Pathway Commons Search and visualize public biological pathway information. Single point of access.



Pathway Commons is a network biology resource and acts as a convenient point of access to biological pathway information collected from public pathway databases, which you can search, visualize and download. All data is freely available, under the license terms of each contributing database.

For biologists

Search, visualize and download Pathway Commons pathways as part of an integrated network analysis (more)

PCViz Logo

Simple

See genes in pathway context

PCViz
ChiBE

Advanced

See detailed processes

ChiBE
CyPath2 Logo

Analyze

Search and analyze pathway relationships

CyPath2

For computational biologists and software developers

Download all pathways in BioPAX, SIF and other formats for pathway and network analysis. Build software on top of Pathway Commons using our web service API (more)

Pathway Commons 2 Logo

PC2: Web service

BioPAX Level 3. Advanced graph queries. Normalized and up-to-date data. Programmatic access. Batch downloads.

Pathway Commons 2
Pathway Commons 2 Logo

BioPAX & Paxtools

Standard language for Biological Pathway Exchange and a software library for handling data in BioPAX.

BioPAX & Paxtools
Pathway Commons Logo

PC: Previous web service

Obsolete, last updated 2011

Pathway Commons

Frequently Asked Questions (F.A.Q.)


What is Pathway Commons?

Pathway Commons is a collection of publicly available pathway information from multiple organisms. It provides researchers with convenient access to a comprehensive collection of biological pathways from multiple sources represented in a common language for gene and metabolic pathway analysis. Access is via a web portal for query and download. Database providers can share their pathway data via a common repository and avoid duplication of effort and reduce software development costs. Bioinformatics software developers can increase efficiency by sharing pathway analysis software components. Pathways can include biochemical reactions, complex assembly, transport and catalysis events, physical interactions involving proteins, DNA, RNA, small molecules and complexes, gene regulation events and genetic interactions involving genes.

Is Pathway Commons free?

Yes, the Pathway Commons data and interactions are available for free! Pathway Commons distributes pathway information with the intellectual property restrictions of the source database. However, only databases that are freely available or free to academics are included. Additionally, this site suggests several free pathway analysis software to conduct gene pathway analysis.

Does Pathway Commons compete with other pathway databases?

No. Pathway Commons does not compete with or duplicate efforts of pathway databases or software tool providers. Pathway Commons will add value to these existing efforts by providing a shared resource for publishing, distributing, querying, and analyzing pathway information. Existing database groups will provide pathway curation, Pathway Commons will provide a mechanism and the technology for sharing. A key aspect of Pathway Commons is clear author attribution. Curation teams at existing databases must be supported by researchers to ensure they can keep performing their valuable work.

What are the future plans for Pathway Commons?

The Pathway Commons work group will continue to provide software systems to collect, store and integrate pathway data from database groups, with clear author attribution; store, validate, index and maintain the information to enable efficient, quality access; distribute pathway information to the scientific public; and, provide a basic set of end user software for querying and analysis of metabolic and gene pathways. We will be adding more databases over time.

What is BioPAX?

BioPAX, or Biological Pathway Exchange, is a standard exchange format for biological pathways. Pathway databases that make their data available in this format can be imported into Pathway Commons. BioPAX is developed through a collaborative effort by many pathway databases. More information is available at http://biopax.org.

What will Pathway Commons not do?

Pathway Commons will avoid duplication of advanced features of source databases. Users are encouraged to explore these features by following hyperlinks from Pathway Commons.

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F.A.Q. for Biologists


What can I do with this information?

You can freely query available pathway information and answer questions such as:

  • What proteins interact with my favorite protein?
  • What cell signaling or metabolic pathways involve my favorite protein?
  • Is my favorite protein involved in transport events or biochemical reactions?
  • What enzymes use my metabolite of interest as a substrate?

What kind of information is part of each cell signaling and metabolic pathway?

