Professor, Principal Investigator

Computations and Systems Biology
Memorial Sloan Kettering Cancer Center

 

Christina Sunita Leslie is a Canadian-American computational biologist whose research applies machine learning to genomics and the patterns of gene transcription, particularly in the study of cancer. She is particularly known for her research on string kernels for support vector machine classification of biological sequences..She works at the Memorial Sloan Kettering Cancer Center as a principal investigator in the Computational & Systems Biology Program,] and holds an additional affiliation as a professor in the Graduate School of Medical Sciences at Cornell University. ​

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The Leslie Lab develops novel computational methods to study cellular biological systems from a global and data-driven perspective. The team seeks to exploit diverse, high-throughput functional and genomic data to understand the molecular networks underlying fundamental cellular processes, including regulation of transcription, pre-mRNA processing, signaling, and post-transcriptional gene silencing. The algorithmic methods draw on machine learning, a computational field concerned with learning accurate, predictive models from noisy and high-dimensional data.

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She was named as a Fellow of the International Society for Computational Biology in 2021, "recognized as bringing rigorous statistical machine learning techniques to computational biology, including basic science and clinical settings, as well as major contributions to conferences and consortia".

(Source: Memorial Sloan Kettering Cancer Center)