Database Commons a catalog of biological databases

Database Commons - PrePPI

PrePPI

Citations: 301

z-index 13.04

Short name PrePPI
Full name A structure-informed database of protein-protein interactions
Description PrePPI is a database of predicted and experimentally determined protein-protein interactions (PPIs) for yeast and human. The database contains ~2 million predictions including 31,402 for yeast and 317,813 for human that are considered high confidence based on our analysis.
URL https://bhapp.c2b2.columbia.edu/PrePPI/
Year founded 2012
Last update & version 2012-01-27    v1.2.0
Availability Free to all users
University/Institution hosted Columbia University
Address New York, New York 10032, USA
City New York
Province/State New York
Country/Region United States
Contact name Barry Honig
Contact email bh6@columbia.edu
Data type(s)
Major organism(s)
Keyword(s)
  • Bayesian framework
  • experimentally determined protein-protein interaction
Publication(s)
  • PrePPI: a structure-informed database of protein-protein interactions. [PMID: 23193263]

    Qiangfeng Cliff Zhang, Donald Petrey, José Ignacio Garzón, Lei Deng, Barry Honig
    Nucleic acids research 2013:41(Database issue)
    71 Citations (Google Scholar as of 2016-01-29)

    Abstract: PrePPI (http://bhapp.c2b2.columbia.edu/PrePPI) is a database that combines predicted and experimentally determined protein-protein interactions (PPIs) using a Bayesian framework. Predicted interactions are assigned probabilities of being correct, which are derived from calculated likelihood ratios (LRs) by combining structural, functional, evolutionary and expression information, with the most important contribution coming from structure. Experimentally determined interactions are compiled from a set of public databases that manually collect PPIs from the literature and are also assigned LRs. A final probability is then assigned to every interaction by combining the LRs for both predicted and experimentally determined interactions. The current version of PrePPI contains ?2 million PPIs that have a probability more than ?0.1 of which ?60 000 PPIs for yeast and ?370 000 PPIs for human are considered high confidence (probability > 0.5). The PrePPI database constitutes an integrated resource that enables users to examine aggregate information on PPIs, including both known and potentially novel interactions, and that provides structural models for many of the PPIs.

  • Structure-based prediction of protein-protein interactions on a genome-wide scale. [PMID: 23023127]

    Qiangfeng Cliff Zhang, Donald Petrey, Lei Deng, Li Qiang, Yu Shi, Chan Aye Thu, Brygida Bisikirska, Celine Lefebvre, Domenico Accili, Tony Hunter, Tom Maniatis, Andrea Califano, Barry Honig
    Nature 2012:490(7421)
    230 Citations (Google Scholar as of 2016-01-23)

    Abstract: The genome-wide identification of pairs of interacting proteins is an important step in the elucidation of cell regulatory mechanisms. Much of our present knowledge derives from high-throughput techniques such as the yeast two-hybrid assay and affinity purification, as well as from manual curation of experiments on individual systems. A variety of computational approaches based, for example, on sequence homology, gene co-expression and phylogenetic profiles, have also been developed for the genome-wide inference of protein-protein interactions (PPIs). Yet comparative studies suggest that the development of accurate and complete repertoires of PPIs is still in its early stages. Here we show that three-dimensional structural information can be used to predict PPIs with an accuracy and coverage that are superior to predictions based on non-structural evidence. Moreover, an algorithm, termed PrePPI, which combines structural information with other functional clues, is comparable in accuracy to high-throughput experiments, yielding over 30,000 high-confidence interactions for yeast and over 300,000 for human. Experimental tests of a number of predictions demonstrate the ability of the PrePPI algorithm to identify unexpected PPIs of considerable biological interest. The surprising effectiveness of three-dimensional structural information can be attributed to the use of homology models combined with the exploitation of both close and remote geometric relationships between proteins.

Community reviews

Data
quality & quantity
Content organization & presentation
System accessibility & reliability
Reviewed by

Word cloud (embeddable)