Pathways from different databases are defined by different levels of detail. Details that may be included are proteins, small molecules, DNA, RNA, complexes and their cellular locations, different types of physical interactions, such as molecular interaction, biochemical reaction, catalysis, complex assembly and transport, gene regulation, genetic interactions, post-translational protein modifications, original citations, experimental evidence and links to other databases e.g. of protein sequence annotation. Some information is only available in the downloaded BioPAX files.

How were the pathways collected?

Pathways were downloaded directly from source databases. Each source pathway database has been created differently, some by manual extraction of pathway information from the literature and some by computational prediction.

How good is the quality of Pathway Commons?

The quality of Pathway Commons pathways is dependent on the quality of the pathways from source databases. Pathway Commons allows users to filter data by various criteria, including data source, which should allow viewing a restricted subset of high quality data. In the future, Pathway Commons will implement published algorithms to automatically assess data quality and allow this as an additional filter.

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F.A.Q. for Computational Biologists


What can I do with this information?

You can download and incorporate this biological pathway data as part of metabolic and gene pathway analysis software in BioPAX Level 3 format. Details about the BioPAX format

How many pathways are part of Pathway Commons?

Please see the statistics page for up to the minute information.

What is cPath2?

cPath2 is an open-source data management software that runs the Pathway Commons web service. You can download it for your own use the developer site.

Can I access Pathway Commons data via a web service?

Yes! A web service is available to answer specific queries with computer readable responses for intergration with other network analysis components. This is designed to enable third party software and scripts to easily access the information.

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Publications


Cerami et al. Pathway Commons, a web resource for biological pathway data (Nucleic Acid Research, 2011)

