Identify split reads in given chromosomal regions

(Under development) Computational framework for probabilistic models of immune receptor assembling.

TCR Enrichment Analysis (TEA) Webtool

Suit of statistical procedures for robust quantification of various BCR and TCR repertoire properties

Statistical classifier for diagnosing ovarian cancer from immune repertoires

MSc Bioinformatics with Systems Biology Dissertation

Adversarial autoencoders for MHCI epitope and immunogenicity prediction

Limitations of machine learning models for specificity prediction of T-cell receptor sequences

T-cell receptor specificity prediction using Deep Learning

Prediction and characterization of T cell response by improved T cell receptors to antigen specificity with interpretable deep learning

Prediction and characterization of T cell response by improved T cell receptors to antigen specificity with interpretable deep learning

The Read Origin Protocol (ROP) is a computational protocol that aims to discover the source of all reads, including those originating from repeat sequences, recombinant B and T cell receptors, and microbial communities.

Benchmarking modern neural networks for scRNA sequencing analysis

[Deprecated, see https://github.com/antigenomics/mirpy and other tools @antigenomics] Post-analysis of immune repertoire sequencing data

HTS-compatible wrapper for IgBlast V-(D)-J mapping tool

TCR embedding expressivity evaluation framework.

A nextflow pipeline for TCR repertoire building with MiXCR

TCR Epitope Generation Model with Top-K Prediction

Standardise TR/MH/IG data

Clustering of immune receptor repertoires