Colorectal Cancer Atlas

NAR Molecular Biology Database Collection entry number 1886
Mathivanan, Suresh; Chisanga, David; Keerthikumar, Shivakumar; Pathan, Mohashin; Ariyaratne, Dinuka; Kalra, Hina; Boukouris, Stephanie; Mathew, Nidhi; Ang, Ching-Seng; Sieber, Oliver; Mariadason, John; Dasgupta, Ramanuj,; Chilamkurti, Naveen
1Department of Computer Science and Information Technology, La Trobe University, Bundoora, Victoria, 3086, Australia
2Department of Biochemistry and Genetics, La Trobe Institute for Molecular Science, La Trobe University, Melbourne, Victoria, 3086, Australia
3The Bio21 Molecular Science and Biotechnology Institute, University of Melbourne, Parkville, Victoria 3010, Australia
4Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria 3052, Australia
5Faculty of Medicine, Dentistry and Health Sciences, Department of Medical Biology, University of Melbourne, Parkville, Victoria 3052, Australia
6Olivia Newton John Cancer Research Institute, Melbourne, Australia, Ludwig Institute for Cancer Research, Melbourne-Austin Branch, Australia, School of Cancer Medicine, La Trobe University, Melbourne, Australia
7Genome Institute of Singapore, A*STAR, 60 Biopolis Street, Singapore 138672

Database Description

Colorectral Cancer Atlas is an web-based resource which integrates genomic and proteomic pertaining to colorectal cancer cell lines and tissues.
Data catalogued includes, quantitative and non-quantitative protein expression, sequence variations, cellular signaling pathways, protein-protein interactions, Gene Ontology terms, protein domains and post-translational modifications (PTMs). Currently, Colorectal Cancer Atlas contains data for >13,711 primary CRC tissues, >165 CRC cell lines, 53,341 protein identifications, >8.3 million MS/MS spectra, >18,410 genes with sequence variations, 404,278 sequence variation entries, 351 pathways with sequence variants, 88,819 PTMs and 253,700 protein-protein interactions.
Data curated in Colorectal Cancer Atlas is available as tab-delimited files and is free for download to all users. Using the custom database option, the tab delimited data can also be uploaded into FunRich, a functional enrichment analysis tool to identify classes of genes/proteins that are overrepresented in a specific category. Users can send their comments and suggestion directly at

Subcategory: Cancer gene databases

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