Anna Shcherbina


Hometown: Los Angeles, California
Stanford University

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Research: In her research Anna seeks to develop deep learning algorithms that synergistically combine multiple types of genetic and epigenetic data to develop accurate models of gene regulation. She is building neural networks that can identify the specific change, or variant, in the DNA code that is responsible for errors in gene regulation and ultimately the onset of disease. She is primarily focusing on developing such models to identify pathogenic variants implicated in colorectal cancer, with plans to extend the model to other types of diseases. 

Bio: Anna is a second year PhD student in the department of Biomedical Informatics at Stanford University, working with Prof. Anshul Kundaje and Prof. Euan Ashley. Her research interests include developing algorithms that utilize deep learning and data mining approaches to derive medically-relevant conclusions from multi-layer omics data . Prior to her graduate studies at Stanford, Anna was a bioinformatician at MIT Lincoln Laboratory, where she developed algorithms to characterize microbiome metagenomic datasets as well as algorithms to predict kinship and biological ancestry from genetic variant data. She holds degrees in Computer Science (M.Eng, B.S) and Biological Engineering (B.S)  from the Massachusetts Institute of Technology.