes.

Science.gov (United States)

Yoshizumi, Takeshi; Oikawa, Kazusato; Chuah, Jo-Ann; Kodama, Yutaka; Numata, Keiji

2018-05-14

Selective gene delivery into organellar genomes (mitochondrial and plastid genomes) has been limited because of a lack of appropriate platform technology, even though these organelles are essential for metabolite and energy production. Techniques for selective organellar modification are needed to functionally improve organelles and produce transplastomic/transmitochondrial plants. However, no method for mitochondrial genome modification has yet been established for multicellular organisms including plants. Likewise, modification of plastid genomes has been limited to a few plant species and algae. In the present study, we developed ionic complexes of fusion peptides containing organellar targeting signal and plasmid DNA for selective delivery of exogenous DNA into the plastid and mitochondrial genomes of intact plants. This is the first report of exogenous DNA being integrated into the mitochondrial genomes of not only plants, but also multicellular organisms in general. This fusion peptide-mediated gene delivery system is a breakthrough platform for both plant organellar biotechnology and gene therapy for mitochondrial diseases in animals.

GMATA: An Integrated Software Package for Genome-Scale SSR Mining, Marker Development and Viewing.

Science.gov (United States)

Wang, Xuewen; Wang, Le

2016-01-01

Simple sequence repeats (SSRs), also referred to as microsatellites, are highly variable tandem DNAs that are widely used as genetic markers. The increasing availability of whole-genome and transcript sequences provides information resources for SSR marker development. However, efficient software is required to efficiently identify and display SSR information along with other gene features at a genome scale. We developed novel software package Genome-wide Microsatellite Analyzing Tool Package (GMATA) integrating SSR mining, statistical analysis and plotting, marker design, polymorphism screening and marker transferability, and enabled simultaneously display SSR markers with other genome features. GMATA applies novel strategies for SSR analysis and primer design in large genomes, which allows GMATA to perform faster calculation and provides more accurate results than existing tools. Our package is also capable of processing DNA sequences of any size on a standard computer. GMATA is user friendly, only requires mouse clicks or types inputs on the command line, and is executable in multiple computing platforms. We demonstrated the application of GMATA in plants genomes and reveal a novel distribution pattern of SSRs in 15 grass genomes. The most abundant motifs are dimer GA/TC, the A/T monomer and the GCG/CGC trimer, rather than the rich G/C content in DNA sequence. We also revealed that SSR count is a linear to the chromosome length in fully assembled grass genomes. GMATA represents a powerful application tool that facilitates genomic sequence analyses. GAMTA is freely available at http://sourceforge.net/projects/gmata/?source=navbar.

Genome puzzle master (GPM): an integrated pipeline for building and editing pseudomolecules from fragmented sequences.

Science.gov (United States)

Zhang, Jianwei; Kudrna, Dave; Mu, Ting; Li, Weiming; Copetti, Dario; Yu, Yeisoo; Goicoechea, Jose Luis; Lei, Yang; Wing, Rod A

2016-10-15

Next generation sequencing technologies have revolutionized our ability to rapidly and affordably generate vast quantities of sequence data. Once generated, raw sequences are assembled into contigs or scaffolds. However, these assemblies are mostly fragmented and inaccurate at the whole genome scale, largely due to the inability to integrate additional informative datasets (e.g. physical, optical and genetic maps). To address this problem, we developed a semi-automated software tool-Genome Puzzle Master (GPM)-that enables the integration of additional genomic signposts to edit and build 'new-gen-assemblies' that result in high-quality 'annotation-ready' pseudomolecules. With GPM, loaded datasets can be connected to each other via their logical relationships which accomplishes tasks to 'group,' 'merge,' 'order and orient' sequences in a draft assembly. Manual editing can also be performed with a user-friendly graphical interface. Final pseudomolecules reflect a user's total data package and are available for long-term project management. GPM is a web-based pipeline and an important part of a Laboratory Information Management System (LIMS) which can be easily deployed on local servers for any genome research laboratory. The GPM (with LIMS) package is available at https://github.com/Jianwei-Zhang/LIMS CONTACTS: jzhang@mail.hzau.edu.cn or rwing@mail.arizona.eduSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

Functional integration of grafted neural stem cell-derived dopaminergic neurons monitored by optogenetics in an in vitro Parkinson model

DEFF Research Database (Denmark)

Tønnesen, Jan; Parish, Clare L; Sørensen, Andreas T

2011-01-01

Intrastriatal grafts of stem cell-derived dopamine (DA) neurons induce behavioral recovery in animal models of Parkinson's disease (PD), but how they functionally integrate in host neural circuitries is poorly understood. Here, Wnt5a-overexpressing neural stem cells derived from embryonic ventral...... of post-synaptic currents, and functional expression of DA D₂ autoreceptors. These properties resembled those recorded from identical cells in acute slices of intrastriatal grafts in the 6-hydroxy-DA-induced mouse PD model and from DA neurons in intact substantia nigra. Optogenetic activation...... using optogenetics that ectopically grafted stem cell-derived DA neurons become functionally integrated in the DA-denervated striatum. Further optogenetic dissection of the synaptic wiring between grafted and host neurons will be crucial to clarify the cellular and synaptic mechanisms underlying...

Integrated low noise low power interface for neural bio-potentials recording and conditioning

Science.gov (United States)

Bottino, Emanuele; Martinoia, Sergio; Valle, Maurizio

2005-06-01

The recent progress in both neurobiology and microelectronics suggests the creation of new, powerful tools to investigate the basic mechanisms of brain functionality. In particular, a lot of efforts are spent by scientific community to define new frameworks devoted to the analysis of in-vitro cultured neurons. One possible approach is recording their spiking activity to monitor the coordinated cellular behaviour and get insights about neural plasticity. Due to the nature of neurons action-potentials, when considering the design of an integrated microelectronic-based recording system, a number of problems arise. First, one would desire to have a high number of recording sites (i.e. several hundreds): this poses constraints on silicon area and power consumption. In this regard, our aim is to integrate-through on-chip post-processing techniques-hundreds of bio-compatible microsensors together with CMOS standard-process low-power (i.e. some tenths of uW per channel) conditioning electronics. Each recording channel is provided with sampling electronics to insure synchronous recording so that, for example, cross-correlation between signals coming from different sites can be performed. Extra-cellular potentials are in the range of [50-150] uV, so a comparison in terms of noise-efficiency was carried out among different architectures and very low-noise pre-amplification electronics (i.e. less than 5 uVrms) was designed. As spikes measurements are made with respect to the voltage of a reference electrode, we opted for an AC-coupled differential-input preamplifier provided with band-pass filtering capability. To achieve this, we implemented large time-constant (up to seconds) integrated components in the preamp feedback path. Thus, we got rid also of random slow-drifting DC-offsets and common mode signals. The paper will present our achievements in the design and implementation of a fully integrated bio-abio interface to record neural spiking activity. In particular

Family genome browser: visualizing genomes with pedigree information.

Science.gov (United States)

Juan, Liran; Liu, Yongzhuang; Wang, Yongtian; Teng, Mingxiang; Zang, Tianyi; Wang, Yadong

2015-07-15

Families with inherited diseases are widely used in Mendelian/complex disease studies. Owing to the advances in high-throughput sequencing technologies, family genome sequencing becomes more and more prevalent. Visualizing family genomes can greatly facilitate human genetics studies and personalized medicine. However, due to the complex genetic relationships and high similarities among genomes of consanguineous family members, family genomes are difficult to be visualized in traditional genome visualization framework. How to visualize the family genome variants and their functions with integrated pedigree information remains a critical challenge. We developed the Family Genome Browser (FGB) to provide comprehensive analysis and visualization for family genomes. The FGB can visualize family genomes in both individual level and variant level effectively, through integrating genome data with pedigree information. Family genome analysis, including determination of parental origin of the variants, detection of de novo mutations, identification of potential recombination events and identical-by-decent segments, etc., can be performed flexibly. Diverse annotations for the family genome variants, such as dbSNP memberships, linkage disequilibriums, genes, variant effects, potential phenotypes, etc., are illustrated as well. Moreover, the FGB can automatically search de novo mutations and compound heterozygous variants for a selected individual, and guide investigators to find high-risk genes with flexible navigation options. These features enable users to investigate and understand family genomes intuitively and systematically. The FGB is available at http://mlg.hit.edu.cn/FGB/. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Neural basis of the time window for subjective motor-auditory integration

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Koichi eToida

2016-01-01

Full Text Available Temporal contiguity between an action and corresponding auditory feedback is crucial to the perception of self-generated sound. However, the neural mechanisms underlying motor–auditory temporal integration are unclear. Here, we conducted four experiments with an oddball paradigm to examine the specific event-related potentials (ERPs elicited by delayed auditory feedback for a self-generated action. The first experiment confirmed that a pitch-deviant auditory stimulus elicits mismatch negativity (MMN and P300, both when it is generated passively and by the participant’s action. In our second and third experiments, we investigated the ERP components elicited by delayed auditory feedback of for a self-generated action. We found that delayed auditory feedback elicited an enhancement of P2 (enhanced-P2 and a N300 component, which were apparently different from the MMN and P300 components observed in the first experiment. We further investigated the sensitivity of the enhanced-P2 and N300 to delay length in our fourth experiment. Strikingly, the amplitude of the N300 increased as a function of the delay length. Additionally, the N300 amplitude was significantly correlated with the conscious detection of the delay (the 50% detection point was around 200 ms, and hence reduction in the feeling of authorship of the sound (the sense of agency. In contrast, the enhanced-P2 was most prominent in short-delay (≤ 200 ms conditions and diminished in long-delay conditions. Our results suggest that different neural mechanisms are employed for the processing of temporally-deviant and pitch-deviant auditory feedback. Additionally, the temporal window for subjective motor–auditory integration is likely about 200 ms, as indicated by these auditory ERP components.

Filling the knowledge gap: Integrating quantitative genetics and genomics in graduate education and outreach

Science.gov (United States)

The genomics revolution provides vital tools to address global food security. Yet to be incorporated into livestock breeding, molecular techniques need to be integrated into a quantitative genetics framework. Within the U.S., with shrinking faculty numbers with the requisite skills, the capacity to ...

The Proteins API: accessing key integrated protein and genome information.

Science.gov (United States)

Nightingale, Andrew; Antunes, Ricardo; Alpi, Emanuele; Bursteinas, Borisas; Gonzales, Leonardo; Liu, Wudong; Luo, Jie; Qi, Guoying; Turner, Edd; Martin, Maria

2017-07-03

The Proteins API provides searching and programmatic access to protein and associated genomics data such as curated protein sequence positional annotations from UniProtKB, as well as mapped variation and proteomics data from large scale data sources (LSS). Using the coordinates service, researchers are able to retrieve the genomic sequence coordinates for proteins in UniProtKB. This, the LSS genomics and proteomics data for UniProt proteins is programmatically only available through this service. A Swagger UI has been implemented to provide documentation, an interface for users, with little or no programming experience, to 'talk' to the services to quickly and easily formulate queries with the services and obtain dynamically generated source code for popular programming languages, such as Java, Perl, Python and Ruby. Search results are returned as standard JSON, XML or GFF data objects. The Proteins API is a scalable, reliable, fast, easy to use RESTful services that provides a broad protein information resource for users to ask questions based upon their field of expertise and allowing them to gain an integrated overview of protein annotations available to aid their knowledge gain on proteins in biological processes. The Proteins API is available at (http://www.ebi.ac.uk/proteins/api/doc). © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Biodiversity Meets Neuroscience: From the Sequencing Ship (Ship-Seq) to Deciphering Parallel Evolution of Neural Systems in Omic's Era.

Science.gov (United States)

Moroz, Leonid L

2015-12-01

The origins of neural systems and centralized brains are one of the major transitions in evolution. These events might occur more than once over 570-600 million years. The convergent evolution of neural circuits is evident from a diversity of unique adaptive strategies implemented by ctenophores, cnidarians, acoels, molluscs, and basal deuterostomes. But, further integration of biodiversity research and neuroscience is required to decipher critical events leading to development of complex integrative and cognitive functions. Here, we outline reference species and interdisciplinary approaches in reconstructing the evolution of nervous systems. In the "omic" era, it is now possible to establish fully functional genomics laboratories aboard of oceanic ships and perform sequencing and real-time analyses of data at any oceanic location (named here as Ship-Seq). In doing so, fragile, rare, cryptic, and planktonic organisms, or even entire marine ecosystems, are becoming accessible directly to experimental and physiological analyses by modern analytical tools. Thus, we are now in a position to take full advantages from countless "experiments" Nature performed for us in the course of 3.5 billion years of biological evolution. Together with progress in computational and comparative genomics, evolutionary neuroscience, proteomic and developmental biology, a new surprising picture is emerging that reveals many ways of how nervous systems evolved. As a result, this symposium provides a unique opportunity to revisit old questions about the origins of biological complexity. © The Author 2015. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

SNUGB: a versatile genome browser supporting comparative and functional fungal genomics

Directory of Open Access Journals (Sweden)

Kim Seungill

2008-12-01

Full Text Available Abstract Background Since the full genome sequences of Saccharomyces cerevisiae were released in 1996, genome sequences of over 90 fungal species have become publicly available. The heterogeneous formats of genome sequences archived in different sequencing centers hampered the integration of the data for efficient and comprehensive comparative analyses. The Comparative Fungal Genomics Platform (CFGP was developed to archive these data via a single standardized format that can support multifaceted and integrated analyses of the data. To facilitate efficient data visualization and utilization within and across species based on the architecture of CFGP and associated databases, a new genome browser was needed. Results The Seoul National University Genome Browser (SNUGB integrates various types of genomic information derived from 98 fungal/oomycete (137 datasets and 34 plant and animal (38 datasets species, graphically presents germane features and properties of each genome, and supports comparison between genomes. The SNUGB provides three different forms of the data presentation interface, including diagram, table, and text, and six different display options to support visualization and utilization of the stored information. Information for individual species can be quickly accessed via a new tool named the taxonomy browser. In addition, SNUGB offers four useful data annotation/analysis functions, including 'BLAST annotation.' The modular design of SNUGB makes its adoption to support other comparative genomic platforms easy and facilitates continuous expansion. Conclusion The SNUGB serves as a powerful platform supporting comparative and functional genomics within the fungal kingdom and also across other kingdoms. All data and functions are available at the web site http://genomebrowser.snu.ac.kr/.

An evolvable oestrogen receptor activity sensor: development of a modular system for integrating multiple genes into the yeast genome

NARCIS (Netherlands)

Fox, J.E.; Bridgham, J.T.; Bovee, T.F.H.; Thornton, J.W.

2007-01-01

To study a gene interaction network, we developed a gene-targeting strategy that allows efficient and stable genomic integration of multiple genetic constructs at distinct target loci in the yeast genome. This gene-targeting strategy uses a modular plasmid with a recyclable selectable marker and a

Direct Neural Conversion from Human Fibroblasts Using Self-Regulating and Nonintegrating Viral Vectors

Directory of Open Access Journals (Sweden)

Shong Lau

2014-12-01

Full Text Available Summary: Recent findings show that human fibroblasts can be directly programmed into functional neurons without passing via a proliferative stem cell intermediate. These findings open up the possibility of generating subtype-specific neurons of human origin for therapeutic use from fetal cell, from patients themselves, or from matched donors. In this study, we present an improved system for direct neural conversion of human fibroblasts. The neural reprogramming genes are regulated by the neuron-specific microRNA, miR-124, such that each cell turns off expression of the reprogramming genes once the cell has reached a stable neuronal fate. The regulated system can be combined with integrase-deficient vectors, providing a nonintegrative and self-regulated conversion system that rids problems associated with the integration of viral transgenes into the host genome. These modifications make the system suitable for clinical use and therefore represent a major step forward in the development of induced neurons for cell therapy. : Lau et al. now use miRNA targeting to build a self-regulating neural conversion system. Combined with nonintegrating vectors, this system can efficiently drive conversion of human fibroblasts into functional induced neurons (iNs suitable for clinical applications.

The Next Generation Precision Medical Record - A Framework for Integrating Genomes and Wearable Sensors with Medical Records

OpenAIRE

Batra, Prag; Singh, Enakshi; Bog, Anja; Wright, Mark; Ashley, Euan; Waggott, Daryl

2016-01-01

Current medical records are rigid with regards to emerging big biomedical data. Examples of poorly integrated big data that already exist in clinical practice include whole genome sequencing and wearable sensors for real time monitoring. Genome sequencing enables conventional diagnostic interrogation and forms the fundamental baseline for precision health throughout a patients lifetime. Mobile sensors enable tailored monitoring regimes for both reducing risk through precision health intervent...

The neural circuits of innate fear: detection, integration, action, and memorization

Science.gov (United States)

Silva, Bianca A.; Gross, Cornelius T.

2016-01-01

How fear is represented in the brain has generated a lot of research attention, not only because fear increases the chances for survival when appropriately expressed but also because it can lead to anxiety and stress-related disorders when inadequately processed. In this review, we summarize recent progress in the understanding of the neural circuits processing innate fear in rodents. We propose that these circuits are contained within three main functional units in the brain: a detection unit, responsible for gathering sensory information signaling the presence of a threat; an integration unit, responsible for incorporating the various sensory information and recruiting downstream effectors; and an output unit, in charge of initiating appropriate bodily and behavioral responses to the threatful stimulus. In parallel, the experience of innate fear also instructs a learning process leading to the memorization of the fearful event. Interestingly, while the detection, integration, and output units processing acute fear responses to different threats tend to be harbored in distinct brain circuits, memory encoding of these threats seems to rely on a shared learning system. PMID:27634145

Induced neural stem cells achieve long-term survival and functional integration in the adult mouse brain.

Science.gov (United States)

Hemmer, Kathrin; Zhang, Mingyue; van Wüllen, Thea; Sakalem, Marna; Tapia, Natalia; Baumuratov, Aidos; Kaltschmidt, Christian; Kaltschmidt, Barbara; Schöler, Hans R; Zhang, Weiqi; Schwamborn, Jens C

2014-09-09

Differentiated cells can be converted directly into multipotent neural stem cells (i.e., induced neural stem cells [iNSCs]). iNSCs offer an attractive alternative to induced pluripotent stem cell (iPSC) technology with regard to regenerative therapies. Here, we show an in vivo long-term analysis of transplanted iNSCs in the adult mouse brain. iNSCs showed sound in vivo long-term survival rates without graft overgrowths. The cells displayed a neural multilineage potential with a clear bias toward astrocytes and a permanent downregulation of progenitor and cell-cycle markers, indicating that iNSCs are not predisposed to tumor formation. Furthermore, the formation of synaptic connections as well as neuronal and glial electrophysiological properties demonstrated that differentiated iNSCs migrated, functionally integrated, and interacted with the existing neuronal circuitry. We conclude that iNSC long-term transplantation is a safe procedure; moreover, it might represent an interesting tool for future personalized regenerative applications. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

MIPS Arabidopsis thaliana Database (MAtDB): an integrated biological knowledge resource for plant genomics

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Schoof, Heiko; Ernst, Rebecca; Nazarov, Vladimir; Pfeifer, Lukas; Mewes, Hans-Werner; Mayer, Klaus F. X.

2004-01-01

Arabidopsis thaliana is the most widely studied model plant. Functional genomics is intensively underway in many laboratories worldwide. Beyond the basic annotation of the primary sequence data, the annotated genetic elements of Arabidopsis must be linked to diverse biological data and higher order information such as metabolic or regulatory pathways. The MIPS Arabidopsis thaliana database MAtDB aims to provide a comprehensive resource for Arabidopsis as a genome model that serves as a primary reference for research in plants and is suitable for transfer of knowledge to other plants, especially crops. The genome sequence as a common backbone serves as a scaffold for the integration of data, while, in a complementary effort, these data are enhanced through the application of state-of-the-art bioinformatics tools. This information is visualized on a genome-wide and a gene-by-gene basis with access both for web users and applications. This report updates the information given in a previous report and provides an outlook on further developments. The MAtDB web interface can be accessed at http://mips.gsf.de/proj/thal/db. PMID:14681437

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

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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 Novel Fractional-Order PID Controller for Integrated Pressurized Water Reactor Based on Wavelet Kernel Neural Network Algorithm

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Yu-xin Zhao

2014-01-01

Full Text Available This paper presents a novel wavelet kernel neural network (WKNN with wavelet kernel function. It is applicable in online learning with adaptive parameters and is applied on parameters tuning of fractional-order PID (FOPID controller, which could handle time delay problem of the complex control system. Combining the wavelet function and the kernel function, the wavelet kernel function is adopted and validated the availability for neural network. Compared to the conservative wavelet neural network, the most innovative character of the WKNN is its rapid convergence and high precision in parameters updating process. Furthermore, the integrated pressurized water reactor (IPWR system is established by RELAP5, and a novel control strategy combining WKNN and fuzzy logic rule is proposed for shortening controlling time and utilizing the experiential knowledge sufficiently. Finally, experiment results verify that the control strategy and controller proposed have the practicability and reliability in actual complicated system.

Integrating Artificial Immune, Neural and Endrocine Systems in Autonomous Sailing Robots

Science.gov (United States)

2010-09-24

system - Development of an adaptive hormone system capable of changing operation and control of the neural network depending on changing enviromental ...and control of the neural network depending on changing enviromental conditions • First basic design of the MOOP and a simple neural-endocrine based

Integration of least angle regression with empirical Bayes for multi-locus genome-wide association studies

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Multi-locus genome-wide association studies has become the state-of-the-art procedure to identify quantitative trait loci (QTL) associated with traits simultaneously. However, implementation of multi-locus model is still difficult. In this study, we integrated least angle regression with empirical B...

Spike Neural Models Part II: Abstract Neural Models

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Johnson, Melissa G.

2018-02-01

Full Text Available Neurons are complex cells that require a lot of time and resources to model completely. In spiking neural networks (SNN though, not all that complexity is required. Therefore simple, abstract models are often used. These models save time, use less computer resources, and are easier to understand. This tutorial presents two such models: Izhikevich's model, which is biologically realistic in the resulting spike trains but not in the parameters, and the Leaky Integrate and Fire (LIF model which is not biologically realistic but does quickly and easily integrate input to produce spikes. Izhikevich's model is based on Hodgkin-Huxley's model but simplified such that it uses only two differentiation equations and four parameters to produce various realistic spike patterns. LIF is based on a standard electrical circuit and contains one equation. Either of these two models, or any of the many other models in literature can be used in a SNN. Choosing a neural model is an important task that depends on the goal of the research and the resources available. Once a model is chosen, network decisions such as connectivity, delay, and sparseness, need to be made. Understanding neural models and how they are incorporated into the network is the first step in creating a SNN.

Integrating Genomic Data Sets for Knowledge Discovery: An Informed Approach to Management of Captive Endangered Species

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Kristopher J. L. Irizarry

2016-01-01

Full Text Available Many endangered captive populations exhibit reduced genetic diversity resulting in health issues that impact reproductive fitness and quality of life. Numerous cost effective genomic sequencing and genotyping technologies provide unparalleled opportunity for incorporating genomics knowledge in management of endangered species. Genomic data, such as sequence data, transcriptome data, and genotyping data, provide critical information about a captive population that, when leveraged correctly, can be utilized to maximize population genetic variation while simultaneously reducing unintended introduction or propagation of undesirable phenotypes. Current approaches aimed at managing endangered captive populations utilize species survival plans (SSPs that rely upon mean kinship estimates to maximize genetic diversity while simultaneously avoiding artificial selection in the breeding program. However, as genomic resources increase for each endangered species, the potential knowledge available for management also increases. Unlike model organisms in which considerable scientific resources are used to experimentally validate genotype-phenotype relationships, endangered species typically lack the necessary sample sizes and economic resources required for such studies. Even so, in the absence of experimentally verified genetic discoveries, genomics data still provides value. In fact, bioinformatics and comparative genomics approaches offer mechanisms for translating these raw genomics data sets into integrated knowledge that enable an informed approach to endangered species management.

Integrating Genomic Data Sets for Knowledge Discovery: An Informed Approach to Management of Captive Endangered Species.

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Irizarry, Kristopher J L; Bryant, Doug; Kalish, Jordan; Eng, Curtis; Schmidt, Peggy L; Barrett, Gini; Barr, Margaret C

2016-01-01

Many endangered captive populations exhibit reduced genetic diversity resulting in health issues that impact reproductive fitness and quality of life. Numerous cost effective genomic sequencing and genotyping technologies provide unparalleled opportunity for incorporating genomics knowledge in management of endangered species. Genomic data, such as sequence data, transcriptome data, and genotyping data, provide critical information about a captive population that, when leveraged correctly, can be utilized to maximize population genetic variation while simultaneously reducing unintended introduction or propagation of undesirable phenotypes. Current approaches aimed at managing endangered captive populations utilize species survival plans (SSPs) that rely upon mean kinship estimates to maximize genetic diversity while simultaneously avoiding artificial selection in the breeding program. However, as genomic resources increase for each endangered species, the potential knowledge available for management also increases. Unlike model organisms in which considerable scientific resources are used to experimentally validate genotype-phenotype relationships, endangered species typically lack the necessary sample sizes and economic resources required for such studies. Even so, in the absence of experimentally verified genetic discoveries, genomics data still provides value. In fact, bioinformatics and comparative genomics approaches offer mechanisms for translating these raw genomics data sets into integrated knowledge that enable an informed approach to endangered species management.

Perspectives on Clinical Informatics: Integrating Large-Scale Clinical, Genomic, and Health Information for Clinical Care

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In Young Choi

2013-12-01

Full Text Available The advances in electronic medical records (EMRs and bioinformatics (BI represent two significant trends in healthcare. The widespread adoption of EMR systems and the completion of the Human Genome Project developed the technologies for data acquisition, analysis, and visualization in two different domains. The massive amount of data from both clinical and biology domains is expected to provide personalized, preventive, and predictive healthcare services in the near future. The integrated use of EMR and BI data needs to consider four key informatics areas: data modeling, analytics, standardization, and privacy. Bioclinical data warehouses integrating heterogeneous patient-related clinical or omics data should be considered. The representative standardization effort by the Clinical Bioinformatics Ontology (CBO aims to provide uniquely identified concepts to include molecular pathology terminologies. Since individual genome data are easily used to predict current and future health status, different safeguards to ensure confidentiality should be considered. In this paper, we focused on the informatics aspects of integrating the EMR community and BI community by identifying opportunities, challenges, and approaches to provide the best possible care service for our patients and the population.

Improved genome recovery and integrated cell-size analyses of individual uncultured microbial cells and viral particles.

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Stepanauskas, Ramunas; Fergusson, Elizabeth A; Brown, Joseph; Poulton, Nicole J; Tupper, Ben; Labonté, Jessica M; Becraft, Eric D; Brown, Julia M; Pachiadaki, Maria G; Povilaitis, Tadas; Thompson, Brian P; Mascena, Corianna J; Bellows, Wendy K; Lubys, Arvydas

2017-07-20

Microbial single-cell genomics can be used to provide insights into the metabolic potential, interactions, and evolution of uncultured microorganisms. Here we present WGA-X, a method based on multiple displacement amplification of DNA that utilizes a thermostable mutant of the phi29 polymerase. WGA-X enhances genome recovery from individual microbial cells and viral particles while maintaining ease of use and scalability. The greatest improvements are observed when amplifying high G+C content templates, such as those belonging to the predominant bacteria in agricultural soils. By integrating WGA-X with calibrated index-cell sorting and high-throughput genomic sequencing, we are able to analyze genomic sequences and cell sizes of hundreds of individual, uncultured bacteria, archaea, protists, and viral particles, obtained directly from marine and soil samples, in a single experiment. This approach may find diverse applications in microbiology and in biomedical and forensic studies of humans and other multicellular organisms.Single-cell genomics can be used to study uncultured microorganisms. Here, Stepanauskas et al. present a method combining improved multiple displacement amplification and FACS, to obtain genomic sequences and cell size information from uncultivated microbial cells and viral particles in environmental samples.

Global assessment of genomic variation in cattle by genome resequencing and high-throughput genotyping

DEFF Research Database (Denmark)

Zhan, Bujie; Fadista, João; Thomsen, Bo

2011-01-01

Background Integration of genomic variation with phenotypic information is an effective approach for uncovering genotype-phenotype associations. This requires an accurate identification of the different types of variation in individual genomes. Results We report the integration of the whole genome...... of split-read and read-pair approaches proved to be complementary in finding different signatures. CNVs were identified on the basis of the depth of sequenced reads, and by using SNP and CGH arrays. Conclusions Our results provide high resolution mapping of diverse classes of genomic variation...

Modeling and interoperability of heterogeneous genomic big data for integrative processing and querying.

