WANT A PROFILE LIKE THIS?
Create my FREE Plan Or learn about other options
Matt Huska
PeerJ Author
35 Points

Contributions by role

Preprint Author 35

Contributions by subject area

Computational Biology
Genomics

Matt Huska

PeerJ Author

Summary

My general research focus is the application of machine learning methods to the understanding of gene regulation. Specifically, I've focused on looking for how much DNA sequence can explain the location of non-methylated regions of the genome, and also the application of semi-supervised learning to the prediction of cis-regulatory elements.

Computational Biology Data Mining & Machine Learning

Work details

PhD Student

Max Planck Institute for Molecular Genetics
September 2011

PeerJ Contributions

  • Preprints 1
September 1, 2016 - Version: 1
Predicting enhancers using a small subset of high confidence examples and co-training
Matthew R Huska, Anna Ramisch, Martin Vingron, Annalisa Marsico
https://doi.org/10.7287/peerj.preprints.2407v1