The Biological General Repository for Interaction Datasets (BioGRID) database was developed to house and distribute collections of protein and genetic interactions from major model organism species. BioGRID currently contains over 198 000 interactions from six different species, as derived from both high-throughput studies and conventional focused studies.
Biomolecular INteraction Network Database
IntAct provides a freely available, open source database system and analysis tools for protein interaction data. All interactions are derived from literature curation or direct user submissions and are freely available.
The DIP database catalogs experimentally determined interactions between proteins. It combines information from a variety of sources to create a single, consistent set of protein-protein interactions.
The Molecular INTeraction database (MINT) focuses on experimentally verified protein-protein interactions mined from the scientific literature by expert curators. The curated data can be analyzed in the context of the high throughput data and viewed graphically with the 'MINT Viewer'.
To faciliate experimentation and integrated computational analysis with model organism PPI networks, we have integrated known, experimental and predicted PPIs for five model organisms and human in the I2D database.
Homomint is a web available tool extending protein-protein interactions experimentally verified in models organisms, to the orthologous proteins in Homo sapiens.
The Unified Human Interactome is a comperehensive database of the computational and experimental based human protein interaction networks. This database is aimed to integrate diverge maps, which offers the research a flexible and direct entry gate into the human interactome.
APID (Agile Protein Interaction DataAnalyzer) is an interactive bioinformatic web-tool that has been developed to allow exploration and analysis of main currently known information about protein-protein interactions integrated and unified in a common and comparative platform.
The Human Protein Reference Database represents a centralized platform to visually depict and integrate information pertaining to domain architecture, post-translational modifications, interaction networks and disease association for each protein in the human proteome.
The Human Protein Interaction Database (HPID, was designed 1) to provide human protein interaction information pre-computed by a statistical method from existing structural and experimental data, 2) to provide integrated human protein interactions derived from BIND, DIP and HPRD, and 3) to find proteins from the databases that potentially interact with proteins submitted by users.
The MIPS Mammalian Protein-Protein Interaction Database is a collection of manually curated high-quality PPI data collected from the scientific literature by expert curators. We took great care to include only data from individually performed experiments since they usually provide the most reliable evidence for physical interactions.
A database of protein-protein interactions between large proteins
PPI section of the Comprehensive Yeast Genome Database.
Interactions between HIV and host proteins at the NCBI
A database of protein-protein interactions mediated by interchain
DOMINE is a database of known and predicted protein domain (domain-domain) interactions. It contains interactions inferred from PDB entries, and those that are predicted by 13 different computational approaches using Pfam domain definitions.
The database of 3D Interaction Domains (3did) is a collection of domain-domain interactions in proteins for which high-resolution three-dimensional structures are known.
DOMINO: a database of domain-peptide interactions. Many protein interactions are mediated by small protein modules binding to short linear peptides. DOMINO is an open-access database comprising more than 3900 annotated experiments describing interactions mediated by protein-interaction domains.
BindingDB is a public, web-accessible database of measured binding affinities, focusing chiefly on the interactions of protein considered to be drug-targets with small, drug-like molecules.
PDZBase is a manually curated protein-protein interaction database developed specifically for interactions involving PDZ domains.
SPOT (Sequence Prediction Of Target) is a procedure that is designed to infer the peptide binding specificity of any member of a family of protein binding domains: SH3, PDZ, and WW domains.
BindN for prediction of DNA and RNA binding residues in proteins
Web server for sequence-based prediction of DNA-binding residues in DNA-binding proteins.
DNA-Binding Domain Hunter (DBD-Hunter) is a knowledge-based method for predicting DNA-binding proteins function from protein structure. The method combines structural comparison and evaluation of DNA-protein interaction energy, which is calculated use a statistical pair potential derived from crystal structures of DNA-protein complexes.
This program predicts the DNA-binding in a protein from their sequence information using neural network.
ProNIT database provides experimentally determined thermodynamic interaction data between proteins and nucleic acids.
DISPLAR is a neural network method. Given the structure of a protein known to bind DNA, the method predicts residues that contact DNA.
PFplus (Path Finder Plus)is an automatic server to extract and display the largest positive electrostatic patch on a protein surface.
Protein-Protein Interaction Web site at the Jena Center for Bioinformatics
meta-PPISP is a metaserver built on three individual web servers: cons-PPISP, PINUP, and Promate.
cons-PPISP is a consensus neural network method for predicting protein-protein interaction sites. Given the structure of a protein, cons-PPISP will predict the residues that will likely form the binding site for another protein.
Identification of computational hotspots in protein interfaces: combining solvent accessibility and inter-residue potentials improves the accuracy.
Predicting the location of potential protein-protein binding sites for unbound proteins.
This server module predicts the atomic level structure of a protein complex. Given at least two protein sequences, this module first searches for homologs in a database of subunit sequences of experimentally determined protein complex structures. If all input sequences are homologous to subunits of an experimentally determined complex, our multimeric comparative modeling will be used to build three dimensional protein complex models for the sequences.
Protein binding site prediction with an empirical scoring function
WHISCY is a program to predict protein-protein interfaces. It is primarily based on conservation, but it also takes into account structural information. A sequence alignment is used to calculate a prediction score for each surface residue of your protein.
The KFC Server (Knowledge-based FADE and Contacts) predicts binding 'hot spots' within protein-protein interfaces by recognizing structural features indicative of important binding contacts.
Interaction Prediction through Tertiary Structure web-based tool to predict protein-protein interactions.
Solvent accessibility based Protein-Protein Interface iDEntification and Recognition
SNAPPI stands for Structures, iNterfaces and Alignments for Protein-Protein Interactions. The SNAPPI-Package consists of SNAPPI-DB, SNAPPI-View and SNAPPI-Predict.
Software platform for the visualization of complex interation networks.
An integrative platform for network/pathway analysis; visANT = Integrative Visual Analysis Tool for Biological Networks and Pathways.
esyN is a web tool that allows the construction of two distinct types of networks, Graphs and Petri nets. Graphs are simply graphs of nodes and edges, which are useful to visualize the relationships between the objects represented by the nodes. Petri nets are more complex and allow you to visually create a model that describes a process, based on adding an underlying formalism (Petri Nets), which can be simulated.
Network Analysis, Visualization, & Graphing TORonto is a software package for visualizing and analyzing protein-protein interaction networks.
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