Database Commons - Word Cloud

Accessibility

Rate of accessibility:
HTTP status codeDate requested
-1 Failed2018-11-20
-1 Failed2018-11-16
-1 Failed2018-11-13
-1 Failed2018-11-09
-1 Failed2018-11-06
-1 Failed2018-11-02
-1 Failed2018-10-30
-1 Failed2018-10-26
-1 Failed2018-10-23
-1 Failed2018-10-19
-1 Failed2018-10-16
-1 Failed2018-10-12
-1 Failed2018-10-09
-1 Failed2018-10-05
-1 Failed2018-10-02
-1 Failed2018-09-28
-1 Failed2018-09-25
-1 Failed2018-09-21
-1 Failed2018-09-18
-1 Failed2018-09-14
-1 Failed2018-09-11
-1 Failed2018-09-07
-1 Failed2018-09-04
-1 Failed2018-08-31
-1 Failed2018-08-28
-1 Failed2018-08-24
-1 Failed2018-08-21
-1 Failed2018-08-17
-1 Failed2018-08-14
-1 Failed2018-08-10
-1 Failed2018-08-07
-1 Failed2018-08-03
-1 Failed2018-07-31
-1 Failed2018-07-27
-1 Failed2018-07-24
-1 Failed2018-07-20
-1 Failed2018-07-17
-1 Failed2018-07-13
-1 Failed2018-07-10
-1 Failed2018-07-06
-1 Failed2018-07-03
-1 Failed2018-06-29
-1 Failed2018-06-26
-1 Failed2018-06-22
-1 Failed2018-06-19
-1 Failed2018-06-15
-1 Failed2018-06-12
-1 Failed2018-06-08
-1 Failed2018-06-05
-1 Failed2018-06-01
-1 Failed2018-05-29
-1 Failed2018-05-25
-1 Failed2018-05-22
-1 Failed2018-05-18
-1 Failed2018-05-15
-1 Failed2018-05-11
-1 Failed2018-05-08
-1 Failed2018-05-04
-1 Failed2018-05-01
-1 Failed2018-04-27
-1 Failed2018-04-24
-1 Failed2018-04-20
-1 Failed2018-04-17
-1 Failed2018-04-13
-1 Failed2018-04-10
-1 Failed2018-04-06
-1 Failed2018-04-03
-1 Failed2018-02-27
-1 Failed2018-02-23
-1 Failed2018-02-20
-1 Failed2018-02-16
-1 Failed2018-02-13
-1 Failed2018-02-09
-1 Failed2018-02-06
-1 Failed2018-02-02
-1 Failed2018-01-30
-1 Failed2018-01-26
-1 Failed2018-01-23
-1 Failed2018-01-19
-1 Failed2018-01-16
-1 Failed2018-01-12
-1 Failed2018-01-09
-1 Failed2018-01-05
-1 Failed2018-01-02
-1 Failed2017-12-29
-1 Failed2017-12-26
-1 Failed2017-12-22
-1 Failed2017-12-19
-1 Failed2017-12-15
-1 Failed2017-12-12
-1 Failed2017-12-08
-1 Failed2017-12-05
-1 Failed2017-12-01
-1 Failed2017-11-28
-1 Failed2017-11-24
-1 Failed2017-11-21
-1 Failed2017-11-17
-1 Failed2017-11-14
-1 Failed2017-11-10
-1 Failed2017-11-07
-1 Failed2017-11-03
-1 Failed2017-10-31
-1 Failed2017-10-27
-1 Failed2017-10-24
-1 Failed2017-10-20
-1 Failed2017-10-17
-1 Failed2017-10-13
-1 Failed2017-10-10
-1 Failed2017-10-06
-1 Failed2017-10-03
-1 Failed2017-09-29
-1 Failed2017-09-26
-1 Failed2017-09-22
-1 Failed2017-09-19
-1 Failed2017-09-15
-1 Failed2017-09-12
-1 Failed2017-09-08
-1 Failed2017-09-05
-1 Failed2017-09-01
-1 Failed2017-08-29
-1 Failed2017-08-25
-1 Failed2017-08-22
-1 Failed2017-08-18
-1 Failed2017-08-15
-1 Failed2017-08-11
-1 Failed2017-08-08
-1 Failed2017-08-04
-1 Failed2017-08-01
-1 Failed2017-07-28
-1 Failed2017-07-25
-1 Failed2017-07-21
-1 Failed2017-07-18
-1 Failed2017-07-14
-1 Failed2017-07-04
-1 Failed2017-06-30
-1 Failed2017-06-27
-1 Failed2017-06-23
-1 Failed2017-06-20
-1 Failed2017-06-16
-1 Failed2017-06-13
-1 Failed2017-06-09
-1 Failed2017-06-06
-1 Failed2017-06-02
-1 Failed2017-05-30
-1 Failed2017-05-26
-1 Failed2017-05-23
-1 Failed2017-05-19
-1 Failed2017-05-16
-1 Failed2017-05-12
-1 Failed2017-05-09
-1 Failed2017-05-05
-1 Failed2017-05-02
-1 Failed2017-04-28
-1 Failed2017-04-25
-1 Failed2017-04-21
