Rate My Professor Aik Choon Tan

Aik Choon Tan, PhD, is Professor of Oncological Sciences and Adjunct Professor of Biomedical Informatics in the Spencer Fox Eccles School of Medicine at the University of Utah. He holds the position of Senior Director of Data Science at Huntsman Cancer Institute, where he also occupies the Jon M. and Karen Huntsman Endowed Chair in Cancer Data Science, appointed in 2023. Affiliated with the Scientific Computing and Imaging Institute, Tan previously served as Vice Chair of the Department of Biostatistics and Bioinformatics at Moffitt Cancer Center in Tampa, Florida. He completed postdoctoral research fellowships at the Johns Hopkins University Whiting School of Engineering and the Johns Hopkins University School of Medicine. Tan earned a Bachelor of Engineering from Universiti Teknologi Malaysia and a PhD in computer science and bioinformatics from the University of Glasgow.

Tan's research focuses on translational bioinformatics, cancer systems biology, cancer data science, computational immuno-oncology, and precision oncology. His work employs artificial intelligence, machine learning, multi-omics data integration, and network-based approaches to discover biomarkers, predict drug combinations, decode tumor ecosystems, and co-target the tumor microenvironment to overcome cancer treatment resistance. He has authored or co-authored more than 200 peer-reviewed publications, including highly cited papers such as "Patient-derived tumour xenografts as models for oncology drug development" (Nature Reviews Clinical Oncology, 2012), "Caspase 3–mediated stimulation of tumor cell repopulation during cancer radiotherapy" (Nature Medicine, 2011), "DSigDB: drug signatures database for gene set analysis" (Bioinformatics, 2015), and "Simple decision rules for classifying human cancers from gene expression profiles" (Bioinformatics, 2005). Tan edited the books "Kinase Signaling Networks" (Methods in Molecular Biology, 2017) and "Next Generation Microarray Bioinformatics" (Methods in Molecular Biology, 2012). His contributions have advanced data-driven precision oncology, bridging computational methods with experimental and clinical research. Tan has secured grants from the National Institutes of Health and the Florida Biomedical Research Program.