P2CS is an integrated and comprehensive database of two-component system (TCS) signal transduction proteins, which contains a compilation of the TCS genes within completely sequenced genomes and metagenomes. It provides detailed annotation of each TCS gene including sequence features, functional domains, as well as chromosomal localization. Data can be downloaded for analysis and users can validate and add annotation to predicted TCS genes.
The database can be browsed and searched with a user-friendly web interface.
Quick access :
All TCS present in the database can be retrieved with:
- P2CS Search - Specific genome, gene or domain architecture search
- P2CS Search - Blast search against all the P2CS database
- P2CS Browse - Complete TCS annotation of each genome
- P2CS Browse - Complete TCS annotation of each metagenome
- P2CS Download - TCS data available for download in a variety of formats
A complete documentation and a How-To section are accessible via the
Documentation menu
See the P2CS publications for further details.
P2CS: a two-component system resource for prokaryotic signal transduction researchBMC Genomics 2009, 10:315.
Abstract [ BMC ] [ PubMed ] Full text [ PDF ] [ HTML ]
P2CS: a database of prokaryotic two-component systemsNucleic Acids Research 2011, 39(suppl 1): D771-D776.
Abstract [ NAR ] [ PubMed ] Full text [ PDF ] [ HTML ]
P2CS: updates of the prokaryotic two-component systems databaseNucleic Acids Research 2015, 43(D1): D536-D541.
Abstract [ NAR ] [ PubMed ] Full text [ PDF ] [ HTML ]
See the P2CS companions.
P2TF (Predicted Prokaryotic Transcription Factors) is available at www.p2tf.org. P2TF, a database of Transcription Factor (TF) proteins, contains the TFs of all available bacterial and archaeal genomes, and 43 microbial metagenomes.
P2RP (Predicted Prokaryotic Regulatory Proteins) is a freely accessible web server for regulatory proteins (RPs) prediction www.p2rp.org. The program can perform several types of analyses depending on the type of request, and provide detailed annotation of each RP gene including classification, sequence features, as well as functional domains.
Related databases and prediction tools :