Pathway Commons citations


Authors Title Journal Year
Babur O., et al. Pattern search in biopax models Bioinformatics 2014
Mitra S., et al. Systems biology of cancer biomarker detection Cancer Biomarkers 2013
Wodak S.J., et al. Protein-protein interaction networks: The puzzling riches Current Opinion in Structural Biology 2013
Araujo G.S., et al. Random forest and gene networks for association of SNPs to Alzheimer's disease Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2013
Hofree M., et al. Network-based stratification of tumor mutations Nature Methods 2013
Snijder B., et al. Predicting functional gene interactions with the hierarchical interaction score Nature Methods 2013
Li J., et al. Pathway-based drug repositioning using causal inference BMC Bioinformatics 2013
Wang Z., et al. Incorporating prior knowledge into Gene Network Study Bioinformatics 2013
Tamborero D., et al. Comprehensive identification of mutational cancer driver genes across 12 tumor types Scientific Reports 2013
Klapa M.I., et al. Reconstruction of the experimentally supported human protein interactome: What can we learn? BMC Systems Biology 2013
Tieri P., et al. Signalling pathway database usability: Lessons learned Molecular BioSystems 2013
Carbonetto P., et al. Integrated Enrichment Analysis of Variants and Pathways in Genome-Wide Association Studies Indicates Central Role for IL-2 Signaling Genes in Type 1 Diabetes, and Cytokine Signaling Genes in Crohn's Disease PLoS Genetics 2013
Croze E., et al. Interferon-beta-1b-induced short-and long-term signatures of treatment activity in multiple sclerosis Pharmacogenomics Journal 2013
Miller M.L., et al. Drug synergy screen and network modeling in dedifferentiated liposarcoma identifies CDK4 and IGF1R as synergistic drug targets Science Signaling 2013
Grandori C. A high-throughput siRNA screening platform to identify MYC-synthetic lethal genes as candidate therapeutic targets Methods in Molecular Biology 2013
Cun Y., et al. Network and Data Integration for Biomarker Signature Discovery via Network Smoothed T-Statistics PLoS ONE 2013
Melas I.N., et al. Detecting and Removing Inconsistencies between Experimental Data and Signaling Network Topologies Using Integer Linear Programming on Interaction Graphs PLoS Computational Biology 2013
Demir E., et al. Using Biological Pathway Data with Paxtools PLoS Computational Biology 2013
Kortenhorst M.S.Q., et al. Analysis of the genomic response of human prostate cancer cells to histone deacetylase inhibitors Epigenetics 2013
Aksoy B.A., et al. PiHelper: An open source framework for drug-target and antibody-target data Bioinformatics 2013
Sambarey A., et al. Mining large-scale response networks reveals 'topmost activities' in Mycobacterium tuberculosis infection Scientific Reports 2013
Garcia Godoy M.J., et al. Sharing and executing linked data queries in a collaborative environment Bioinformatics 2013
Ho A.S., et al. The mutational landscape of adenoid cystic carcinoma Nature Genetics 2013
Rajagopalan P., et al. Systems biology characterization of engineered tissues Annual Review of Biomedical Engineering 2013
Stobbe M.D., et al. Consensus and conflict cards for metabolic pathway databases BMC Systems Biology 2013
Praveen P., et al. Boosting Probabilistic Graphical Model Inference by Incorporating Prior Knowledge from Multiple Sources PLoS ONE 2013
Goudarzi A., et al. Protein kinase c epsilon and genetic networks in osteosarcoma metastasis Cancers 2013
Sun J., et al. IBIG: An Integrative Network Tool for Supporting Human Disease Mechanism Studies Genomics, Proteomics and Bioinformatics 2013
Pagliarini R., et al. A genome-scale modeling approach to study inborn errors of liver metabolism: Toward an in silico patient Journal of Computational Biology 2013
Sorokina S.Y., et al. Databases as instruments for analysis of large-scale data sets of interactions between molecular biological objects Biology Bulletin 2013
Sadeghi A., et al. Steiner tree methods for optimal sub-network identification: An empirical study BMC Bioinformatics 2013
Dolinski K., et al. Systematic curation of protein and genetic interaction data for computable biology BMC Biology 2013
Fanayan S., et al. Proteogenomic analysis of human colon carcinoma cell lines LIM1215, LIM1899, and LIM2405 Journal of Proteome Research 2013
Gao J., et al. Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal Science Signaling 2013
Gu Y., et al. Network analysis of genomic alteration profiles reveals co-altered functional modules and driver genes for glioblastoma Molecular BioSystems 2013
Mukherjee S., et al. Current trends in modeling host-pathogen interactions Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 2013
Liu Z., et al. In silico drug repositioning-what we need to know Drug Discovery Today 2013
Mayer M.L., et al. Rescue of dysfunctional autophagy attenuates hyperinflammatory responses from cystic fibrosis cells Journal of Immunology 2013
Kamburov A., et al. The ConsensusPathDB interaction database: 2013 Update Nucleic Acids Research 2013
Zhao M., et al. TSGene: A web resource for tumor suppressor genes Nucleic Acids Research 2013