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Masseroli, Marco; Kaitoua, Abdulrahman; Pinoli, Pietro; Ceri, Stefano

2016-12-01

While a huge amount of (epi)genomic data of multiple types is becoming available by using Next Generation Sequencing (NGS) technologies, the most important emerging problem is the so-called tertiary analysis, concerned with sense making, e.g., discovering how different (epi)genomic regions and their products interact and cooperate with each other. We propose a paradigm shift in tertiary analysis, based on the use of the Genomic Data Model (GDM), a simple data model which links genomic feature data to their associated experimental, biological and clinical metadata. GDM encompasses all the data formats which have been produced for feature extraction from (epi)genomic datasets. We specifically describe the mapping to GDM of SAM (Sequence Alignment/Map), VCF (Variant Call Format), NARROWPEAK (for called peaks produced by NGS ChIP-seq or DNase-seq methods), and BED (Browser Extensible Data) formats, but GDM supports as well all the formats describing experimental datasets (e.g., including copy number variations, DNA somatic mutations, or gene expressions) and annotations (e.g., regarding transcription start sites, genes, enhancers or CpG islands). We downloaded and integrated samples of all the above-mentioned data types and formats from multiple sources. The GDM is able to homogeneously describe semantically heterogeneous data and makes the ground for providing data interoperability, e.g., achieved through the GenoMetric Query Language (GMQL), a high-level, declarative query language for genomic big data. The combined use of the data model and the query language allows comprehensive processing of multiple heterogeneous data, and supports the development of domain-specific data-driven computations and bio-molecular knowledge discovery. Copyright © 2016 Elsevier Inc. All rights reserved.

Glucocorticoid control of gene transcription in neural tissue

NARCIS (Netherlands)

Morsink, Maarten Christian

2007-01-01

Glucocorticoid hormones exert modulatory effects on neural function in a delayed genomic fashion. The two receptor types that can bind glucocorticoids, the mineralocorticoid receptor (MR) and the glucocorticoid receptor (GR), are ligand-inducible transcription factors. Therefore, changes in gene

Reconstruction of putative DNA virus from endogenous rice tungro bacilliform virus-like sequences in the rice genome: implications for integration and evolution

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Kishima Yuji

2004-10-01

Full Text Available Abstract Background Plant genomes contain various kinds of repetitive sequences such as transposable elements, microsatellites, tandem repeats and virus-like sequences. Most of them, with the exception of virus-like sequences, do not allow us to trace their origins nor to follow the process of their integration into the host genome. Recent discoveries of virus-like sequences in plant genomes led us to set the objective of elucidating the origin of the repetitive sequences. Endogenous rice tungro bacilliform virus (RTBV-like sequences (ERTBVs have been found throughout the rice genome. Here, we reconstructed putative virus structures from RTBV-like sequences in the rice genome and characterized to understand evolutionary implication, integration manner and involvements of endogenous virus segments in the corresponding disease response. Results We have collected ERTBVs from the rice genomes. They contain rearranged structures and no intact ORFs. The identified ERTBV segments were shown to be phylogenetically divided into three clusters. For each phylogenetic cluster, we were able to make a consensus alignment for a circular virus-like structure carrying two complete ORFs. Comparisons of DNA and amino acid sequences suggested the closely relationship between ERTBV and RTBV. The Oryza AA-genome species vary in the ERTBV copy number. The species carrying low-copy-number of ERTBV segments have been reported to be extremely susceptible to RTBV. The DNA methylation state of the ERTBV sequences was correlated with their copy number in the genome. Conclusions These ERTBV segments are unlikely to have functional potential as a virus. However, these sequences facilitate to establish putative virus that provided information underlying virus integration and evolutionary relationship with existing virus. Comparison of ERTBV among the Oryza AA-genome species allowed us to speculate a possible role of endogenous virus segments against its related disease.

Integrated control of the cooling system and surface openings using the artificial neural networks

International Nuclear Information System (INIS)

Moon, Jin Woo

2015-01-01

This study aimed at suggesting an indoor temperature control method that can provide a comfortable thermal environment through the integrated control of the cooling system and the surface openings. Four control logic were developed, employing different application levels of rules and artificial neural network models. Rule-based control methods represented the conventional approach while ANN-based methods were applied for the predictive and adaptive controls. Comparative performance tests for the conventional- and ANN-based methods were numerically conducted for the double-skin-facade building, using the MATLAB (Matrix Laboratory) and TRNSYS (Transient Systems Simulation) software, after proving the validity by comparing the simulation and field measurement results. Analysis revealed that the ANN-based controls of the cooling system and surface openings improved the indoor temperature conditions with increased comfortable temperature periods and decreased standard deviation of the indoor temperature from the center of the comfortable range. In addition, the proposed ANN-based logic effectively reduced the number of operating condition changes of the cooling system and surface openings, which can prevent system failure. The ANN-based logic, however, did not show superiority in energy efficiency over the conventional logic. Instead, they have increased the amount of heat removal by the cooling system. From the analysis, it can be concluded that the ANN-based temperature control logic was able to keep the indoor temperature more comfortably and stably within the comfortable range due to its predictive and adaptive features. - Highlights: • Integrated rule-based and artificial neural network based logics were developed. • A cooling device and surface openings were controlled in an integrated manner. • Computer simulation method was employed for comparative performance tests. • ANN-based logics showed the advanced features of thermal environment. • Rule

Deciphering the genomes of 16 Acanthamoeba species does not provide evidence of integration of known giant virus-associated mobile genetic elements.

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Chelkha, Nisrine; Colson, Philippe; Levasseur, Anthony; La Scola, Bernard

2018-06-02

Giant viruses infect protozoa, especially amoebae of the genus Acanthamoeba. These viruses possess genetic elements named Mobilome. So far, this mobilome comprises provirophages which are integrated into the genome of their hosts, transpovirons, and Maverick/Polintons. Virophages replicate inside virus factories within Acanthamoeba and can decrease the infectivity of giant viruses. The virophage infecting CroV was found to be integrated in the host of CroV, Cafeteria roenbergensis, thus protecting C. roenbergensis by reduction of CroV multiplication. Because of this unique property, assessment of the mechanisms of replication of virophages and their relationship with giant viruses is a key element of this investigation. This work aimed at evaluating the presence and the dynamic of these mobile elements in sixteen Acanthamoeba genomes. No significant traces of the integration of genomes or sequences from known virophages were identified in all the available Acanthamoeba genomes. These results brought us to hypothesize that the interactions between mimiviruses and their virophages might occur through different mechanisms, or at low frequency. An additional explanation could be that our knowledge of the diversity of virophages is still very limited. Copyright © 2018 Elsevier B.V. All rights reserved.

Genome-wide association mapping in dogs enables identification of the homeobox gene, NKX2-8, as a genetic component of neural tube defects in humans.

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Noa Safra

Full Text Available Neural tube defects (NTDs is a general term for central nervous system malformations secondary to a failure of closure or development of the neural tube. The resulting pathologies may involve the brain, spinal cord and/or vertebral column, in addition to associated structures such as soft tissue or skin. The condition is reported among the more common birth defects in humans, leading to significant infant morbidity and mortality. The etiology remains poorly understood but genetic, nutritional, environmental factors, or a combination of these, are known to play a role in the development of NTDs. The variable conditions associated with NTDs occur naturally in dogs, and have been previously reported in the Weimaraner breed. Taking advantage of the strong linkage-disequilibrium within dog breeds we performed genome-wide association analysis and mapped a genomic region for spinal dysraphism, a presumed NTD, using 4 affected and 96 unaffected Weimaraners. The associated region on canine chromosome 8 (pgenome  =3.0 × 10(-5, after 100,000 permutations, encodes 18 genes, including NKX2-8, a homeobox gene which is expressed in the developing neural tube. Sequencing NKX2-8 in affected Weimaraners revealed a G to AA frameshift mutation within exon 2 of the gene, resulting in a premature stop codon that is predicted to produce a truncated protein. The exons of NKX2-8 were sequenced in human patients with spina bifida and rare variants (rs61755040 and rs10135525 were found to be significantly over-represented (p=0.036. This is the first documentation of a potential role for NKX2-8 in the etiology of NTDs, made possible by investigating the molecular basis of naturally occurring mutations in dogs.

Stable integration of recombinant adeno-associated virus vector genomes after transduction of murine hematopoietic stem cells.

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Han, Zongchao; Zhong, Li; Maina, Njeri; Hu, Zhongbo; Li, Xiaomiao; Chouthai, Nitin S; Bischof, Daniela; Weigel-Van Aken, Kirsten A; Slayton, William B; Yoder, Mervin C; Srivastava, Arun

2008-03-01

We previously reported that among single-stranded adeno-associated virus (ssAAV) vectors, serotypes 1 through 5, ssAAV1 is the most efficient in transducing murine hematopoietic stem cells (HSCs), but viral second-strand DNA synthesis remains a rate-limiting step. Subsequently, using double-stranded, self-complementary AAV (scAAV) vectors, serotypes 7 through 10, we observed that scAAV7 vectors also transduce murine HSCs efficiently. In the present study, we used scAAV1 and scAAV7 shuttle vectors to transduce HSCs in a murine bone marrow serial transplant model in vivo, which allowed examination of the AAV proviral integration pattern in the mouse genome, as well as recovery and nucleotide sequence analyses of AAV-HSC DNA junction fragments. The proviral genomes were stably integrated, and integration sites were localized to different mouse chromosomes. None of the integration sites was found to be in a transcribed gene, or near a cellular oncogene. None of the animals, monitored for up to 1 year, exhibited pathological abnormalities. Thus, AAV proviral integration-induced risk of oncogenesis was not found in our study, which provides functional confirmation of stable transduction of self-renewing multipotential HSCs by scAAV vectors as well as promise for the use of these vectors in the potential treatment of disorders of the hematopoietic system.

Polymorphic integrations of an endogenous gammaretrovirus in the mule deer genome.

Science.gov (United States)

Elleder, Daniel; Kim, Oekyung; Padhi, Abinash; Bankert, Jason G; Simeonov, Ivan; Schuster, Stephan C; Wittekindt, Nicola E; Motameny, Susanne; Poss, Mary

2012-03-01

Endogenous retroviruses constitute a significant genomic fraction in all mammalian species. Typically they are evolutionarily old and fixed in the host species population. Here we report on a novel endogenous gammaretrovirus (CrERVγ; for cervid endogenous gammaretrovirus) in the mule deer (Odocoileus hemionus) that is insertionally polymorphic among individuals from the same geographical location, suggesting that it has a more recent evolutionary origin. Using PCR-based methods, we identified seven CrERVγ proviruses and demonstrated that they show various levels of insertional polymorphism in mule deer individuals. One CrERVγ provirus was detected in all mule deer sampled but was absent from white-tailed deer, indicating that this virus originally integrated after the split of the two species, which occurred approximately one million years ago. There are, on average, 100 CrERVγ copies in the mule deer genome based on quantitative PCR analysis. A CrERVγ provirus was sequenced and contained intact open reading frames (ORFs) for three virus genes. Transcripts were identified covering the entire provirus. CrERVγ forms a distinct branch of the gammaretrovirus phylogeny, with the closest relatives of CrERVγ being endogenous gammaretroviruses from sheep and pig. We demonstrated that white-tailed deer (Odocoileus virginianus) and elk (Cervus canadensis) DNA contain proviruses that are closely related to mule deer CrERVγ in a conserved region of pol; more distantly related sequences can be identified in the genome of another member of the Cervidae, the muntjac (Muntiacus muntjak). The discovery of a novel transcriptionally active and insertionally polymorphic retrovirus in mammals could provide a useful model system to study the dynamic interaction between the host genome and an invading retrovirus.

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.

Two multichannel integrated circuits for neural recording and signal processing.

Science.gov (United States)

Obeid, Iyad; Morizio, James C; Moxon, Karen A; Nicolelis, Miguel A L; Wolf, Patrick D

2003-02-01

We have developed, manufactured, and tested two analog CMOS integrated circuit "neurochips" for recording from arrays of densely packed neural electrodes. Device A is a 16-channel buffer consisting of parallel noninverting amplifiers with a gain of 2 V/V. Device B is a 16-channel two-stage analog signal processor with differential amplification and high-pass filtering. It features selectable gains of 250 and 500 V/V as well as reference channel selection. The resulting amplifiers on Device A had a mean gain of 1.99 V/V with an equivalent input noise of 10 microV(rms). Those on Device B had mean gains of 53.4 and 47.4 dB with a high-pass filter pole at 211 Hz and an equivalent input noise of 4.4 microV(rms). Both devices were tested in vivo with electrode arrays implanted in the somatosensory cortex.

Integration of Multiple Genomic and Phenotype Data to Infer Novel miRNA-Disease Associations.

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Shi, Hongbo; Zhang, Guangde; Zhou, Meng; Cheng, Liang; Yang, Haixiu; Wang, Jing; Sun, Jie; Wang, Zhenzhen

2016-01-01

MicroRNAs (miRNAs) play an important role in the development and progression of human diseases. The identification of disease-associated miRNAs will be helpful for understanding the molecular mechanisms of diseases at the post-transcriptional level. Based on different types of genomic data sources, computational methods for miRNA-disease association prediction have been proposed. However, individual source of genomic data tends to be incomplete and noisy; therefore, the integration of various types of genomic data for inferring reliable miRNA-disease associations is urgently needed. In this study, we present a computational framework, CHNmiRD, for identifying miRNA-disease associations by integrating multiple genomic and phenotype data, including protein-protein interaction data, gene ontology data, experimentally verified miRNA-target relationships, disease phenotype information and known miRNA-disease connections. The performance of CHNmiRD was evaluated by experimentally verified miRNA-disease associations, which achieved an area under the ROC curve (AUC) of 0.834 for 5-fold cross-validation. In particular, CHNmiRD displayed excellent performance for diseases without any known related miRNAs. The results of case studies for three human diseases (glioblastoma, myocardial infarction and type 1 diabetes) showed that all of the top 10 ranked miRNAs having no known associations with these three diseases in existing miRNA-disease databases were directly or indirectly confirmed by our latest literature mining. All these results demonstrated the reliability and efficiency of CHNmiRD, and it is anticipated that CHNmiRD will serve as a powerful bioinformatics method for mining novel disease-related miRNAs and providing a new perspective into molecular mechanisms underlying human diseases at the post-transcriptional level. CHNmiRD is freely available at http://www.bio-bigdata.com/CHNmiRD.

Integration of Multiple Genomic and Phenotype Data to Infer Novel miRNA-Disease Associations.

Directory of Open Access Journals (Sweden)

Hongbo Shi

Full Text Available MicroRNAs (miRNAs play an important role in the development and progression of human diseases. The identification of disease-associated miRNAs will be helpful for understanding the molecular mechanisms of diseases at the post-transcriptional level. Based on different types of genomic data sources, computational methods for miRNA-disease association prediction have been proposed. However, individual source of genomic data tends to be incomplete and noisy; therefore, the integration of various types of genomic data for inferring reliable miRNA-disease associations is urgently needed. In this study, we present a computational framework, CHNmiRD, for identifying miRNA-disease associations by integrating multiple genomic and phenotype data, including protein-protein interaction data, gene ontology data, experimentally verified miRNA-target relationships, disease phenotype information and known miRNA-disease connections. The performance of CHNmiRD was evaluated by experimentally verified miRNA-disease associations, which achieved an area under the ROC curve (AUC of 0.834 for 5-fold cross-validation. In particular, CHNmiRD displayed excellent performance for diseases without any known related miRNAs. The results of case studies for three human diseases (glioblastoma, myocardial infarction and type 1 diabetes showed that all of the top 10 ranked miRNAs having no known associations with these three diseases in existing miRNA-disease databases were directly or indirectly confirmed by our latest literature mining. All these results demonstrated the reliability and efficiency of CHNmiRD, and it is anticipated that CHNmiRD will serve as a powerful bioinformatics method for mining novel disease-related miRNAs and providing a new perspective into molecular mechanisms underlying human diseases at the post-transcriptional level. CHNmiRD is freely available at http://www.bio-bigdata.com/CHNmiRD.

Construction of an integrated genetic linkage map for the A genome of Brassica napus using SSR markers derived from sequenced BACs in B. rapa

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King Graham J

2010-10-01

Full Text Available Abstract Background The Multinational Brassica rapa Genome Sequencing Project (BrGSP has developed valuable genomic resources, including BAC libraries, BAC-end sequences, genetic and physical maps, and seed BAC sequences for Brassica rapa. An integrated linkage map between the amphidiploid B. napus and diploid B. rapa will facilitate the rapid transfer of these valuable resources from B. rapa to B. napus (Oilseed rape, Canola. Results In this study, we identified over 23,000 simple sequence repeats (SSRs from 536 sequenced BACs. 890 SSR markers (designated as BrGMS were developed and used for the construction of an integrated linkage map for the A genome in B. rapa and B. napus. Two hundred and nineteen BrGMS markers were integrated to an existing B. napus linkage map (BnaNZDH. Among these mapped BrGMS markers, 168 were only distributed on the A genome linkage groups (LGs, 18 distrubuted both on the A and C genome LGs, and 33 only distributed on the C genome LGs. Most of the A genome LGs in B. napus were collinear with the homoeologous LGs in B. rapa, although minor inversions or rearrangements occurred on A2 and A9. The mapping of these BAC-specific SSR markers enabled assignment of 161 sequenced B. rapa BACs, as well as the associated BAC contigs to the A genome LGs of B. napus. Conclusion The genetic mapping of SSR markers derived from sequenced BACs in B. rapa enabled direct links to be established between the B. napus linkage map and a B. rapa physical map, and thus the assignment of B. rapa BACs and the associated BAC contigs to the B. napus linkage map. This integrated genetic linkage map will facilitate exploitation of the B. rapa annotated genomic resources for gene tagging and map-based cloning in B. napus, and for comparative analysis of the A genome within Brassica species.

Complete Genome Sequence of Germline Chromosomally Integrated Human Herpesvirus 6A and Analyses Integration Sites Define a New Human Endogenous Virus with Potential to Reactivate as an Emerging Infection.

Science.gov (United States)

Tweedy, Joshua; Spyrou, Maria Alexandra; Pearson, Max; Lassner, Dirk; Kuhl, Uwe; Gompels, Ursula A

2016-01-15

Human herpesvirus-6A and B (HHV-6A, HHV-6B) have recently defined endogenous genomes, resulting from integration into the germline: chromosomally-integrated "CiHHV-6A/B". These affect approximately 1.0% of human populations, giving potential for virus gene expression in every cell. We previously showed that CiHHV-6A was more divergent than CiHHV-6B by examining four genes in 44 European CiHHV-6A/B cardiac/haematology patients. There was evidence for gene expression/reactivation, implying functional non-defective genomes. To further define the relationship between HHV-6A and CiHHV-6A we used next-generation sequencing to characterize genomes from three CiHHV-6A cardiac patients. Comparisons to known exogenous HHV-6A showed CiHHV-6A genomes formed a separate clade; including all 85 non-interrupted genes and necessary cis-acting signals for reactivation as infectious virus. Greater single nucleotide polymorphism (SNP) density was defined in 16 genes and the direct repeats (DR) terminal regions. Using these SNPs, deep sequencing analyses demonstrated superinfection with exogenous HHV-6A in two of the CiHHV-6A patients with recurrent cardiac disease. Characterisation of the integration sites in twelve patients identified the human chromosome 17p subtelomere as a prevalent site, which had specific repeat structures and phylogenetically related CiHHV-6A coding sequences indicating common ancestral origins. Overall CiHHV-6A genomes were similar, but distinct from known exogenous HHV-6A virus, and have the capacity to reactivate as emerging virus infections.

Knowledge base and neural network approach for protein secondary structure prediction.

Science.gov (United States)

Patel, Maulika S; Mazumdar, Himanshu S

2014-11-21

Protein structure prediction is of great relevance given the abundant genomic and proteomic data generated by the genome sequencing projects. Protein secondary structure prediction is addressed as a sub task in determining the protein tertiary structure and function. In this paper, a novel algorithm, KB-PROSSP-NN, which is a combination of knowledge base and modeling of the exceptions in the knowledge base using neural networks for protein secondary structure prediction (PSSP), is proposed. The knowledge base is derived from a proteomic sequence-structure database and consists of the statistics of association between the 5-residue words and corresponding secondary structure. The predicted results obtained using knowledge base are refined with a Backpropogation neural network algorithm. Neural net models the exceptions of the knowledge base. The Q3 accuracy of 90% and 82% is achieved on the RS126 and CB396 test sets respectively which suggest improvement over existing state of art methods. Copyright © 2014 Elsevier Ltd. All rights reserved.

VarB Plus: An Integrated Tool for Visualization of Genome Variation Datasets

KAUST Repository

Hidayah, Lailatul

2012-07-01

Research on genomic sequences has been improving significantly as more advanced technology for sequencing has been developed. This opens enormous opportunities for sequence analysis. Various analytical tools have been built for purposes such as sequence assembly, read alignments, genome browsing, comparative genomics, and visualization. From the visualization perspective, there is an increasing trend towards use of large-scale computation. However, more than power is required to produce an informative image. This is a challenge that we address by providing several ways of representing biological data in order to advance the inference endeavors of biologists. This thesis focuses on visualization of variations found in genomic sequences. We develop several visualization functions and embed them in an existing variation visualization tool as extensions. The tool we improved is named VarB, hence the nomenclature for our enhancement is VarB Plus. To the best of our knowledge, besides VarB, there is no tool that provides the capability of dynamic visualization of genome variation datasets as well as statistical analysis. Dynamic visualization allows users to toggle different parameters on and off and see the results on the fly. The statistical analysis includes Fixation Index, Relative Variant Density, and Tajima’s D. Hence we focused our efforts on this tool. The scope of our work includes plots of per-base genome coverage, Principal Coordinate Analysis (PCoA), integration with a read alignment viewer named LookSeq, and visualization of geo-biological data. In addition to description of embedded functionalities, significance, and limitations, future improvements are discussed. The result is four extensions embedded successfully in the original tool, which is built on the Qt framework in C++. Hence it is portable to numerous platforms. Our extensions have shown acceptable execution time in a beta testing with various high-volume published datasets, as well as positive

INTEGRATING ARTIFICIAL NEURAL NETWORKS FOR DEVELOPING TELEMEDICINE SOLUTION

Directory of Open Access Journals (Sweden)

Mihaela GHEORGHE

2015-06-01

Full Text Available Artificial intelligence is assuming an increasing important role in the telemedicine field, especially neural networks with their ability to achieve meaning from large sets of data characterized by lacking exactness and accuracy. These can be used for assisting physicians or other clinical staff in the process of taking decisions under uncertainty. Thus, machine learning methods which are specific to this technology are offering an approach for prediction based on pattern classification. This paper aims to present the importance of neural networks in detecting trends and extracting patterns which can be used within telemedicine domains, particularly for taking medical diagnosis decisions.

Biodiversity Meets Neuroscience: From the Sequencing Ship (Ship-Seq) to Deciphering Parallel Evolution of Neural Systems in Omic’s Era

Science.gov (United States)

Moroz, Leonid L.

2015-01-01

The origins of neural systems and centralized brains are one of the major transitions in evolution. These events might occur more than once over 570–600 million years. The convergent evolution of neural circuits is evident from a diversity of unique adaptive strategies implemented by ctenophores, cnidarians, acoels, molluscs, and basal deuterostomes. But, further integration of biodiversity research and neuroscience is required to decipher critical events leading to development of complex integrative and cognitive functions. Here, we outline reference species and interdisciplinary approaches in reconstructing the evolution of nervous systems. In the “omic” era, it is now possible to establish fully functional genomics laboratories aboard of oceanic ships and perform sequencing and real-time analyses of data at any oceanic location (named here as Ship-Seq). In doing so, fragile, rare, cryptic, and planktonic organisms, or even entire marine ecosystems, are becoming accessible directly to experimental and physiological analyses by modern analytical tools. Thus, we are now in a position to take full advantages from countless “experiments” Nature performed for us in the course of 3.5 billion years of biological evolution. Together with progress in computational and comparative genomics, evolutionary neuroscience, proteomic and developmental biology, a new surprising picture is emerging that reveals many ways of how nervous systems evolved. As a result, this symposium provides a unique opportunity to revisit old questions about the origins of biological complexity. PMID:26163680

Evolution of plant virus movement proteins from the 30K superfamily and of their homologs integrated in plant genomes

Energy Technology Data Exchange (ETDEWEB)

Mushegian, Arcady R., E-mail: mushegian2@gmail.com [Division of Molecular and Cellular Biosciences, National Science Foundation, 4201 Wilson Boulevard, Arlington, VA 22230 (United States); Elena, Santiago F., E-mail: sfelena@ibmcp.upv.es [Instituto de Biología Molecular y Celular de Plantas, CSIC-UPV, 46022 València (Spain); The Santa Fe Institute, Santa Fe, NM 87501 (United States)

2015-02-15

Homologs of Tobacco mosaic virus 30K cell-to-cell movement protein are encoded by diverse plant viruses. Mechanisms of action and evolutionary origins of these proteins remain obscure. We expand the picture of conservation and evolution of the 30K proteins, producing sequence alignment of the 30K superfamily with the broadest phylogenetic coverage thus far and illuminating structural features of the core all-beta fold of these proteins. Integrated copies of pararetrovirus 30K movement genes are prevalent in euphyllophytes, with at least one copy intact in nearly every examined species, and mRNAs detected for most of them. Sequence analysis suggests repeated integrations, pseudogenizations, and positive selection in those provirus genes. An unannotated 30K-superfamily gene in Arabidopsis thaliana genome is likely expressed as a fusion with the At1g37113 transcript. This molecular background of endopararetrovirus gene products in plants may change our view of virus infection and pathogenesis, and perhaps of cellular homeostasis in the hosts. - Highlights: • Sequence region shared by plant virus “30K” movement proteins has an all-beta fold. • Most euphyllophyte genomes contain integrated copies of pararetroviruses. • These integrated virus genomes often include intact movement protein genes. • Molecular evidence suggests that these “30K” genes may be selected for function.

Complete Genome Sequence of Germline Chromosomally Integrated Human Herpesvirus 6A and Analyses Integration Sites Define a New Human Endogenous Virus with Potential to Reactivate as an Emerging Infection

Science.gov (United States)

Tweedy, Joshua; Spyrou, Maria Alexandra; Pearson, Max; Lassner, Dirk; Kuhl, Uwe; Gompels, Ursula A.

2016-01-01

Human herpesvirus-6A and B (HHV-6A, HHV-6B) have recently defined endogenous genomes, resulting from integration into the germline: chromosomally-integrated “CiHHV-6A/B”. These affect approximately 1.0% of human populations, giving potential for virus gene expression in every cell. We previously showed that CiHHV-6A was more divergent than CiHHV-6B by examining four genes in 44 European CiHHV-6A/B cardiac/haematology patients. There was evidence for gene expression/reactivation, implying functional non-defective genomes. To further define the relationship between HHV-6A and CiHHV-6A we used next-generation sequencing to characterize genomes from three CiHHV-6A cardiac patients. Comparisons to known exogenous HHV-6A showed CiHHV-6A genomes formed a separate clade; including all 85 non-interrupted genes and necessary cis-acting signals for reactivation as infectious virus. Greater single nucleotide polymorphism (SNP) density was defined in 16 genes and the direct repeats (DR) terminal regions. Using these SNPs, deep sequencing analyses demonstrated superinfection with exogenous HHV-6A in two of the CiHHV-6A patients with recurrent cardiac disease. Characterisation of the integration sites in twelve patients identified the human chromosome 17p subtelomere as a prevalent site, which had specific repeat structures and phylogenetically related CiHHV-6A coding sequences indicating common ancestral origins. Overall CiHHV-6A genomes were similar, but distinct from known exogenous HHV-6A virus, and have the capacity to reactivate as emerging virus infections. PMID:26784220

A robust network of double-strand break repair pathways governs genome integrity during C. elegans development.

NARCIS (Netherlands)

Pontier, D.B.; Tijsterman, M.

2009-01-01

To preserve genomic integrity, various mechanisms have evolved to repair DNA double-strand breaks (DSBs). Depending on cell type or cell cycle phase, DSBs can be repaired error-free, by homologous recombination, or with concomitant loss of sequence information, via nonhomologous end-joining (NHEJ)

metabolicMine: an integrated genomics, genetics and proteomics data warehouse for common metabolic disease research.

Science.gov (United States)

Lyne, Mike; Smith, Richard N; Lyne, Rachel; Aleksic, Jelena; Hu, Fengyuan; Kalderimis, Alex; Stepan, Radek; Micklem, Gos

2013-01-01

Common metabolic and endocrine diseases such as diabetes affect millions of people worldwide and have a major health impact, frequently leading to complications and mortality. In a search for better prevention and treatment, there is ongoing research into the underlying molecular and genetic bases of these complex human diseases, as well as into the links with risk factors such as obesity. Although an increasing number of relevant genomic and proteomic data sets have become available, the quantity and diversity of the data make their efficient exploitation challenging. Here, we present metabolicMine, a data warehouse with a specific focus on the genomics, genetics and proteomics of common metabolic diseases. Developed in collaboration with leading UK metabolic disease groups, metabolicMine integrates data sets from a range of experiments and model organisms alongside tools for exploring them. The current version brings together information covering genes, proteins, orthologues, interactions, gene expression, pathways, ontologies, diseases, genome-wide association studies and single nucleotide polymorphisms. Although the emphasis is on human data, key data sets from mouse and rat are included. These are complemented by interoperation with the RatMine rat genomics database, with a corresponding mouse version under development by the Mouse Genome Informatics (MGI) group. The web interface contains a number of features including keyword search, a library of Search Forms, the QueryBuilder and list analysis tools. This provides researchers with many different ways to analyse, view and flexibly export data. Programming interfaces and automatic code generation in several languages are supported, and many of the features of the web interface are available through web services. The combination of diverse data sets integrated with analysis tools and a powerful query system makes metabolicMine a valuable research resource. The web interface makes it accessible to first

Genome Modeling System: A Knowledge Management Platform for Genomics.

