1. Biomedical Data Science for Precision Medicine
Vanathi Gopalakrishnan, PhD
Associate Professor of Biomedical Informatics, Intelligent Systems and Computational & Systems Biology
Director, PRoBE Laboratory for Pattern Recognition from Biomedical Evidence
Department of Biomedical Informatics
School of Medicine
University of Pittsburgh

2. PRoBE Lab: Research Interests
Overall Goal: To Accelerate Biomedical Knowledge Discovery
PRIOR
KNOWLEDGE
DATA
RULE LEARNING METHODOLOGIES
Example: Transfer Rule Learning
project funded by NIGMS
R01GM to VG
PREDICTIVE MODELS FOR
BIOMEDICINE
Enable predictions about for example: mechanism of action, target selection, useful biomarkers, toxicity, and clinical trial outcomes.

3. DATA WE WORK WITH
From biomarker* discovery studies for early detection of:
Amyotrophic Lateral Sclerosis
Alzheimer’s
Lung Cancer
Breast Cancer
Esophageal Cancer
Inflammatory Bowel Diseases Ulcerative Colitis, Crohn’s
Coronary Artery Disease
Pediatric Cardiomyopathy
Proteomic
Mass Spectral (large/wide/deep)
Immunoassay
Genomic
GWAS/SNPs(very large)
DNA Methylation
Gene Expression
microRNA
Images
Cardiac MRI
Brain fMRI
*The term “biomarker” or “biological marker”, refers to “a broad subcategory of medical signs – that is, objective indications of medical state observed from outside the patient – which can be measured accurately and reproducibly. Medical signs stand in contrast to medical symptoms, which are limited to those indications of health or illness perceived by patients themselves.” -
Kyle Strimbu, Jorge A. Tavel. What are Biomarkers? Curr Opin HIV AIDS Nov 5(6): 463–466.

4. Example: Lung Cancer Early Detection
RISK
PREDICTION
MODEL
Clinical
History ?
Accuracy of early detection
# Unnecessary biopsies
CT screen
Results
Blood
Test
Multiplexed serologic
Quantitative immunoassays
Luminex xMAP® technology
UPCI Lung Cancer SPORE Project funded by the NCI using P50 mechanism:
VG co-directs the Biostatistics and Bioinformatics Core