Chatr-Aryamontri A., et al. The BioGRID interaction database: 2013 Update Nucleic Acids Research 2013
Cheng L., et al. Global gene expression and functional network analysis of gastric cancer identify extended pathway maps and GPRC5A as a potential biomarker Cancer Letters 2012
Johnson S., et al. StRAP: An Integrated Resource for Profiling High-Throughput Cancer Genomic Data from Stress Response Studies PLoS ONE 2012
Droniou-Bonzom M.E., et al. A systems biology starter kit for arenaviruses Viruses 2012
Mitsos A., et al. Non Linear Programming (NLP) Formulation for Quantitative Modeling of Protein Signal Transduction Pathways PLoS ONE 2012
West J., et al. Differential network entropy reveals cancer system hallmarks Scientific Reports 2012
Blinov M.L., et al. Logic modeling and the ridiculome under the rug BMC Biology 2012
Feiglin A., et al. Static network structure can be used to model the phenotypic effects of perturbations in regulatory networks Bioinformatics 2012
Saito R., et al. A travel guide to Cytoscape plugins Nature Methods 2012
Videla S., et al. Revisiting the training of logic models of protein signaling networks with ASP Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2012
Terfve C., et al. CellNOptR: A flexible toolkit to train protein signaling networks to data using multiple logic formalisms BMC Systems Biology 2012
Eo H.-S., et al. A pathway-based classification of breast cancer integrating data on differentially expressed genes, copy number variations and microrna target genes Molecules and Cells 2012
Forst C.V. Influenza infection and therapy: A systems approach Future Virology 2012
Tsuji S., et al. A simple knowledge-based mining method for exploring hidden key molecules in a human biomolecular network BMC Systems Biology 2012
Wyner A., et al. Argumentation to represent and reason over biological systems Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2012
Guziolowski C., et al. Automatic generation of causal networks linking growth factor stimuli to functional cell state changes FEBS Journal 2012
Eduati F., et al. Integrating literature-constrained and data-driven inference of signalling networks Bioinformatics 2012
Engin H.B., et al. A strategy based on protein-protein interface motifs may help in identifying drug off-targets Journal of Chemical Information and Modeling 2012
Davis M.P.A., et al. Large-scale identification of microRNA targets in murine Dgcr8-deficient embryonic stem cell lines PLoS ONE 2012
Helikar T., et al. The Cell Collective: Toward an open and collaborative approach to systems biology BMC Systems Biology 2012
Tang H., et al. A quick guide to biomolecular network studies: Construction, analysis, applications, and resources Biochemical and Biophysical Research Communications 2012
Kavlock R., et al. Update on EPA's ToxCast program: Providing high throughput decision support tools for chemical risk management Chemical Research in Toxicology 2012
Al-Lazikani B., et al. Combinatorial drug therapy for cancer in the post-genomic era Nature Biotechnology 2012
Carkacioglu L., et al. iSNP: An integrated, automatically updated SNP database 2012 7th International Symposium on Health Informatics and Bioinformatics, HIBIT 2012 2012
Komurov K., et al. NetWalker: A contextual network analysis tool for functional genomics BMC Genomics 2012
Papp D., et al. The NRF2-related interactome and regulome contain multifunctional proteins and fine-tuned autoregulatory loops FEBS Letters 2012
Mori T., et al. NIRF/UHRF2 occupies a central position in the cell cycle network and allows coupling with the epigenetic landscape FEBS Letters 2012
Weile J., et al. Bayesian integration of networks without gold standards Bioinformatics 2012
Julfayev E.S., et al. KB-Rank: Efficient protein structure and functional annotation identification via text query Journal of Structural and Functional Genomics 2012
Kirik U., et al. Multimodel pathway enrichment methods for functional evaluation of expression regulation Journal of Proteome Research 2012
Cerami E., et al. The cBio Cancer Genomics Portal: An open platform for exploring multidimensional cancer genomics data Cancer Discovery 2012
Kirouac D.C., et al. Creating and analyzing pathway and protein interaction compendia for modelling signal transduction networks BMC Systems Biology 2012
Cun Y., et al. Prognostic gene signatures for patient stratification in breast cancer - accuracy, stability and interpretability of gene selection approaches using prior knowledge on protein-protein interactions BMC Bioinformatics 2012
Garcia-Godoy M.J., et al. Bioqueries: A social community sharing experiences while querying Biological Linked Data ACM International Conference Proceeding Series 2012
Kholodenko B., et al. Computational approaches for analyzing information flow in biological networks Science Signaling 2012
Ronnberg T., et al. Searching for cellular partners of hantaviral nonstructural protein NSs: Y2H screening of mouse cDNA library and analysis of cellular interactome PLoS ONE 2012
Garay J.P., et al. Omics and therapy - A basis for precision medicine Molecular Oncology 2012
