Pypath & Omnipath: integrate, analyze and extract signaling networks from literature curated resources
Creators
- 1. European Molecular Biology Laboratory-European Bioinformatics Institute, Wellcome Trust Genome Campus
- 2. RWTH Aachen University, Faculty of Medicine, Joint Research Centre for Computational Biomedicine
- 3. Institut Curie, PSL Research University, Mines Paris Tech
- 4. Earlham Institute / Institute of Food Research, Norwich Research Park
- 5. European Molecular Biology Laboratory-European Bioinformatics Institute, Wellcome Trust Genome Campus / RWTH Aachen University, Faculty of Medicine, Joint Research Centre for Computational Biomedicine
Description
Literature curated information on signaling pathways is an extremely valuable resource for researchers studying different biological questions. These resources can help in the generation of hypothesis to explain experimental data and they provide support for the building of computational models. The existing curated information is currently distributed throughout a large number of online resources. Gathering and retrieving this information in a consistent manner is a non-trivial endeavour. Omnipath and Pypath greatly facilitate the integration and extraction of biological prior knowledge for analysis and model building, and they can be incorporated into wider data processing pipelines.
Files
20160919poster_ICSB_Barcelona.pdf
Files
(3.7 MB)
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