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p-TAREF 2.0: Deep learning based accurate identification of miRNA targets in plants coming soon....

GANGE: Generative Additive Nucleotides Based Genome Evolver Read the research article here  Listen to the Podcast

ProMaya: a hierarchical universal Deep Learning framework for accurate and interpretable Protein-Protein interaction identification Read the research article here Access: 655  Listen to the Podcast

CritiCal C : Detecting critical cytosines in gene regulation Read the research article here Access: 4712  Listen to the Podcast

CTF-BIND: Resource and software portal to detect abiotic stress specific regulation of genes and spatiotemporal study of transcription factors Read the research article here Access: 1816  Listen to the Podcast

DMRU: Generative deep learning to unravel condition-specific cytosine methylation in plants Read the research article here Access: 4206  Listen to the Podcast

PTF-Vāc:An explainable and generative deep co-learning encoders-decoders system for ab-initio discovery of plant transcription factor binding sites Read the research article here Access: 4883  Listen to the Podcast

PTFSpot : Deep co-learning algorithm to discover transcription factor binding region in plants. Read the research article here Access: 4003 Standalone version of the program:  Github link  Listen to the Podcast

miWords : A revolutionary algorithm to identify plant pre-miRNAs  Read the research article here Access: 4163 Standalone version of the program:  Github link  Listen to the Podcast

DeepPlnc : A tool to detect plant lncRNAs through multimodal deep learning on sequential data  Read the research article here Access: 5740 Standalone version of the program:  Github link  Listen to the Podcast

RBPSpot : A tool to identify RBP binding spots in RNA  Read the research article here Access: 8472 Standalone version of the program:  Github link  Listen to the Podcast

miRbiom : A webserver for miRNA profiling and miRNA biogenesis-a resultant of spatio-temporal combinations of several RNA-binding proteins.  Read the research article here Standalone version of the program:  Github link  Access: 10018  Listen to the Podcast

Picro-DB : A comprehensive information database for Picrorhiza kurroa genome and its various genomic components  Read the research article here

PRP:  The Plant Regulomics Portal: An ultimate resource for integrated information and study of plant regulatory systems including NGS, Epigenomics, miRNA, Transcription factor and network analysis. Enriched with cutting edge browser and visualization tools, selecting downloading and analytical tools. Read the research article here Discontinued

IPFIP : Molecular systems based study information portal for Idiopathic Pulmonary Fibrosis (IPFIP) Read the research article here

MauPIR :  Click logo image for redirection of database Read the research article here

AssemblyVAlidator : A tool to detect misassembly in de novo assembled contigs Read the research article here

The Mythology of "micro"-RNAs. Click logo image for redirection of database Read the research article here

pPromotif: A novel and accurate algorithm to identify Transcription Factor Binding Sites on plant genomic sequences. Read the research article here

miReader: New version of miReader coming soon Read the research article here Download standalone version of miReader

miR-BAG: An Avant-garde parallely coded tool, based on machine learning for accurate miRNA identification. Works universely on genomic and NGS (Next Generation Sequencing) data. Read the research article here Download standalone version of miR-BAG

p-TAREF: A concurrent application for fast and accurate plant miRNA target identifications. Read the research article here Click logo to download standalone verion of P-TAREF

filteR: Parallely coded tool for fast Next Generation Sequencing Read filtering and cleaning. (Coded in Qt, C++, Parallel library used:OpenMP). Download here the standalone verion   Read the research article here

Picrorhiza kurrooa Information House

TAREF: A tool to Refine microRNAs target prediction in animal. Read the research article here