Directory of Open Access Journals (Sweden)

Malachi Griffith

2015-07-01

Full Text Available In this work, we present the Genome Modeling System (GMS, an analysis information management system capable of executing automated genome analysis pipelines at a massive scale. The GMS framework provides detailed tracking of samples and data coupled with reliable and repeatable analysis pipelines. The GMS also serves as a platform for bioinformatics development, allowing a large team to collaborate on data analysis, or an individual researcher to leverage the work of others effectively within its data management system. Rather than separating ad-hoc analysis from rigorous, reproducible pipelines, the GMS promotes systematic integration between the two. As a demonstration of the GMS, we performed an integrated analysis of whole genome, exome and transcriptome sequencing data from a breast cancer cell line (HCC1395 and matched lymphoblastoid line (HCC1395BL. These data are available for users to test the software, complete tutorials and develop novel GMS pipeline configurations. The GMS is available at https://github.com/genome/gms.

Enhanced robust fractional order proportional-plus-integral controller based on neural network for velocity control of permanent magnet synchronous motor.

Science.gov (United States)

Zhang, Bitao; Pi, YouGuo

2013-07-01

The traditional integer order proportional-integral-differential (IO-PID) controller is sensitive to the parameter variation or/and external load disturbance of permanent magnet synchronous motor (PMSM). And the fractional order proportional-integral-differential (FO-PID) control scheme based on robustness tuning method is proposed to enhance the robustness. But the robustness focuses on the open-loop gain variation of controlled plant. In this paper, an enhanced robust fractional order proportional-plus-integral (ERFOPI) controller based on neural network is proposed. The control law of the ERFOPI controller is acted on a fractional order implement function (FOIF) of tracking error but not tracking error directly, which, according to theory analysis, can enhance the robust performance of system. Tuning rules and approaches, based on phase margin, crossover frequency specification and robustness rejecting gain variation, are introduced to obtain the parameters of ERFOPI controller. And the neural network algorithm is used to adjust the parameter of FOIF. Simulation and experimental results show that the method proposed in this paper not only achieve favorable tracking performance, but also is robust with regard to external load disturbance and parameter variation. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

Statistical Viewer: a tool to upload and integrate linkage and association data as plots displayed within the Ensembl genome browser

Directory of Open Access Journals (Sweden)

Hauser Elizabeth R

2005-04-01

Full Text Available Abstract Background To facilitate efficient selection and the prioritization of candidate complex disease susceptibility genes for association analysis, increasingly comprehensive annotation tools are essential to integrate, visualize and analyze vast quantities of disparate data generated by genomic screens, public human genome sequence annotation and ancillary biological databases. We have developed a plug-in package for Ensembl called "Statistical Viewer" that facilitates the analysis of genomic features and annotation in the regions of interest defined by linkage analysis. Results Statistical Viewer is an add-on package to the open-source Ensembl Genome Browser and Annotation System that displays disease study-specific linkage and/or association data as 2 dimensional plots in new panels in the context of Ensembl's Contig View and Cyto View pages. An enhanced upload server facilitates the upload of statistical data, as well as additional feature annotation to be displayed in DAS tracts, in the form of Excel Files. The Statistical View panel, drawn directly under the ideogram, illustrates lod score values for markers from a study of interest that are plotted against their position in base pairs. A module called "Get Map" easily converts the genetic locations of markers to genomic coordinates. The graph is placed under the corresponding ideogram features a synchronized vertical sliding selection box that is seamlessly integrated into Ensembl's Contig- and Cyto- View pages to choose the region to be displayed in Ensembl's "Overview" and "Detailed View" panels. To resolve Association and Fine mapping data plots, a "Detailed Statistic View" plot corresponding to the "Detailed View" may be displayed underneath. Conclusion Features mapping to regions of linkage are accentuated when Statistic View is used in conjunction with the Distributed Annotation System (DAS to display supplemental laboratory information such as differentially expressed disease

Precision Interval Estimation of the Response Surface by Means of an Integrated Algorithm of Neural Network and Linear Regression

Science.gov (United States)

Lo, Ching F.

1999-01-01

The integration of Radial Basis Function Networks and Back Propagation Neural Networks with the Multiple Linear Regression has been accomplished to map nonlinear response surfaces over a wide range of independent variables in the process of the Modem Design of Experiments. The integrated method is capable to estimate the precision intervals including confidence and predicted intervals. The power of the innovative method has been demonstrated by applying to a set of wind tunnel test data in construction of response surface and estimation of precision interval.

Microenvironmental Heterogeneity Parallels Breast Cancer Progression: A Histology-Genomic Integration Analysis.

Directory of Open Access Journals (Sweden)

Rachael Natrajan

2016-02-01

Full Text Available The intra-tumor diversity of cancer cells is under intense investigation; however, little is known about the heterogeneity of the tumor microenvironment that is key to cancer progression and evolution. We aimed to assess the degree of microenvironmental heterogeneity in breast cancer and correlate this with genomic and clinical parameters.We developed a quantitative measure of microenvironmental heterogeneity along three spatial dimensions (3-D in solid tumors, termed the tumor ecosystem diversity index (EDI, using fully automated histology image analysis coupled with statistical measures commonly used in ecology. This measure was compared with disease-specific survival, key mutations, genome-wide copy number, and expression profiling data in a retrospective study of 510 breast cancer patients as a test set and 516 breast cancer patients as an independent validation set. In high-grade (grade 3 breast cancers, we uncovered a striking link between high microenvironmental heterogeneity measured by EDI and a poor prognosis that cannot be explained by tumor size, genomics, or any other data types. However, this association was not observed in low-grade (grade 1 and 2 breast cancers. The prognostic value of EDI was superior to known prognostic factors and was enhanced with the addition of TP53 mutation status (multivariate analysis test set, p = 9 × 10-4, hazard ratio = 1.47, 95% CI 1.17-1.84; validation set, p = 0.0011, hazard ratio = 1.78, 95% CI 1.26-2.52. Integration with genome-wide profiling data identified losses of specific genes on 4p14 and 5q13 that were enriched in grade 3 tumors with high microenvironmental diversity that also substratified patients into poor prognostic groups. Limitations of this study include the number of cell types included in the model, that EDI has prognostic value only in grade 3 tumors, and that our spatial heterogeneity measure was dependent on spatial scale and tumor size.To our knowledge, this is the first

Signal Processing and Neural Network Simulator

Science.gov (United States)

Tebbe, Dennis L.; Billhartz, Thomas J.; Doner, John R.; Kraft, Timothy T.

1995-04-01

The signal processing and neural network simulator (SPANNS) is a digital signal processing simulator with the capability to invoke neural networks into signal processing chains. This is a generic tool which will greatly facilitate the design and simulation of systems with embedded neural networks. The SPANNS is based on the Signal Processing WorkSystemTM (SPWTM), a commercial-off-the-shelf signal processing simulator. SPW provides a block diagram approach to constructing signal processing simulations. Neural network paradigms implemented in the SPANNS include Backpropagation, Kohonen Feature Map, Outstar, Fully Recurrent, Adaptive Resonance Theory 1, 2, & 3, and Brain State in a Box. The SPANNS was developed by integrating SAIC's Industrial Strength Neural Networks (ISNN) Software into SPW.

A statistical framework to predict functional non-coding regions in the human genome through integrated analysis of annotation data.

Science.gov (United States)

Lu, Qiongshi; Hu, Yiming; Sun, Jiehuan; Cheng, Yuwei; Cheung, Kei-Hoi; Zhao, Hongyu

2015-05-27

Identifying functional regions in the human genome is a major goal in human genetics. Great efforts have been made to functionally annotate the human genome either through computational predictions, such as genomic conservation, or high-throughput experiments, such as the ENCODE project. These efforts have resulted in a rich collection of functional annotation data of diverse types that need to be jointly analyzed for integrated interpretation and annotation. Here we present GenoCanyon, a whole-genome annotation method that performs unsupervised statistical learning using 22 computational and experimental annotations thereby inferring the functional potential of each position in the human genome. With GenoCanyon, we are able to predict many of the known functional regions. The ability of predicting functional regions as well as its generalizable statistical framework makes GenoCanyon a unique and powerful tool for whole-genome annotation. The GenoCanyon web server is available at http://genocanyon.med.yale.edu.

Neural Parallel Engine: A toolbox for massively parallel neural signal processing.

Science.gov (United States)

Tam, Wing-Kin; Yang, Zhi

2018-05-01

Large-scale neural recordings provide detailed information on neuronal activities and can help elicit the underlying neural mechanisms of the brain. However, the computational burden is also formidable when we try to process the huge data stream generated by such recordings. In this study, we report the development of Neural Parallel Engine (NPE), a toolbox for massively parallel neural signal processing on graphical processing units (GPUs). It offers a selection of the most commonly used routines in neural signal processing such as spike detection and spike sorting, including advanced algorithms such as exponential-component-power-component (EC-PC) spike detection and binary pursuit spike sorting. We also propose a new method for detecting peaks in parallel through a parallel compact operation. Our toolbox is able to offer a 5× to 110× speedup compared with its CPU counterparts depending on the algorithms. A user-friendly MATLAB interface is provided to allow easy integration of the toolbox into existing workflows. Previous efforts on GPU neural signal processing only focus on a few rudimentary algorithms, are not well-optimized and often do not provide a user-friendly programming interface to fit into existing workflows. There is a strong need for a comprehensive toolbox for massively parallel neural signal processing. A new toolbox for massively parallel neural signal processing has been created. It can offer significant speedup in processing signals from large-scale recordings up to thousands of channels. Copyright © 2018 Elsevier B.V. All rights reserved.

The catfish genome database cBARBEL: an informatic platform for genome biology of ictalurid catfish.

Science.gov (United States)

Lu, Jianguo; Peatman, Eric; Yang, Qing; Wang, Shaolin; Hu, Zhiliang; Reecy, James; Kucuktas, Huseyin; Liu, Zhanjiang

2011-01-01

The catfish genome database, cBARBEL (abbreviated from catfish Breeder And Researcher Bioinformatics Entry Location) is an online open-access database for genome biology of ictalurid catfish (Ictalurus spp.). It serves as a comprehensive, integrative platform for all aspects of catfish genetics, genomics and related data resources. cBARBEL provides BLAST-based, fuzzy and specific search functions, visualization of catfish linkage, physical and integrated maps, a catfish EST contig viewer with SNP information overlay, and GBrowse-based organization of catfish genomic data based on sequence similarity with zebrafish chromosomes. Subsections of the database are tightly related, allowing a user with a sequence or search string of interest to navigate seamlessly from one area to another. As catfish genome sequencing proceeds and ongoing quantitative trait loci (QTL) projects bear fruit, cBARBEL will allow rapid data integration and dissemination within the catfish research community and to interested stakeholders. cBARBEL can be accessed at http://catfishgenome.org.

The openness of pluripotent epigenome - Defining the genomic integrity of stemness for regenerative medicine

Directory of Open Access Journals (Sweden)

Xuejun H Parsons

2014-02-01

Full Text Available This article is an editorial, and it doesn't include an abstract. Full text of this article is available in HTML and PDF.Cite this article as: Parsons XH. The openness of pluripotent epigenome - Defining the genomic Integrity of stemness for regenerative medicine. Int J Cancer Ther Oncol 2014; 2(1:020114.DOI: http://dx.doi.org/10.14319/ijcto.0201.14

FISH Oracle 2: a web server for integrative visualization of genomic data in cancer research.

Science.gov (United States)

Mader, Malte; Simon, Ronald; Kurtz, Stefan

2014-03-31

A comprehensive view on all relevant genomic data is instrumental for understanding the complex patterns of molecular alterations typically found in cancer cells. One of the most effective ways to rapidly obtain an overview of genomic alterations in large amounts of genomic data is the integrative visualization of genomic events. We developed FISH Oracle 2, a web server for the interactive visualization of different kinds of downstream processed genomics data typically available in cancer research. A powerful search interface and a fast visualization engine provide a highly interactive visualization for such data. High quality image export enables the life scientist to easily communicate their results. A comprehensive data administration allows to keep track of the available data sets. We applied FISH Oracle 2 to published data and found evidence that, in colorectal cancer cells, the gene TTC28 may be inactivated in two different ways, a fact that has not been published before. The interactive nature of FISH Oracle 2 and the possibility to store, select and visualize large amounts of downstream processed data support life scientists in generating hypotheses. The export of high quality images supports explanatory data visualization, simplifying the communication of new biological findings. A FISH Oracle 2 demo server and the software is available at http://www.zbh.uni-hamburg.de/fishoracle.

High speed digital interfacing for a neural data acquisition system

Directory of Open Access Journals (Sweden)

Bahr Andreas

2016-09-01

Full Text Available Diseases like schizophrenia and genetic epilepsy are supposed to be caused by disorders in the early development of the brain. For the further investigation of these relationships a custom designed application specific integrated circuit (ASIC was developed that is optimized for the recording from neonatal mice [Bahr A, Abu-Saleh L, Schroeder D, Krautschneider W. 16 Channel Neural Recording Integrated Circuit with SPI Interface and Error Correction Coding. Proc. 9th BIOSTEC 2016. Biodevices: Rome, Italy, 2016; 1: 263; Bahr A, Abu-Saleh L, Schroeder D, Krautschneider W. Development of a neural recording mixed signal integrated circuit for biomedical signal acquisition. Biomed Eng Biomed Tech Abstracts 2015; 60(S1: 298–299; Bahr A, Abu-Saleh L, Schroeder D, Krautschneider WH. 16 Channel Neural Recording Mixed Signal ASIC. CDNLive EMEA 2015 Conference Proceedings, 2015.]. To enable the live display of the neural signals a multichannel neural data acquisition system with live display functionality is presented. It implements a high speed data transmission from the ASIC to a computer with a live display functionality. The system has been successfully implemented and was used in a neural recording of a head-fixed mouse.

Toward allotetraploid cotton genome assembly: integration of a high-density molecular genetic linkage map with DNA sequence information

Science.gov (United States)

2012-01-01

Background Cotton is the world’s most important natural textile fiber and a significant oilseed crop. Decoding cotton genomes will provide the ultimate reference and resource for research and utilization of the species. Integration of high-density genetic maps with genomic sequence information will largely accelerate the process of whole-genome assembly in cotton. Results In this paper, we update a high-density interspecific genetic linkage map of allotetraploid cultivated cotton. An additional 1,167 marker loci have been added to our previously published map of 2,247 loci. Three new marker types, InDel (insertion-deletion) and SNP (single nucleotide polymorphism) developed from gene information, and REMAP (retrotransposon-microsatellite amplified polymorphism), were used to increase map density. The updated map consists of 3,414 loci in 26 linkage groups covering 3,667.62 cM with an average inter-locus distance of 1.08 cM. Furthermore, genome-wide sequence analysis was finished using 3,324 informative sequence-based markers and publicly-available Gossypium DNA sequence information. A total of 413,113 EST and 195 BAC sequences were physically anchored and clustered by 3,324 sequence-based markers. Of these, 14,243 ESTs and 188 BACs from different species of Gossypium were clustered and specifically anchored to the high-density genetic map. A total of 2,748 candidate unigenes from 2,111 ESTs clusters and 63 BACs were mined for functional annotation and classification. The 337 ESTs/genes related to fiber quality traits were integrated with 132 previously reported cotton fiber quality quantitative trait loci, which demonstrated the important roles in fiber quality of these genes. Higher-level sequence conservation between different cotton species and between the A- and D-subgenomes in tetraploid cotton was found, indicating a common evolutionary origin for orthologous and paralogous loci in Gossypium. Conclusion This study will serve as a valuable genomic resource

Inter-replicon Gene Flow Contributes to Transcriptional Integration in the Sinorhizobium meliloti Multipartite Genome.

Science.gov (United States)

diCenzo, George C; Wellappili, Deelaka; Golding, G Brian; Finan, Turlough M

2018-05-04

Integration of newly acquired genes into existing regulatory networks is necessary for successful horizontal gene transfer (HGT). Ten percent of bacterial species contain at least two DNA replicons over 300 kilobases in size, with the secondary replicons derived predominately through HGT. The Sinorhizobium meliloti genome is split between a 3.7 Mb chromosome, a 1.7 Mb chromid consisting largely of genes acquired through ancient HGT, and a 1.4 Mb megaplasmid consisting primarily of recently acquired genes. Here, RNA-sequencing is used to examine the transcriptional consequences of massive, synthetic genome reduction produced through the removal of the megaplasmid and/or the chromid. Removal of the pSymA megaplasmid influenced the transcription of only six genes. In contrast, removal of the chromid influenced expression of ∼8% of chromosomal genes and ∼4% of megaplasmid genes. This was mediated in part by the loss of the ETR DNA region whose presence on pSymB is due to a translocation from the chromosome. No obvious functional bias among the up-regulated genes was detected, although genes with putative homologs on the chromid were enriched. Down-regulated genes were enriched in motility and sensory transduction pathways. Four transcripts were examined further, and in each case the transcriptional change could be traced to loss of specific pSymB regions. In particularly, a chromosomal transporter was induced due to deletion of bdhA likely mediated through 3-hydroxybutyrate accumulation. These data provide new insights into the evolution of the multipartite bacterial genome, and more generally into the integration of horizontally acquired genes into the transcriptome. Copyright © 2018 diCenzo, et al.

Inter-replicon Gene Flow Contributes to Transcriptional Integration in the Sinorhizobium meliloti Multipartite Genome

Directory of Open Access Journals (Sweden)

George C. diCenzo

2018-05-01

Full Text Available Integration of newly acquired genes into existing regulatory networks is necessary for successful horizontal gene transfer (HGT. Ten percent of bacterial species contain at least two DNA replicons over 300 kilobases in size, with the secondary replicons derived predominately through HGT. The Sinorhizobium meliloti genome is split between a 3.7 Mb chromosome, a 1.7 Mb chromid consisting largely of genes acquired through ancient HGT, and a 1.4 Mb megaplasmid consisting primarily of recently acquired genes. Here, RNA-sequencing is used to examine the transcriptional consequences of massive, synthetic genome reduction produced through the removal of the megaplasmid and/or the chromid. Removal of the pSymA megaplasmid influenced the transcription of only six genes. In contrast, removal of the chromid influenced expression of ∼8% of chromosomal genes and ∼4% of megaplasmid genes. This was mediated in part by the loss of the ETR DNA region whose presence on pSymB is due to a translocation from the chromosome. No obvious functional bias among the up-regulated genes was detected, although genes with putative homologs on the chromid were enriched. Down-regulated genes were enriched in motility and sensory transduction pathways. Four transcripts were examined further, and in each case the transcriptional change could be traced to loss of specific pSymB regions. In particularly, a chromosomal transporter was induced due to deletion of bdhA likely mediated through 3-hydroxybutyrate accumulation. These data provide new insights into the evolution of the multipartite bacterial genome, and more generally into the integration of horizontally acquired genes into the transcriptome.

Plasmid-based generation of induced neural stem cells from adult human fibroblasts

Directory of Open Access Journals (Sweden)

Philipp Capetian

2016-10-01

Full Text Available Direct reprogramming from somatic to neural cell types has become an alternative to induced pluripotent stem cells. Most protocols employ viral expression systems, posing the risk of random genomic integration. Recent developments led to plasmid-based protocols, lowering this risk. However, these protocols either relied on continuous presence of a variety of small molecules or were only able to reprogram murine cells. We therefore established a reprogramming protocol based on vectors containing the Epstein-Barr virus (EBV-derived oriP/EBNA1 as well as the defined expression factors Oct3/4, Sox2, Klf4, L-myc, Lin28, and a small hairpin directed against p53. We employed a defined neural medium in combination with the neurotrophins bFGF, EGF and FGF4 for cultivation without the addition of small molecules. After reprogramming, cells demonstrated a temporary increase in the expression of endogenous Oct3/4. We obtained induced neural stem cells (iNSC 30 days after transfection. In contrast to previous results, plasmid vectors as well as a residual expression of reprogramming factors remained detectable in all cell lines. Cells showed a robust differentiation into neuronal (72% and glial cells (9% astrocytes, 6% oligodendrocytes. Despite the temporary increase of pluripotency-associated Oct3/4 expression during reprogramming, we did not detect pluripotent stem cells or non-neural cells in culture (except occasional residual fibroblasts. Neurons showed electrical activity and functional glutamatergic synapses. Our results demonstrate that reprogramming adult human fibroblasts to iNSC by plasmid vectors and basic neural medium without small molecules is possible and feasible. However, a full set of pluripotency-associated transcription factors may indeed result in the acquisition of a transient (at least partial pluripotent intermediate during reprogramming. In contrast to previous reports, the EBV-based plasmid system remained present and active inside

Neural Network Based Model of an Industrial Oil-Fired Boiler System ...

African Journals Online (AJOL)

A two-layer feed-forward neural network with Hyperbolic tangent sigmoid ... The neural network model when subjected to test, using the validation input data; ... Proportional Integral Derivative (PID) Controller is used to control the neural ...

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.

Integrative computational approach for genome-based study of microbial lipid-degrading enzymes.

Science.gov (United States)

Vorapreeda, Tayvich; Thammarongtham, Chinae; Laoteng, Kobkul

2016-07-01

Lipid-degrading or lipolytic enzymes have gained enormous attention in academic and industrial sectors. Several efforts are underway to discover new lipase enzymes from a variety of microorganisms with particular catalytic properties to be used for extensive applications. In addition, various tools and strategies have been implemented to unravel the functional relevance of the versatile lipid-degrading enzymes for special purposes. This review highlights the study of microbial lipid-degrading enzymes through an integrative computational approach. The identification of putative lipase genes from microbial genomes and metagenomic libraries using homology-based mining is discussed, with an emphasis on sequence analysis of conserved motifs and enzyme topology. Molecular modelling of three-dimensional structure on the basis of sequence similarity is shown to be a potential approach for exploring the structural and functional relationships of candidate lipase enzymes. The perspectives on a discriminative framework of cutting-edge tools and technologies, including bioinformatics, computational biology, functional genomics and functional proteomics, intended to facilitate rapid progress in understanding lipolysis mechanism and to discover novel lipid-degrading enzymes of microorganisms are discussed.

The ctenophore genome and the evolutionary origins of neural systems

NARCIS (Netherlands)

Moroz, Leonid L.; Kocot, Kevin M.; Citarella, Mathew R.; Dosung, Sohn; Norekian, Tigran P.; Povolotskaya, Inna S.; Grigorenko, Anastasia P.; Dailey, Christopher; Berezikov, Eugene; Buckley, Katherine M.; Ptitsyn, Andrey; Reshetov, Denis; Mukherjee, Krishanu; Moroz, Tatiana P.; Bobkova, Yelena; Yu, Fahong; Kapitonov, Vladimir V.; Jurka, Jerzy; Bobkov, Yuri V.; Swore, Joshua J.; Girardo, David O.; Fodor, Alexander; Gusev, Fedor; Sanford, Rachel; Bruders, Rebecca; Kittler, Ellen; Mills, Claudia E.; Rast, Jonathan P.; Derelle, Romain; Solovyev, Victor V.; Kondrashov, Fyodor A.; Swalla, Billie J.; Sweedler, Jonathan V.; Rogaev, Evgeny I.; Halanych, Kenneth M.; Kohn, Andrea B.

2014-01-01

The origins of neural systems remain unresolved. In contrast to other basal metazoans, ctenophores (comb jellies) have both complex nervous and mesoderm-derived muscular systems. These holoplanktonic predators also have sophisticated ciliated locomotion, behaviour and distinct development. Here we

Genome Variation Map: a data repository of genome variations in BIG Data Center

OpenAIRE

Song, Shuhui; Tian, Dongmei; Li, Cuiping; Tang, Bixia; Dong, Lili; Xiao, Jingfa; Bao, Yiming; Zhao, Wenming; He, Hang; Zhang, Zhang

2017-01-01

Abstract The Genome Variation Map (GVM; http://bigd.big.ac.cn/gvm/) is a public data repository of genome variations. As a core resource in the BIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, GVM dedicates to collect, integrate and visualize genome variations for a wide range of species, accepts submissions of different types of genome variations from all over the world and provides free open access to all publicly available data in support of worldwide research a...

Molecular annotation of integrative feeding neural circuits.

Science.gov (United States)

Pérez, Cristian A; Stanley, Sarah A; Wysocki, Robert W; Havranova, Jana; Ahrens-Nicklas, Rebecca; Onyimba, Frances; Friedman, Jeffrey M

2011-02-02

The identity of higher-order neurons and circuits playing an associative role to control feeding is unknown. We injected pseudorabies virus, a retrograde tracer, into masseter muscle, salivary gland, and tongue of BAC-transgenic mice expressing GFP in specific neural populations and identified several CNS regions that project multisynaptically to the periphery. MCH and orexin neurons were identified in the lateral hypothalamus, and Nurr1 and Cnr1 in the amygdala and insular/rhinal cortices. Cholera toxin β tracing showed that insular Nurr1(+) and Cnr1(+) neurons project to the amygdala or lateral hypothalamus, respectively. Finally, we show that cortical Cnr1(+) neurons show increased Cnr1 mRNA and c-Fos expression after fasting, consistent with a possible role for Cnr1(+) neurons in feeding. Overall, these studies define a general approach for identifying specific molecular markers for neurons in complex neural circuits. These markers now provide a means for functional studies of specific neuronal populations in feeding or other complex behaviors. Copyright © 2011 Elsevier Inc. All rights reserved.

DNA double-strand break response in stem cells: mechanisms to maintain genomic integrity.

Science.gov (United States)

Nagaria, Pratik; Robert, Carine; Rassool, Feyruz V

2013-02-01

Embryonic stem cells (ESCs) represent the point of origin of all cells in a given organism and must protect their genomes from both endogenous and exogenous genotoxic stress. DNA double-strand breaks (DSBs) are one of the most lethal forms of damage, and failure to adequately repair DSBs would not only compromise the ability of SCs to self-renew and differentiate, but will also lead to genomic instability and disease. Herein, we describe the mechanisms by which ESCs respond to DSB-inducing agents such as reactive oxygen species (ROS) and ionizing radiation, compared to somatic cells. We will also discuss whether the DSB response is fully reprogrammed in induced pluripotent stem cells (iPSCs) and the role of the DNA damage response (DDR) in the reprogramming of these cells. ESCs have distinct mechanisms to protect themselves against DSBs and oxidative stress compared to somatic cells. The response to damage and stress is crucial for the maintenance of self-renewal and differentiation capacity in SCs. iPSCs appear to reprogram some of the responses to genotoxic stress. However, it remains to be determined if iPSCs also retain some DDR characteristics of the somatic cells of origin. The mechanisms regulating the genomic integrity in ESCs and iPSCs are critical for its safe use in regenerative medicine and may shed light on the pathways and factors that maintain genomic stability, preventing diseases such as cancer. This article is part of a Special Issue entitled Biochemistry of Stem Cells. Copyright © 2012 Elsevier B.V. All rights reserved.

Chromatin Remodeling BAF (SWI/SNF Complexes in Neural Development and Disorders

Directory of Open Access Journals (Sweden)

Godwin Sokpor

2017-08-01

Full Text Available The ATP-dependent BRG1/BRM associated factor (BAF chromatin remodeling complexes are crucial in regulating gene expression by controlling chromatin dynamics. Over the last decade, it has become increasingly clear that during neural development in mammals, distinct ontogenetic stage-specific BAF complexes derived from combinatorial assembly of their subunits are formed in neural progenitors and post-mitotic neural cells. Proper functioning of the BAF complexes plays critical roles in neural development, including the establishment and maintenance of neural fates and functionality. Indeed, recent human exome sequencing and genome-wide association studies have revealed that mutations in BAF complex subunits are linked to neurodevelopmental disorders such as Coffin-Siris syndrome, Nicolaides-Baraitser syndrome, Kleefstra's syndrome spectrum, Hirschsprung's disease, autism spectrum disorder, and schizophrenia. In this review, we focus on the latest insights into the functions of BAF complexes during neural development and the plausible mechanistic basis of how mutations in known BAF subunits are associated with certain neurodevelopmental disorders.

