Theofanis Karaletsos | Search bioRxiv

bioRxiv2016

An Empirical Analysis of Topic Modeling for Mining Cancer Clinical Notes

Using a variety of techniques including Topic Modeling, Principal Component Analysis and Bi-clustering, we explore electronic patient records in the form of unstructured clinical notes and genetic mutation test results. Our ultimate goal is to gain insight into a unique body of clinical data, specifically regarding the topics discussed within the note content and relationships between patient clinical notes and their underlying genetics.

Bioinformatics↗

bioRxiv2015

RiboDiff: Detecting Changes of Translation Efficiency from Ribosome Footprints

MotivationDeep sequencing based ribosome footprint profiling can provide novel insights into the regulatory mechanisms of protein translation. However, the observed ribosome profile is fundamentally confounded by transcriptional activity. In order to decipher principles of translation regulation, tools that can reliably detect changes in translation efficiency in case-control studies are needed.\n\nResultsWe present a statistical framework and analysis tool, RiboDiff, to detect genes with changes in translation efficiency across experimental treatments. RiboDiff uses generalized linear models to estimate the over-dispersion of RNA-Seq and ribosome profiling measurements separately, and performs a statistical test for differential translation efficiency using both mRNA abundance and ribosome occupancy.\n\nAvailabilityRiboDiff webpage http://bioweb.me/ribodiff. Source code including scripts for preprocessing the FASTQ data are available at http://github.com/ratschlab/ribodiff.\n\nContactzhongy@cbio.mskcc.org and Gunnar.Ratsch@ratschlab.org.

Bioinformatics↗