Jason M. Knight

Computational Biologist  |  jason@jasonknight.us

ABOUT

I'm a computational biologist/engineer/bioinformatician with several years experience with high-dimensional data analysis. I have a penchant for programming and programming language design with some hardware and entrepreneurial experience mixed in. I also have a wide range of additional interests and hobbies (cryptocurriencies, biohacking, etc.).

I am currently finishing my Ph.D. at Texas A&M University in the Genomic Signal Processing laboratory where I apply tools from modern engineering, mathematics, and statistics in order to understand and treat cancer.

Specifically, I have worked closely with biologists to develop Bayesian statistical models to uncover multivariate interactions among genes from RNA-Seq data. This allows us to classify types of cancer better than nonlinear SVM methods (which themselves are typically considered state of the art). I have also modeled biological regulatory networks using probabilistic Markov models that incorporate pathway knowledge from the biology literature as well as high-throughput data.

In the future, I want to continue using my knowledge and skills to enable principled approaches towards the detection, classification, and treatment of human diseases.


RESEARCH/PROJECTS
Coming soon...

EDUCATION

Ph.D. Electrical Engineering
Texas A&M University
Advisor: Edward Dougherty

Graduating in May 2015
In Progress

B.S. Biomedical Engineering
Texas A&M University
Minor: Mathematics (summa cum laude)

May 2009


SKILLS
Programming
  • Proficient: Julia, Python, Haskell
  • Working-level: C, Bash
  • Passable: R, C++, Javascript
Bioinformatics
  • RNA-Seq (alignment, quantification, single cell, differential expression, multivariate analysis, pattern detection),
  • RT-qPCR(normalization, correlation with RNA-Seq),
  • ChIP-Seq (publiclyavailable SRA data, bedtools)
Statistics
  • Bayesian inference
  • MCMC techniques (including stochastic approximation Monte Carlo (SAMC) and some thermodynamic integration)
  • Monte Carlo Integration

SOCIAL LINKS

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