The Christina Leslie Lab

Our lab develops novel computational methods to study cellular biological systems from a global and data-driven perspective. We seek 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. Our 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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Pictured: Christina Leslie

Christina Leslie, PhD

Associate Member

Associate Professor

Research Focus

Computational biologist Christina Leslie focuses on developing machine learning algorithms for computational and systems biology.


PhD, University of California, Berkeley

Selected Achievements

  • Introduction of string kernel methodology for SVM classification of biological sequences
  • Development of algorithms for predictive modeling of gene regulation
  • First systems-level analyses of competition between microRNAs and between target transcripts