DAVID bioinformatics resources consists of an integrated biological knowledgebase and analytic tools aimed at systematically extracting biological meaning from large gene/protein lists. This protocol explains how to use DAVID, a high-throughput and integrated data-mining environment, to analyze gene lists derived from high-throughput genomic experiments. The procedure first requires uploading a gene list containing any number of common gene identifiers followed by analysis using one or more text and pathway-mining tools such as gene functional classification, functional annotation chart or clustering and functional annotation table. By following this protocol, investigators are able to gain an in-depth understanding of the biological themes in lists of genes that are enriched in genome-scale studies.

http://dmrocke.ucdavis.edu/Class/BST226.2014.Winter/Nature%20Protocols%20DAVID.pdf

Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources.

抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Functional analysis of large gene lists, derived in most cases from emerging high-throughput genomic, proteomic and bioinformatics scanning approaches, is still a challenging and daunting task. The gene-annotation enrichment analysis is a promising high-throughput strategy that increases the likelihood for investigators to identify biological processes most pertinent to their study. Approximately 68 bioinformatics enrichment tools that are currently available in the community are collected in this survey. Tools are uniquely categorized into three major classes, according to their underlying enrichment algorithms. The comprehensive collections, unique tool classifications and associated questions/issues will provide a more comprehensive and up-to-date view regarding the advantages, pitfalls and recent trends in a simpler tool-class level rather than by a tool-by-tool approach. Thus, the survey will help tool designers/developers and experienced end users understand the underlying algorithms and pertinent details of particular tool categories/tools, enabling them to make the best choices for their particular research interests.

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Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists

Complex networks are studied across many fields of science. To uncover their structural design principles, we defined “network motifs,” patterns of interconnections occurring in complex networks at numbers that are significantly higher than those in randomized networks. We found such motifs in networks from biochemistry, neurobiology, ecology, and engineering. The motifs shared by ecological food webs were distinct from the motifs shared by the genetic networks of Escherichia coli and Saccharomyces cerevisiae or from those found in the World Wide Web. Similar motifs were found in networks that perform information processing, even though they describe elements as different as biomolecules within a cell and synaptic connections between neurons in Caenorhabditis elegans. Motifs may thus define universal classes of networks. This

/pdf/network-motifs-simple-building-blocks-of-complex-networks-4arf58zy7p.pdf

Network Motifs: Simple Building Blocks of Complex Networks

A critical component in the interpretation of systems-level studies is the inference of enriched biological pathways and protein complexes contained within OMICs datasets Successful analysis requires the integration of a broad set of current biological databases and the application of a robust analytical pipeline to produce readily interpretable results Metascape is a web-based portal designed to provide a comprehensive gene list annotation and analysis resource for experimental biologists In terms of design features, Metascape combines functional enrichment, interactome analysis, gene annotation, and membership search to leverage over 40 independent knowledgebases within one integrated portal Additionally, it facilitates comparative analyses of datasets across multiple independent and orthogonal experiments Metascape provides a significantly simplified user experience through a one-click Express Analysis interface to generate interpretable outputs Taken together, Metascape is an effective and efficient tool for experimental biologists to comprehensively analyze and interpret OMICs-based studies in the big data era

/pdf/metascape-provides-a-biologist-oriented-resource-for-the-1ovoy8ih4d.pdf

Metascape provides a biologist-oriented resource for the analysis of systems-level datasets.

Motivation: To understand the behaviour of complex biological regulatory networks, a proper integration of molecular data into a full-fledge formal dynamical model is ultimately required. As most available data on regulatory interactions are qualitative, logical modelling offers an interesting framework to delineate the main dynamical properties of the underlying networks. Results: Transposing a generic model of the core network controlling the mammalian cell cycle into the logical framework, we compare different strategies to explore its dynamical properties. In particular, we assess the respective advantages and limits of synchronous versus asynchronous updating assumptions to delineate the asymptotical behaviour of regulatory networks. Furthermore, we propose several intermediate strategies to optimize the computation of asymptotical properties depending on available knowledge. Availability: The mammalian cell cycle model is available in a dedicated XML format (GINML) on our website, along with our logical simulation software GINsim ( ). Higher resolution state transitions graphs are also found on this web site (Model Repository page). Contact: thieffry@ibdm.univ-mrs.fr

Dynamical analysis of a generic Boolean model for the control of the mammalian cell cycle

This work offers a sustained exploration of modules from developmental and evolutionary perspectives. Contributors discuss what modularity is, how it can be identified and modeled, how it originated and evolved, and why it matters.

Modularity in development and evolution.

Summary Because a large number of molecular mechanisms involved in gene regulation have been described during the last decades, it is now becoming possible to address questions about the global structure of gene regulatory networks, at least in the case of some of the best-characterized organisms.This paper presents a global characterization of the transcriptional regulation in Escherichia coli on the basis of the current data. The connectivity of the corresponding network was evaluated by analyzing the distribution of the number of genes regulated by a given regulatory protein, and the distribution of the number of regulatory genes regulating a given regulated gene. The mean connectivity found (between 2 and 3) shows a rather loosely interconnected structure. Special emphasis is given to circular sequences of interactions (‘‘circuits’’) because of their critical dynamical properties. Only one-element circuits were found, in which negative autoregulation is the dominant architecture. These global properties are discussed in light of several pertinent theoretical approaches, as well as in terms of physiological and evolutionary considerations. BioEssays 20:433‐440, 1998. r 1998 John Wiley & Sons, Inc.

/pdf/from-specific-gene-regulation-to-genomic-networks-a-global-4tx4vmgdsm.pdf

From specific gene regulation to genomic networks: a global analysis of transcriptional regulation in Escherichia coli

Dynamical behaviour of biological regulatory networks--I. Biological role of feedback loops and practical use of the concept of the loop-characteristic state.

We have developed methods and tools based on the Gene Ontology (GO) resource allowing the identification of statistically over- or under-represented terms in a gene dataset; the clustering of functionally related genes within a set; and the retrieval of genes sharing annotations with a query gene. GO annotations can also be constrained to a slim hierarchy or a given level of the ontology. The source codes are available upon request, and distributed under the GPL license.

/pdf/gotoolbox-functional-analysis-of-gene-datasets-based-on-gene-1ai7ucngtj.pdf

Denis Thieffry

Papers

Dynamical analysis of a generic Boolean model for the control of the mammalian cell cycle

Modularity in development and evolution.

From specific gene regulation to genomic networks: a global analysis of transcriptional regulation in Escherichia coli

Dynamical behaviour of biological regulatory networks--I. Biological role of feedback loops and practical use of the concept of the loop-characteristic state.

GOToolBox: functional analysis of gene datasets based on Gene Ontology