Chromatin Remodeling BAF (SWI/SNF) Complexes in Neural Development and Disorders

Science.gov (United States)

Sokpor, Godwin; Xie, Yuanbin; Rosenbusch, Joachim; Tuoc, Tran

2017-01-01

The ATP-dependent BRG1/BRM associated factor (BAF) chromatin remodeling complexes are crucial in regulating gene expression by controlling chromatin dynamics. Over the last decade, it has become increasingly clear that during neural development in mammals, distinct ontogenetic stage-specific BAF complexes derived from combinatorial assembly of their subunits are formed in neural progenitors and post-mitotic neural cells. Proper functioning of the BAF complexes plays critical roles in neural development, including the establishment and maintenance of neural fates and functionality. Indeed, recent human exome sequencing and genome-wide association studies have revealed that mutations in BAF complex subunits are linked to neurodevelopmental disorders such as Coffin-Siris syndrome, Nicolaides-Baraitser syndrome, Kleefstra's syndrome spectrum, Hirschsprung's disease, autism spectrum disorder, and schizophrenia. In this review, we focus on the latest insights into the functions of BAF complexes during neural development and the plausible mechanistic basis of how mutations in known BAF subunits are associated with certain neurodevelopmental disorders. PMID:28824374

Chromatin Remodeling BAF (SWI/SNF) Complexes in Neural Development and Disorders.

Science.gov (United States)

Sokpor, Godwin; Xie, Yuanbin; Rosenbusch, Joachim; Tuoc, Tran

2017-01-01

The ATP-dependent BRG1/BRM associated factor (BAF) chromatin remodeling complexes are crucial in regulating gene expression by controlling chromatin dynamics. Over the last decade, it has become increasingly clear that during neural development in mammals, distinct ontogenetic stage-specific BAF complexes derived from combinatorial assembly of their subunits are formed in neural progenitors and post-mitotic neural cells. Proper functioning of the BAF complexes plays critical roles in neural development, including the establishment and maintenance of neural fates and functionality. Indeed, recent human exome sequencing and genome-wide association studies have revealed that mutations in BAF complex subunits are linked to neurodevelopmental disorders such as Coffin-Siris syndrome, Nicolaides-Baraitser syndrome, Kleefstra's syndrome spectrum, Hirschsprung's disease, autism spectrum disorder, and schizophrenia. In this review, we focus on the latest insights into the functions of BAF complexes during neural development and the plausible mechanistic basis of how mutations in known BAF subunits are associated with certain neurodevelopmental disorders.

Integrative Genomic and Proteomic Analysis of the Response of Lactobacillus casei Zhang to Glucose Restriction.

Science.gov (United States)

Yu, Jie; Hui, Wenyan; Cao, Chenxia; Pan, Lin; Zhang, Heping; Zhang, Wenyi

2018-03-02

Nutrient starvation is an important survival challenge for bacteria during industrial production of functional foods. As next-generation sequencing technology has greatly advanced, we performed proteomic and genomic analysis to investigate the response of Lactobacillus casei Zhang to a glucose-restricted environment. L. casei Zhang strains were permitted to evolve in glucose-restricted or normal medium from a common ancestor over a 3 year period, and they were sampled at 1000, 2000, 3000, 4000, 5000, 6000, 7000, and 8000 generations and subjected to proteomic and genomic analyses. Genomic resequencing data revealed different point mutations and other mutational events in each selected generation of L. casei Zhang under glucose restriction stress. The differentially expressed proteins induced by glucose restriction were mostly related to fructose and mannose metabolism, carbohydrate metabolic processes, lyase activity, and amino-acid-transporting ATPase activity. Integrative proteomic and genomic analysis revealed that the mutations protected L. casei Zhang against glucose starvation by regulating other cellular carbohydrate, fatty acid, and amino acid catabolism; phosphoenolpyruvate system pathway activation; glycogen synthesis; ATP consumption; pyruvate metabolism; and general stress-response protein expression. The results help reveal the mechanisms of adapting to glucose starvation and provide new strategies for enhancing the industrial utility of L. casei Zhang.

Integrative Genomics Reveals Mechanisms of Copy Number Alterations Responsible for Transcriptional Deregulation in Colorectal Cancer

Science.gov (United States)

Camps, Jordi; Nguyen, Quang Tri; Padilla-Nash, Hesed M.; Knutsen, Turid; McNeil, Nicole E.; Wangsa, Danny; Hummon, Amanda B.; Grade, Marian; Ried, Thomas; Difilippantonio, Michael J.

2016-01-01

To evaluate the mechanisms and consequences of chromosomal aberrations in colorectal cancer (CRC), we used a combination of spectral karyotyping, array comparative genomic hybridization (aCGH), and array-based global gene expression profiling on 31 primary carcinomas and 15 established cell lines. Importantly, aCGH showed that the genomic profiles of primary tumors are recapitulated in the cell lines. We revealed a preponderance of chromosome breakpoints at sites of copy number variants (CNVs) in the CRC cell lines, a novel mechanism of DNA breakage in cancer. The integration of gene expression and aCGH led to the identification of 157 genes localized within high-level copy number changes whose transcriptional deregulation was significantly affected across all of the samples, thereby suggesting that these genes play a functional role in CRC. Genomic amplification at 8q24 was the most recurrent event and led to the overexpression of MYC and FAM84B. Copy number dependent gene expression resulted in deregulation of known cancer genes such as APC, FGFR2, and ERBB2. The identification of only 36 genes whose localization near a breakpoint could account for their observed deregulated expression demonstrates that the major mechanism for transcriptional deregulation in CRC is genomic copy number changes resulting from chromosomal aberrations. PMID:19691111

Neural precursor cells in the ischemic brain - integration, cellular crosstalk and consequences for stroke recovery

Directory of Open Access Journals (Sweden)

Dirk M. Hermann

2014-09-01

Full Text Available After an ischemic stroke, neural precursor cells (NPCs proliferate within major germinal niches of the brain. Endogenous NPCs subsequently migrate towards the ischemic lesion where they promote tissue remodelling and neural repair. Unfortunately, this restorative process is generally insufficient and thus unable to support a full recovery of lost neurological functions. Supported by solid experimental and preclinical data, the transplantation of exogenous NPCs has emerged as a potential tool for stroke treatment. Transplanted NPCs are thought to act mainly via trophic and immune modulatory effects, thereby complementing the restorative responses initially executed by the endogenous NPC population. Recent studies have attempted to elucidate how the therapeutic properties of transplanted NPCs vary depending on the route of transplantation. Systemic NPC delivery leads to potent immune modulatory actions, which prevent secondary neuronal degeneration, reduces glial scar formation, diminishes oxidative stress and stabilizes blood-brain barrier integrity. On the contrary, local stem cell delivery, allows for the accumulation of large numbers of transplanted NPCs in the brain, thus achieving high levels of locally available tissue trophic factors, which may better induce a strong endogenous NPC proliferative response.Herein we describe the diverse capabilities of exogenous (systemically vs locally transplanted NPCs in enhancing the endogenous neurogenic response after stroke, and how the route of transplantation may affect migration, survival, bystander effects and integration of the cellular graft. It is the authors’ claim that understanding these aspects will be of pivotal importance in discerning how transplanted NPCs exert their therapeutic effects in stroke.

The MedSeq Project: a randomized trial of integrating whole genome sequencing into clinical medicine.

Science.gov (United States)

Vassy, Jason L; Lautenbach, Denise M; McLaughlin, Heather M; Kong, Sek Won; Christensen, Kurt D; Krier, Joel; Kohane, Isaac S; Feuerman, Lindsay Z; Blumenthal-Barby, Jennifer; Roberts, J Scott; Lehmann, Lisa Soleymani; Ho, Carolyn Y; Ubel, Peter A; MacRae, Calum A; Seidman, Christine E; Murray, Michael F; McGuire, Amy L; Rehm, Heidi L; Green, Robert C

2014-03-20

illuminate the impact of integrating genomic medicine into the clinical care of patients but also inform the design of future studies. ClinicalTrials.gov identifier NCT01736566.

An Experimentation Platform for On-Chip Integration of Analog Neural Networks: A Pathway to Trusted and Robust Analog/RF ICs.

Science.gov (United States)

Maliuk, Dzmitry; Makris, Yiorgos

2015-08-01

We discuss the design of an experimentation platform intended for prototyping low-cost analog neural networks for on-chip integration with analog/RF circuits. The objective of such integration is to support various tasks, such as self-test, self-tuning, and trust/aging monitoring, which require classification of analog measurements obtained from on-chip sensors. Particular emphasis is given to cost-efficient implementation reflected in: 1) low energy and area budgets of circuits dedicated to neural networks; 2) robust learning in presence of analog inaccuracies; and 3) long-term retention of learned functionality. Our chip consists of a reconfigurable array of synapses and neurons operating below threshold and featuring sub-μW power consumption. The synapse circuits employ dual-mode weight storage: 1) a dynamic mode, for fast bidirectional weight updates during training and 2) a nonvolatile mode, for permanent storage of learned functionality. We discuss a robust learning strategy, and we evaluate the system performance on several benchmark problems, such as the XOR2-6 and two-spirals classification tasks.

Genomics in Public Health: Perspective from the Office of Public Health Genomics at the Centers for Disease Control and Prevention (CDC).

Science.gov (United States)

Green, Ridgely Fisk; Dotson, W David; Bowen, Scott; Kolor, Katherine; Khoury, Muin J

2015-01-01

The national effort to use genomic knowledge to save lives is gaining momentum, as illustrated by the inclusion of genomics in key public health initiatives, including Healthy People 2020, and the recent launch of the precision medicine initiative. The Office of Public Health Genomics (OPHG) at the Centers for Disease Control and Prevention (CDC) partners with state public health departments and others to advance the translation of genome-based discoveries into disease prevention and population health. To do this, OPHG has adopted an "identify, inform, and integrate" model: identify evidence-based genomic applications ready for implementation, inform stakeholders about these applications, and integrate these applications into public health at the local, state, and national level. This paper addresses current and future work at OPHG for integrating genomics into public health programs.

Genome Maps, a new generation genome browser.

Science.gov (United States)

Medina, Ignacio; Salavert, Francisco; Sanchez, Rubén; de Maria, Alejandro; Alonso, Roberto; Escobar, Pablo; Bleda, Marta; Dopazo, Joaquín

2013-07-01

Genome browsers have gained importance as more genomes and related genomic information become available. However, the increase of information brought about by new generation sequencing technologies is, at the same time, causing a subtle but continuous decrease in the efficiency of conventional genome browsers. Here, we present Genome Maps, a genome browser that implements an innovative model of data transfer and management. The program uses highly efficient technologies from the new HTML5 standard, such as scalable vector graphics, that optimize workloads at both server and client sides and ensure future scalability. Thus, data management and representation are entirely carried out by the browser, without the need of any Java Applet, Flash or other plug-in technology installation. Relevant biological data on genes, transcripts, exons, regulatory features, single-nucleotide polymorphisms, karyotype and so forth, are imported from web services and are available as tracks. In addition, several DAS servers are already included in Genome Maps. As a novelty, this web-based genome browser allows the local upload of huge genomic data files (e.g. VCF or BAM) that can be dynamically visualized in real time at the client side, thus facilitating the management of medical data affected by privacy restrictions. Finally, Genome Maps can easily be integrated in any web application by including only a few lines of code. Genome Maps is an open source collaborative initiative available in the GitHub repository (https://github.com/compbio-bigdata-viz/genome-maps). Genome Maps is available at: http://www.genomemaps.org.

Semantic Congruence Accelerates the Onset of the Neural Signals of Successful Memory Encoding.

Science.gov (United States)

Packard, Pau A; Rodríguez-Fornells, Antoni; Bunzeck, Nico; Nicolás, Berta; de Diego-Balaguer, Ruth; Fuentemilla, Lluís

2017-01-11

As the stream of experience unfolds, our memory system rapidly transforms current inputs into long-lasting meaningful memories. A putative neural mechanism that strongly influences how input elements are transformed into meaningful memory codes relies on the ability to integrate them with existing structures of knowledge or schemas. However, it is not yet clear whether schema-related integration neural mechanisms occur during online encoding. In the current investigation, we examined the encoding-dependent nature of this phenomenon in humans. We showed that actively integrating words with congruent semantic information provided by a category cue enhances memory for words and increases false recall. The memory effect of such active integration with congruent information was robust, even with an interference task occurring right after each encoding word list. In addition, via electroencephalography, we show in 2 separate studies that the onset of the neural signals of successful encoding appeared early (∼400 ms) during the encoding of congruent words. That the neural signals of successful encoding of congruent and incongruent information followed similarly ∼200 ms later suggests that this earlier neural response contributed to memory formation. We propose that the encoding of events that are congruent with readily available contextual semantics can trigger an accelerated onset of the neural mechanisms, supporting the integration of semantic information with the event input. This faster onset would result in a long-lasting and meaningful memory trace for the event but, at the same time, make it difficult to distinguish it from plausible but never encoded events (i.e., related false memories). Conceptual or schema congruence has a strong influence on long-term memory. However, the question of whether schema-related integration neural mechanisms occur during online encoding has yet to be clarified. We investigated the neural mechanisms reflecting how the active

A wireless integrated circuit for 100-channel charge-balanced neural stimulation.

Science.gov (United States)

Thurgood, B K; Warren, D J; Ledbetter, N M; Clark, G A; Harrison, R R

2009-12-01

The authors present the design of an integrated circuit for wireless neural stimulation, along with benchtop and in - vivo experimental results. The chip has the ability to drive 100 individual stimulation electrodes with constant-current pulses of varying amplitude, duration, interphasic delay, and repetition rate. The stimulation is performed by using a biphasic (cathodic and anodic) current source, injecting and retracting charge from the nervous system. Wireless communication and power are delivered over a 2.765-MHz inductive link. Only three off-chip components are needed to operate the stimulator: a 10-nF capacitor to aid in power-supply regulation, a small capacitor (power and command reception. The chip was fabricated in a commercially available 0.6- mum 2P3M BiCMOS process. The chip was able to activate motor fibers to produce muscle twitches via a Utah Slanted Electrode Array implanted in cat sciatic nerve, and to activate sensory fibers to recruit evoked potentials in somatosensory cortex.

Identifying the Integrated Neural Networks Involved in Capsaicin-Induced Pain Using fMRI in Awake TRPV1 Knockout and Wild-Type Rats

Directory of Open Access Journals (Sweden)

Jason Richard Yee

2015-02-01

Full Text Available In the present study, we used functional MRI in awake rats to investigate the pain response that accompanies intradermal injection of capsaicin into the hindpaw. To this end, we used BOLD imaging together with a 3D segmented, annotated rat atlas and computational analysis to identify the integrated neural circuits involved in capsaicin-induced pain. The specificity of the pain response to capsaicin was tested in a transgenic model that contains a biallelic deletion of the gene encoding for the transient receptor potential cation channel subfamily V member 1 (TRPV1. Capsaicin is an exogenous ligand for the TRPV1 receptor, and in wild-type rats, activated the putative pain neural circuit. In addition, capsaicin-treated wild-type rats exhibited activation in brain regions comprising the Papez circuit and habenular system, systems that play important roles in the integration of emotional information, and learning and memory of aversive information, respectively. As expected, capsaicin administration to TRPV1-KO rats failed to elicit the robust BOLD activation pattern observed in wild-type controls. However, the intradermal injection of formalin elicited a significant activation of the putative pain pathway as represented by such areas as the anterior cingulate, somatosensory cortex, parabrachial nucleus, and periaqueductal gray. Notably, comparison of neural responses to capsaicin in wild-type versus knock-out rats uncovered evidence that capsaicin may function in an antinociceptive capacity independent of TRPV1 signaling. Our data suggest that neuroimaging of pain in awake, conscious animals has the potential to inform the neurobiological basis of full and integrated perceptions of pain.

Rhesus monkey neural stem cell transplantation promotes neural regeneration in rats with hippocampal lesions

Directory of Open Access Journals (Sweden)

Li-juan Ye

2016-01-01

Full Text Available Rhesus monkey neural stem cells are capable of differentiating into neurons and glial cells. Therefore, neural stem cell transplantation can be used to promote functional recovery of the nervous system. Rhesus monkey neural stem cells (1 × 105 cells/μL were injected into bilateral hippocampi of rats with hippocampal lesions. Confocal laser scanning microscopy demonstrated that green fluorescent protein-labeled transplanted cells survived and grew well. Transplanted cells were detected at the lesion site, but also in the nerve fiber-rich region of the cerebral cortex and corpus callosum. Some transplanted cells differentiated into neurons and glial cells clustering along the ventricular wall, and integrated into the recipient brain. Behavioral tests revealed that spatial learning and memory ability improved, indicating that rhesus monkey neural stem cells noticeably improve spatial learning and memory abilities in rats with hippocampal lesions.

Development of an integrated genome informatics, data management and workflow infrastructure: A toolbox for the study of complex disease genetics

Directory of Open Access Journals (Sweden)

Burren Oliver S

2004-01-01

Full Text Available Abstract The genetic dissection of complex disease remains a significant challenge. Sample-tracking and the recording, processing and storage of high-throughput laboratory data with public domain data, require integration of databases, genome informatics and genetic analyses in an easily updated and scaleable format. To find genes involved in multifactorial diseases such as type 1 diabetes (T1D, chromosome regions are defined based on functional candidate gene content, linkage information from humans and animal model mapping information. For each region, genomic information is extracted from Ensembl, converted and loaded into ACeDB for manual gene annotation. Homology information is examined using ACeDB tools and the gene structure verified. Manually curated genes are extracted from ACeDB and read into the feature database, which holds relevant local genomic feature data and an audit trail of laboratory investigations. Public domain information, manually curated genes, polymorphisms, primers, linkage and association analyses, with links to our genotyping database, are shown in Gbrowse. This system scales to include genetic, statistical, quality control (QC and biological data such as expression analyses of RNA or protein, all linked from a genomics integrative display. Our system is applicable to any genetic study of complex disease, of either large or small scale.

Multiplexed precision genome editing with trackable genomic barcodes in yeast.

Science.gov (United States)

Roy, Kevin R; Smith, Justin D; Vonesch, Sibylle C; Lin, Gen; Tu, Chelsea Szu; Lederer, Alex R; Chu, Angela; Suresh, Sundari; Nguyen, Michelle; Horecka, Joe; Tripathi, Ashutosh; Burnett, Wallace T; Morgan, Maddison A; Schulz, Julia; Orsley, Kevin M; Wei, Wu; Aiyar, Raeka S; Davis, Ronald W; Bankaitis, Vytas A; Haber, James E; Salit, Marc L; St Onge, Robert P; Steinmetz, Lars M

2018-07-01

Our understanding of how genotype controls phenotype is limited by the scale at which we can precisely alter the genome and assess the phenotypic consequences of each perturbation. Here we describe a CRISPR-Cas9-based method for multiplexed accurate genome editing with short, trackable, integrated cellular barcodes (MAGESTIC) in Saccharomyces cerevisiae. MAGESTIC uses array-synthesized guide-donor oligos for plasmid-based high-throughput editing and features genomic barcode integration to prevent plasmid barcode loss and to enable robust phenotyping. We demonstrate that editing efficiency can be increased more than fivefold by recruiting donor DNA to the site of breaks using the LexA-Fkh1p fusion protein. We performed saturation editing of the essential gene SEC14 and identified amino acids critical for chemical inhibition of lipid signaling. We also constructed thousands of natural genetic variants, characterized guide mismatch tolerance at the genome scale, and ascertained that cryptic Pol III termination elements substantially reduce guide efficacy. MAGESTIC will be broadly useful to uncover the genetic basis of phenotypes in yeast.

cisMEP: an integrated repository of genomic epigenetic profiles and cis-regulatory modules in Drosophila.

Science.gov (United States)

Yang, Tzu-Hsien; Wang, Chung-Ching; Hung, Po-Cheng; Wu, Wei-Sheng

2014-01-01

Cis-regulatory modules (CRMs), or the DNA sequences required for regulating gene expression, play the central role in biological researches on transcriptional regulation in metazoan species. Nowadays, the systematic understanding of CRMs still mainly resorts to computational methods due to the time-consuming and small-scale nature of experimental methods. But the accuracy and reliability of different CRM prediction tools are still unclear. Without comparative cross-analysis of the results and combinatorial consideration with extra experimental information, there is no easy way to assess the confidence of the predicted CRMs. This limits the genome-wide understanding of CRMs. It is known that transcription factor binding and epigenetic profiles tend to determine functions of CRMs in gene transcriptional regulation. Thus integration of the genome-wide epigenetic profiles with systematically predicted CRMs can greatly help researchers evaluate and decipher the prediction confidence and possible transcriptional regulatory functions of these potential CRMs. However, these data are still fragmentary in the literatures. Here we performed the computational genome-wide screening for potential CRMs using different prediction tools and constructed the pioneer database, cisMEP (cis-regulatory module epigenetic profile database), to integrate these computationally identified CRMs with genomic epigenetic profile data. cisMEP collects the literature-curated TFBS location data and nine genres of epigenetic data for assessing the confidence of these potential CRMs and deciphering the possible CRM functionality. cisMEP aims to provide a user-friendly interface for researchers to assess the confidence of different potential CRMs and to understand the functions of CRMs through experimentally-identified epigenetic profiles. The deposited potential CRMs and experimental epigenetic profiles for confidence assessment provide experimentally testable hypotheses for the molecular mechanisms

Neural network and its application to CT imaging

Energy Technology Data Exchange (ETDEWEB)

Nikravesh, M.; Kovscek, A.R.; Patzek, T.W. [Lawrence Berkeley National Lab., CA (United States)] [and others

1997-02-01

We present an integrated approach to imaging the progress of air displacement by spontaneous imbibition of oil into sandstone. We combine Computerized Tomography (CT) scanning and neural network image processing. The main aspects of our approach are (I) visualization of the distribution of oil and air saturation by CT, (II) interpretation of CT scans using neural networks, and (III) reconstruction of 3-D images of oil saturation from the CT scans with a neural network model. Excellent agreement between the actual images and the neural network predictions is found.

Neural basis of limb ownership in individuals with body integrity identity disorder.

Directory of Open Access Journals (Sweden)

Milenna T van Dijk

Full Text Available Our body feels like it is ours. However, individuals with body integrity identity disorder (BIID lack this feeling of ownership for distinct limbs and desire amputation of perfectly healthy body parts. This extremely rare condition provides us with an opportunity to study the neural basis underlying the feeling of limb ownership, since these individuals have a feeling of disownership for a limb in the absence of apparent brain damage. Here we directly compared brain activation between limbs that do and do not feel as part of the body using functional MRI during separate tactile stimulation and motor execution experiments. In comparison to matched controls, individuals with BIID showed heightened responsivity of a large somatosensory network including the parietal cortex and right insula during tactile stimulation, regardless of whether the stimulated leg felt owned or alienated. Importantly, activity in the ventral premotor cortex depended on the feeling of ownership and was reduced during stimulation of the alienated compared to the owned leg. In contrast, no significant differences between groups were observed during the performance of motor actions. These results suggest that altered somatosensory processing in the premotor cortex is associated with the feeling of disownership in BIID, which may be related to altered integration of somatosensory and proprioceptive information.

Neural basis of limb ownership in individuals with body integrity identity disorder.

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van Dijk, Milenna T; van Wingen, Guido A; van Lammeren, Anouk; Blom, Rianne M; de Kwaasteniet, Bart P; Scholte, H Steven; Denys, Damiaan

2013-01-01

Our body feels like it is ours. However, individuals with body integrity identity disorder (BIID) lack this feeling of ownership for distinct limbs and desire amputation of perfectly healthy body parts. This extremely rare condition provides us with an opportunity to study the neural basis underlying the feeling of limb ownership, since these individuals have a feeling of disownership for a limb in the absence of apparent brain damage. Here we directly compared brain activation between limbs that do and do not feel as part of the body using functional MRI during separate tactile stimulation and motor execution experiments. In comparison to matched controls, individuals with BIID showed heightened responsivity of a large somatosensory network including the parietal cortex and right insula during tactile stimulation, regardless of whether the stimulated leg felt owned or alienated. Importantly, activity in the ventral premotor cortex depended on the feeling of ownership and was reduced during stimulation of the alienated compared to the owned leg. In contrast, no significant differences between groups were observed during the performance of motor actions. These results suggest that altered somatosensory processing in the premotor cortex is associated with the feeling of disownership in BIID, which may be related to altered integration of somatosensory and proprioceptive information.

Genome-wide association study identifies 74 loci associated with educational attainment

DEFF Research Database (Denmark)

Okbay, Aysu; P. Beauchamp, Jonathan; Alan Fontana, Mark

2016-01-01

-nucleotide polymorphisms associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural......Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals1. Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends...... development. Our findings demonstrate that, even for a behavioural phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because educational attainment is measured in large numbers of individuals...

Construction of reference chromosome-scale pseudomolecules for potato: integrating the potato genome with genetic and physical maps.

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Sharma, Sanjeev Kumar; Bolser, Daniel; de Boer, Jan; Sønderkær, Mads; Amoros, Walter; Carboni, Martin Federico; D'Ambrosio, Juan Martín; de la Cruz, German; Di Genova, Alex; Douches, David S; Eguiluz, Maria; Guo, Xiao; Guzman, Frank; Hackett, Christine A; Hamilton, John P; Li, Guangcun; Li, Ying; Lozano, Roberto; Maass, Alejandro; Marshall, David; Martinez, Diana; McLean, Karen; Mejía, Nilo; Milne, Linda; Munive, Susan; Nagy, Istvan; Ponce, Olga; Ramirez, Manuel; Simon, Reinhard; Thomson, Susan J; Torres, Yerisf; Waugh, Robbie; Zhang, Zhonghua; Huang, Sanwen; Visser, Richard G F; Bachem, Christian W B; Sagredo, Boris; Feingold, Sergio E; Orjeda, Gisella; Veilleux, Richard E; Bonierbale, Merideth; Jacobs, Jeanne M E; Milbourne, Dan; Martin, David Michael Alan; Bryan, Glenn J

2013-11-06

The genome of potato, a major global food crop, was recently sequenced. The work presented here details the integration of the potato reference genome (DM) with a new sequence-tagged site marker-based linkage map and other physical and genetic maps of potato and the closely related species tomato. Primary anchoring of the DM genome assembly was accomplished by the use of a diploid segregating population, which was genotyped with several types of molecular genetic markers to construct a new ~936 cM linkage map comprising 2469 marker loci. In silico anchoring approaches used genetic and physical maps from the diploid potato genotype RH89-039-16 (RH) and tomato. This combined approach has allowed 951 superscaffolds to be ordered into pseudomolecules corresponding to the 12 potato chromosomes. These pseudomolecules represent 674 Mb (~93%) of the 723 Mb genome assembly and 37,482 (~96%) of the 39,031 predicted genes. The superscaffold order and orientation within the pseudomolecules are closely collinear with independently constructed high density linkage maps. Comparisons between marker distribution and physical location reveal regions of greater and lesser recombination, as well as regions exhibiting significant segregation distortion. The work presented here has led to a greatly improved ordering of the potato reference genome superscaffolds into chromosomal "pseudomolecules".

The Banana Genome Hub

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Droc, Gaëtan; Larivière, Delphine; Guignon, Valentin; Yahiaoui, Nabila; This, Dominique; Garsmeur, Olivier; Dereeper, Alexis; Hamelin, Chantal; Argout, Xavier; Dufayard, Jean-François; Lengelle, Juliette; Baurens, Franc-Christophe; Cenci, Alberto; Pitollat, Bertrand; D’Hont, Angélique; Ruiz, Manuel; Rouard, Mathieu; Bocs, Stéphanie

2013-01-01

Banana is one of the world’s favorite fruits and one of the most important crops for developing countries. The banana reference genome sequence (Musa acuminata) was recently released. Given the taxonomic position of Musa, the completed genomic sequence has particular comparative value to provide fresh insights about the evolution of the monocotyledons. The study of the banana genome has been enhanced by a number of tools and resources that allows harnessing its sequence. First, we set up essential tools such as a Community Annotation System, phylogenomics resources and metabolic pathways. Then, to support post-genomic efforts, we improved banana existing systems (e.g. web front end, query builder), we integrated available Musa data into generic systems (e.g. markers and genetic maps, synteny blocks), we have made interoperable with the banana hub, other existing systems containing Musa data (e.g. transcriptomics, rice reference genome, workflow manager) and finally, we generated new results from sequence analyses (e.g. SNP and polymorphism analysis). Several uses cases illustrate how the Banana Genome Hub can be used to study gene families. Overall, with this collaborative effort, we discuss the importance of the interoperability toward data integration between existing information systems. Database URL: http://banana-genome.cirad.fr/ PMID:23707967

Toward genome-enabled mycology.

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Hibbett, David S; Stajich, Jason E; Spatafora, Joseph W

2013-01-01

Genome-enabled mycology is a rapidly expanding field that is characterized by the pervasive use of genome-scale data and associated computational tools in all aspects of fungal biology. Genome-enabled mycology is integrative and often requires teams of researchers with diverse skills in organismal mycology, bioinformatics and molecular biology. This issue of Mycologia presents the first complete fungal genomes in the history of the journal, reflecting the ongoing transformation of mycology into a genome-enabled science. Here, we consider the prospects for genome-enabled mycology and the technical and social challenges that will need to be overcome to grow the database of complete fungal genomes and enable all fungal biologists to make use of the new data.

