राष्ट्रीय प्रजनन एवं बाल स्वास्थ्य अनुसंधान संस्थान
National Institute for Research in Reproductive and Child Health

GeDiPNet is an open access, unified database on human Gene Disease Pathway Networks. The gene-disease associations are fetched from multiple data sources (DisGeNET, ClinGen, ClinVar, HPO, OrphaNet, and PsyGeNET) and are manually curated to reduce redundancy and at the same time minimise data loss. Sub-types or similar disease names are merged into unique terms for efficient analysis. It has linked information on human genes, SNPs, diseases and pathways. Using GeDiPNet, high level annotated data can be retrieved for human genes such as synonyms, chromosome location, expression profile, gene ontology, protein-related information, SNPs, associated diseases and pathways.

Multimorbidity Risk Prediction for Schizophrenia (MRPS) is an open access comorbidity analysis tool developed for predicting the risk of morbidities in schizophrenia, based on shared gene-disease associations. This tool is based on the meta-analysis of  22 GWA studies and 654 SNPs (P Value < 5 × 10-8). The GWA studies had individuals with SCZ (and no other comorbidities) as case group and healthy individuals as control group. The ethnicity distribution of the 22 GWA studies included Asian (5), European (5), Ashkenazi Jews (1) and mix of east Asian, European and others (11). The gene-disease associations are sourced from GeDiPNet.

PrecocityDB is the first manually curated online database on genes, SNPs, pathways, and ontologies associated with precocious puberty. The database has curated information of 44 genes, 235 pathways, 199 SNPs, and 26874 ontology terms associated with precocious puberty. SNP visualizer can be used for visualizing SNP coordinates and allelic variation on each chromosome for the genes associated with precocious puberty. Graphical representations of the pathway and disease enrichment analyses based on genes associated with precocious puberty can be viewed from the Enrichment analysis tab.

PBIT: Pipeline builder for identification of target (PBIT) has been developed to enable users to access information on all these aspects for studying microbial proteomes. Users can build their own pipeline for target identification by selecting, integrating and executing the independent modules that give information on aspects known to be critical in target discovery.

An offline version for identification of targets from pathogen proteomes, protein-protein interaction network and genome scale metabolic model may be downloaded and used.

CAMPSign is a tool for identification of antimicrobial peptides belonging to one of the 45 major AMP families present in CAMPR3. The peptides are identified based on family signatures such as patterns and HMMs generated for experimentally known AMPs. Users can submit sequences for screening the presence of these AMP signatures. Users can further BLAST the sequence/s of interest to find homologous sequences in popular AMP databases such as CAMP, APD, AVPdb, BACTIBASE etc.

PCOSKB is a manually curated knowledgebase on PCOS. PCOS-related information available through scientific literature is cross-linked with molecular, biochemical and clinical databases. Information on associated genes, SNPs, diseases, gene ontologies and pathways along with supporting reference literature is collated and integrated in PCOSKB. Various tools are embedded in the database such as Comorbidity analysis for estimating the risk of diseases to co-occur with PCOS; Network analysis for identifying enriched pathways and hub genes and Venn analysis for finding common and unique genes, pathways and ontologies.

 

ClassAMP: Antimicrobial peptides (AMPs) are being explored as substitutes to antibiotics. The broad range of activity of AMPs, multiple cellular targets and their ability to inhibit multi-drug resistant microbes make them ideal candidates as future drugs. To explore AMPs as drugs it is essential to understand sequence-specificity relationship of AMPs. ClassAMP has been developed using Random Forests method to understand the role of sequence of AMPs in its specificity towards bacteria, fungii and viruses.

ClotBase is a curated knowledgebase on the proteins that are involved in the blood coagulation pathway. It contains information on sequence, accession number, source, taxonomy, keywords, function, subcellular location,  tissue specificity, associated diseases and links to external databases such as NCBI, PubMed, EMBL, PIR, PDB and OMIM. Information on the known disease-causing mutations and evolutionarily conserved residues for all these proteins is also incorporated. Clinicians can use the Screen-Mutation tool to identify lethal mutations in protein sequences.

PBIT V3 -Pipeline builder for identification of target (PBIT) has been developed to enable users to access information on all these aspects for studying microbial proteomes. Users can build their own pipeline for target identification by selecting, integrating and executing the independent modules that give information on aspects known to be critical in target discovery.  Identification of drug targets for human infectious diseases is dependent on information on several aspects like non-homology to human proteins and proteins of human gut flora, essentiality for survival of the pathogen, druggability, subcellular localization, functional annotation, unique metabolic pathways, antigenicity etc.

EpiCandin – Infections caused by Candida species are associated with high morbidity and mortality. EpiCandIn has been created to track the epidemiology of candidiasis in India. It is a collection of manually curated publications that report the data on candidiasis such as Candida species, geographical location, niche affected, disease characteristics and drug therapy details. This resource is integrated with visualization tools and will be useful for public health researchers and policy makers to gain insights on the emerging trends and management of Candida infections in India.

CanDRes (Candida Drug Resistance) is a curated database of genes and mutations that are associated with antifungal drug resistance (ADR). This data has been retrieved by manually curating published literature. CanDRes contains information on Candida isolates/strains, genes, mutations associated with ADR, antifungal drugs with MICs. The data is adequately crosslinked to relevant databases like UniProt and PubMed. Users can visualize the mutation details and positions on sequences. The 3D structures of the mutants are modeled and available to users in a downloadable format for further analysis.