Bebek G. Identifying gene interaction networks Methods in Molecular Biology 2012
Kozhenkov S., et al. Mining and integration of pathway diagrams from imaging data Bioinformatics 2012
Komurov K. Modeling community-wide molecular networks of multicellular systems Bioinformatics 2012
Goh W.W.B., et al. How advancement in biological network analysis methods empowers proteomics Proteomics 2012
Ciriello G., et al. Mutual exclusivity analysis identifies oncogenic network modules Genome Research 2012
Sales G., et al. Graphite - a Bioconductor package to convert pathway topology to gene network BMC Bioinformatics 2012
Alexeyenko A., et al. Comparative interactomics with Funcoup 2.0 Nucleic Acids Research 2012
Kuchta K., et al. DNAtraffic - A new database for systems biology of DNA dynamics during the cell life Nucleic Acids Research 2012
Kelder T., et al. WikiPathways: Building research communities on biological pathways Nucleic Acids Research 2012
Haibe-Kains B., et al. Predictive networks: A flexible, open source, web application for integration and analysis of human gene networks Nucleic Acids Research 2012
Cheng Y.-K., et al. A mathematical methodology for determining the temporal order of pathway alterations arising during gliomagenesis PLoS Computational Biology 2012
Yu N., et al. hiPathDB: A human-integrated pathway database with facile visualization Nucleic Acids Research 2012
Sreenivasaiah P.K., et al. IPAVS: Integrated pathway resources, analysis and visualization system Nucleic Acids Research 2012
Mohammad F., et al. A heuristic algorithm for detecting intercellular interactions Proceedings - 2011 11th IEEE International Conference on Bioinformatics and Bioengineering, BIBE 2011 2011
le Novere N., et al. Meeting report from the first meetings of the Computational Modeling in Biology Network (COMBINE) Standards in Genomic Sciences 2011
Doderer M.S., et al. Multisource biological pathway consolidation Proceedings - IEEE International Workshop on Genomic Signal Processing and Statistics 2011
Brockschmidt F.F., et al. Susceptibility variants on chromosome 7p21.1 suggest HDAC9 as a new candidate gene for male-pattern baldness British Journal of Dermatology 2011
Hsu C.-L., et al. Prioritizing disease candidate genes by a gene interconnectedness-based approach 10th Int. Conference on Bioinformatics - 1st ISCB Asia Joint Conference 2011, InCoB 2011/ISCB-Asia 2011: Computational Biology - Proceedings from Asia Pacific Bioinformatics Network (APBioNet) 2011
Ghosh S., et al. Software for systems biology: From tools to integrated platforms Nature Reviews Genetics 2011
Goldenberg A., et al. Unsupervised detection of genes of influence in lung cancer using biological networks Bioinformatics 2011
Frohlich H. Network based consensus gene signatures for biomarker discovery in breast cancer PLoS ONE 2011
Martha V.-S., et al. Constructing a robust protein-protein interaction network by integrating multiple public databases BMC Bioinformatics 2011
Yaspan B.L., et al. Strategies for pathway analysis from UNIT 1.20 GWAS Data Current Protocols in Human Genetics 2011
Fortney K., et al. Integrative computational biology for cancer research Human Genetics 2011
Mori T., et al. NIRF constitutes a nodal point in the cell cycle network and is a candidate tumor suppressor Cell Cycle 2011
Symons S., et al. MGV: A generic graph viewer for comparative omics data Bioinformatics 2011
Nishiyama T., et al. A scan statistic to extract causal gene clusters from case-control genome-wide rare CNV data BMC Bioinformatics 2011
Julfayev E.S., et al. A new approach to assess and predict the functional roles of proteins across all known structures Journal of Structural and Functional Genomics 2011
Saltzman A.L., et al. Regulation of alternative splicing by the core spliceosomal machinery Genes and Development 2011

Contact


Pathway Commons is built and maintained by Memorial Sloan-Kettering Cancer Center and the University of Toronto.

Please send us questions and feedback.

About cBio @ MSKCC

The Computational Biology Center at Memorial Sloan-Kettering Cancer Center pursues computational biology research projects and the development of bioinformatics resources available for free in the areas of: sequence-structure analysis; network biology; gene pathway analysis; metabolic pathway analysis; gene regulation; molecular pathways and networks; diagnostic and prognostic indicators.

The mission of cBio is to move the theoretical methods and genome-scale data resources of computational biology into everyday laboratory practice and use, and is reflected in the organization of cBio into research and service components -- the intention being that new computational methods created through the process of scientific inquiry should be generalized and supported as free/open-source and shared community resources.

About the University of Toronto

The University of Toronto is Canada's largest university, with a strong focus on research. Pathway Commons work is performed in the Bader Lab.

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