A new source difference artificial neural network for enhanced positioning accuracy

International Nuclear Information System (INIS)

Bhatt, Deepak; Aggarwal, Priyanka; Devabhaktuni, Vijay; Bhattacharya, Prabir

2012-01-01

Integrated inertial navigation system (INS) and global positioning system (GPS) units provide reliable navigation solution compared to standalone INS or GPS. Traditional Kalman filter-based INS/GPS integration schemes have several inadequacies related to sensor error model and immunity to noise. Alternatively, multi-layer perceptron (MLP) neural networks with three layers have been implemented to improve the position accuracy of the integrated system. However, MLP neural networks show poor accuracy for low-cost INS because of the large inherent sensor errors. For the first time the paper demonstrates the use of knowledge-based source difference artificial neural network (SDANN) to improve navigation performance of low-cost sensor, with or without external aiding sources. Unlike the conventional MLP or artificial neural networks (ANN), the structure of SDANN consists of two MLP neural networks called the coarse model and the difference model. The coarse model learns the input–output data relationship whereas the difference model adds knowledge to the system and fine-tunes the coarse model output by learning the associated training or estimation error. Our proposed SDANN model illustrated a significant improvement in navigation accuracy of up to 81% over conventional MLP. The results demonstrate that the proposed SDANN method is effective for GPS/INS integration schemes using low-cost inertial sensors, with and without GPS

Integration of HIV in the Human Genome: Which Sites Are Preferential? A Genetic and Statistical Assessment

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Gonçalves, Juliana; Moreira, Elsa; Sequeira, Inês J.; Rodrigues, António S.; Rueff, José; Brás, Aldina

2016-01-01

Chromosomal fragile sites (FSs) are loci where gaps and breaks may occur and are preferential integration targets for some viruses, for example, Hepatitis B, Epstein-Barr virus, HPV16, HPV18, and MLV vectors. However, the integration of the human immunodeficiency virus (HIV) in Giemsa bands and in FSs is not yet completely clear. This study aimed to assess the integration preferences of HIV in FSs and in Giemsa bands using an in silico study. HIV integration positions from Jurkat cells were used and two nonparametric tests were applied to compare HIV integration in dark versus light bands and in FS versus non-FS (NFSs). The results show that light bands are preferential targets for integration of HIV-1 in Jurkat cells and also that it integrates with equal intensity in FSs and in NFSs. The data indicates that HIV displays different preferences for FSs compared to other viruses. The aim was to develop and apply an approach to predict the conditions and constraints of HIV insertion in the human genome which seems to adequately complement empirical data. PMID:27294106

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.

Advantages of comparative studies in songbirds to understand the neural basis of sensorimotor integration.

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Murphy, Karagh; James, Logan S; Sakata, Jon T; Prather, Jonathan F

2017-08-01

Sensorimotor integration is the process through which the nervous system creates a link between motor commands and associated sensory feedback. This process allows for the acquisition and refinement of many behaviors, including learned communication behaviors such as speech and birdsong. Consequently, it is important to understand fundamental mechanisms of sensorimotor integration, and comparative analyses of this process can provide vital insight. Songbirds offer a powerful comparative model system to study how the nervous system links motor and sensory information for learning and control. This is because the acquisition, maintenance, and control of birdsong critically depend on sensory feedback. Furthermore, there is an incredible diversity of song organizations across songbird species, ranging from songs with simple, stereotyped sequences to songs with complex sequencing of vocal gestures, as well as a wide diversity of song repertoire sizes. Despite this diversity, the neural circuitry for song learning, control, and maintenance remains highly similar across species. Here, we highlight the utility of songbirds for the analysis of sensorimotor integration and the insights about mechanisms of sensorimotor integration gained by comparing different songbird species. Key conclusions from this comparative analysis are that variation in song sequence complexity seems to covary with the strength of feedback signals in sensorimotor circuits and that sensorimotor circuits contain distinct representations of elements in the vocal repertoire, possibly enabling evolutionary variation in repertoire sizes. We conclude our review by highlighting important areas of research that could benefit from increased comparative focus, with particular emphasis on the integration of new technologies. Copyright © 2017 the American Physiological Society.

An Integrated Circuit for Simultaneous Extracellular Electrophysiology Recording and Optogenetic Neural Manipulation.

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Chen, Chang Hao; McCullagh, Elizabeth A; Pun, Sio Hang; Mak, Peng Un; Vai, Mang I; Mak, Pui In; Klug, Achim; Lei, Tim C

2017-03-01

The ability to record and to control action potential firing in neuronal circuits is critical to understand how the brain functions. The objective of this study is to develop a monolithic integrated circuit (IC) to record action potentials and simultaneously control action potential firing using optogenetics. A low-noise and high input impedance (or low input capacitance) neural recording amplifier is combined with a high current laser/light-emitting diode (LED) driver in a single IC. The low input capacitance of the amplifier (9.7 pF) was achieved by adding a dedicated unity gain stage optimized for high impedance metal electrodes. The input referred noise of the amplifier is [Formula: see text], which is lower than the estimated thermal noise of the metal electrode. Thus, the action potentials originating from a single neuron can be recorded with a signal-to-noise ratio of at least 6.6. The LED/laser current driver delivers a maximum current of 330 mA, which is adequate for optogenetic control. The functionality of the IC was tested with an anesthetized Mongolian gerbil and auditory stimulated action potentials were recorded from the inferior colliculus. Spontaneous firings of fifth (trigeminal) nerve fibers were also inhibited using the optogenetic protein Halorhodopsin. Moreover, a noise model of the system was derived to guide the design. A single IC to measure and control action potentials using optogenetic proteins is realized so that more complicated behavioral neuroscience research and the translational neural disorder treatments become possible in the future.

Genome Variation Map: a data repository of genome variations in BIG Data Center.

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Song, Shuhui; Tian, Dongmei; Li, Cuiping; Tang, Bixia; Dong, Lili; Xiao, Jingfa; Bao, Yiming; Zhao, Wenming; He, Hang; Zhang, Zhang

2018-01-04

The Genome Variation Map (GVM; http://bigd.big.ac.cn/gvm/) is a public data repository of genome variations. As a core resource in the BIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, GVM dedicates to collect, integrate and visualize genome variations for a wide range of species, accepts submissions of different types of genome variations from all over the world and provides free open access to all publicly available data in support of worldwide research activities. Unlike existing related databases, GVM features integration of a large number of genome variations for a broad diversity of species including human, cultivated plants and domesticated animals. Specifically, the current implementation of GVM not only houses a total of ∼4.9 billion variants for 19 species including chicken, dog, goat, human, poplar, rice and tomato, but also incorporates 8669 individual genotypes and 13 262 manually curated high-quality genotype-to-phenotype associations for non-human species. In addition, GVM provides friendly intuitive web interfaces for data submission, browse, search and visualization. Collectively, GVM serves as an important resource for archiving genomic variation data, helpful for better understanding population genetic diversity and deciphering complex mechanisms associated with different phenotypes. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Genome Variation Map: a data repository of genome variations in BIG Data Center

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Tian, Dongmei; Li, Cuiping; Tang, Bixia; Dong, Lili; Xiao, Jingfa; Bao, Yiming; Zhao, Wenming; He, Hang

2018-01-01

Abstract The Genome Variation Map (GVM; http://bigd.big.ac.cn/gvm/) is a public data repository of genome variations. As a core resource in the BIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences, GVM dedicates to collect, integrate and visualize genome variations for a wide range of species, accepts submissions of different types of genome variations from all over the world and provides free open access to all publicly available data in support of worldwide research activities. Unlike existing related databases, GVM features integration of a large number of genome variations for a broad diversity of species including human, cultivated plants and domesticated animals. Specifically, the current implementation of GVM not only houses a total of ∼4.9 billion variants for 19 species including chicken, dog, goat, human, poplar, rice and tomato, but also incorporates 8669 individual genotypes and 13 262 manually curated high-quality genotype-to-phenotype associations for non-human species. In addition, GVM provides friendly intuitive web interfaces for data submission, browse, search and visualization. Collectively, GVM serves as an important resource for archiving genomic variation data, helpful for better understanding population genetic diversity and deciphering complex mechanisms associated with different phenotypes. PMID:29069473

Ginseng Genome Database: an open-access platform for genomics of Panax ginseng.

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Jayakodi, Murukarthick; Choi, Beom-Soon; Lee, Sang-Choon; Kim, Nam-Hoon; Park, Jee Young; Jang, Woojong; Lakshmanan, Meiyappan; Mohan, Shobhana V G; Lee, Dong-Yup; Yang, Tae-Jin

2018-04-12

The ginseng (Panax ginseng C.A. Meyer) is a perennial herbaceous plant that has been used in traditional oriental medicine for thousands of years. Ginsenosides, which have significant pharmacological effects on human health, are the foremost bioactive constituents in this plant. Having realized the importance of this plant to humans, an integrated omics resource becomes indispensable to facilitate genomic research, molecular breeding and pharmacological study of this herb. The first draft genome sequences of P. ginseng cultivar "Chunpoong" were reported recently. Here, using the draft genome, transcriptome, and functional annotation datasets of P. ginseng, we have constructed the Ginseng Genome Database http://ginsengdb.snu.ac.kr /, the first open-access platform to provide comprehensive genomic resources of P. ginseng. The current version of this database provides the most up-to-date draft genome sequence (of approximately 3000 Mbp of scaffold sequences) along with the structural and functional annotations for 59,352 genes and digital expression of genes based on transcriptome data from different tissues, growth stages and treatments. In addition, tools for visualization and the genomic data from various analyses are provided. All data in the database were manually curated and integrated within a user-friendly query page. This database provides valuable resources for a range of research fields related to P. ginseng and other species belonging to the Apiales order as well as for plant research communities in general. Ginseng genome database can be accessed at http://ginsengdb.snu.ac.kr /.

Computational genomics of hyperthermophiles

NARCIS (Netherlands)

Werken, van de H.J.G.

2008-01-01

With the ever increasing number of completely sequenced prokaryotic genomes and the subsequent use of functional genomics tools, e.g. DNA microarray and proteomics, computational data analysis and the integration of microbial and molecular data is inevitable. This thesis describes the computational

Evolutionary time-scale of the begomoviruses: evidence from integrated sequences in the Nicotiana genome.

Directory of Open Access Journals (Sweden)

Pierre Lefeuvre

Full Text Available Despite having single stranded DNA genomes that are replicated by host DNA polymerases, viruses in the family Geminiviridae are apparently evolving as rapidly as some RNA viruses. The observed substitution rates of geminiviruses in the genera Begomovirus and Mastrevirus are so high that the entire family could conceivably have originated less than a million years ago (MYA. However, the existence of geminivirus related DNA (GRD integrated within the genomes of various Nicotiana species suggests that the geminiviruses probably originated >10 MYA. Some have even suggested that a distinct New-World (NW lineage of begomoviruses may have arisen following the separation by continental drift of African and American proto-begomoviruses ∼110 MYA. We evaluate these various geminivirus origin hypotheses using Bayesian coalescent-based approaches to date firstly the Nicotiana GRD integration events, and then the divergence of the NW and Old-World (OW begomoviruses. Besides rejecting the possibility of a<2 MYA OW-NW begomovirus split, we could also discount that it may have occurred concomitantly with the breakup of Gondwanaland 110 MYA. Although we could only confidently narrow the date of the split down to between 2 and 80 MYA, the most plausible (and best supported date for the split is between 20 and 30 MYA--a time when global cooling ended the dispersal of temperate species between Asia and North America via the Beringian land bridge.

FPGA IMPLEMENTATION OF ADAPTIVE INTEGRATED SPIKING NEURAL NETWORK FOR EFFICIENT IMAGE RECOGNITION SYSTEM

Directory of Open Access Journals (Sweden)

T. Pasupathi

2014-05-01

Full Text Available Image recognition is a technology which can be used in various applications such as medical image recognition systems, security, defense video tracking, and factory automation. In this paper we present a novel pipelined architecture of an adaptive integrated Artificial Neural Network for image recognition. In our proposed work we have combined the feature of spiking neuron concept with ANN to achieve the efficient architecture for image recognition. The set of training images are trained by ANN and target output has been identified. Real time videos are captured and then converted into frames for testing purpose and the image were recognized. The machine can operate at up to 40 frames/sec using images acquired from the camera. The system has been implemented on XC3S400 SPARTAN-3 Field Programmable Gate Arrays.

Integrated Genomic Analysis of the Ubiquitin Pathway across Cancer Types

Directory of Open Access Journals (Sweden)

Zhongqi Ge

2018-04-01

Full Text Available Summary: Protein ubiquitination is a dynamic and reversible process of adding single ubiquitin molecules or various ubiquitin chains to target proteins. Here, using multidimensional omic data of 9,125 tumor samples across 33 cancer types from The Cancer Genome Atlas, we perform comprehensive molecular characterization of 929 ubiquitin-related genes and 95 deubiquitinase genes. Among them, we systematically identify top somatic driver candidates, including mutated FBXW7 with cancer-type-specific patterns and amplified MDM2 showing a mutually exclusive pattern with BRAF mutations. Ubiquitin pathway genes tend to be upregulated in cancer mediated by diverse mechanisms. By integrating pan-cancer multiomic data, we identify a group of tumor samples that exhibit worse prognosis. These samples are consistently associated with the upregulation of cell-cycle and DNA repair pathways, characterized by mutated TP53, MYC/TERT amplification, and APC/PTEN deletion. Our analysis highlights the importance of the ubiquitin pathway in cancer development and lays a foundation for developing relevant therapeutic strategies. : Ge et al. analyze a cohort of 9,125 TCGA samples across 33 cancer types to provide a comprehensive characterization of the ubiquitin pathway. They detect somatic driver candidates in the ubiquitin pathway and identify a cluster of patients with poor survival, highlighting the importance of this pathway in cancer development. Keywords: ubiquitin pathway, pan-cancer analysis, The Cancer Genome Atlas, tumor subtype, cancer prognosis, therapeutic targets, biomarker, FBXW7

Preserving genome integrity: the DdrA protein of Deinococcus radiodurans R1.

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Harris, Dennis R; Tanaka, Masashi; Saveliev, Sergei V; Jolivet, Edmond; Earl, Ashlee M; Cox, Michael M; Battista, John R

2004-10-01

The bacterium Deinococcus radiodurans can withstand extraordinary levels of ionizing radiation, reflecting an equally extraordinary capacity for DNA repair. The hypothetical gene product DR0423 has been implicated in the recovery of this organism from DNA damage, indicating that this protein is a novel component of the D. radiodurans DNA repair system. DR0423 is a homologue of the eukaryotic Rad52 protein. Following exposure to ionizing radiation, DR0423 expression is induced relative to an untreated control, and strains carrying a deletion of the DR0423 gene exhibit increased sensitivity to ionizing radiation. When recovering from ionizing-radiation-induced DNA damage in the absence of nutrients, wild-type D. radiodurans reassembles its genome while the mutant lacking DR0423 function does not. In vitro, the purified DR0423 protein binds to single-stranded DNA with an apparent affinity for 3' ends, and protects those ends from nuclease degradation. We propose that DR0423 is part of a DNA end-protection system that helps to preserve genome integrity following exposure to ionizing radiation. We designate the DR0423 protein as DNA damage response A protein.

Preserving genome integrity: the DdrA protein of Deinococcus radiodurans R1.

Directory of Open Access Journals (Sweden)

Dennis R Harris

2004-10-01

Full Text Available The bacterium Deinococcus radiodurans can withstand extraordinary levels of ionizing radiation, reflecting an equally extraordinary capacity for DNA repair. The hypothetical gene product DR0423 has been implicated in the recovery of this organism from DNA damage, indicating that this protein is a novel component of the D. radiodurans DNA repair system. DR0423 is a homologue of the eukaryotic Rad52 protein. Following exposure to ionizing radiation, DR0423 expression is induced relative to an untreated control, and strains carrying a deletion of the DR0423 gene exhibit increased sensitivity to ionizing radiation. When recovering from ionizing-radiation-induced DNA damage in the absence of nutrients, wild-type D. radiodurans reassembles its genome while the mutant lacking DR0423 function does not. In vitro, the purified DR0423 protein binds to single-stranded DNA with an apparent affinity for 3' ends, and protects those ends from nuclease degradation. We propose that DR0423 is part of a DNA end-protection system that helps to preserve genome integrity following exposure to ionizing radiation. We designate the DR0423 protein as DNA damage response A protein.

Cancer prevention, the need to preserve the integrity of the genome at all cost.

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Okafor, M T; Nwagha, T U; Anusiem, C; Okoli, U A; Nubila, N I; Al-Alloosh, F; Udenyia, I J

2018-05-01

The entire genetic information carried by an organism makes up its genome. Genes have a diverse number of functions. They code different proteins for normal proliferation of cells. However, changes in the base sequence of genes affect their protein by-products which act as messengers for normal cellular functions such as proliferation and repairs. Salient processes for maintaining the integrity of the genome are hinged on intricate mechanisms put in place for the evolution to tackle genomic stresses. To discuss how cells sense and repair damage to their deoxyribonucleic acid (DNA) as well as to highlight how defects in the genes involved in DNA repair contribute to cancer development. Methodology: Online searches on the following databases such as Google Scholar, PubMed, Biomed Central, and SciELO were done. Attempt was made to review articles with keywords such as cancer, cell cycle, tumor suppressor genes, and DNA repair. The cell cycle, tumor suppression genes, DNA repair mechanism, as well as their contribution to cancer development, were discussed and reviewed. Knowledge on how cells detect and repair DNA damage through an array of mechanisms should allay our anxiety as regards cancer development. More studies on DNA damage detection and repair processes are important toward a holistic approach to cancer treatment.

Enhanced annotations and features for comparing thousands of Pseudomonas genomes in the Pseudomonas genome database.

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Winsor, Geoffrey L; Griffiths, Emma J; Lo, Raymond; Dhillon, Bhavjinder K; Shay, Julie A; Brinkman, Fiona S L

2016-01-04

The Pseudomonas Genome Database (http://www.pseudomonas.com) is well known for the application of community-based annotation approaches for producing a high-quality Pseudomonas aeruginosa PAO1 genome annotation, and facilitating whole-genome comparative analyses with other Pseudomonas strains. To aid analysis of potentially thousands of complete and draft genome assemblies, this database and analysis platform was upgraded to integrate curated genome annotations and isolate metadata with enhanced tools for larger scale comparative analysis and visualization. Manually curated gene annotations are supplemented with improved computational analyses that help identify putative drug targets and vaccine candidates or assist with evolutionary studies by identifying orthologs, pathogen-associated genes and genomic islands. The database schema has been updated to integrate isolate metadata that will facilitate more powerful analysis of genomes across datasets in the future. We continue to place an emphasis on providing high-quality updates to gene annotations through regular review of the scientific literature and using community-based approaches including a major new Pseudomonas community initiative for the assignment of high-quality gene ontology terms to genes. As we further expand from thousands of genomes, we plan to provide enhancements that will aid data visualization and analysis arising from whole-genome comparative studies including more pan-genome and population-based approaches. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Integrative Genomics: Quantifying significance of phenotype-genotype relationships from multiple sources of high-throughput data

Directory of Open Access Journals (Sweden)

Eric eGamazon

2013-05-01

Full Text Available Given recent advances in the generation of high-throughput data such as whole genome genetic variation and transcriptome expression, it is critical to come up with novel methods to integrate these heterogeneous datasets and to assess the significance of identified phenotype-genotype relationships. Recent studies show that genome-wide association findings are likely to fall in loci with gene regulatory effects such as expression quantitative trait loci (eQTLs, demonstrating the utility of such integrative approaches. When genotype and gene expression data are available on the same individuals, we developed methods wherein top phenotype-associated genetic variants are prioritized if they are associated, as eQTLs, with gene expression traits that are themselves associated with the phenotype. Yet there has been no method to determine an overall p-value for the findings that arise specifically from the integrative nature of the approach. We propose a computationally feasible permutation method that accounts for the assimilative nature of the method and the correlation structure among gene expression traits and among genotypes. We apply the method to data from a study of cellular sensitivity to etoposide, one of the most widely used chemotherapeutic drugs. To our knowledge, this study is the first statistically sound quantification of the significance of the genotype-phenotype relationships resulting from applying an integrative approach. This method can be easily extended to cases in which gene expression data are replaced by other molecular phenotypes of interest, e.g., microRNA or proteomic data. This study has important implications for studies seeking to expand on genetic association studies by the use of omics data. Finally, we provide an R code to compute the empirical FDR when p-values for the observed and simulated phenotypes are available.

An amphioxus Msx gene expressed predominantly in the dorsal neural tube.

Science.gov (United States)

Sharman, A C; Shimeld, S M; Holland, P W

1999-04-01

Genomic and cDNA clones of an Msx class homeobox gene were isolated from amphioxus (Branchiostoma floridae). The gene, AmphiMsx, is expressed in the neural plate from late gastrulation; in later embryos it is expressed in dorsal cells of the neural tube, excluding anterior and posterior regions, in an irregular reiterated pattern. There is transient expression in dorsal cells within somites, reminiscent of migrating neural crest cells of vertebrates. In larvae, mRNA is detected in two patches of anterior ectoderm proposed to be placodes. Evolutionary analyses show there is little phylogenetic information in Msx protein sequences; however, it is likely that duplication of Msx genes occurred in the vertebrate lineage.

Brassica ASTRA: an integrated database for Brassica genomic research.

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Love, Christopher G; Robinson, Andrew J; Lim, Geraldine A C; Hopkins, Clare J; Batley, Jacqueline; Barker, Gary; Spangenberg, German C; Edwards, David

2005-01-01

Brassica ASTRA is a public database for genomic information on Brassica species. The database incorporates expressed sequences with Swiss-Prot and GenBank comparative sequence annotation as well as secondary Gene Ontology (GO) annotation derived from the comparison with Arabidopsis TAIR GO annotations. Simple sequence repeat molecular markers are identified within resident sequences and mapped onto the closely related Arabidopsis genome sequence. Bacterial artificial chromosome (BAC) end sequences derived from the Multinational Brassica Genome Project are also mapped onto the Arabidopsis genome sequence enabling users to identify candidate Brassica BACs corresponding to syntenic regions of Arabidopsis. This information is maintained in a MySQL database with a web interface providing the primary means of interrogation. The database is accessible at http://hornbill.cspp.latrobe.edu.au.

JGI Fungal Genomics Program

Energy Technology Data Exchange (ETDEWEB)

Grigoriev, Igor V.

2011-03-14

Genomes of energy and environment fungi are in focus of the Fungal Genomic Program at the US Department of Energy Joint Genome Institute (JGI). Its key project, the Genomics Encyclopedia of Fungi, targets fungi related to plant health (symbionts, pathogens, and biocontrol agents) and biorefinery processes (cellulose degradation, sugar fermentation, industrial hosts), and explores fungal diversity by means of genome sequencing and analysis. Over 50 fungal genomes have been sequenced by JGI to date and released through MycoCosm (www.jgi.doe.gov/fungi), a fungal web-portal, which integrates sequence and functional data with genome analysis tools for user community. Sequence analysis supported by functional genomics leads to developing parts list for complex systems ranging from ecosystems of biofuel crops to biorefineries. Recent examples of such 'parts' suggested by comparative genomics and functional analysis in these areas are presented here

Genomic Encyclopedia of Fungi

Energy Technology Data Exchange (ETDEWEB)

Grigoriev, Igor

2012-08-10

Genomes of fungi relevant to energy and environment are in focus of the Fungal Genomic Program at the US Department of Energy Joint Genome Institute (JGI). Its key project, the Genomics Encyclopedia of Fungi, targets fungi related to plant health (symbionts, pathogens, and biocontrol agents) and biorefinery processes (cellulose degradation, sugar fermentation, industrial hosts), and explores fungal diversity by means of genome sequencing and analysis. Over 150 fungal genomes have been sequenced by JGI to date and released through MycoCosm (www.jgi.doe.gov/fungi), a fungal web-portal, which integrates sequence and functional data with genome analysis tools for user community. Sequence analysis supported by functional genomics leads to developing parts list for complex systems ranging from ecosystems of biofuel crops to biorefineries. Recent examples of such parts suggested by comparative genomics and functional analysis in these areas are presented here.

Flexible neural interfaces with integrated stiffening shank

Energy Technology Data Exchange (ETDEWEB)

Tooker, Angela C.; Felix, Sarah H.; Pannu, Satinderpall S.; Shah, Kedar G.; Sheth, Heeral; Tolosa, Vanessa

2017-10-17

A neural interface includes a first dielectric material having at least one first opening for a first electrical conducting material, a first electrical conducting material in the first opening, and at least one first interconnection trace electrical conducting material connected to the first electrical conducting material. A stiffening shank material is located adjacent the first dielectric material, the first electrical conducting material, and the first interconnection trace electrical conducting material.

Flexible neural interfaces with integrated stiffening shank

Science.gov (United States)

Tooker, Angela C.; Felix, Sarah H.; Pannu, Satinderpall S.; Shah, Kedar G.; Sheth, Heeral; Tolosa, Vanessa

2016-07-26

A neural interface includes a first dielectric material having at least one first opening for a first electrical conducting material, a first electrical conducting material in the first opening, and at least one first interconnection trace electrical conducting material connected to the first electrical conducting material. A stiffening shank material is located adjacent the first dielectric material, the first electrical conducting material, and the first interconnection trace electrical conducting material.

Advanced Applications of Neural Networks and Artificial Intelligence: A Review

OpenAIRE

Koushal Kumar; Gour Sundar Mitra Thakur

2012-01-01

Artificial Neural Network is a branch of Artificial intelligence and has been accepted as a new computing technology in computer science fields. This paper reviews the field of Artificial intelligence and focusing on recent applications which uses Artificial Neural Networks (ANN’s) and Artificial Intelligence (AI). It also considers the integration of neural networks with other computing methods Such as fuzzy logic to enhance the interpretation ability of data. Artificial Neural Networks is c...

Savant Genome Browser 2: visualization and analysis for population-scale genomics.

Science.gov (United States)

Fiume, Marc; Smith, Eric J M; Brook, Andrew; Strbenac, Dario; Turner, Brian; Mezlini, Aziz M; Robinson, Mark D; Wodak, Shoshana J; Brudno, Michael

2012-07-01

High-throughput sequencing (HTS) technologies are providing an unprecedented capacity for data generation, and there is a corresponding need for efficient data exploration and analysis capabilities. Although most existing tools for HTS data analysis are developed for either automated (e.g. genotyping) or visualization (e.g. genome browsing) purposes, such tools are most powerful when combined. For example, integration of visualization and computation allows users to iteratively refine their analyses by updating computational parameters within the visual framework in real-time. Here we introduce the second version of the Savant Genome Browser, a standalone program for visual and computational analysis of HTS data. Savant substantially improves upon its predecessor and existing tools by introducing innovative visualization modes and navigation interfaces for several genomic datatypes, and synergizing visual and automated analyses in a way that is powerful yet easy even for non-expert users. We also present a number of plugins that were developed by the Savant Community, which demonstrate the power of integrating visual and automated analyses using Savant. The Savant Genome Browser is freely available (open source) at www.savantbrowser.com.

Brains--Computers--Machines: Neural Engineering in Science Classrooms

Science.gov (United States)

Chudler, Eric H.; Bergsman, Kristen Clapper

2016-01-01

Neural engineering is an emerging field of high relevance to students, teachers, and the general public. This feature presents online resources that educators and scientists can use to introduce students to neural engineering and to integrate core ideas from the life sciences, physical sciences, social sciences, computer science, and engineering…

Recurrent Neural Network For Forecasting Time Series With Long Memory Pattern

Science.gov (United States)

Walid; Alamsyah

2017-04-01

Recurrent Neural Network as one of the hybrid models are often used to predict and estimate the issues related to electricity, can be used to describe the cause of the swelling of electrical load which experienced by PLN. In this research will be developed RNN forecasting procedures at the time series with long memory patterns. Considering the application is the national electrical load which of course has a different trend with the condition of the electrical load in any country. This research produces the algorithm of time series forecasting which has long memory pattern using E-RNN after this referred to the algorithm of integrated fractional recurrent neural networks (FIRNN).The prediction results of long memory time series using models Fractional Integrated Recurrent Neural Network (FIRNN) showed that the model with the selection of data difference in the range of [-1,1] and the model of Fractional Integrated Recurrent Neural Network (FIRNN) (24,6,1) provides the smallest MSE value, which is 0.00149684.

HGVA: the Human Genome Variation Archive

OpenAIRE

Lopez, Javier; Coll, Jacobo; Haimel, Matthias; Kandasamy, Swaathi; Tarraga, Joaquin; Furio-Tari, Pedro; Bari, Wasim; Bleda, Marta; Rueda, Antonio; Gr?f, Stefan; Rendon, Augusto; Dopazo, Joaquin; Medina, Ignacio

2017-01-01

Abstract High-profile genomic variation projects like the 1000 Genomes project or the Exome Aggregation Consortium, are generating a wealth of human genomic variation knowledge which can be used as an essential reference for identifying disease-causing genotypes. However, accessing these data, contrasting the various studies and integrating those data in downstream analyses remains cumbersome. The Human Genome Variation Archive (HGVA) tackles these challenges and facilitates access to genomic...

