Chemical Biology & Therapeutics
Basel, Switzerland
We translate data into biological knowledge to develop better drugs and improve peoples' lives. To understand novel drug targets and drugging modalities, we exploit technologies in molecular biology that result in genome-scale data measurements. We evaluate, develop, and apply computational, statistical and machine learning methods to analyze these large, high-throughput, high-dimensional, multi-omic data. These data include human genetics (GWAS, CRISPR screens), genome-wide chromatin profiles (ATAC-seq, CUT&RUN, Hi-C), and RNA transcript measurements at both bulk and single-cell resolution (RNA-seq, spatial transcriptomics, long-read sequencing). To make data and code useful to other drug-hunters, we document our analyses in reproducible workflows and interactive graphic interfaces, we implement algorithms in well-documented software packages, and we follow the FAIR (Findability, Accessibility, Interoperability, and Reusability) Data Principles.
We lead the technological, data and design aspects of early drug-discovery projects conducted in close collaboration with multidisciplinary teams at NIBR. Our projects span several disease areas, including liver, blood, musculoskeletal and neurodegenerative conditions. Our research is done following Novartis’ inspired, curious, and unbossed values, which enable self-empowerment and a speak-up culture.
Selected Publications
An orally available, brain penetrant, small molecule lowers huntingtin levels by enhancing pseudoexon inclusion
Keller CG, Shin Y, Monteys AM, Renaud N, Beibel M, Teider N, Peters T, Faller T, St-Cyr S, Knehr J, Roma G, Reyes A, Hild M, Lukashev D, Theil D, Dales N, Cha JH, Borowsky B, Dolmetsch R, Davidson BL, Sivasankaran R.
Nature Communications. 2022 Mar 3;13(1):1150
Large-Scale Topological Changes Restrain Malignant Progression in Colorectal Cancer
Johnstone SE*, Reyes A*, Qi Y, Adriaens C, Hegazi E, Pelka P, Chen JH, Zou LS, Drier Y, Hecht V, Shoresh N, Selig MK, Lareau CA, Iyer S, Nguyen SC, Joyce EF, Hacohen N, Irizarry RA, Zhang B, Aryee MJ, Bernstein BE.
Cell. 2020 Sept 17;182(6):1474-1489
Alternative start and termination sites of transcription drive most transcript isoform differences across human tissues
Reyes A* & Huber W*.
Nucleic Acids Research. 2018 Jan 25;46(2):582-592
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