DPPI – Convolutional Neural network to predict PPI Interactions

DPPI

:: DESCRIPTION

DPPI uses a convolutional neural network to predict PPI interactions by using only the protein sequences.

::DEVELOPER

Somaye Hashemifar

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

DPPI

:: MORE INFORMATION

Citation:

Hashemifar S, Neyshabur B, Khan AA, Xu J.
Predicting protein-protein interactions through sequence-based deep learning.
Bioinformatics. 2018 Sep 1;34(17):i802-i810. doi: 10.1093/bioinformatics/bty573. PMID: 30423091; PMCID: PMC6129267.

stringgaussnet 1.1 – PPI and Gaussian Network Construction from Transcriptomic Analysis Results Integrating a Multilevel Factor

stringgaussnet 1.1

:: DESCRIPTION

stringgaussnet is a toolbox for a construction of protein-protein interaction networks through the ‘STRING’ application programming interface, and an inference of Gaussian networks through ‘SIMoNe’ and ‘WGCNA’ approach, from DE genes analysis results and expression data. Additional functions are provided to import automatically networks into an active ‘Cytoscape’ session.

::DEVELOPER

Emmanuel Chaplais <emmanuel.chaplais at inserm.fr>, Henri-Jean Garchon

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows / Linux/ MacOsX
  • R

:: DOWNLOAD

 stringgaussnet

:: MORE INFORMATION

Citation

stringgaussnet: from differentially expressed genes to semantic and gaussian networks generation.
Chaplais E, Garchon HJ.
Bioinformatics. 2015 Jul 30. pii: btv450.

PiPa – Setup and Maintain a Database for Information on PPI and Biological Pathways

PiPa

:: DESCRIPTION

PiPa is a java-based tool to setup and maintain a database for information on Protein-Protein Interactions and biological Pathways integrated from multiple public databases.

::DEVELOPER

Wissensmanagement in der Bioinformatik

:: SCREENSHOTS

:: REQUIREMENTS

  • Linux / Windows /MacOsX
  • Java

:: DOWNLOAD

 PiPa

:: MORE INFORMATION

Citation

Arzt, S., Starlinger, J., Arnold, O., Kröger, S., Jaeger, S., and Leser, U. (2011).
PiPa: Custom Integration of Protein Interactions and Pathways
GI-Jahrestagung 2011, Workshop “Daten In den Lebenswissenschaften”.

EvoPPI 1.0 – Inter-specific comparisons from PPI Databases

EvoPPI 1.0

:: DESCRIPTION

EvoPPI allows the easy comparison of publicly available data from the main Protein-Protein Interaction (PPI) databases for distinct species.

::DEVELOPER

SING Group.

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux

:: DOWNLOAD

EvoPPI

:: MORE INFORMATION

Citation

Vázquez N, Rocha S, López-Fernández H, Torres A, Camacho R, Fdez-Riverola F, Vieira J, Vieira CP, Reboiro-Jato M.
EvoPPI 1.0: a Web Platform for Within- and Between-Species Multiple Interactome Comparisons and Application to Nine PolyQ Proteins Determining Neurodegenerative Diseases.
Interdiscip Sci. 2019 Mar;11(1):45-56. doi: 10.1007/s12539-019-00317-y. Epub 2019 Feb 1. PMID: 30707359.

PEWCC – Identify Protein Complexes from PPI

PEWCC

:: DESCRIPTION

PEWCC is a novel graph mining algorithm to identify protein complexes from protein-protein interaction data.

::DEVELOPER

Nazar Zaki , Bioinformatics Laboratory, UAE University.

:: SCREENSHOTS

N/A

::REQUIREMENTS

  • Windows / Linux/ MacOsX
  • Python

:: DOWNLOAD

 PEWCC

:: MORE INFORMATION

Citation

BMC Bioinformatics. 2013 May 20;14:163. doi: 10.1186/1471-2105-14-163.
Protein complex detection using interaction reliability assessment and weighted clustering coefficient.
Zaki N, Efimov D, Berengueres J.

PPI / PPI_RF – Prediction of Protein-Protein Interactions

PPI / PPI_RF

:: DESCRIPTION

The web-server PPI  is used to predict the protein-protein interaction.The protein sequence are represented by chaos game representation and wavelets transform. The chaos game representation encodes the amino acid position of the proteion and then two discrete series are gotten. The wavelets transform is used to analyse the two series. Finally the random forests algorithm is used for PPIs prediction.

The web-server PPI_RF is used to predict the protein-protein interaction. Based on the physicochemical descriptors, a protein could be converted into several digital signals and then wavelet transform was used to analyze them. With such a formulation frame to represent the samples of protein sequences, the random forests algorithm was adopted to conduct prediction.

::DEVELOPER

Xiao Lab

:: SCREENSHOTS

n/a

:: REQUIREMENTS

  • Web browser

:: DOWNLOAD

 NO

:: MORE INFORMATION

Citation

Prediction of protein-protein interactions using chaos game representation and wavelet transform via the random forest algorithm.
Jia JH, Liu Z, Chen X, Xiao X, Liu BX.
Genet Mol Res. 2015 Oct 2;14(4):11791-805. doi: 10.4238/2015.

Prediction of Protein-Protein Interactions with Physicochemical Descriptors and Wavelet Transform via Random Forests.
Jia J, Xiao X, Liu B.
J Lab Autom. 2015 Apr 16. pii: 2211068215581487

MDCinfer 1.0 – PPI Prediction tool based on Multiple Domain Cooperation analysis

MDCinfer 1.0

:: DESCRIPTION

MDCinfer aims to infer protein-protein interaction by considering cooperative domain interactions. Unlike most existing methods, it assumes cooperative-domain pairs but not only single-domain pairs as the basic units of a protein interaction. The interaction probabilities of single-domain pairs and cooperative-domain pairs are computed by a linear programming algorithm and a fast association probabilistic method. Novel protein interactions can be predicted by an extended probabilities model which can accommodate cooperative-domain pairs.

::DEVELOPER

APORC

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows

:: DOWNLOAD

 MDCinfer

:: MORE INFORMATION

Citation

Rui-Sheng Wang, Yong Wang, Ling-Yun Wu, Xiang-Sun Zhang, and Luonan Chen.
Analysis on multi-domain cooperation for predicting protein-protein interactions.
BMC Bioinformatics, Vol. 8, 391, 2007.

 

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