CHESS (CgHExpreSS): a comprehensive analysis tool for the analysis of genomic alterations and their effects on the expression profile of the genome.

Science.gov (United States)

Lee, Mikyung; Kim, Yangseok

2009-12-16

Genomic alterations frequently occur in many cancer patients and play important mechanistic roles in the pathogenesis of cancer. Furthermore, they can modify the expression level of genes due to altered copy number in the corresponding region of the chromosome. An accumulating body of evidence supports the possibility that strong genome-wide correlation exists between DNA content and gene expression. Therefore, more comprehensive analysis is needed to quantify the relationship between genomic alteration and gene expression. A well-designed bioinformatics tool is essential to perform this kind of integrative analysis. A few programs have already been introduced for integrative analysis. However, there are many limitations in their performance of comprehensive integrated analysis using published software because of limitations in implemented algorithms and visualization modules. To address this issue, we have implemented the Java-based program CHESS to allow integrative analysis of two experimental data sets: genomic alteration and genome-wide expression profile. CHESS is composed of a genomic alteration analysis module and an integrative analysis module. The genomic alteration analysis module detects genomic alteration by applying a threshold based method or SW-ARRAY algorithm and investigates whether the detected alteration is phenotype specific or not. On the other hand, the integrative analysis module measures the genomic alteration's influence on gene expression. It is divided into two separate parts. The first part calculates overall correlation between comparative genomic hybridization ratio and gene expression level by applying following three statistical methods: simple linear regression, Spearman rank correlation and Pearson's correlation. In the second part, CHESS detects the genes that are differentially expressed according to the genomic alteration pattern with three alternative statistical approaches: Student's t-test, Fisher's exact test and Chi square

Integrate genome-based assessment of safety for probiotic strains: Bacillus coagulans GBI-30, 6086 as a case study.

Science.gov (United States)

Salvetti, Elisa; Orrù, Luigi; Capozzi, Vittorio; Martina, Alessia; Lamontanara, Antonella; Keller, David; Cash, Howard; Felis, Giovanna E; Cattivelli, Luigi; Torriani, Sandra; Spano, Giuseppe

2016-05-01

Probiotics are microorganisms that confer beneficial effects on the host; nevertheless, before being allowed for human consumption, their safety must be verified with accurate protocols. In the genomic era, such procedures should take into account the genomic-based approaches. This study aims at assessing the safety traits of Bacillus coagulans GBI-30, 6086 integrating the most updated genomics-based procedures and conventional phenotypic assays. Special attention was paid to putative virulence factors (VF), antibiotic resistance (AR) genes and genes encoding enzymes responsible for harmful metabolites (i.e. biogenic amines, BAs). This probiotic strain was phenotypically resistant to streptomycin and kanamycin, although the genome analysis suggested that the AR-related genes were not easily transferrable to other bacteria, and no other genes with potential safety risks, such as those related to VF or BA production, were retrieved. Furthermore, no unstable elements that could potentially lead to genomic rearrangements were detected. Moreover, a workflow is proposed to allow the proper taxonomic identification of a microbial strain and the accurate evaluation of risk-related gene traits, combining whole genome sequencing analysis with updated bioinformatics tools and standard phenotypic assays. The workflow presented can be generalized as a guideline for the safety investigation of novel probiotic strains to help stakeholders (from scientists to manufacturers and consumers) to meet regulatory requirements and avoid misleading information.

An integrative approach to predicting the functional effects of small indels in non-coding regions of the human genome.

Science.gov (United States)

Ferlaino, Michael; Rogers, Mark F; Shihab, Hashem A; Mort, Matthew; Cooper, David N; Gaunt, Tom R; Campbell, Colin

2017-10-06

Small insertions and deletions (indels) have a significant influence in human disease and, in terms of frequency, they are second only to single nucleotide variants as pathogenic mutations. As the majority of mutations associated with complex traits are located outside the exome, it is crucial to investigate the potential pathogenic impact of indels in non-coding regions of the human genome. We present FATHMM-indel, an integrative approach to predict the functional effect, pathogenic or neutral, of indels in non-coding regions of the human genome. Our method exploits various genomic annotations in addition to sequence data. When validated on benchmark data, FATHMM-indel significantly outperforms CADD and GAVIN, state of the art models in assessing the pathogenic impact of non-coding variants. FATHMM-indel is available via a web server at indels.biocompute.org.uk. FATHMM-indel can accurately predict the functional impact and prioritise small indels throughout the whole non-coding genome.

Neural PID Control of Robot Manipulators With Application to an Upper Limb Exoskeleton.

Science.gov (United States)

Yu, Wen; Rosen, Jacob

2013-04-01

In order to minimize steady-state error with respect to uncertainties in robot control, proportional-integral-derivative (PID) control needs a big integral gain, or a neural compensator is added to the classical proportional-derivative (PD) control with a large derivative gain. Both of them deteriorate transient performances of the robot control. In this paper, we extend the popular neural PD control into neural PID control. This novel control is a natural combination of industrial linear PID control and neural compensation. The main contributions of this paper are semiglobal asymptotic stability of the neural PID control and local asymptotic stability of the neural PID control with a velocity observer which are proved with standard weight training algorithms. These conditions give explicit selection methods for the gains of the linear PID control. An experimental study on an upper limb exoskeleton with this neural PID control is addressed.

Comparing the neural basis of monetary reward and cognitive feedback during information-integration category learning.

Science.gov (United States)

Daniel, Reka; Pollmann, Stefan

2010-01-06

The dopaminergic system is known to play a central role in reward-based learning (Schultz, 2006), yet it was also observed to be involved when only cognitive feedback is given (Aron et al., 2004). Within the domain of information-integration category learning, in which information from several stimulus dimensions has to be integrated predecisionally (Ashby and Maddox, 2005), the importance of contingent feedback is well established (Maddox et al., 2003). We examined the common neural correlates of reward anticipation and prediction error in this task. Sixteen subjects performed two parallel information-integration tasks within a single event-related functional magnetic resonance imaging session but received a monetary reward only for one of them. Similar functional areas including basal ganglia structures were activated in both task versions. In contrast, a single structure, the nucleus accumbens, showed higher activation during monetary reward anticipation compared with the anticipation of cognitive feedback in information-integration learning. Additionally, this activation was predicted by measures of intrinsic motivation in the cognitive feedback task and by measures of extrinsic motivation in the rewarded task. Our results indicate that, although all other structures implicated in category learning are not significantly affected by altering the type of reward, the nucleus accumbens responds to the positive incentive properties of an expected reward depending on the specific type of the reward.

Integration of transcriptome and whole genomic resequencing data to identify key genes affecting swine fat deposition.

Directory of Open Access Journals (Sweden)

Kai Xing

Full Text Available Fat deposition is highly correlated with the growth, meat quality, reproductive performance and immunity of pigs. Fatty acid synthesis takes place mainly in the adipose tissue of pigs; therefore, in this study, a high-throughput massively parallel sequencing approach was used to generate adipose tissue transcriptomes from two groups of Songliao black pigs that had opposite backfat thickness phenotypes. The total number of paired-end reads produced for each sample was in the range of 39.29-49.36 millions. Approximately 188 genes were differentially expressed in adipose tissue and were enriched for metabolic processes, such as fatty acid biosynthesis, lipid synthesis, metabolism of fatty acids, etinol, caffeine and arachidonic acid and immunity. Additionally, many genetic variations were detected between the two groups through pooled whole-genome resequencing. Integration of transcriptome and whole-genome resequencing data revealed important genomic variations among the differentially expressed genes for fat deposition, for example, the lipogenic genes. Further studies are required to investigate the roles of candidate genes in fat deposition to improve pig breeding programs.

PopGenome: An Efficient Swiss Army Knife for Population Genomic Analyses in R

OpenAIRE

Pfeifer, Bastian; Wittelsbürger, Ulrich; Ramos-Onsins, Sebastian E.; Lercher, Martin J.

2014-01-01

Although many computer programs can perform population genetics calculations, they are typically limited in the analyses and data input formats they offer; few applications can process the large data sets produced by whole-genome resequencing projects. Furthermore, there is no coherent framework for the easy integration of new statistics into existing pipelines, hindering the development and application of new population genetics and genomics approaches. Here, we present PopGenome, a populati...

The human vascular endothelial cell line HUV-EC-C harbors the integrated HHV-6B genome which remains stable in long term culture.

Science.gov (United States)

Shioda, Setsuko; Kasai, Fumio; Ozawa, Midori; Hirayama, Noriko; Satoh, Motonobu; Kameoka, Yousuke; Watanabe, Ken; Shimizu, Norio; Tang, Huamin; Mori, Yasuko; Kohara, Arihiro

2018-02-01

Human herpes virus 6 (HHV-6) is a common human pathogen that is most often detected in hematopoietic cells. Although human cells harboring chromosomally integrated HHV-6 can be generated in vitro, the availability of such cell lines originating from in vivo tissues is limited. In this study, chromosomally integrated HHV-6B has been identified in a human vascular endothelial cell line, HUV-EC-C (IFO50271), derived from normal umbilical cord tissue. Sequence analysis revealed that the viral genome was similar to the HHV-6B HST strain. FISH analysis using a HHV-6 DNA probe showed one signal in each cell, detected at the distal end of the long arm of chromosome 9. This was consistent with a digital PCR assay, validating one copy of the viral DNA. Because exposure of HUV-EC-C to chemicals did not cause viral reactivation, long term cell culture of HUV-EC-C was carried out to assess the stability of viral integration. The growth rate was altered depending on passage numbers, and morphology also changed during culture. SNP microarray profiles showed some differences between low and high passages, implying that the HUV-EC-C genome had changed during culture. However, no detectable change was observed in chromosome 9, where HHV-6B integration and the viral copy number remained unchanged. Our results suggest that integrated HHV-6B is stable in HUV-EC-C despite genome instability.

HiView: an integrative genome browser to leverage Hi-C results for the interpretation of GWAS variants.

Science.gov (United States)

Xu, Zheng; Zhang, Guosheng; Duan, Qing; Chai, Shengjie; Zhang, Baqun; Wu, Cong; Jin, Fulai; Yue, Feng; Li, Yun; Hu, Ming

2016-03-11

Genome-wide association studies (GWAS) have identified thousands of genetic variants associated with complex traits and diseases. However, most of them are located in the non-protein coding regions, and therefore it is challenging to hypothesize the functions of these non-coding GWAS variants. Recent large efforts such as the ENCODE and Roadmap Epigenomics projects have predicted a large number of regulatory elements. However, the target genes of these regulatory elements remain largely unknown. Chromatin conformation capture based technologies such as Hi-C can directly measure the chromatin interactions and have generated an increasingly comprehensive catalog of the interactome between the distal regulatory elements and their potential target genes. Leveraging such information revealed by Hi-C holds the promise of elucidating the functions of genetic variants in human diseases. In this work, we present HiView, the first integrative genome browser to leverage Hi-C results for the interpretation of GWAS variants. HiView is able to display Hi-C data and statistical evidence for chromatin interactions in genomic regions surrounding any given GWAS variant, enabling straightforward visualization and interpretation. We believe that as the first GWAS variants-centered Hi-C genome browser, HiView is a useful tool guiding post-GWAS functional genomics studies. HiView is freely accessible at: http://www.unc.edu/~yunmli/HiView .

An integrative genomic and transcriptomic analysis reveals potential targets associated with cell proliferation in uterine leiomyomas.

Directory of Open Access Journals (Sweden)

Priscila Daniele Ramos Cirilo

Full Text Available Uterine Leiomyomas (ULs are the most common benign tumours affecting women of reproductive age. ULs represent a major problem in public health, as they are the main indication for hysterectomy. Approximately 40-50% of ULs have non-random cytogenetic abnormalities, and half of ULs may have copy number alterations (CNAs. Gene expression microarrays studies have demonstrated that cell proliferation genes act in response to growth factors and steroids. However, only a few genes mapping to CNAs regions were found to be associated with ULs.We applied an integrative analysis using genomic and transcriptomic data to identify the pathways and molecular markers associated with ULs. Fifty-one fresh frozen specimens were evaluated by array CGH (JISTIC and gene expression microarrays (SAM. The CONEXIC algorithm was applied to integrate the data.The integrated analysis identified the top 30 significant genes (P<0.01, which comprised genes associated with cancer, whereas the protein-protein interaction analysis indicated a strong association between FANCA and BRCA1. Functional in silico analysis revealed target molecules for drugs involved in cell proliferation, including FGFR1 and IGFBP5. Transcriptional and protein analyses showed that FGFR1 (P = 0.006 and P<0.01, respectively and IGFBP5 (P = 0.0002 and P = 0.006, respectively were up-regulated in the tumours when compared with the adjacent normal myometrium.The integrative genomic and transcriptomic approach indicated that FGFR1 and IGFBP5 amplification, as well as the consequent up-regulation of the protein products, plays an important role in the aetiology of ULs and thus provides data for potential drug therapies development to target genes associated with cellular proliferation in ULs.

Causes of genome instability

DEFF Research Database (Denmark)

Langie, Sabine A S; Koppen, Gudrun; Desaulniers, Daniel

2015-01-01

function, chromosome segregation, telomere length). The purpose of this review is to describe the crucial aspects of genome instability, to outline the ways in which environmental chemicals can affect this cancer hallmark and to identify candidate chemicals for further study. The overall aim is to make......Genome instability is a prerequisite for the development of cancer. It occurs when genome maintenance systems fail to safeguard the genome's integrity, whether as a consequence of inherited defects or induced via exposure to environmental agents (chemicals, biological agents and radiation). Thus...

Neural complexity: A graph theoretic interpretation

Science.gov (United States)

Barnett, L.; Buckley, C. L.; Bullock, S.

2011-04-01

One of the central challenges facing modern neuroscience is to explain the ability of the nervous system to coherently integrate information across distinct functional modules in the absence of a central executive. To this end, Tononi [Proc. Natl. Acad. Sci. USA.PNASA60027-842410.1073/pnas.91.11.5033 91, 5033 (1994)] proposed a measure of neural complexity that purports to capture this property based on mutual information between complementary subsets of a system. Neural complexity, so defined, is one of a family of information theoretic metrics developed to measure the balance between the segregation and integration of a system’s dynamics. One key question arising for such measures involves understanding how they are influenced by network topology. Sporns [Cereb. Cortex53OPAV1047-321110.1093/cercor/10.2.127 10, 127 (2000)] employed numerical models in order to determine the dependence of neural complexity on the topological features of a network. However, a complete picture has yet to be established. While De Lucia [Phys. Rev. EPLEEE81539-375510.1103/PhysRevE.71.016114 71, 016114 (2005)] made the first attempts at an analytical account of this relationship, their work utilized a formulation of neural complexity that, we argue, did not reflect the intuitions of the original work. In this paper we start by describing weighted connection matrices formed by applying a random continuous weight distribution to binary adjacency matrices. This allows us to derive an approximation for neural complexity in terms of the moments of the weight distribution and elementary graph motifs. In particular, we explicitly establish a dependency of neural complexity on cyclic graph motifs.

IW-Scoring: an Integrative Weighted Scoring framework for annotating and prioritizing genetic variations in the noncoding genome.

Science.gov (United States)

Wang, Jun; Dayem Ullah, Abu Z; Chelala, Claude

2018-01-30

The vast majority of germline and somatic variations occur in the noncoding part of the genome, only a small fraction of which are believed to be functional. From the tens of thousands of noncoding variations detectable in each genome, identifying and prioritizing driver candidates with putative functional significance is challenging. To address this, we implemented IW-Scoring, a new Integrative Weighted Scoring model to annotate and prioritise functionally relevant noncoding variations. We evaluate 11 scoring methods, and apply an unsupervised spectral approach for subsequent selective integration into two linear weighted functional scoring schemas for known and novel variations. IW-Scoring produces stable high-quality performance as the best predictors for three independent data sets. We demonstrate the robustness of IW-Scoring in identifying recurrent functional mutations in the TERT promoter, as well as disease SNPs in proximity to consensus motifs and with gene regulatory effects. Using follicular lymphoma as a paradigmatic cancer model, we apply IW-Scoring to locate 11 recurrently mutated noncoding regions in 14 follicular lymphoma genomes, and validate 9 of these regions in an extension cohort, including the promoter and enhancer regions of PAX5. Overall, IW-Scoring demonstrates greater versatility in identifying trait- and disease-associated noncoding variants. Scores from IW-Scoring as well as other methods are freely available from http://www.snp-nexus.org/IW-Scoring/. © The Author(s) 2018. Published by Oxford University Press on behalf of Nucleic Acids Research.

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.

Implementing genomics and pharmacogenomics in the clinic: The National Human Genome Research Institute's genomic medicine portfolio.

Science.gov (United States)

Manolio, Teri A

2016-10-01

Increasing knowledge about the influence of genetic variation on human health and growing availability of reliable, cost-effective genetic testing have spurred the implementation of genomic medicine in the clinic. As defined by the National Human Genome Research Institute (NHGRI), genomic medicine uses an individual's genetic information in his or her clinical care, and has begun to be applied effectively in areas such as cancer genomics, pharmacogenomics, and rare and undiagnosed diseases. In 2011 NHGRI published its strategic vision for the future of genomic research, including an ambitious research agenda to facilitate and promote the implementation of genomic medicine. To realize this agenda, NHGRI is consulting and facilitating collaborations with the external research community through a series of "Genomic Medicine Meetings," under the guidance and leadership of the National Advisory Council on Human Genome Research. These meetings have identified and begun to address significant obstacles to implementation, such as lack of evidence of efficacy, limited availability of genomics expertise and testing, lack of standards, and difficulties in integrating genomic results into electronic medical records. The six research and dissemination initiatives comprising NHGRI's genomic research portfolio are designed to speed the evaluation and incorporation, where appropriate, of genomic technologies and findings into routine clinical care. Actual adoption of successful approaches in clinical care will depend upon the willingness, interest, and energy of professional societies, practitioners, patients, and payers to promote their responsible use and share their experiences in doing so. Published by Elsevier Ireland Ltd.

Path integration of head direction: updating a packet of neural activity at the correct speed using neuronal time constants.

Science.gov (United States)

Walters, D M; Stringer, S M

2010-07-01

A key question in understanding the neural basis of path integration is how individual, spatially responsive, neurons may self-organize into networks that can, through learning, integrate velocity signals to update a continuous representation of location within an environment. It is of vital importance that this internal representation of position is updated at the correct speed, and in real time, to accurately reflect the motion of the animal. In this article, we present a biologically plausible model of velocity path integration of head direction that can solve this problem using neuronal time constants to effect natural time delays, over which associations can be learned through associative Hebbian learning rules. The model comprises a linked continuous attractor network and competitive network. In simulation, we show that the same model is able to learn two different speeds of rotation when implemented with two different values for the time constant, and without the need to alter any other model parameters. The proposed model could be extended to path integration of place in the environment, and path integration of spatial view.

Optimization and modeling of a photovoltaic solar integrated system by neural networks

International Nuclear Information System (INIS)

Ashhab, Moh'd Sami S.

2008-01-01

A photovoltaic solar integrated system is modeled with artificial neural networks (ANN's). Data relevant to the system performance was collected on April, 4th 1993 and every 15 min during the day. This input-output data is used to train the ANN. The ANN approximates the data well and therefore can be relied on in predicting the system performance, namely, system efficiencies. The solar system consists of a solar trainer which contains a photovoltaic panel, a DC centrifugal pump, flat plate collectors, storage tank, a flowmeter for measuring the water mass flow rate, pipes, pyranometer for measuring the solar intensity, thermocouples for measuring various system temperatures and wind speed meter. The complex method constrained optimization is applied to the solar system ANN model to find the operating conditions of the system that will produce the maximum system efficiencies. This information will be very hard to obtain by just looking at the available historical input-output data

Optimization and modeling of a photovoltaic solar integrated system by neural networks

Energy Technology Data Exchange (ETDEWEB)

Ashhab, Moh' d Sami S. [Department of Mechanical Engineering, The Hashemite University, Zarqa 13115 (Jordan)

2008-11-15

A photovoltaic solar integrated system is modeled with artificial neural networks (ANN's). Data relevant to the system performance was collected on April, 4th 1993 and every 15 min during the day. This input-output data is used to train the ANN. The ANN approximates the data well and therefore can be relied on in predicting the system performance, namely, system efficiencies. The solar system consists of a solar trainer which contains a photovoltaic panel, a DC centrifugal pump, flat plate collectors, storage tank, a flowmeter for measuring the water mass flow rate, pipes, pyranometer for measuring the solar intensity, thermocouples for measuring various system temperatures and wind speed meter. The complex method constrained optimization is applied to the solar system ANN model to find the operating conditions of the system that will produce the maximum system efficiencies. This information will be very hard to obtain by just looking at the available historical input-output data. (author)

Graph-based semi-supervised learning with genomic data integration using condition-responsive genes applied to phenotype classification.

Science.gov (United States)

Doostparast Torshizi, Abolfazl; Petzold, Linda R

2018-01-01

Data integration methods that combine data from different molecular levels such as genome, epigenome, transcriptome, etc., have received a great deal of interest in the past few years. It has been demonstrated that the synergistic effects of different biological data types can boost learning capabilities and lead to a better understanding of the underlying interactions among molecular levels. In this paper we present a graph-based semi-supervised classification algorithm that incorporates latent biological knowledge in the form of biological pathways with gene expression and DNA methylation data. The process of graph construction from biological pathways is based on detecting condition-responsive genes, where 3 sets of genes are finally extracted: all condition responsive genes, high-frequency condition-responsive genes, and P-value-filtered genes. The proposed approach is applied to ovarian cancer data downloaded from the Human Genome Atlas. Extensive numerical experiments demonstrate superior performance of the proposed approach compared to other state-of-the-art algorithms, including the latest graph-based classification techniques. Simulation results demonstrate that integrating various data types enhances classification performance and leads to a better understanding of interrelations between diverse omics data types. The proposed approach outperforms many of the state-of-the-art data integration algorithms. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Multiple-integrations of HPV16 genome and altered transcription of viral oncogenes and cellular genes are associated with the development of cervical cancer.

Directory of Open Access Journals (Sweden)

Xulian Lu

Full Text Available The constitutive expression of the high-risk HPV E6 and E7 viral oncogenes is the major cause of cervical cancer. To comprehensively explore the composition of HPV16 early transcripts and their genomic annotation, cervical squamous epithelial tissues from 40 HPV16-infected patients were collected for analysis of papillomavirus oncogene transcripts (APOT. We observed different transcription patterns of HPV16 oncogenes in progression of cervical lesions to cervical cancer and identified one novel transcript. Multiple-integration events in the tissues of cervical carcinoma (CxCa are significantly more often than those of low-grade squamous intraepithelial lesions (LSIL and high-grade squamous intraepithelial lesions (HSIL. Moreover, most cellular genes within or near these integration sites are cancer-associated genes. Taken together, this study suggests that the multiple-integrations of HPV genome during persistent viral infection, which thereby alters the expression patterns of viral oncogenes and integration-related cellular genes, play a crucial role in progression of cervical lesions to cervix cancer.

Patient-controlled encrypted genomic data: an approach to advance clinical genomics

Directory of Open Access Journals (Sweden)

Trakadis Yannis J

2012-07-01

Full Text Available Abstract Background The revolution in DNA sequencing technologies over the past decade has made it feasible to sequence an individual’s whole genome at a relatively low cost. The potential value of the information generated by genomic technologies for medicine and society is enormous. However, in order for exome sequencing, and eventually whole genome sequencing, to be implemented clinically, a number of major challenges need to be overcome. For instance, obtaining meaningful informed-consent, managing incidental findings and the great volume of data generated (including multiple findings with uncertain clinical significance, re-interpreting the genomic data and providing additional counselling to patients as genetic knowledge evolves are issues that need to be addressed. It appears that medical genetics is shifting from the present “phenotype-first” medical model to a “data-first” model which leads to multiple complexities. Discussion This manuscript discusses the different challenges associated with integrating genomic technologies into clinical practice and describes a “phenotype-first” approach, namely, “Individualized Mutation-weighed Phenotype Search”, and its benefits. The proposed approach allows for a more efficient prioritization of the genes to be tested in a clinical lab based on both the patient’s phenotype and his/her entire genomic data. It simplifies “informed-consent” for clinical use of genomic technologies and helps to protect the patient’s autonomy and privacy. Overall, this approach could potentially render widespread use of genomic technologies, in the immediate future, practical, ethical and clinically useful. Summary The “Individualized Mutation-weighed Phenotype Search” approach allows for an incremental integration of genomic technologies into clinical practice. It ensures that we do not over-medicalize genomic data but, rather, continue our current medical model which is based on serving

Robust and rapid algorithms facilitate large-scale whole genome sequencing downstream analysis in an integrative framework.

Science.gov (United States)

Li, Miaoxin; Li, Jiang; Li, Mulin Jun; Pan, Zhicheng; Hsu, Jacob Shujui; Liu, Dajiang J; Zhan, Xiaowei; Wang, Junwen; Song, Youqiang; Sham, Pak Chung

2017-05-19

Whole genome sequencing (WGS) is a promising strategy to unravel variants or genes responsible for human diseases and traits. However, there is a lack of robust platforms for a comprehensive downstream analysis. In the present study, we first proposed three novel algorithms, sequence gap-filled gene feature annotation, bit-block encoded genotypes and sectional fast access to text lines to address three fundamental problems. The three algorithms then formed the infrastructure of a robust parallel computing framework, KGGSeq, for integrating downstream analysis functions for whole genome sequencing data. KGGSeq has been equipped with a comprehensive set of analysis functions for quality control, filtration, annotation, pathogenic prediction and statistical tests. In the tests with whole genome sequencing data from 1000 Genomes Project, KGGSeq annotated several thousand more reliable non-synonymous variants than other widely used tools (e.g. ANNOVAR and SNPEff). It took only around half an hour on a small server with 10 CPUs to access genotypes of ∼60 million variants of 2504 subjects, while a popular alternative tool required around one day. KGGSeq's bit-block genotype format used 1.5% or less space to flexibly represent phased or unphased genotypes with multiple alleles and achieved a speed of over 1000 times faster to calculate genotypic correlation. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

SilkDB: a knowledgebase for silkworm biology and genomics

DEFF Research Database (Denmark)

Wang, Jing; Xia, Qingyou; He, Ximiao

2005-01-01

The Silkworm Knowledgebase (SilkDB) is a web-based repository for the curation, integration and study of silkworm genetic and genomic data. With the recent accomplishment of a approximately 6X draft genome sequence of the domestic silkworm (Bombyx mori), SilkDB provides an integrated representati....... SilkDB is publicly accessible at http://silkworm.genomics.org.cn. Udgivelsesdato: 2005-Jan-1...

VaProS: a database-integration approach for protein/genome information retrieval

KAUST Repository

Gojobori, Takashi; Ikeo, Kazuho; Katayama, Yukie; Kawabata, Takeshi; Kinjo, Akira R.; Kinoshita, Kengo; Kwon, Yeondae; Migita, Ohsuke; Mizutani, Hisashi; Muraoka, Masafumi; Nagata, Koji; Omori, Satoshi; Sugawara, Hideaki; Yamada, Daichi; Yura, Kei

2016-01-01

Life science research now heavily relies on all sorts of databases for genome sequences, transcription, protein three-dimensional (3D) structures, protein–protein interactions, phenotypes and so forth. The knowledge accumulated by all the omics research is so vast that a computer-aided search of data is now a prerequisite for starting a new study. In addition, a combinatory search throughout these databases has a chance to extract new ideas and new hypotheses that can be examined by wet-lab experiments. By virtually integrating the related databases on the Internet, we have built a new web application that facilitates life science researchers for retrieving experts’ knowledge stored in the databases and for building a new hypothesis of the research target. This web application, named VaProS, puts stress on the interconnection between the functional information of genome sequences and protein 3D structures, such as structural effect of the gene mutation. In this manuscript, we present the notion of VaProS, the databases and tools that can be accessed without any knowledge of database locations and data formats, and the power of search exemplified in quest of the molecular mechanisms of lysosomal storage disease. VaProS can be freely accessed at http://p4d-info.nig.ac.jp/vapros/.

VaProS: a database-integration approach for protein/genome information retrieval

KAUST Repository

Gojobori, Takashi

2016-12-24

Life science research now heavily relies on all sorts of databases for genome sequences, transcription, protein three-dimensional (3D) structures, protein–protein interactions, phenotypes and so forth. The knowledge accumulated by all the omics research is so vast that a computer-aided search of data is now a prerequisite for starting a new study. In addition, a combinatory search throughout these databases has a chance to extract new ideas and new hypotheses that can be examined by wet-lab experiments. By virtually integrating the related databases on the Internet, we have built a new web application that facilitates life science researchers for retrieving experts’ knowledge stored in the databases and for building a new hypothesis of the research target. This web application, named VaProS, puts stress on the interconnection between the functional information of genome sequences and protein 3D structures, such as structural effect of the gene mutation. In this manuscript, we present the notion of VaProS, the databases and tools that can be accessed without any knowledge of database locations and data formats, and the power of search exemplified in quest of the molecular mechanisms of lysosomal storage disease. VaProS can be freely accessed at http://p4d-info.nig.ac.jp/vapros/.

