The Bioinformatics Section (BIS) develops and applies integrated computational biology and data science methods to generate an analytical suite that:

  • Aids in variant review and prioritization by automating variant annotation, classification, and prioritization of variants.
  • Identifies potential therapeutics for screening using ensemble machine learning methods with rank-based prioritization of novel targets and repurposed drugs.
  • Manages the data life-cycle including dissemination, tracking, and sharing.
The BIS develops and applies machine and transfer learning approaches to identify and prioritize genome-driven therapeutic targets and repurposing candidates for patient and cellular phenotypes, including disease and tissue-agnostic or -aware biomarkers. Through collaboration, we test hypotheses generated from these approaches in pre-clinical models (i.e., iPSCs, PDXs, etc.). Additionally, through data science approaches, we optimize the selection and interpretation of preclinical models for modeling human diseases.

The Team

Elizabeth Worthey, PhD

BIS Core Lead

Worthey Lab

Brittany Lasseigne, PhD

BIS Core Co-Lead

Lasseigne Lab

Rabab Fatima

Software Developer II – Genomics

Worthey Lab

Angelina Uno-Antonison

Software Architect – Genomics

Worthey Lab

Elizabeth Wilk

Researcher III

Lasseigne Lab

Vishal Oza, PhD

Scientist II

Lasseigne Lab