The Systems Biology of Drug Resistance in Cancer group, led by professor Sampsa Hautaniemi, focuses on understanding and finding effective means to overcome drug resistance in cancers. Our approach is to use systems biology, i.e., analyze molecular & clinical data from cancer patients with machine learning and mathematical methods, to identify efficient patient-specific therapeutic targets. Our work is cross-disciplinary and done in close collaboration with researchers from various disciplines, including clinicians, cell biologists and geneticians. The main objective of our research is to obtain hypotheses and predictions that can be tested in wet-lab or in clinical trials and thereby translate medical data into benefits in cancer patient care.
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@HautaniemiLab

We belong to cross-disciplinary #ONCOSYS, @HerculesOvCa, @RESCUER2020 consortia in which computational predictions… twitter.com/i/web/status/1…

Join us to discover drivers of #chemotherapy resistance and means to overcome it! #WGS, #RNASeq, #cytof, #scRNAseqtwitter.com/i/web/status/1…

A Nature article ucla.in/31F1C8k reports a breakthrough in medical diagnosis. While most ML enthusiasts are… twitter.com/i/web/status/1…

A new paper by Antti Häkkinen et al. presenting a t-SNE optimizer with automatic parameter tuning for large data se… twitter.com/i/web/status/1…