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BIOFIN is a machine learning based tool for the identification of novel and effective biofilm inhibitory peptides (BIPs). Tools like Peptide prediction, Protein scan, Epitope Mapping, Similarity search are included to assist user.
ProInflam is a comprehensive web server for analysis and prediction of proinflamatory response of any peptide/protein antigen. Tools like Peptide prediction, Protein scan, Epitope Mapping, Similarity search are included to assist user.
'Hype' tool helps in the identification and classification of novel peptidoglycan hydrolases from complete genomic or metagenomic ORFs. HyPe is also available as stand-alone tool.
Microtaxi uses an taxon-specific gene based approach and provides an alternate valuable methodology to carry out the taxonomic classification of newly sequenced or existing bacterial genomes.
Woods tool using an integrated approach for fast and accurate functional annotation of proteins in both genomic and metagenomic datasets. It is available as stand-alone tool as well as a publicly available web-server.
'16S Classifier' is a Random Forest based tool which is developed to carry out fast, efficient and accurate taxonomic classification of 16S rRNA sequences. It has the unique ability to classify small Hypervariable Regions of 16S rRNA.
MP3 software is developed using an integrated SVM-HMM approach to provide improved efficiency and accuracy to predict pathogenic proteins in both genomic and metagenomic datasets.
A Machine learning based tool for predicting antiinflammatory response of any peptide/protein antigen
BioFuelDB is a database of enzymes which have application in biofuel production.
DrugBug predicts the biotransformation of drugs in human gut through microbial enzymes present in the gut microbes.
This database constructed using metabolic proteins from 491 gut microbial genomes, 2036 EC numbers (with representative PDB ID and domains present) and 1689 FDA approved drugs.
Antigen-specific induction of IL-17 cytokines leads to proinflammatory responses in various autoimmune diseases. Here, we have provided a machine learning based tool for predicting IL-17 inducing response of any peptide/protein antigen.
ToxiM is a machine-learning based binary classifier for the prediction of toxicity of molecules. Regression models for CaCo-2 permeability and Aqueous solubility has been provided to support the predicted toxicity for a given molecule.
MoliB is a machine learning based tool for the prediction of biofilm inhibitory property in different classes of small molecules.
SkinBug: A tool to predict metabolism of biotic and xenobiotic molecules by skin microbes.
MP4 tool which uses SVM-based approach to not only predict pathogenic proteins from genomic or metagenomic datasets but also further sub-categories them according totheir function.
