Profiling tool for Mycobacterium tuberculosis to detect ressistance and strain type from WGS data

Minor Variant Calling and Phasing Tools

Drug Response Estimation from single-cell Expression Profiles

Generate a rich feature space describing all possible mutations in a given protein sequence (+ structure)

Snakemake pipelines to run the analysis for the Illumina vs. Nanopore comparison.

A comprehensive pipeline for HIV drug resistance identification, variant evaluation, and surveillance.

Multipurpose tool for targeted variant calling of genetic polymorphisms in Mycobacterium Tuberculosis

Data and analysis scripts used in Predicting resistance of clinical Abl mutations to targeted kinase inhibitors using alchemical free-energy calculations

A method to predict activating, deactivating and resistance mutations in kinases

A GLUE project for Hepatitis C virus (HCV)

This study assessed the spatial genetic variation in P. falciparum populations in Mali

Clusters phosphoproteomics data based on a combination of the sequence information and abundance changes over conditions.

Flexible and disposable paper and plastic-based gel micropads for nematode handling, imaging and chemical testing

The SNP and gene datasets of M. Tuberculosis for drug resistance prediction.

HCV drug resistance extension based on collaboration with PHE.

Personalised scoring system for lung cancer patients that enables ranking of the activated interventional nodes.

A GLUE project for hepatitis B virus (HBV).

Examine treatment outcomes, and predict the incidence of Tuberculosis

Drug release analysis based on different statistical metrics

This project contains the code for the manuscript "Explainable Machine Learning Identifies Factors for Dosage Compensation in Aneuploid Human Cancer Cells" by Heller et al. (https://doi.org/10.1101/2025.05.12.653427).