Bioinformatics Tools & Platforms
Discover powerful computational tools and databases for multi-omics data analysis, genomic research, and biological discovery.
Multiomics Frameworks
Integrated platforms for analyzing and visualizing multiple omics data types including genomics, transcriptomics, proteomics, and metabolomics.
KBCommons
A framework that automates database establishment and provides informatics tools and visualization capabilities for multiple organisms. Incorporates transcriptomics, proteomics, metabolomics, epigenomics, and molecular breeding data.
SoyKB
A comprehensive knowledge base for soybean research, providing integrated genomics, transcriptomics, proteomics, and metabolomics data for soybean and related species.
Omicsverse
A comprehensive multi-omics data integration and analysis platform that enables researchers to explore, visualize, and interpret complex biological datasets across different omics layers in a unified environment.
SARS-CoV-2 Genomics
The Covid-19 Genomics Surveillance Portal provides the trends in the identified variants of concern (VOC) and the regional map showing counties with total number of sequenced samples.
Predictive Tools
Advanced computational tools for predicting biological outcomes, pathway analysis, and cross-modality data translation.
IMPRes
Step-wise active pathway optimization and detection method using dynamic programming and multi-omics data as evidence. Incorporates KEGG pathways, transcriptomics and protein-protein interactions as background networks.
CrossMP
A web-based portal for cross-modality translation between single-cell RNA-seq and single-cell ATAC-seq data. It lets researchers upload one modality and predict the other using deep neural network modeling.
Pathotrack
A predictive tool for tracking and analyzing pathogenic pathways, enabling researchers to monitor disease progression and identify critical intervention points in biological systems.
Deep Learning & AI Based Methods
Cutting-edge artificial intelligence and deep learning approaches for genotype-to-phenotype prediction, regulatory network analysis, and single-cell annotation.
G2PDeep
Genotype-to-Phenotype Deep Learning platform for predicting complex traits from genomic data. Uses advanced deep learning models to bridge the gap between genetic variations and phenotypic outcomes in various organisms.
IRNET
A comprehensive platform for integrative regulatory network analysis, providing tools for reconstructing and analyzing gene regulatory networks from multi-omics data to uncover key regulatory mechanisms in biological systems.
scPlantAnnotate
A web-based deep learning tool for automated cell-type annotation in plant single-cell RNA sequencing (scRNA-seq) data. It uses transformer-based models optimized for plants to provide accurate and efficient identification of plant cell types across multiple species.