1. Biomedical Data Science for Precision Medicine
Room 530, BAUM
Biomedical Data Science for Precision Medicine
Vanathi Gopalakrishnan, PhD
Associate Professor of Biomedical Informatics
Associate Professor of Intelligent Systems
Associate Professor of Computational & Systems Biology
Director, PRoBE Laboratory for Pattern Recognition from Biomedical Evidence
Co-director, Bioengineering, Biotechnology and Innovation Area of Concentration
School of Medicine
University of Pittsburgh

2. PRoBE Lab: Research Interests
To Accelerate Biomedical Knowledge Discovery by Developing and Applying novel hybrid Artificial Intelligence Methods
Obtained for
example from:
Biomedical
Assays, Clinical
Assessments,
Imaging tests
Obtained for
example from:
Literature,
Ontologies,
Past analyses
PRIOR
KNOWLEDGE
DATA
Integrative Modeling
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 for early detection or monitoring of disease, toxicity risk, and clinical trial outcomes.

3. SOME TYPES OF 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
Bigbee, W. L*., Gopalakrishnan, V.*, Weissfeld J, L., Wilson, D. O., Dacic, S. Lokshin, A. E., Siegfried, J. M. A Multiplexed Serum Biomarker Immunoassay Panel Discriminates Clinical Lung Cancer Patients from High-Risk Individuals Found to be Cancer-Free by CT Screening. J Thorac Oncol Apr;7(4): (*These authors contributed equally to the study).

5. Some Current Projects
Transfer Learning of Classification Rules applied to microbiome data modeling – NIGMS funded R01 – collaboration with Washington University.
Biomarker/Pathway discovery from metabolomic data for personalizing heart disease treatment – collaboration with Industry (Metabolon, Inc.) and Dr. Steve Reis (CTSI Pitt).
Computer Aided Imaging Diagnostics to support Children’s Hospital of UPMC Radiologists – collaboration with Dr. Ashok Panigrahy and group.