Applications of neural network to numerical analyses

International Nuclear Information System (INIS)

Takeda, Tatsuoki; Fukuhara, Makoto; Ma, Xiao-Feng; Liaqat, Ali

1999-01-01

Applications of a multi-layer neural network to numerical analyses are described. We are mainly concerned with the computed tomography and the solution of differential equations. In both cases as the objective functions for the training process of the neural network we employed residuals of the integral equation or the differential equations. This is different from the conventional neural network training where sum of the squared errors of the output values is adopted as the objective function. For model problems both the methods gave satisfactory results and the methods are considered promising for some kind of problems. (author)

Event- and Time-Driven Techniques Using Parallel CPU-GPU Co-processing for Spiking Neural Networks.

Science.gov (United States)

Naveros, Francisco; Garrido, Jesus A; Carrillo, Richard R; Ros, Eduardo; Luque, Niceto R

2017-01-01

Modeling and simulating the neural structures which make up our central neural system is instrumental for deciphering the computational neural cues beneath. Higher levels of biological plausibility usually impose higher levels of complexity in mathematical modeling, from neural to behavioral levels. This paper focuses on overcoming the simulation problems (accuracy and performance) derived from using higher levels of mathematical complexity at a neural level. This study proposes different techniques for simulating neural models that hold incremental levels of mathematical complexity: leaky integrate-and-fire (LIF), adaptive exponential integrate-and-fire (AdEx), and Hodgkin-Huxley (HH) neural models (ranged from low to high neural complexity). The studied techniques are classified into two main families depending on how the neural-model dynamic evaluation is computed: the event-driven or the time-driven families. Whilst event-driven techniques pre-compile and store the neural dynamics within look-up tables, time-driven techniques compute the neural dynamics iteratively during the simulation time. We propose two modifications for the event-driven family: a look-up table recombination to better cope with the incremental neural complexity together with a better handling of the synchronous input activity. Regarding the time-driven family, we propose a modification in computing the neural dynamics: the bi-fixed-step integration method. This method automatically adjusts the simulation step size to better cope with the stiffness of the neural model dynamics running in CPU platforms. One version of this method is also implemented for hybrid CPU-GPU platforms. Finally, we analyze how the performance and accuracy of these modifications evolve with increasing levels of neural complexity. We also demonstrate how the proposed modifications which constitute the main contribution of this study systematically outperform the traditional event- and time-driven techniques under

The genome portal of the Department of Energy Joint Genome Institute: 2014 updates

Energy Technology Data Exchange (ETDEWEB)

Nordberg, Henrik [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States); Cantor, Michael [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States); Dusheyko, Serge [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States); Hua, Susan [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States); Poliakov, Alexander [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States); Shabalov, Igor [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States); Smirnova, Tatyana [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States); Grigoriev, Igor V. [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States); Dubchak, Inna [USDOE Joint Genome Institute (JGI), Walnut Creek, CA (United States)

2013-11-12

The U.S. Department of Energy (DOE) Joint Genome Institute (JGI), a national user facility, serves the diverse scientific community by providing integrated high-throughput sequencing and computational analysis to enable system-based scientific approaches in support of DOE missions related to clean energy generation and environmental characterization. The JGI Genome Portal (http://genome.jgi.doe.gov) provides unified access to all JGI genomic databases and analytical tools. The JGI maintains extensive data management systems and specialized analytical capabilities to manage and interpret complex genomic data. A user can search, download and explore multiple data sets available for all DOE JGI sequencing projects including their status, assemblies and annotations of sequenced genomes. In this paper, we describe major updates of the Genome Portal in the past 2 years with a specific emphasis on efficient handling of the rapidly growing amount of diverse genomic data accumulated in JGI.

Implementing genomics and pharmacogenomics in the clinic: The National Human Genome Research Institute’s genomic medicine portfolio

Science.gov (United States)

Manolio, Teri A.

2016-01-01

Increasing knowledge about the influence of genetic variation on human health and growing availability of reliable, cost-effective genetic testing have spurred the implementation of genomic medicine in the clinic. As defined by the National Human Genome Research Institute (NHGRI), genomic medicine uses an individual’s genetic information in his or her clinical care, and has begun to be applied effectively in areas such as cancer genomics, pharmacogenomics, and rare and undiagnosed diseases. In 2011 NHGRI published its strategic vision for the future of genomic research, including an ambitious research agenda to facilitate and promote the implementation of genomic medicine. To realize this agenda, NHGRI is consulting and facilitating collaborations with the external research community through a series of “Genomic Medicine Meetings,” under the guidance and leadership of the National Advisory Council on Human Genome Research. These meetings have identified and begun to address significant obstacles to implementation, such as lack of evidence of efficacy, limited availability of genomics expertise and testing, lack of standards, and diffficulties in integrating genomic results into electronic medical records. The six research and dissemination initiatives comprising NHGRI’s genomic research portfolio are designed to speed the evaluation and incorporation, where appropriate, of genomic technologies and findings into routine clinical care. Actual adoption of successful approaches in clinical care will depend upon the willingness, interest, and energy of professional societies, practitioners, patients, and payers to promote their responsible use and share their experiences in doing so. PMID:27612677

Integration of heterologous DNA into the genome of Paracoccus denitrificans is mediated by a family of IS1248-related elements and a second type of integrative recombination event

NARCIS (Netherlands)

Van Spanning, R J; Reijnders, W N; Stouthamer, A.H.

All members of the IS1248 family residing in the genome of Paracoccus denitrificans have been isolated by using a set of insertion sequence entrapment vectors. The family consists of five closely related members that integrate the entrapment vectors at distinct sites. One of these, IS1248b, was

An integrated multichannel neural recording analog front-end ASIC with area-efficient driven right leg circuit.

Science.gov (United States)

Tao Tang; Wang Ling Goh; Lei Yao; Jia Hao Cheong; Yuan Gao

2017-07-01

This paper describes an integrated multichannel neural recording analog front end (AFE) with a novel area-efficient driven right leg (DRL) circuit to improve the system common mode rejection ratio (CMRR). The proposed AFE consists of an AC-coupled low-noise programmable-gain amplifier, an area-efficient DRL block and a 10-bit SAR ADC. Compared to conventional DRL circuit, the proposed capacitor-less DRL design achieves 90% chip area reduction with enhanced CMRR performance, making it ideal for multichannel biomedical recording applications. The AFE circuit has been designed in a standard 0.18-μm CMOS process. Post-layout simulation results show that the AFE provides two gain settings of 54dB/60dB while consuming 1 μA per channel under a supply voltage of 1 V. The input-referred noise of the AFE integrated from 1 Hz to 10k Hz is only 4 μVrms and the CMRR is 110 dB.

Neural decoding of collective wisdom with multi-brain computing.

Science.gov (United States)

Eckstein, Miguel P; Das, Koel; Pham, Binh T; Peterson, Matthew F; Abbey, Craig K; Sy, Jocelyn L; Giesbrecht, Barry

2012-01-02

Group decisions and even aggregation of multiple opinions lead to greater decision accuracy, a phenomenon known as collective wisdom. Little is known about the neural basis of collective wisdom and whether its benefits arise in late decision stages or in early sensory coding. Here, we use electroencephalography and multi-brain computing with twenty humans making perceptual decisions to show that combining neural activity across brains increases decision accuracy paralleling the improvements shown by aggregating the observers' opinions. Although the largest gains result from an optimal linear combination of neural decision variables across brains, a simpler neural majority decision rule, ubiquitous in human behavior, results in substantial benefits. In contrast, an extreme neural response rule, akin to a group following the most extreme opinion, results in the least improvement with group size. Analyses controlling for number of electrodes and time-points while increasing number of brains demonstrate unique benefits arising from integrating neural activity across different brains. The benefits of multi-brain integration are present in neural activity as early as 200 ms after stimulus presentation in lateral occipital sites and no additional benefits arise in decision related neural activity. Sensory-related neural activity can predict collective choices reached by aggregating individual opinions, voting results, and decision confidence as accurately as neural activity related to decision components. Estimation of the potential for the collective to execute fast decisions by combining information across numerous brains, a strategy prevalent in many animals, shows large time-savings. Together, the findings suggest that for perceptual decisions the neural activity supporting collective wisdom and decisions arises in early sensory stages and that many properties of collective cognition are explainable by the neural coding of information across multiple brains. Finally

Neural Tube Defects, Folic Acid and Methylation

Science.gov (United States)

Imbard, Apolline; Benoist, Jean-François; Blom, Henk J.

2013-01-01

Neural tube defects (NTDs) are common complex congenital malformations resulting from failure of the neural tube closure during embryogenesis. It is established that folic acid supplementation decreases the prevalence of NTDs, which has led to national public health policies regarding folic acid. To date, animal studies have not provided sufficient information to establish the metabolic and/or genomic mechanism(s) underlying human folic acid responsiveness in NTDs. However, several lines of evidence suggest that not only folates but also choline, B12 and methylation metabolisms are involved in NTDs. Decreased B12 vitamin and increased total choline or homocysteine in maternal blood have been shown to be associated with increased NTDs risk. Several polymorphisms of genes involved in these pathways have also been implicated in risk of development of NTDs. This raises the question whether supplementation with B12 vitamin, betaine or other methylation donors in addition to folic acid periconceptional supplementation will further reduce NTD risk. The objective of this article is to review the role of methylation metabolism in the onset of neural tube defects. PMID:24048206

Sparse multivariate factor analysis regression models and its applications to integrative genomics analysis.

Science.gov (United States)

Zhou, Yan; Wang, Pei; Wang, Xianlong; Zhu, Ji; Song, Peter X-K

2017-01-01

The multivariate regression model is a useful tool to explore complex associations between two kinds of molecular markers, which enables the understanding of the biological pathways underlying disease etiology. For a set of correlated response variables, accounting for such dependency can increase statistical power. Motivated by integrative genomic data analyses, we propose a new methodology-sparse multivariate factor analysis regression model (smFARM), in which correlations of response variables are assumed to follow a factor analysis model with latent factors. This proposed method not only allows us to address the challenge that the number of association parameters is larger than the sample size, but also to adjust for unobserved genetic and/or nongenetic factors that potentially conceal the underlying response-predictor associations. The proposed smFARM is implemented by the EM algorithm and the blockwise coordinate descent algorithm. The proposed methodology is evaluated and compared to the existing methods through extensive simulation studies. Our results show that accounting for latent factors through the proposed smFARM can improve sensitivity of signal detection and accuracy of sparse association map estimation. We illustrate smFARM by two integrative genomics analysis examples, a breast cancer dataset, and an ovarian cancer dataset, to assess the relationship between DNA copy numbers and gene expression arrays to understand genetic regulatory patterns relevant to the disease. We identify two trans-hub regions: one in cytoband 17q12 whose amplification influences the RNA expression levels of important breast cancer genes, and the other in cytoband 9q21.32-33, which is associated with chemoresistance in ovarian cancer. © 2016 WILEY PERIODICALS, INC.

Early warning of illegal development for protected areas by integrating cellular automata with neural networks.

Science.gov (United States)

Li, Xia; Lao, Chunhua; Liu, Yilun; Liu, Xiaoping; Chen, Yimin; Li, Shaoying; Ai, Bing; He, Zijian

2013-11-30

Ecological security has become a major issue under fast urbanization in China. As the first two cities in this country, Shenzhen and Dongguan issued the ordinance of Eco-designated Line of Control (ELC) to "wire" ecologically important areas for strict protection in 2005 and 2009 respectively. Early warning systems (EWS) are a useful tool for assisting the implementation ELC. In this study, a multi-model approach is proposed for the early warning of illegal development by integrating cellular automata (CA) and artificial neural networks (ANN). The objective is to prevent the ecological risks or catastrophe caused by such development at an early stage. The integrated model is calibrated by using the empirical information from both remote sensing and handheld GPS (global positioning systems). The MAR indicator which is the ratio of missing alarms to all the warnings is proposed for better assessment of the model performance. It is found that the fast urban development has caused significant threats to natural-area protection in the study area. The integration of CA, ANN and GPS provides a powerful tool for describing and predicting illegal development which is in highly non-linear and fragmented forms. The comparison shows that this multi-model approach has much better performances than the single-model approach for the early warning. Compared with the single models of CA and ANN, this integrated multi-model can improve the value of MAR by 65.48% and 5.17% respectively. Copyright © 2013 Elsevier Ltd. All rights reserved.

Endogenous viral elements in animal genomes.

Directory of Open Access Journals (Sweden)

Aris Katzourakis

2010-11-01

Full Text Available Integration into the nuclear genome of germ line cells can lead to vertical inheritance of retroviral genes as host alleles. For other viruses, germ line integration has only rarely been documented. Nonetheless, we identified endogenous viral elements (EVEs derived from ten non-retroviral families by systematic in silico screening of animal genomes, including the first endogenous representatives of double-stranded RNA, reverse-transcribing DNA, and segmented RNA viruses, and the first endogenous DNA viruses in mammalian genomes. Phylogenetic and genomic analysis of EVEs across multiple host species revealed novel information about the origin and evolution of diverse virus groups. Furthermore, several of the elements identified here encode intact open reading frames or are expressed as mRNA. For one element in the primate lineage, we provide statistically robust evidence for exaptation. Our findings establish that genetic material derived from all known viral genome types and replication strategies can enter the animal germ line, greatly broadening the scope of paleovirological studies and indicating a more significant evolutionary role for gene flow from virus to animal genomes than has previously been recognized.

The Laplacian spectrum of neural networks

Science.gov (United States)

de Lange, Siemon C.; de Reus, Marcel A.; van den Heuvel, Martijn P.

2014-01-01

The brain is a complex network of neural interactions, both at the microscopic and macroscopic level. Graph theory is well suited to examine the global network architecture of these neural networks. Many popular graph metrics, however, encode average properties of individual network elements. Complementing these “conventional” graph metrics, the eigenvalue spectrum of the normalized Laplacian describes a network's structure directly at a systems level, without referring to individual nodes or connections. In this paper, the Laplacian spectra of the macroscopic anatomical neuronal networks of the macaque and cat, and the microscopic network of the Caenorhabditis elegans were examined. Consistent with conventional graph metrics, analysis of the Laplacian spectra revealed an integrative community structure in neural brain networks. Extending previous findings of overlap of network attributes across species, similarity of the Laplacian spectra across the cat, macaque and C. elegans neural networks suggests a certain level of consistency in the overall architecture of the anatomical neural networks of these species. Our results further suggest a specific network class for neural networks, distinct from conceptual small-world and scale-free models as well as several empirical networks. PMID:24454286

Genomics in Public Health: Perspective from the Office of Public Health Genomics at the Centers for Disease Control and Prevention (CDC

Directory of Open Access Journals (Sweden)

Ridgely Fisk Green

2015-09-01

Full Text Available The national effort to use genomic knowledge to save lives is gaining momentum, as illustrated by the inclusion of genomics in key public health initiatives, including Healthy People 2020, and the recent launch of the precision medicine initiative. The Office of Public Health Genomics (OPHG at the Centers for Disease Control and Prevention (CDC partners with state public health departments and others to advance the translation of genome-based discoveries into disease prevention and population health. To do this, OPHG has adopted an “identify, inform, and integrate” model: identify evidence-based genomic applications ready for implementation, inform stakeholders about these applications, and integrate these applications into public health at the local, state, and national level. This paper addresses current and future work at OPHG for integrating genomics into public health programs.

Robust Adaptive Neural Control of Morphing Aircraft with Prescribed Performance

OpenAIRE

Wu, Zhonghua; Lu, Jingchao; Shi, Jingping; Liu, Yang; Zhou, Qing

2017-01-01

This study proposes a low-computational composite adaptive neural control scheme for the longitudinal dynamics of a swept-back wing aircraft subject to parameter uncertainties. To efficiently release the constraint often existing in conventional neural designs, whose closed-loop stability analysis always necessitates that neural networks (NNs) be confined in the active regions, a smooth switching function is presented to conquer this issue. By integrating minimal learning parameter (MLP) tech...

HGVA: the Human Genome Variation Archive.

Science.gov (United States)

Lopez, Javier; Coll, Jacobo; Haimel, Matthias; Kandasamy, Swaathi; Tarraga, Joaquin; Furio-Tari, Pedro; Bari, Wasim; Bleda, Marta; Rueda, Antonio; Gräf, Stefan; Rendon, Augusto; Dopazo, Joaquin; Medina, Ignacio

2017-07-03

High-profile genomic variation projects like the 1000 Genomes project or the Exome Aggregation Consortium, are generating a wealth of human genomic variation knowledge which can be used as an essential reference for identifying disease-causing genotypes. However, accessing these data, contrasting the various studies and integrating those data in downstream analyses remains cumbersome. The Human Genome Variation Archive (HGVA) tackles these challenges and facilitates access to genomic data for key reference projects in a clean, fast and integrated fashion. HGVA provides an efficient and intuitive web-interface for easy data mining, a comprehensive RESTful API and client libraries in Python, Java and JavaScript for fast programmatic access to its knowledge base. HGVA calculates population frequencies for these projects and enriches their data with variant annotation provided by CellBase, a rich and fast annotation solution. HGVA serves as a proof-of-concept of the genome analysis developments being carried out by the University of Cambridge together with UK's 100 000 genomes project and the National Institute for Health Research BioResource Rare-Diseases, in particular, deploying open-source for Computational Biology (OpenCB) software platform for storing and analyzing massive genomic datasets. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Individual capacity for DNA repair and maintenance of genomic integrity: a fertile ground for studies in the field of assisted reproduction

Directory of Open Access Journals (Sweden)

Radoslava Vazharova

2016-05-01

Full Text Available Many factors may affect the chances for successful pregnancy, especially at a later age. Fertility evaluations including genetic analysis are recommended to couples that have not achieved pregnancy within 6–12 months of unprotected intercourse. This review discusses some of the common polymorphisms in genes coding for proteins functioning in DNA damage identification and repair and maintenance of genomic integrity that may affect the chances of success in natural conception as well as in assisted reproduction (AR. Common polymorphisms in genes coding for proteins functioning in DNA damage identification and repair and maintenance of genomic integrity may affect the chances of success in assisted reproduction as well as in natural conception. The effects of carriership of different alleles of key genes of DNA repair may have differential effects in men and women and at different ages, suggesting complex interactions with the mechanisms controlling cell and tissue aging and programmed cell death. Future studies in the field are needed in order to elucidate the genotype–phenotype relationships and to translate the knowledge about individual repair capacity and maintenance of genomic integrity to potential clinical applications. Abbreviations: aCGH: microarray-based comparative genomic hybridization; AR: assisted reproduction; ATM: ataxia-telangiectasia mutated; ATP: adenosine triphosphate; BER: base excision repair; BFE: basic fertility evaluation; DMSO: dimethyl sulfoxide; FSH: follicle-stimulating hormone; GNRHR: gonadotropin-releasing hormone receptor; HMG: high-mobility group; ICSI: intracytoplasmic sperm injection; IUI: intrauterine insemination; IVF: in vitro fertilization; LH: luteinizing hormone; LIF: leukaemia inhibitory factor; MTR: methionine synthase; MTRR: methionine synthase reductase; NGS: next-generation sequencing; NER: nucleotide excision repair; NHEJ: non-homologous end joining; PAH: polycyclic aromatic hydrocarbons; PCOS

Puzzle Pieces: Neural Structure and Function in Prader-Willi Syndrome

Science.gov (United States)

Manning, Katherine E.; Holland, Anthony J.

2015-01-01

Prader-Willi syndrome (PWS) is a neurodevelopmental disorder of genomic imprinting, presenting with a behavioural phenotype encompassing hyperphagia, intellectual disability, social and behavioural difficulties, and propensity to psychiatric illness. Research has tended to focus on the cognitive and behavioural investigation of these features, and, with the exception of eating behaviour, the neural physiology is currently less well understood. A systematic review was undertaken to explore findings relating to neural structure and function in PWS, using search terms designed to encompass all published articles concerning both in vivo and post-mortem studies of neural structure and function in PWS. This supported the general paucity of research in this area, with many articles reporting case studies and qualitative descriptions or focusing solely on the overeating behaviour, although a number of systematic investigations were also identified. Research to date implicates a combination of subcortical and higher order structures in PWS, including those involved in processing reward, motivation, affect and higher order cognitive functions, with both anatomical and functional investigations indicating abnormalities. It appears likely that PWS involves aberrant activity across distributed neural networks. The characterisation of neural structure and function warrants both replication and further systematic study. PMID:28943631

Puzzle Pieces: Neural Structure and Function in Prader-Willi Syndrome

Directory of Open Access Journals (Sweden)

Katherine E. Manning

2015-12-01

Full Text Available Prader-Willi syndrome (PWS is a neurodevelopmental disorder of genomic imprinting, presenting with a behavioural phenotype encompassing hyperphagia, intellectual disability, social and behavioural difficulties, and propensity to psychiatric illness. Research has tended to focus on the cognitive and behavioural investigation of these features, and, with the exception of eating behaviour, the neural physiology is currently less well understood. A systematic review was undertaken to explore findings relating to neural structure and function in PWS, using search terms designed to encompass all published articles concerning both in vivo and post-mortem studies of neural structure and function in PWS. This supported the general paucity of research in this area, with many articles reporting case studies and qualitative descriptions or focusing solely on the overeating behaviour, although a number of systematic investigations were also identified. Research to date implicates a combination of subcortical and higher order structures in PWS, including those involved in processing reward, motivation, affect and higher order cognitive functions, with both anatomical and functional investigations indicating abnormalities. It appears likely that PWS involves aberrant activity across distributed neural networks. The characterisation of neural structure and function warrants both replication and further systematic study.

Integrative genome-wide expression profiling identifies three distinct molecular subgroups of renal cell carcinoma with different patient outcome

Directory of Open Access Journals (Sweden)

Beleut Manfred

2012-07-01

Full Text Available Abstract Background Renal cell carcinoma (RCC is characterized by a number of diverse molecular aberrations that differ among individuals. Recent approaches to molecularly classify RCC were based on clinical, pathological as well as on single molecular parameters. As a consequence, gene expression patterns reflecting the sum of genetic aberrations in individual tumors may not have been recognized. In an attempt to uncover such molecular features in RCC, we used a novel, unbiased and integrative approach. Methods We integrated gene expression data from 97 primary RCC of different pathologic parameters, 15 RCC metastases as well as 34 cancer cell lines for two-way nonsupervised hierarchical clustering using gene groups suggested by the PANTHER Classification System. We depicted the genomic landscape of the resulted tumor groups by means of Single Nuclear Polymorphism (SNP technology. Finally, the achieved results were immunohistochemically analyzed using a tissue microarray (TMA composed of 254 RCC. Results We found robust, genome wide expression signatures, which split RCC into three distinct molecular subgroups. These groups remained stable even if randomly selected gene sets were clustered. Notably, the pattern obtained from RCC cell lines was clearly distinguishable from that of primary tumors. SNP array analysis demonstrated differing frequencies of chromosomal copy number alterations among RCC subgroups. TMA analysis with group-specific markers showed a prognostic significance of the different groups. Conclusion We propose the existence of characteristic and histologically independent genome-wide expression outputs in RCC with potential biological and clinical relevance.

Distinct high resolution genome profiles of early onset and late onset colorectal cancer integrated with gene expression data identify candidate susceptibility loci

Directory of Open Access Journals (Sweden)

Merok Marianne A

2010-05-01

Full Text Available Abstract Background Estimates suggest that up to 30% of colorectal cancers (CRC may develop due to an increased genetic risk. The mean age at diagnosis for CRC is about 70 years. Time of disease onset 20 years younger than the mean age is assumed to be indicative of genetic susceptibility. We have compared high resolution tumor genome copy number variation (CNV (Roche NimbleGen, 385 000 oligo CGH array in microsatellite stable (MSS tumors from two age groups, including 23 young at onset patients without known hereditary syndromes and with a median age of 44 years (range: 28-53 and 17 elderly patients with median age 79 years (range: 69-87. Our aim was to identify differences in the tumor genomes between these groups and pinpoint potential susceptibility loci. Integration analysis of CNV and genome wide mRNA expression data, available for the same tumors, was performed to identify a restricted candidate gene list. Results The total fraction of the genome with aberrant copy number, the overall genomic profile and the TP53 mutation spectrum were similar between the two age groups. However, both the number of chromosomal aberrations and the number of breakpoints differed significantly between the groups. Gains of 2q35, 10q21.3-22.1, 10q22.3 and 19q13.2-13.31 and losses from 1p31.3, 1q21.1, 2q21.2, 4p16.1-q28.3, 10p11.1 and 19p12, positions that in total contain more than 500 genes, were found significantly more often in the early onset group as compared to the late onset group. Integration analysis revealed a covariation of DNA copy number at these sites and mRNA expression for 107 of the genes. Seven of these genes, CLC, EIF4E, LTBP4, PLA2G12A, PPAT, RG9MTD2, and ZNF574, had significantly different mRNA expression comparing median expression levels across the transcriptome between the two groups. Conclusions Ten genomic loci, containing more than 500 protein coding genes, are identified as more often altered in tumors from early onset versus late

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.

Collaborative Genomics Study Advances Precision Oncology

Science.gov (United States)

A collaborative study conducted by two Office of Cancer Genomics (OCG) initiatives highlights the importance of integrating structural and functional genomics programs to improve cancer therapies, and more specifically, contribute to precision oncology treatments for children.

Neural synchronization during face-to-face communication.

Science.gov (United States)

Jiang, Jing; Dai, Bohan; Peng, Danling; Zhu, Chaozhe; Liu, Li; Lu, Chunming

2012-11-07

Although the human brain may have evolutionarily adapted to face-to-face communication, other modes of communication, e.g., telephone and e-mail, increasingly dominate our modern daily life. This study examined the neural difference between face-to-face communication and other types of communication by simultaneously measuring two brains using a hyperscanning approach. The results showed a significant increase in the neural synchronization in the left inferior frontal cortex during a face-to-face dialog between partners but none during a back-to-back dialog, a face-to-face monologue, or a back-to-back monologue. Moreover, the neural synchronization between partners during the face-to-face dialog resulted primarily from the direct interactions between the partners, including multimodal sensory information integration and turn-taking behavior. The communicating behavior during the face-to-face dialog could be predicted accurately based on the neural synchronization level. These results suggest that face-to-face communication, particularly dialog, has special neural features that other types of communication do not have and that the neural synchronization between partners may underlie successful face-to-face communication.

[Investigation of neural stem cell-derived donor contribution in the inner ear following blastocyst injection].

Science.gov (United States)

Volkenstein, S; Brors, D; Hansen, S; Mlynski, R; Dinger, T C; Müller, A M; Dazert, S

2008-03-01

Utilising the enormous proliferation and multi-lineage differentiation potentials of somatic stem cells represents a possible therapeutical strategy for diseases of non-regenerative tissues like the inner ear. In the current study, the possibility of murine neural stem cells to contribute to the developing inner ear following blastocyst injection was investigated. Fetal brain-derived neural stem cells from the embryonic day 14 cortex of male mice were isolated and expanded for four weeks in neurobasal media supplemented with bFGF and EGF. Neural stem cells of male animals were harvested, injected into blastocysts and the blastocysts were transferred into pseudo-pregnant foster animals. Each blastocyst was injected with 5-15 microspheres growing from single cell suspension from neurospheres dissociated the day before. The resulting mice were investigated six months POST PARTUM for the presence of donor cells. Brainstem evoked response audiometry (BERA) was performed in six animals. To visualize donor cells Lac-Z staining was performed on sliced cochleas of two animals. In addition, the cochleas of four female animals were isolated and genomic DNA of the entire cochlea was analyzed for donor contribution by Y-chromosome-specific PCR. All animals had normal thresholds in brainstem evoked response audiometry. The male-specific PCR product indicating the presence of male donor cells were detected in the cochleas of three of the four female animals investigated. In two animals, male donor cells were detected unilateral, in one animal bilateral. The results suggest that descendants of neural stem cells are detectable in the inner ear after injection into blastocysts and possess the ability to integrate into the developing inner ear without obvious loss in hearing function.

The Dynamics and Neural Correlates of Audio-Visual Integration Capacity as Determined by Temporal Unpredictability, Proactive Interference, and SOA.

Science.gov (United States)

Wilbiks, Jonathan M P; Dyson, Benjamin J

2016-01-01

Over 5 experiments, we challenge the idea that the capacity of audio-visual integration need be fixed at 1 item. We observe that the conditions under which audio-visual integration is most likely to exceed 1 occur when stimulus change operates at a slow rather than fast rate of presentation and when the task is of intermediate difficulty such as when low levels of proactive interference (3 rather than 8 interfering visual presentations) are combined with the temporal unpredictability of the critical frame (Experiment 2), or, high levels of proactive interference are combined with the temporal predictability of the critical frame (Experiment 4). Neural data suggest that capacity might also be determined by the quality of perceptual information entering working memory. Experiment 5 supported the proposition that audio-visual integration was at play during the previous experiments. The data are consistent with the dynamic nature usually associated with cross-modal binding, and while audio-visual integration capacity likely cannot exceed uni-modal capacity estimates, performance may be better than being able to associate only one visual stimulus with one auditory stimulus.

