Bamgineer: Introduction of simulated allele-specific copy number variants into exome and targeted sequence data sets

A Transformer-based model for read-level DNA methylation pattern identification and tumour deconvolution

A simple tumour classifier based on microRNA expression profiles

MATLAB scripts for the paper "Deep learning and 3D-DESI imaging reveal the hidden metabolic heterogeneity of cancer"

Implementation of tumoral growth using a discrete celullar automata, based on Dustin D.Phan work

A bunch of PK/PD patient models with various diseases for open-/closed-loop control systems

ML Algorithms for Classifying Tissue According to Methylation and Gene Expression

Grouped Read Testing

This project uses machine learning to detect brain tumors early. Different models are trained on metabolite data to classify healthy and carcinoma-afflicted individuals. The top-performing EvoHDTree model is enhanced with the ADASYN up-sampling algorithm to accurately distinguish between malignant and non-malignant tumors.

Glioblastoma tumour classfication and tumour grade segmentattion using U-NET CNN

A deep learning model to detect tumors in the given MRI images.