Colm Seale's MSc thesis in #OUP_Bioinformatics! On selection bias in synthetic lethality prediction. What's up with bias in SL data? Are published models robust? How to diagnose, build more resilient models? doi.org/10.1093/bioinf… with Yasin Tepeli. #MachineLearning Automated Synthetic Lethality Papers

Latest by Yasin Tepeli in our quest to improve synthetic lethality prediction. Isn’t sequence homology indicative of related function? We integrate it with cancer omics to predict SL gene pairs. Differences in patient survival suggest therapeutic potential. Automated Synthetic Lethality Papers w/ C. Seale

👋 Come visit the poster if you are interested in synthetic lethality. #ECCB2020

Our graduated BSc students, Andrei Tociu & Emiel Witting, will present their theses at BNAIC/Benelearn'23: assessing domain adaptation for mitigating sample selection bias. Great supervision by Yasin Tepeli! #bnaic #benelearn #MachineLearning #fairnessML #responsibleAI @eemcs_tud

Paper by our Yasin Tepeli: How to train fairer ML models from data affected by selection bias? Diversity! DCAST learns from diverse vs. most confident samples to avoid confirmation bias via semi-supervised learning. #MachineLearning #FairnessML @eemcs_tud arxiv.org/abs/2409.20126

Paper by our Sander Goossens! Shows we can learn tumor-relevant mutational signatures of DDR deficiency from gene perturbation screens with mutation profiling after DNA damage. Check out SNMF (supervised NMF)! doi.org/10.1101/2024.1… #DDR #DNARepair #MachineLearning @eemcs_tud