- All Software Types
- Reverse Engineering and Analysis of Regulatory Networks
- Protein/RNA Structure Prediction, Analysis, and Visualization
- Nucleic Acid and Protein Sequence Analysis and Annotation
- Gene Expression Data Analysis
- Genetic Data Analysis
- Computational Learning and Natural Language Processing
- Simulation
- Integration of Genomics Data
- Immuno-Genomics Data Analysis
- Protein Interaction Prediction
- Protein Structure Prediction and Analysis
- Other Tools
Two R scripts for removing location biases from a multiwell dataset.
Provides an integrated suite of genomics tools.
A tool for constructing modules regulated by eQTLs using gene expression and SNP variation data across multiple individuals.
A multi-step pipeline for finding pathogen sequences in RNA-seq data.
Enables annotation and prediction of oncogenic gene fusions using RNA-seq data.
Randomly is a python package for denoising single-cell data using Random Matrix Theory.
An object-oriented python library for topological data analysis of high-throughput single-cell RNA-seq data.