PIPs 1.1 – Human Protein-Protein Interaction Predictions

PIPs 1.1

:: DESCRIPTION

PIPs is a database of predicted human protein-protein interactions. The predictions have been made using a na?ve Bayesian classifier to calculate a Score of interaction.

::DEVELOPER

The Barton Group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web Browser

 NO

:: MORE INFORMATION

Citation

PIPs: human protein–protein interaction prediction database
Mark D. McDowall, Michelle S. Scott and Geoffrey J. Barton
Nucl. Acids Res. (2009) 37 (suppl 1): D651-D656. doi: 10.1093/nar/gkn870

MEGADOCK 4.1.1 / MEGADOCK-K 3.0 / MEGADOCK-GPU 1.0 – Protein-protein Interaction Prediction System

MEGADOCK 4.1.1 / MEGADOCK-K 3.0 / MEGADOCK-GPU 1.0

:: DESCRIPTION

MEGADOCK is an fft-based protein-protein docking system for all-to-all protein-protein interaction predictions.

MEGADOCK-K is an MEGADOCK on K computer

MEGADOCK-GPU is an ultra-fast protein-protein docking software on GPUs.

::DEVELOPER

Akiyama Laboratory, Tokyo Institute of Technology

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • C++ Compiler
  • FFTW3
:: DOWNLOAD

  MEGADOCK / MEGADOCK-K/ MEGADOCK-GPU

:: MORE INFORMATION

Citation

MEGADOCK 4.0: an ultra-high-performance protein-protein docking software for heterogeneous supercomputers.
Ohue M, Shimoda T, Suzuki S, Matsuzaki Y, Ishida T, Akiyama Y.
Bioinformatics. 2014 Aug 6. pii: btu532.

MEGADOCK 3.0: a high-performance protein-protein interaction prediction software using hybrid parallel computing for petascale supercomputing environments.
Matsuzaki Y, Uchikoga N, Ohue M, Shimoda T, Sato T, Ishida T, Akiyama Y.
Source Code Biol Med. 2013 Sep 3;8(1):18

MEGADOCK: An All-to-all Protein-protein Interaction Prediction System Using Tertiary Structure Data.
Ohue M, Matsuzaki Y, Uchikoga N, Ishida T, Akiyama Y.
Protein Pept Lett. 2013 Jul 9

Takehiro Shimoda, Takashi Ishida, Shuji Suzuki, Masahito Ohue, Yutaka Akiyama.
MEGADOCK-GPU: An accelerated protein-protein docking calculation on GPUs,
Parallel and Cloud-based Bioinformatics and Biomedicine, 2013. (accepted)

Struct2Net – Structure-based Computational Predictions of Protein-protein interactions

Struct2Net

:: DESCRIPTION

The Struct2Net program predicts protein-protein interactions (PPI) by integrating structure-based information with other functional annotations, e.g. GO, co-expression and co-localization etc. The structure-based protein interaction prediction is conducted using a protein threading server RAPTOR plus logistic regression.

::DEVELOPER

Berger Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • WebServer

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation:

Struct2Net: a web service to predict protein-protein interactions using a structure-based approach.
Singh R, Park D, Xu J, Hosur R, Berger B.
Nucleic Acids Res. 2010 Jul;38(Web Server issue):W508-15. doi: 10.1093/nar/gkq481

LocFuse – Human protein-protein Interaction Prediction

LocFuse

:: DESCRIPTION

LocFuse is a novel ensemble learning method of human protein-protein interaction prediction via classifier fusion using protein localization information.

::DEVELOPER

Laboratory of Systems Biology & Bioinformatics (LBB)

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux
  • JRE

:: DOWNLOAD

 LocFuse

:: MORE INFORMATION

Citation

LocFuse: human protein-protein interaction prediction via classifier fusion using protein localization information.
Zahiri J, Mohammad-Noori M, Ebrahimpour R, Saadat S, Bozorgmehr JH, Goldberg T, Masoudi-Nejad A.
Genomics. 2014 Dec;104(6 Pt B):496-503. doi: 10.1016/j.ygeno.2014.10.006.

