​   Research

Topics

  • Machine Learning

  • Computational Biology

  • Bioinformatics

  • Alternative splicing quantification

  • Post-transcriptional regulation

  • Regulatory elements modeling

  • Genetic variations effect on RNA processing

  • Personalized medicine based on clinical, genetic, and genomic profiling

Projects

The role of splicing variations in human disease


Multiple projects in the lab involve the role of splicing variations in disease such as cancer and neurodegeneration. We develop algorithms to detect these splicing variations from RNASeq, combine them with other data (multi-omics), experimentally validate those in relevant cell lines/primary tissues, and study their functional consequences

In collaboration with

Kristen Lynch, Sara Cherry, Martin Carrol, Andrei Thomas-Tikhonenko, David Elliot, Elizabeth Bhoj

High-throughput assays development

We are involved in several projects involving the development of new high-throughput assays for RNA processing.

Lab member

Kevin Yang, Mathieu Quesnel-Vallieres 

In collaboration with

Peter Choi, Alessandro Gardini

Quantification and Visualization of RNA splicing



A main focus is developing methods and tools for the community to address the computational challenges posed by high throughput data for accurately quantifying and visualizing splice variants and how these change across different conditions.

RNA Processing Regulatory

Mechanisms



The lab iterates between computational modeling and experimental verifications of mechanisms involved in RNA processing

Lab member

Matthew Gazzara

In collaboration with

Kristen Lynch, Russ Carstens,

David Elliot, Steve Liebhaber

Alternative Splicing Prediction



A major focus of the lab is developing algorithms and tools for predicting and analyzing splicing outcome under varying conditions.

Genetic Variations Effect on RNA Processing

We study how genetic variations affect splicing or other RNA processing and how these changes correlate with maligant state and phenotipic diversity.

In collaboration with

Elizabeth Bhoj, Lou Ghanem, Doug Epstein

Tools

© BIOCIPHERS - 2020 · Department of Genetics Perelman School of Medicine Department of Computer and Information Science School of Engineering University of Pennsylvania