Welcome to the ESBG Lab


We are an inter-disciplinary research group using concepts and techniques from diverse disciplines including biophysics, biochemistry, and bioinformatics to understand how proteins, the molecular machines of life, work. Our current efforts are focused on protein kinases, a large and diverse family of enzymes that propagate cellular signals through the controlled phosphorylation of protein and small molecule substrates. We are using a combination of computational and experimental approaches to understand how natural sequence variation contributes to functional variation in protein kinases, and how non-natural variation contributes to disease.

See the research page to learn more about our ongoing projects.

Latest news

Tuan Nguyen receives the Goldwater Scholarship

June 27, 2014

Tuan Nguyen has been named a 2014 Barry M. Goldwater Scholar. Congratulations to Tuan for earning this prestigious award!

New publication in PLOS Computational Biology demonstrates the application of machine learning to the study of cancers

April 17, 2014

ManChon U, Eric Talevich, Samiksha Katiyar, Khaled Rasheed, and Dr. Natarajan Kannan have published a new research article in the PLOS Computational Biology journal titled "Prediction and prioritization of rare oncogenic mutations in the cancer Kinome using novel features and multiple classifiers." This paper elucidates the importance of developing an effective machine learning approach in identifying and analyzing mutations in the kinome which are implicated in rare cancers.

Eric Talevich secures a post-doctoral position at UCSF

August 1, 2013

Eric Talevich graduated this summer and has started his post-doctoral stint at UCSF. Congratulations Eric!!

>> more news