MetaPred2CS 1.1 – Meta-predictor for Protein-protein Interactions of Prokaryotic Two-component System Proteins

MetaPred2CS 1.1

:: DESCRIPTION

MetaPred2CS Web server is a meta-predictor based on Support Vector Machine (SVM) that combines 6 individual sequence based protein-protein interaction prediction methods to predict prokaryotic two-component system protein-protein interactions (PPIs).

::DEVELOPER

Bioinformatics @ IBERS

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

 MetaPred2CS

:: MORE INFORMATION

Citation

Bioinformatics. 2016 Jul 4. pii: btw403.
MetaPred2CS: a sequence-based meta-predictor for protein-protein interactions of prokaryotic two-component system proteins.
Kara A, Vickers M, Swain M, Whitworth DE, Fernandez-Fuentes N.

PRISM 2.0 – Prediction of Protein-protein Interactions and Modeling their 3D Complexes

PRISM 2.0

:: DESCRIPTION

The PRISM web server enables fast and accurate prediction of protein-protein interactions (PPIs).

::DEVELOPER

the COSBI (Computational Systems Biology) group

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux
  • Python

:: DOWNLOAD

PRISM PROTOCOL

:: MORE INFORMATION

Citation

Baspinar A, Cukuroglu E, Nussinov R, Keskin O, Gursoy A.
PRISM: A web server and repository for prediction of protein-protein interactions and modeling their 3D complexes.
Nucl. Acids Res. (2014) doi: 10.1093/nar/gku397

DeNovo – Virus-Host Sequence-Based Protein-Protein Interaction Prediction

DeNovo

:: DESCRIPTION

DeNovo is a sequence-based negative sampling and machine learning framework that learns from PPIs of different viruses to predict for a novel one, exploiting the shared host proteins.

::DEVELOPER

Fatma Elzahraa S. Eid

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows
  • MatLab

:: DOWNLOAD

 DeNovo

:: MORE INFORMATION

Citation

DeNovo: Virus-Host Sequence-Based Protein-Protein Interaction Prediction.
Eid FE, ElHefnawi M, Heath LS.
Bioinformatics. 2015 Dec 16. pii: btv737.

DynaFace – Discrimination between Obligatory and Non-obligatory Protein-Protein Interactions

DynaFace

:: DESCRIPTION

DynaFace predicts obligatory and non-obligatory interactions among a set of 300 putative protein complexes.

::DEVELOPER

Polymer Research Center

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Web browser
:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation:

DynaFace: Discrimination between Obligatory and Non-obligatory Protein-Protein Interactions Based on the Complex’s Dynamics.
Soner S, Ozbek P, Garzon JI, Ben-Tal N, Haliloglu T.
PLoS Comput Biol. 2015 Oct 27;11(10):e1004461. doi: 10.1371/journal.pcbi.1004461.

ppiPre 1.9 – Predict Protein-Protein Interactions Based on Functional and Topological Similarities

ppiPre 1.9

:: DESCRIPTION

ppiPre is an open-source framework for PPI analysis and prediction using a combination of heterogeneous features including three GO-based semantic similarities, one KEGG-based co-pathway similarity and three topology-based similarities.

::DEVELOPER

Yue Deng <anfdeng at 163.com>, Rongjie Shao, Gang Wang and Yuanjun Sun

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/MacOsX / Windows
  • R
  • BioConductor

:: DOWNLOAD

 ppiPre

:: MORE INFORMATION

Citation

BMC Syst Biol. 2013;7 Suppl 2:S8. doi: 10.1186/1752-0509-7-S2-S8. Epub 2013 Oct 14.
ppiPre: predicting protein-protein interactions by combining heterogeneous features.
Deng Y, Gao L, Wang B.

Profppikernel 1.0.4 – Protein-protein Interaction Prediction

Profppikernel 1.0.4

:: DESCRIPTION

Profppikernel uses an accelerated version of the original profile kernel to train SVM based protein-protein interaction (PPI) prediction models and to predict new PPIs from sequence alone.

::DEVELOPER

Rost Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

 Profppikernel

:: MORE INFORMATION

Citation

Evolutionary profiles improve protein-protein interaction prediction from sequence.
Hamp T, Rost B.
Bioinformatics. 2015 Feb 4. pii: btv077.