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Open AccessJournal ArticleDOI

Pathway Commons, a web resource for biological pathway data

TLDR
A web-based interface that enables biologists to browse and search a comprehensive collection of pathways from multiple sources represented in a common language, a download site that provides integrated bulk sets of pathway information in standard or convenient formats and a web service that software developers can use to conveniently query and access all data.
Abstract
Pathway Commons (http://www.pathwaycommons.org) is a collection of publicly available pathway data from multiple organisms. Pathway Commons provides a web-based interface that enables biologists to browse and search a comprehensive collection of pathways from multiple sources represented in a common language, a download site that provides integrated bulk sets of pathway information in standard or convenient formats and a web service that software developers can use to conveniently query and access all data. Database providers can share their pathway data via a common repository. Pathways include biochemical reactions, complex assembly, transport and catalysis events and physical interactions involving proteins, DNA, RNA, small molecules and complexes. Pathway Commons aims to collect and integrate all public pathway data available in standard formats. Pathway Commons currently contains data from nine databases with over 1400 pathways and 687,000 interactions and will be continually expanded and updated.

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The cBio Cancer Genomics Portal: An Open Platform for Exploring Multidimensional Cancer Genomics Data

TL;DR: The cBio Cancer Genomics Portal significantly lowers the barriers between complex genomic data and cancer researchers who want rapid, intuitive, and high-quality access to molecular profiles and clinical attributes from large-scale cancer genomics projects and empowers researchers to translate these rich data sets into biologic insights and clinical applications.
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Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal

TL;DR: A practical guide to the analysis and visualization features of the cBioPortal for Cancer Genomics, which makes complex cancer genomics profiles accessible to researchers and clinicians without requiring bioinformatics expertise, thus facilitating biological discoveries.
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Large-scale gene function analysis with the PANTHER classification system

TL;DR: This protocol provides a detailed description of how to analyze genome-wide experimental data with the PANTHER classification system, and redesigned the website interface to improve both user experience and the system's analytical capability.
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Oncogenic Signaling Pathways in The Cancer Genome Atlas

TL;DR: This work charted the detailed landscape of pathway alterations in 33 cancer types, stratified into 64 subtypes, and identified patterns of co-occurrence and mutual exclusivity.
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WEB-based GEne SeT AnaLysis Toolkit (WebGestalt): update 2013

TL;DR: By integrating functional categories derived from centrally and publicly curated databases as well as computational analyses, WebGestalt has significantly increased the coverage of functional categories in various biological contexts, leading to a total of 78 612 functional categories.
References
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Journal ArticleDOI

Gene Ontology: tool for the unification of biology

TL;DR: 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.
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Cytoscape: A Software Environment for Integrated Models of Biomolecular Interaction Networks

TL;DR: Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
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Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists

TL;DR: 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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Database resources of the National Center for Biotechnology Information

TL;DR: In addition to maintaining the GenBank(R) nucleic acid sequence database, the National Center for Biotechnology Information (NCBI) provides data analysis and retrieval resources for the data in GenBank and other biological data made available through NCBI’s website.
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