Softwares and tools

Here are the softwares/tools developed by our lab,

  1. miRfluence

    miRNAs of influence: This tool predicts influential disease-miRNAs in several diseases using an influence diffusion algorithm. The detected miRNAs have the highest coverage and impact-ability in a miRNA-miRNA network in a particular diseasei
    Citation:Under preparation (2017)

  2. miRsig

    A novel computational pipeline to predict common signature/core sets of miRNA--miRNA interactions for different diseases using network inference algorithms on miRNA-disease expression profiles. The predicted miRNA-miRNA interaction networks are used to generate disease-specific miRNA-miRNA interaction networks which are analyzed to identify common signature/core miRNA-miRNA interactions across different disease categories
    Citation: JJ Nalluri, D Barh, V Azevedo, P Ghosh. "miRsig: a consensus-based network inference methodology to identify pan-cancer miRNA-miRNA interaction signatures" Scientific Reports 7 (2017): 0-0.

  3. iMiR

    iMir allows users to enter miRNAs, chemical, TFs, genes and diseases and extract their underlying relationships. It features search and analysis tools with visualizations. It is a one-stop web portal for biologists and drug researchers to study the biological factors responsible for disease regulation in cells via miRNA, genes, and drugs.It allows researchers to investigate and test their hypotheses for determining disease prognosis and therapeutics. [Poster Link, 2016]

  4. BioRobust

    BioRobust is an online framework to determine the strength (robustness) of biological network. It combines the quantitative power of in-silico models with predictive abilities of machine learning regression techniques. (2015)

  5. DismiRa

    DismiRa (Disease-miRna associations) approaches the miRNA-disease interactions from a network-scientific perspective and implements two methodologies - maximum weighted matching model (a graph theoretical algorithm which provides the results by solving an optimization equation of selecting the most prominent set of diseases) and motif-based analyses (which investigates the motifs in the miRNA-disease network). The tool presents an interactive visualization which helps the user in exploring the networking dynamics of miRNAs and diseases.
    Citation: JJ Nalluri, BK Kamapantula, D Barh, N Jain, A Bhattacharya, .... "DISMIRA: Prioritization of disease candidates in miRNA-disease associations based on maximum weighted matching inference model and motif-based analysis" BMC genomics 16 (5), S 12 (2015): 0-0.

  6. miRegulome: a knowledge base for miRNA regulomics

    miRegulome is an integrated online repository that provides entire regulatory modules of a miRNA, based on manually curated validated published data. Each module is hyperlinked to appropriate external database such as CTD, mir2Disease, miRNApath, KEGG, Entrez, and PubMed etc. to give the best possible picture of a miRNA regulome. The modules of a miRNA regulome consist of upstream regulators (transcription factors and various chemicals), downstream targets, pathways, functions, and disease associations etc. The relationships between modules and miRNA and experimental details have also been provided.
    Citation: D Barh, B Kamapantula, N Jain, J Nalluri, A Bhattacharya, L Juneja, .... "miRegulome: a knowledge-base of miRNA regulomics and analysis" Scientific reports 5 (2015): 12832-12832.

  7. Pannotator: An automated tool for annotation of pan-genomes

    Pannotator is an automated pipeline for the annotation of closely related genomes well suited for pangenome studies. This tool reduces the manual work needed to generate reports and corrections of various genome strains. Important contribution of this tool is the fast and automatic generation of an annotation based on a gold standard manual annotation.
    Citation: AR Santos, E Barbosa, K Fiaux, M Zurita-Turk, V Chaitankar, B Kamapantula, A Abdelzaher, P Ghosh, S Tiwari, N Barve, N Jain, D Barh, A Silva, A Miyoshi, V Azevedo "PANNOTATOR: an automated tool for annotation of pan-genomes" Genet Mol Res 12 (2013): 2982-2989.