6 citations · 17 across the 8 of their papers we have counts for
3 papers · 1 filter
DRIVE: Machine Learning to Identify Drivers of Cancer with High-Dimensional Genomic Data & Imputed Labels
Adnan Akbar, Andrey Solovyev, John W Cassidy +2
Identifying the mutations that drive cancer growth is key in clinical decision making and precision oncology. As driver mutations confer selective advantage and thus have an increa…
Effective Sub-clonal Cancer Representation to Predict Tumor Evolution
Adnan Akbar, Geoffroy Dubourg-Felonneau, Andrey Solovyev +3
The majority of cancer treatments end in failure due to Intra-Tumor Heterogeneity (ITH). ITH in cancer is represented by clonal evolution where different sub-clones compete with ea…
Interlacing Personal and Reference Genomes for Machine Learning Disease-Variant Detection
Luke R Harries, Suyi Zhang, Geoffroy Dubourg-Felonneau +7
DNA sequencing to identify genetic variants is becoming increasingly valuable in clinical settings. Assessment of variants in such sequencing data is commonly implemented through B…