Scientist Machine Learning

Grad Student, bioinformatics; NSF Fellow; HHMI Gilliam Fellow (2015-2021). Elena graduated from UCSD with a B.Sc. in molecular biology and a minor in mathematics. As of 2014, she was a graduate student in the Bioinformatics program as part of the iPQB program at UCSF. She is interested in applying techniques from statistics and machine learning to better understand and predict features underlying drug-target interactions.

Lab papers

  1. Adding Stochastic Negative Examples into Machine Learning Improves Molecular Bioactivity Prediction.

    Caceres EL, Mew NC, Keiser MJ. J Chem Inf Model. 2020 Dec 28.

  2. A Simple Representation of Three-Dimensional Molecular Structure.

    Axen SD, Huang XP, Caceres EL, Gendelev L, Roth BL, Keiser MJ. J Med Chem. 2017 Sep 14.