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- 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
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- Integration of Genomics Data
- Immuno-Genomics Data Analysis
- Protein Interaction Prediction
- Protein Structure Prediction and Analysis
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Bias Removal
Lead Investigator(s) Andrea Califano
Two R scripts for removing location biases from a multiwell dataset.
▶ Software Page geWorkbench
Lead Investigator(s) Aris Floratos
Provides an integrated suite of genomics tools.
▶ Software Page Inference of Modules Associated with eQTL's
Lead Investigator(s) Itsik Pe'er
A tool for constructing modules regulated by eQTLs using gene expression and SNP variation data across multiple individuals.
Pandora
Lead Investigator(s) Raul Rabadan
A multi-step pipeline for finding pathogen sequences in RNA-seq data.
▶ Software Page Pegasus
Lead Investigator(s) Raul Rabadan
Enables annotation and prediction of oncogenic gene fusions using RNA-seq data.
▶ Software Page Randomly
Lead Investigator(s) Raul Rabadan
Randomly is a python package for denoising single-cell data using Random Matrix Theory.
▶ Software Page scTDA
Lead Investigator(s) Raul Rabadan
An object-oriented python library for topological data analysis of high-throughput single-cell RNA-seq data.
▶ Software Page