A Tensor-Product-Kernel Framework for Multiscale Neural Activity Decoding and Control

Science.gov (United States)

Li, Lin; Brockmeier, Austin J.; Choi, John S.; Francis, Joseph T.; Sanchez, Justin C.; Príncipe, José C.

2014-01-01

Brain machine interfaces (BMIs) have attracted intense attention as a promising technology for directly interfacing computers or prostheses with the brain's motor and sensory areas, thereby bypassing the body. The availability of multiscale neural recordings including spike trains and local field potentials (LFPs) brings potential opportunities to enhance computational modeling by enriching the characterization of the neural system state. However, heterogeneity on data type (spike timing versus continuous amplitude signals) and spatiotemporal scale complicates the model integration of multiscale neural activity. In this paper, we propose a tensor-product-kernel-based framework to integrate the multiscale activity and exploit the complementary information available in multiscale neural activity. This provides a common mathematical framework for incorporating signals from different domains. The approach is applied to the problem of neural decoding and control. For neural decoding, the framework is able to identify the nonlinear functional relationship between the multiscale neural responses and the stimuli using general purpose kernel adaptive filtering. In a sensory stimulation experiment, the tensor-product-kernel decoder outperforms decoders that use only a single neural data type. In addition, an adaptive inverse controller for delivering electrical microstimulation patterns that utilizes the tensor-product kernel achieves promising results in emulating the responses to natural stimulation. PMID:24829569

Neural network CT image reconstruction method for small amount of projection data

International Nuclear Information System (INIS)

Ma, X.F.; Fukuhara, M.; Takeda, T.

2000-01-01

This paper presents a new method for two-dimensional image reconstruction by using a multi-layer neural network. Though a conventionally used object function of such a neural network is composed of a sum of squared errors of the output data, we define an object function composed of a sum of squared residuals of an integral equation. By employing an appropriate numerical line integral for this integral equation, we can construct a neural network which can be used for CT image reconstruction for cases with small amount of projection data. We applied this method to some model problems and obtained satisfactory results. This method is especially useful for analyses of laboratory experiments or field observations where only a small amount of projection data is available in comparison with the well-developed medical applications

Neural network CT image reconstruction method for small amount of projection data

CERN Document Server

Ma, X F; Takeda, T

2000-01-01

This paper presents a new method for two-dimensional image reconstruction by using a multi-layer neural network. Though a conventionally used object function of such a neural network is composed of a sum of squared errors of the output data, we define an object function composed of a sum of squared residuals of an integral equation. By employing an appropriate numerical line integral for this integral equation, we can construct a neural network which can be used for CT image reconstruction for cases with small amount of projection data. We applied this method to some model problems and obtained satisfactory results. This method is especially useful for analyses of laboratory experiments or field observations where only a small amount of projection data is available in comparison with the well-developed medical applications.

Inferring genetic architecture of complex traits using Bayesian integrative analysis of genome and transcriptiome data

DEFF Research Database (Denmark)

Ehsani, Alireza; Sørensen, Peter; Pomp, Daniel

2012-01-01

Background To understand the genetic architecture of complex traits and bridge the genotype-phenotype gap, it is useful to study intermediate -omics data, e.g. the transcriptome. The present study introduces a method for simultaneous quantification of the contributions from single nucleotide......-modal distribution of genomic values collapses, when gene expressions are added to the model Conclusions With increased availability of various -omics data, integrative approaches are promising tools for understanding the genetic architecture of complex traits. Partitioning of explained variances at the chromosome...

DFAST and DAGA: web-based integrated genome annotation tools and resources.

Science.gov (United States)

Tanizawa, Yasuhiro; Fujisawa, Takatomo; Kaminuma, Eli; Nakamura, Yasukazu; Arita, Masanori

2016-01-01

Quality assurance and correct taxonomic affiliation of data submitted to public sequence databases have been an everlasting problem. The DDBJ Fast Annotation and Submission Tool (DFAST) is a newly developed genome annotation pipeline with quality and taxonomy assessment tools. To enable annotation of ready-to-submit quality, we also constructed curated reference protein databases tailored for lactic acid bacteria. DFAST was developed so that all the procedures required for DDBJ submission could be done seamlessly online. The online workspace would be especially useful for users not familiar with bioinformatics skills. In addition, we have developed a genome repository, DFAST Archive of Genome Annotation (DAGA), which currently includes 1,421 genomes covering 179 species and 18 subspecies of two genera, Lactobacillus and Pediococcus , obtained from both DDBJ/ENA/GenBank and Sequence Read Archive (SRA). All the genomes deposited in DAGA were annotated consistently and assessed using DFAST. To assess the taxonomic position based on genomic sequence information, we used the average nucleotide identity (ANI), which showed high discriminative power to determine whether two given genomes belong to the same species. We corrected mislabeled or misidentified genomes in the public database and deposited the curated information in DAGA. The repository will improve the accessibility and reusability of genome resources for lactic acid bacteria. By exploiting the data deposited in DAGA, we found intraspecific subgroups in Lactobacillus gasseri and Lactobacillus jensenii , whose variation between subgroups is larger than the well-accepted ANI threshold of 95% to differentiate species. DFAST and DAGA are freely accessible at https://dfast.nig.ac.jp.

UNMANNED AIR VEHICLE STABILIZATION BASED ON NEURAL NETWORK REGULATOR

Directory of Open Access Journals (Sweden)

S. S. Andropov

2016-09-01

Full Text Available A problem of stabilizing for the multirotor unmanned aerial vehicle in an environment with external disturbances is researched. A classic proportional-integral-derivative controller is analyzed, its flaws are outlined: inability to respond to changing of external conditions and the need for manual adjustment of coefficients. The paper presents an adaptive adjustment method for coefficients of the proportional-integral-derivative controller based on neural networks. A neural network structure, its input and output data are described. Neural networks with three layers are used to create an adaptive stabilization system for the multirotor unmanned aerial vehicle. Training of the networks is done with the back propagation method. Each neural network produces regulator coefficients for each angle of stabilization as its output. A method for network training is explained. Several graphs of transition process on different stages of learning, including processes with external disturbances, are presented. It is shown that the system meets stabilization requirements with sufficient number of iterations. Described adjustment method for coefficients can be used in remote control of unmanned aerial vehicles, operating in the changing environment.

Genome-wide association study identifies 74 loci associated with educational attainment

Science.gov (United States)

Okbay, Aysu; Beauchamp, Jonathan P.; Fontana, Mark A.; Lee, James J.; Pers, Tune H.; Rietveld, Cornelius A.; Turley, Patrick; Chen, Guo-Bo; Emilsson, Valur; Meddens, S. Fleur W.; Oskarsson, Sven; Pickrell, Joseph K.; Thom, Kevin; Timshel, Pascal; de Vlaming, Ronald; Abdellaoui, Abdel; Ahluwalia, Tarunveer S.; Bacelis, Jonas; Baumbach, Clemens; Bjornsdottir, Gyda; Brandsma, Johannes H.; Concas, Maria Pina; Derringer, Jaime; Furlotte, Nicholas A.; Galesloot, Tessel E.; Girotto, Giorgia; Gupta, Richa; Hall, Leanne M.; Harris, Sarah E.; Hofer, Edith; Horikoshi, Momoko; Huffman, Jennifer E.; Kaasik, Kadri; Kalafati, Ioanna P.; Karlsson, Robert; Kong, Augustine; Lahti, Jari; van der Lee, Sven J.; de Leeuw, Christiaan; Lind, Penelope A.; Lindgren, Karl-Oskar; Liu, Tian; Mangino, Massimo; Marten, Jonathan; Mihailov, Evelin; Miller, Michael B.; van der Most, Peter J.; Oldmeadow, Christopher; Payton, Antony; Pervjakova, Natalia; Peyrot, Wouter J.; Qian, Yong; Raitakari, Olli; Rueedi, Rico; Salvi, Erika; Schmidt, Börge; Schraut, Katharina E.; Shi, Jianxin; Smith, Albert V.; Poot, Raymond A.; Pourcain, Beate; Teumer, Alexander; Thorleifsson, Gudmar; Verweij, Niek; Vuckovic, Dragana; Wellmann, Juergen; Westra, Harm-Jan; Yang, Jingyun; Zhao, Wei; Zhu, Zhihong; Alizadeh, Behrooz Z.; Amin, Najaf; Bakshi, Andrew; Baumeister, Sebastian E.; Biino, Ginevra; Bønnelykke, Klaus; Boyle, Patricia A.; Campbell, Harry; Cappuccio, Francesco P.; Davies, Gail; De Neve, Jan-Emmanuel; Deloukas, Panos; Demuth, Ilja; Ding, Jun; Eibich, Peter; Eisele, Lewin; Eklund, Niina; Evans68, David M.; Faul, Jessica D.; Feitosa, Mary F.; Forstner, Andreas J.; Gandin, Ilaria; Gunnarsson, Bjarni; Halldórsson, Bjarni V.; Harris, Tamara B.; Heath, Andrew C.; Hocking, Lynne J.; Holliday, Elizabeth G.; Homuth, Georg; Horan, Michael A.; Hottenga, Jouke-Jan; de Jager, Philip L.; Joshi, Peter K.; Jugessur, Astanand; Kaakinen, Marika A.; Kähönen, Mika; Kanoni, Stavroula; Keltigangas-Järvinen, Liisa; Kiemeney, Lambertus A.L.M.; Kolcic, Ivana; Koskinen, Seppo; Kraja, Aldi T.; Kroh, Martin; Kutalik, Zoltan; Latvala, Antti; Launer, Lenore J.; Lebreton, Maël P.; Levinson, Douglas F.; Lichtenstein, Paul; Lichtner, Peter; Liewald, David C.M.; Loukola, Anu; Madden, Pamela A.; Mägi, Reedik; Mäki-Opas, Tomi; Marioni, Riccardo E.; Marques-Vidal, Pedro; Meddens, Gerardus A.; McMahon, George; Meisinger, Christa; Meitinger, Thomas; Milaneschi, Yusplitri; Milani, Lili; Montgomery, Grant W.; Myhre, Ronny; Nelson, Christopher P.; Nyholt, Dale R.; Ollier, William E.R.; Palotie, Aarno; Paternoster, Lavinia; Pedersen, Nancy L.; Petrovic, Katja E.; Porteous, David J.; Räikkönen, Katri; Ring, Susan M.; Robino, Antonietta; Rostapshova, Olga; Rudan, Igor; Rustichini, Aldo; Salomaa, Veikko; Sanders, Alan R.; Sarin, Antti-Pekka; Schmidt, Helena; Scott, Rodney J.; Smith, Blair H.; Smith, Jennifer A.; Staessen, Jan A.; Steinhagen-Thiessen, Elisabeth; Strauch, Konstantin; Terracciano, Antonio; Tobin, Martin D.; Ulivi, Sheila; Vaccargiu, Simona; Quaye, Lydia; van Rooij, Frank J.A.; Venturini, Cristina; Vinkhuyzen, Anna A.E.; Völker, Uwe; Völzke, Henry; Vonk, Judith M.; Vozzi, Diego; Waage, Johannes; Ware, Erin B.; Willemsen, Gonneke; Attia, John R.; Bennett, David A.; Berger, Klaus; Bertram, Lars; Bisgaard, Hans; Boomsma, Dorret I.; Borecki, Ingrid B.; Bultmann, Ute; Chabris, Christopher F.; Cucca, Francesco; Cusi, Daniele; Deary, Ian J.; Dedoussis, George V.; van Duijn, Cornelia M.; Eriksson, Johan G.; Franke, Barbara; Franke, Lude; Gasparini, Paolo; Gejman, Pablo V.; Gieger, Christian; Grabe, Hans-Jörgen; Gratten, Jacob; Groenen, Patrick J.F.; Gudnason, Vilmundur; van der Harst, Pim; Hayward, Caroline; Hinds, David A.; Hoffmann, Wolfgang; Hyppönen, Elina; Iacono, William G.; Jacobsson, Bo; Järvelin, Marjo-Riitta; Jöckel, Karl-Heinz; Kaprio, Jaakko; Kardia, Sharon L.R.; Lehtimäki, Terho; Lehrer, Steven F.; Magnusson, Patrik K.E.; Martin, Nicholas G.; McGue, Matt; Metspalu, Andres; Pendleton, Neil; Penninx, Brenda W.J.H.; Perola, Markus; Pirastu, Nicola; Pirastu, Mario; Polasek, Ozren; Posthuma, Danielle; Power, Christine; Province, Michael A.; Samani, Nilesh J.; Schlessinger, David; Schmidt, Reinhold; Sørensen, Thorkild I.A.; Spector, Tim D.; Stefansson, Kari; Thorsteinsdottir, Unnur; Thurik, A. Roy; Timpson, Nicholas J.; Tiemeier, Henning; Tung, Joyce Y.; Uitterlinden, André G.; Vitart, Veronique; Vollenweider, Peter; Weir, David R.; Wilson, James F.; Wright, Alan F.; Conley, Dalton C.; Krueger, Robert F.; Smith, George Davey; Hofman, Albert; Laibson, David I.; Medland, Sarah E.; Meyer, Michelle N.; Yang, Jian; Johannesson, Magnus; Visscher, Peter M.; Esko, Tõnu; Koellinger, Philipp D.; Cesarini, David; Benjamin, Daniel J.

2016-01-01

Summary Educational attainment (EA) is strongly influenced by social and other environmental factors, but genetic factors are also estimated to account for at least 20% of the variation across individuals1. We report the results of a genome-wide association study (GWAS) for EA that extends our earlier discovery sample1,2 of 101,069 individuals to 293,723 individuals, and a replication in an independent sample of 111,349 individuals from the UK Biobank. We now identify 74 genome-wide significant loci associated with number of years of schooling completed. Single-nucleotide polymorphisms (SNPs) associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioral phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because EA is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric disease. PMID:27225129

Chromatin dynamics in genome stability

DEFF Research Database (Denmark)

Nair, Nidhi; Shoaib, Muhammad; Sørensen, Claus Storgaard

2017-01-01

Genomic DNA is compacted into chromatin through packaging with histone and non-histone proteins. Importantly, DNA accessibility is dynamically regulated to ensure genome stability. This is exemplified in the response to DNA damage where chromatin relaxation near genomic lesions serves to promote...... access of relevant enzymes to specific DNA regions for signaling and repair. Furthermore, recent data highlight genome maintenance roles of chromatin through the regulation of endogenous DNA-templated processes including transcription and replication. Here, we review research that shows the importance...... of chromatin structure regulation in maintaining genome integrity by multiple mechanisms including facilitating DNA repair and directly suppressing endogenous DNA damage....

OryzaGenome: Genome Diversity Database of Wild Oryza Species

KAUST Repository

Ohyanagi, Hajime

2015-11-18

The species in the genus Oryza, encompassing nine genome types and 23 species, are a rich genetic resource and may have applications in deeper genomic analyses aiming to understand the evolution of plant genomes. With the advancement of next-generation sequencing (NGS) technology, a flood of Oryza species reference genomes and genomic variation information has become available in recent years. This genomic information, combined with the comprehensive phenotypic information that we are accumulating in our Oryzabase, can serve as an excellent genotype-phenotype association resource for analyzing rice functional and structural evolution, and the associated diversity of the Oryza genus. Here we integrate our previous and future phenotypic/habitat information and newly determined genotype information into a united repository, named OryzaGenome, providing the variant information with hyperlinks to Oryzabase. The current version of OryzaGenome includes genotype information of 446 O. rufipogon accessions derived by imputation and of 17 accessions derived by imputation-free deep sequencing. Two variant viewers are implemented: SNP Viewer as a conventional genome browser interface and Variant Table as a textbased browser for precise inspection of each variant one by one. Portable VCF (variant call format) file or tabdelimited file download is also available. Following these SNP (single nucleotide polymorphism) data, reference pseudomolecules/ scaffolds/contigs and genome-wide variation information for almost all of the closely and distantly related wild Oryza species from the NIG Wild Rice Collection will be available in future releases. All of the resources can be accessed through http://viewer.shigen.info/oryzagenome/.

Artificial Neural Network Based State Estimators Integrated into Kalmtool

DEFF Research Database (Denmark)

Bayramoglu, Enis; Ravn, Ole; Poulsen, Niels Kjølstad

2012-01-01

In this paper we present a toolbox enabling easy evaluation and comparison of dierent ltering algorithms. The toolbox is called Kalmtool and is a set of MATLAB tools for state estimation of nonlinear systems. The toolbox now contains functions for Articial Neural Network Based State Estimation as...

The neural signature of emotional memories in serial crimes.

Science.gov (United States)

Chassy, Philippe

2017-10-01

Neural plasticity is the process whereby semantic information and emotional responses are stored in neural networks. It is hypothesized that the neural networks built over time to encode the sexual fantasies that motivate serial killers to act should display a unique, detectable activation pattern. The pathological neural watermark hypothesis posits that such networks comprise activation of brain sites that reflect four cognitive components: autobiographical memory, sexual arousal, aggression, and control over aggression. The neural sites performing these cognitive functions have been successfully identified by previous research. The key findings are reviewed to hypothesise the typical pattern of activity that serial killers should display. Through the integration of biological findings into one framework, the neural approach proposed in this paper is in stark contrast with the many theories accounting for serial killers that offer non-medical taxonomies. The pathological neural watermark hypothesis offers a new framework to understand and detect deviant individuals. The technical and legal issues are briefly discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Oscillatory neural representations in the sensory thalamus predict neuropathic pain relief by deep brain stimulation.

Science.gov (United States)

Huang, Yongzhi; Green, Alexander L; Hyam, Jonathan; Fitzgerald, James; Aziz, Tipu Z; Wang, Shouyan

2018-01-01

Understanding the function of sensory thalamic neural activity is essential for developing and improving interventions for neuropathic pain. However, there is a lack of investigation of the relationship between sensory thalamic oscillations and pain relief in patients with neuropathic pain. This study aims to identify the oscillatory neural characteristics correlated with pain relief induced by deep brain stimulation (DBS), and develop a quantitative model to predict pain relief by integrating characteristic measures of the neural oscillations. Measures of sensory thalamic local field potentials (LFPs) in thirteen patients with neuropathic pain were screened in three dimensional feature space according to the rhythm, balancing, and coupling neural behaviours, and correlated with pain relief. An integrated approach based on principal component analysis (PCA) and multiple regression analysis is proposed to integrate the multiple measures and provide a predictive model. This study reveals distinct thalamic rhythms of theta, alpha, high beta and high gamma oscillations correlating with pain relief. The balancing and coupling measures between these neural oscillations were also significantly correlated with pain relief. The study enriches the series research on the function of thalamic neural oscillations in neuropathic pain and relief, and provides a quantitative approach for predicting pain relief by DBS using thalamic neural oscillations. Copyright © 2017 Elsevier Inc. All rights reserved.

Genetic counselors' views and experiences with the clinical integration of genome sequencing.

Science.gov (United States)

Machini, Kalotina; Douglas, Jessica; Braxton, Alicia; Tsipis, Judith; Kramer, Kate

2014-08-01

In recent years, new sequencing technologies known as next generation sequencing (NGS) have provided scientists the ability to rapidly sequence all known coding as well as non-coding sequences in the human genome. As the two emerging approaches, whole exome (WES) and whole genome (WGS) sequencing, have started to be integrated in the clinical arena, we sought to survey health care professionals who are likely to be involved in the implementation process now and/or in the future (e.g., genetic counselors, geneticists and nurse practitioners). Two hundred twenty-one genetic counselors- one third of whom currently offer WES/WGS-participated in an anonymous online survey. The aims of the survey were first, to identify barriers to the implementation of WES/WGS, as perceived by survey participants; second, to provide the first systematic report of current practices regarding the integration of WES/WGS in clinic and/or research across the US and Canada and to illuminate the roles and challenges of genetic counselors participating in this process; and third to evaluate the impact of WES/WGS on patient care. Our results showed that genetic counseling practices with respect to WES/WGS are consistent with the criteria set forth in the ACMG 2012 policy statement, which highlights indications for testing, reporting, and pre/post test considerations. Our respondents described challenges related to offering WES/WGS, which included billing issues, the duration and content of the consent process, result interpretation and disclosure of incidental findings and variants of unknown significance. In addition, respondents indicated that specialty area (i.e., prenatal and cancer), lack of clinical utility of WES/WGS and concerns about interpretation of test results were factors that prevented them from offering this technology to patients. Finally, study participants identified the aspects of their professional training which have been most beneficial in aiding with the integration of

Complete Genome Sequence of Germline Chromosomally Integrated Human Herpesvirus 6A and Analyses Integration Sites Define a New Human Endogenous Virus with Potential to Reactivate as an Emerging Infection.

OpenAIRE

Tweedy, J; Spyrou, MA; Pearson, M; Lassner, D; Kuhl, U; Gompels, UA

2016-01-01

Human herpesvirus-6A and B (HHV-6A, HHV-6B) have recently defined endogenous genomes, resulting from integration into the germline: chromosomally-integrated "CiHHV-6A/B". These affect approximately 1.0% of human populations, giving potential for virus gene expression in every cell. We previously showed that CiHHV-6A was more divergent than CiHHV-6B by examining four genes in 44 European CiHHV-6A/B cardiac/haematology patients. There was evidence for gene expression/reactivation, imp...

Comparative Genome Viewer

International Nuclear Information System (INIS)

Molineris, I.; Sales, G.

2009-01-01

The amount of information about genomes, both in the form of complete sequences and annotations, has been exponentially increasing in the last few years. As a result there is the need for tools providing a graphical representation of such information that should be comprehensive and intuitive. Visual representation is especially important in the comparative genomics field since it should provide a combined view of data belonging to different genomes. We believe that existing tools are limited in this respect as they focus on a single genome at a time (conservation histograms) or compress alignment representation to a single dimension. We have therefore developed a web-based tool called Comparative Genome Viewer (Cgv): it integrates a bidimensional representation of alignments between two regions, both at small and big scales, with the richness of annotations present in other genome browsers. We give access to our system through a web-based interface that provides the user with an interactive representation that can be updated in real time using the mouse to move from region to region and to zoom in on interesting details.

Implantable neurotechnologies: bidirectional neural interfaces--applications and VLSI circuit implementations.

Science.gov (United States)

Greenwald, Elliot; Masters, Matthew R; Thakor, Nitish V

2016-01-01

A bidirectional neural interface is a device that transfers information into and out of the nervous system. This class of devices has potential to improve treatment and therapy in several patient populations. Progress in very large-scale integration has advanced the design of complex integrated circuits. System-on-chip devices are capable of recording neural electrical activity and altering natural activity with electrical stimulation. Often, these devices include wireless powering and telemetry functions. This review presents the state of the art of bidirectional circuits as applied to neuroprosthetic, neurorepair, and neurotherapeutic systems.

CpGAVAS, an integrated web server for the annotation, visualization, analysis, and GenBank submission of completely sequenced chloroplast genome sequences

Science.gov (United States)

2012-01-01

Background The complete sequences of chloroplast genomes provide wealthy information regarding the evolutionary history of species. With the advance of next-generation sequencing technology, the number of completely sequenced chloroplast genomes is expected to increase exponentially, powerful computational tools annotating the genome sequences are in urgent need. Results We have developed a web server CPGAVAS. The server accepts a complete chloroplast genome sequence as input. First, it predicts protein-coding and rRNA genes based on the identification and mapping of the most similar, full-length protein, cDNA and rRNA sequences by integrating results from Blastx, Blastn, protein2genome and est2genome programs. Second, tRNA genes and inverted repeats (IR) are identified using tRNAscan, ARAGORN and vmatch respectively. Third, it calculates the summary statistics for the annotated genome. Fourth, it generates a circular map ready for publication. Fifth, it can create a Sequin file for GenBank submission. Last, it allows the extractions of protein and mRNA sequences for given list of genes and species. The annotation results in GFF3 format can be edited using any compatible annotation editing tools. The edited annotations can then be uploaded to CPGAVAS for update and re-analyses repeatedly. Using known chloroplast genome sequences as test set, we show that CPGAVAS performs comparably to another application DOGMA, while having several superior functionalities. Conclusions CPGAVAS allows the semi-automatic and complete annotation of a chloroplast genome sequence, and the visualization, editing and analysis of the annotation results. It will become an indispensible tool for researchers studying chloroplast genomes. The software is freely accessible from http://www.herbalgenomics.org/cpgavas. PMID:23256920

CpGAVAS, an integrated web server for the annotation, visualization, analysis, and GenBank submission of completely sequenced chloroplast genome sequences

Directory of Open Access Journals (Sweden)

Liu Chang

2012-12-01

Full Text Available Abstract Background The complete sequences of chloroplast genomes provide wealthy information regarding the evolutionary history of species. With the advance of next-generation sequencing technology, the number of completely sequenced chloroplast genomes is expected to increase exponentially, powerful computational tools annotating the genome sequences are in urgent need. Results We have developed a web server CPGAVAS. The server accepts a complete chloroplast genome sequence as input. First, it predicts protein-coding and rRNA genes based on the identification and mapping of the most similar, full-length protein, cDNA and rRNA sequences by integrating results from Blastx, Blastn, protein2genome and est2genome programs. Second, tRNA genes and inverted repeats (IR are identified using tRNAscan, ARAGORN and vmatch respectively. Third, it calculates the summary statistics for the annotated genome. Fourth, it generates a circular map ready for publication. Fifth, it can create a Sequin file for GenBank submission. Last, it allows the extractions of protein and mRNA sequences for given list of genes and species. The annotation results in GFF3 format can be edited using any compatible annotation editing tools. The edited annotations can then be uploaded to CPGAVAS for update and re-analyses repeatedly. Using known chloroplast genome sequences as test set, we show that CPGAVAS performs comparably to another application DOGMA, while having several superior functionalities. Conclusions CPGAVAS allows the semi-automatic and complete annotation of a chloroplast genome sequence, and the visualization, editing and analysis of the annotation results. It will become an indispensible tool for researchers studying chloroplast genomes. The software is freely accessible from http://www.herbalgenomics.org/cpgavas.

Bioinformatics decoding the genome

CERN Multimedia

CERN. Geneva; Deutsch, Sam; Michielin, Olivier; Thomas, Arthur; Descombes, Patrick

2006-01-01

Extracting the fundamental genomic sequence from the DNA From Genome to Sequence : Biology in the early 21st century has been radically transformed by the availability of the full genome sequences of an ever increasing number of life forms, from bacteria to major crop plants and to humans. The lecture will concentrate on the computational challenges associated with the production, storage and analysis of genome sequence data, with an emphasis on mammalian genomes. The quality and usability of genome sequences is increasingly conditioned by the careful integration of strategies for data collection and computational analysis, from the construction of maps and libraries to the assembly of raw data into sequence contigs and chromosome-sized scaffolds. Once the sequence is assembled, a major challenge is the mapping of biologically relevant information onto this sequence: promoters, introns and exons of protein-encoding genes, regulatory elements, functional RNAs, pseudogenes, transposons, etc. The methodological ...

A novel neural-wavelet approach for process diagnostics and complex system modeling

Science.gov (United States)

Gao, Rong

Neural networks have been effective in several engineering applications because of their learning abilities and robustness. However certain shortcomings, such as slow convergence and local minima, are always associated with neural networks, especially neural networks applied to highly nonlinear and non-stationary problems. These problems can be effectively alleviated by integrating a new powerful tool, wavelets, into conventional neural networks. The multi-resolution analysis and feature localization capabilities of the wavelet transform offer neural networks new possibilities for learning. A neural wavelet network approach developed in this thesis enjoys fast convergence rate with little possibility to be caught at a local minimum. It combines the localization properties of wavelets with the learning abilities of neural networks. Two different testbeds are used for testing the efficiency of the new approach. The first is magnetic flowmeter-based process diagnostics: here we extend previous work, which has demonstrated that wavelet groups contain process information, to more general process diagnostics. A loop at Applied Intelligent Systems Lab (AISL) is used for collecting and analyzing data through the neural-wavelet approach. The research is important for thermal-hydraulic processes in nuclear and other engineering fields. The neural-wavelet approach developed is also tested with data from the electric power grid. More specifically, the neural-wavelet approach is used for performing short-term and mid-term prediction of power load demand. In addition, the feasibility of determining the type of load using the proposed neural wavelet approach is also examined. The notion of cross scale product has been developed as an expedient yet reliable discriminator of loads. Theoretical issues involved in the integration of wavelets and neural networks are discussed and future work outlined.

HHV-6A/B Integration and the Pathogenesis Associated with the Reactivation of Chromosomally Integrated HHV-6A/B.

Science.gov (United States)

Collin, Vanessa; Flamand, Louis

2017-06-26