-1 Failed2017-04-18
-1 Failed2017-04-14
-1 Failed2017-04-11
-1 Failed2017-04-07
-1 Failed2017-04-04
-1 Failed2017-03-31
-1 Failed2017-03-28
-1 Failed2017-03-24
-1 Failed2017-03-21
-1 Failed2017-03-17
-1 Failed2017-03-14
-1 Failed2017-03-10
-1 Failed2017-03-07
-1 Failed2017-03-03
-1 Failed2017-02-28
-1 Failed2017-02-24
-1 Failed2017-02-21
-1 Failed2017-02-17
-1 Failed2017-02-14
-1 Failed2017-02-10
-1 Failed2017-02-07
-1 Failed2017-02-03
-1 Failed2017-01-31
-1 Failed2017-01-27
-1 Failed2017-01-24
-1 Failed2017-01-20
-1 Failed2017-01-17
-1 Failed2017-01-13
-1 Failed2017-01-10
-1 Failed2017-01-06
-1 Failed2017-01-03
-1 Failed2016-12-30
-1 Failed2016-12-27
-1 Failed2016-12-23
-1 Failed2016-12-20
-1 Failed2016-12-16
-1 Failed2016-12-13
-1 Failed2016-12-09
-1 Failed2016-12-06
-1 Failed2016-12-02
-1 Failed2016-11-29
-1 Failed2016-11-25
-1 Failed2016-11-22
-1 Failed2016-11-18
-1 Failed2016-11-15
-1 Failed2016-11-11
-1 Failed2016-11-08
-1 Failed2016-11-04
-1 Failed2016-11-01
-1 Failed2016-10-28
-1 Failed2016-10-25
-1 Failed2016-10-21
-1 Failed2016-10-18
-1 Failed2016-10-14
-1 Failed2016-10-11
-1 Failed2016-10-07
-1 Failed2016-10-04
-1 Failed2016-09-30
-1 Failed2016-09-27
-1 Failed2016-09-23
-1 Failed2016-09-20
-1 Failed2016-09-16
-1 Failed2016-09-13
-1 Failed2016-09-09
-1 Failed2016-09-06
-1 Failed2016-09-02
-1 Failed2016-08-30
-1 Failed2016-08-26
-1 Failed2016-08-23
-1 Failed2016-08-19
-1 Failed2016-08-16
-1 Failed2016-08-12
-1 Failed2016-08-09
-1 Failed2016-08-05
200 OK2016-08-02
200 OK2016-07-29
200 OK2016-07-26
200 OK2016-07-22
200 OK2016-07-19
200 OK2016-07-15
200 OK2016-07-12
200 OK2016-07-08
200 OK2016-07-05
200 OK2016-07-01
200 OK2016-06-28
200 OK2016-06-24
200 OK2016-06-21
200 OK2016-06-17
200 OK2016-06-14
200 OK2016-06-10
200 OK2016-06-07
200 OK2016-06-03
200 OK2016-05-31
200 OK2016-05-27
200 OK2016-05-24
200 OK2016-05-20
200 OK2016-05-17
200 OK2016-05-13
200 OK2016-05-10
200 OK2016-05-06
200 OK2016-05-03
200 OK2016-04-29
200 OK2016-04-26
200 OK2016-04-22
200 OK2016-04-19
200 OK2016-04-15
200 OK2016-04-12
200 OK2016-04-08
200 OK2016-04-05
200 OK2016-04-01
200 OK2016-03-29
200 OK2016-03-28
200 OK2016-03-25
200 OK2016-03-23
200 OK2016-03-21
200 OK2016-03-18
200 OK2016-03-16
200 OK2016-03-14
200 OK2016-03-11
200 OK2016-03-09
200 OK2016-03-07
200 OK2016-03-04
200 OK2016-03-02
200 OK2016-02-29
200 OK2016-02-26
200 OK2016-02-24
200 OK2016-02-22
200 OK2016-02-19
200 OK2016-02-17
200 OK2016-02-15
200 OK2016-02-14
200 OK2016-02-12
200 OK2016-02-10
200 OK2016-02-08
200 OK2016-02-07
200 OK2016-02-05
200 OK2016-02-03
200 OK2016-02-01
200 OK2016-01-31
200 OK2016-01-29
200 OK2016-01-27
200 OK2016-01-25
200 OK2016-01-24
200 OK2016-01-22
200 OK2016-01-20
200 OK2016-01-18
200 OK2016-01-17
200 OK2016-01-15
200 OK2016-01-13
200 OK2016-01-11
200 OK2016-01-10
200 OK2016-01-08
200 OK2016-01-06
200 OK2016-01-04

Tags

Interaction and Network Protein
Homo sapiens Saccharomyces cerevisiae
Bayesian framework experimentally determined protein-protein interaction

Record metadata

  • Created on: 2015-06-20
  • Curated by:
    • Shixiang Sun [2016-03-28]
    • Shixiang Sun [2015-11-21]
    • Shixiang Sun [2015-06-28]
    • Shixiang Sun [2015-06-26]
Stats