Can Cenik

  • Associate Professor
  • Molecular Biosciences
  • Interdisciplinary Life Sciences Graduate Program

Our long-term goal is to develop the necessary computational and experimental framework for predictive models that explain how cells determine their protein abundance. Achieving this goal involves two major components: (1) higher-resolution and higher-precision measurements of various gene expression modalities, and (2) computational and theoretical advancements capable of integrating these quantitative measurements into cohesive, predictive frameworks. We are looking for highly motivated and ambitious PhD students and postdoctoral fellows to join our team. 

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Contact Information

Biography

Cenik received his B.A. in Applied Mathematics from Harvard College, followed by his Ph.D. in Genetics at Harvard Medical School with Dr. Frederick P. Roth. Prior to joining UT Austin, he completed a postdoctoral fellowship under Dr. Michael P. Snyder in genetics at Stanford University, School of Medicine. Cenik has received both an NIH early investigator award and a CPRIT recruitment award

Research

Cenik Lab’s research involves analyses of RNA, RNA translation, and protein levels to understand molecular mechanisms governing translation of specific RNAs. Cenik’s work requires cutting-edge genomic and proteomic studies coupled with rigorous bioinformatic analysis.

Research Areas

  • AI for Health or Computational Science
  • Molecular Biology or Genetics
  • Statistics, Big Data or Machine Learning

Fields of Interest

  • Molecular Biology, Genetics & Genomics
  • System and Synthetic Biology
  • Cell and Developmental Biology

Education

  • Postdoctoral Training, Stanford University School of Medicine
  • Ph.D. in Genetics, Harvard Medical School
  • B.A. in Applied Mathematics, Harvard College

Publications