September 17, 2009

ADAN: A Database for Prediction of Protein Protein Interactions

Filed under: Bioinformatics,Computational Biology,Proteomics — Biointelligence: Education,Training & Consultancy Services @ 12:51 pm
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In the last post we had given an introductions to MIPS (Mammalian Prtein Protein Interaction database). Most of the structures and functions of proteome globular domains are yet unknown. We can use high-resolution structures from different modular domains in combination with automatic protein design algorithms to predict genome-wide potential interactions of a protein. Todays post introduces a database whcih helps in prediction of such protein interactions.

ADAN database is a collection of different modular protein domains (SH2, SH3, PDZ, WW, etc.). It contains 3505 entries with extensive structural and functional information available, manually integrated, curated and annotated with cross-references to other databases, biochemical and thermodynamical data, simplified coordinate files, sequence files and alignments. Prediadan, a subset of ADAN database, offers position-specific scoring matrices for protein?protein interactions, calculated by FoldX, and predictions of optimum ligands and putative binding partners. Users can also scan a query sequence against selected matrices, or improve a ligand?domain interaction. The ADAN Database can be accessed from here:

September 16, 2009

Database for Protein Protein Interactions

Filed under: Bioinformatics,Computational Biology,Proteomics — Biointelligence: Education,Training & Consultancy Services @ 1:28 pm
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Proteins are organic compounds made of amino acids arranged in a linear chain and folded into a globular form. These molecules are of great importance because of the function they perform.

Protein associations are studied from the perspectives of biochemistry, quantum chemistry, molecular dynamics, signal transduction and other metabolic or genetic/epigenetic networks. Protein-protein interactions are at the core of the entire Interactomics system of any living cell.These interactions involve not only the direct-contact association of protein molecules but also longer range interactions through the electrolyte, aqueous solution medium surrounding neighbor hydrated proteins over distances from less than one nanometer to distances of several tens of nanometers. Furthermore, such protein-protein interactions are thermodynamically linked functions of dynamically bound ions and water that exchange rapidly with the surrounding solution by comparison with the molecular tumbling rate (or correlation times) of the interacting proteins.

The MIPS Mammalian Protein-Protein Interaction Database is a collection of manually curated high-quality Protein Protein Interaction data collected from the scientific literature by expert curators.The content is based on published experimental evidence that has been processed by human expert curators. MIPS provides the full dataset for download and a flexible and powerful web interface for users with various requirements.

Click here to access MIPS:

September 3, 2009

WebArrayDB: A Platform for Microarray Data Analysis

Filed under: Bioinformatics,Microarray — Biointelligence: Education,Training & Consultancy Services @ 3:02 pm
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 Microarray Data Analysis

Cross-platform microarray analysis is an increasingly important research tool, but researchers still lack open source tools for storing, integrating, and analyzing large amounts of microarray data obtained from different array platforms.

An open source integrated microarray database and analysis suite, WebArrayDB (, has been developed that features convenient uploading of data for storage in a MIAME (Minimal Information about a Microarray Experiment) compliant fashion, and allows data to be mined with a large variety of R-based tools, including data analysis across multiple platforms. Different methods for probe alignment, normalization and statistical analysis are included to account for systematic bias. Student’s t-test, moderated t-tests, non-parametric tests, and analysis of variance or covariance (ANOVA/ANCOVA) are among the choices of algorithms for differential analysis of data. Users also have the flexibility to define new factors and create new analysis models to fit complex experimental designs. All data can be queried or browsed through a web browser. The computations can be performed in parallel on symmetric multiprocessing (SMP) systems or Linux clusters.
The software package is available for use on a public web server ( or can be downloaded.

Check out WebArray at: