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Gene Ontology: tool for the unification of biology

TLDR
The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing.
Abstract
Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.

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ClueGO: a Cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks

TL;DR: ClueGO is an easy to use Cytoscape plug-in that strongly improves biological interpretation of large lists of genes and creates a functionally organized GO/pathway term network.
Journal ArticleDOI

Enrichr: Interactive and collaborative HTML5 gene list enrichment analysis tool

TL;DR: Enrichr is an easy to use intuitive enrichment analysis web-based tool providing various types of visualization summaries of collective functions of gene lists, and can be embedded into any tool that performs gene list analysis.
Journal ArticleDOI

Long non-coding RNA HOTAIR reprograms chromatin state to promote cancer metastasis

TL;DR: It is shown that lincRNAs in the HOX loci become systematically dysregulated during breast cancer progression, indicating that l incRNAs have active roles in modulating the cancer epigenome and may be important targets for cancer diagnosis and therapy.
Journal ArticleDOI

An automated method for finding molecular complexes in large protein interaction networks.

TL;DR: A novel graph theoretic clustering algorithm, "Molecular Complex Detection" (MCODE), that detects densely connected regions in large protein-protein interaction networks that may represent molecular complexes is described.

Integrative analysis of 111 reference human epigenomes

TL;DR: In this article, the authors describe the integrative analysis of 111 reference human epigenomes generated as part of the NIH Roadmap Epigenomics Consortium, profiled for histone modification patterns, DNA accessibility, DNA methylation and RNA expression.
References
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Journal ArticleDOI

Cluster analysis and display of genome-wide expression patterns

TL;DR: A system of cluster analysis for genome-wide expression data from DNA microarray hybridization is described that uses standard statistical algorithms to arrange genes according to similarity in pattern of gene expression, finding in the budding yeast Saccharomyces cerevisiae that clustering gene expression data groups together efficiently genes of known similar function.
Journal ArticleDOI

The Pfam protein families database

TL;DR: The definition and use of family-specific, manually curated gathering thresholds are explained and some of the features of domains of unknown function (also known as DUFs) are discussed, which constitute a rapidly growing class of families within Pfam.
Journal ArticleDOI

The genome sequence of Drosophila melanogaster

Mark Raymond Adams, +194 more
- 24 Mar 2000 - 
TL;DR: The nucleotide sequence of nearly all of the approximately 120-megabase euchromatic portion of the Drosophila genome is determined using a whole-genome shotgun sequencing strategy supported by extensive clone-based sequence and a high-quality bacterial artificial chromosome physical map.
Journal ArticleDOI

Comprehensive Identification of Cell Cycle–regulated Genes of the Yeast Saccharomyces cerevisiae by Microarray Hybridization

TL;DR: A comprehensive catalog of yeast genes whose transcript levels vary periodically within the cell cycle is created, and it is found that the mRNA levels of more than half of these 800 genes respond to one or both of these cyclins.
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