Genome Informatics

Biological information from genome sequences is derived by the application of computer and statistical techniques. Additionally, protein sequence and structure can be predicted by analyzing DNA sequence information. Tremendous advancements have been made to broaden sequencing applications from research to the clinic, especially as genomics becomes more integrated with precision medicine and AI initiatives. In spite of this, enormous problems still exist with data integration and analysis pipelines and sensitivity to accuracy in diagnosis and/or disease stratification. What is the role of computer science in modeling cells, analyzing and mapping data networks, and incorporating clinical and pathological data to determine how diseases arise from mutations? How do Bio-IT approaches help relate SNPs, expression, and disease? What is the role of AI in data curation techniques, text mining approaches, and statistical analytics to discover disease or drug response pathways to identify personalized and focused treatments and cures? Presentations in the Genome Informatics track will explore these issues and how organizations and research teams are implementing computational approaches to understand the biology of genomes.

Preliminary Agenda

PRECISION CANCER MEDICINE METHODS

Talk Title to be Announced

John Quackenbush, PhD, Henry Pickering Walcott Professor of Computational Biology and Bioinformatics; Chair, Department of Biostatistics, Harvard T.H. Chan School of Public Health

Precision Cancer Medicine

Jeffrey Rosenfeld, PhD, Manager, Biomedical Informatics Shared Resource and Assistant Professor of Pathology and Laboratory Medicine, Rutgers Cancer Institute of New Jersey; President, Rosenfeld Consulting LLC

ENABLING INDIVIDUALIZED DIAGNOSIS AND OPTIMAL TREATMENT

Building an Artificial Intelligence-based Vaccine Discovery System- Applications in Infectious Diseases & Personalized Neoantigen-related Immunotherapy for Treatment of Cancers

Kamal Rawal, PhD, Associate Professor, Amity University, India; Adjunct Faculty, Baylor College of Medicine, Houston, USA

Deciphering the Complex Heterogeneity of Cancer

Patrice Milos, PhD, Co-founder, President and CEO, Medley Genomics, Inc.

GENOME-WIDE DNA METHYLATION PROFILING

M2A: DNA Methylome Reveals Genome-wide Promoter Activities in Individual Tumors and Captures Tumor-Type-Specific Promoter Usages

Xiang Chen, PhD, Assistant Member, Computational Biology, St. Jude Children's Research Hospital

APPLICATION OF TOOLS IN CLINICAL AND POPULATION HEALTH SETTINGS 

Development of Polygenic Risk Scores Using Deep Learning: Case Study from an Ongoing Collaboration between Department of Energy and Department of Veteran Affairs

Ravi Madduri, Scientist, Data Science and Learning, Argonne National Laboratory; Senior Scientist, University of Chicago Consortium for Advanced Science and Engineering (UChicago CASE)

Wrangling the UK BioBank Data

Ariella Sasson, PhD, Senior Research Investigator, Bristol-Myers Squibb


Platinum Sponsors

accenture

BenchlingNEW

Elsevier-square

L7-informatics

linguamatics

PerkinElmer

Weka