Machine Learning in Genomics: Tools, Resources, Clinical Applications and Ethics

Additional Information

The primary purpose of the workshop is to stimulate discussion around the opportunities and obstacles underlying the application of machine learning (ML) methods to basic genome sciences and genomic medicine, to define the key scientific topic areas in genomics that could benefit from ML analyses and NHGRI’s unique role at the convergence of genomic and ML research.

The data-intensive fields of genomics and ML are in an early stage of convergence. This workshop will include a combination of lectures from ML, genomics, and ethics researchers with substantial time set aside for virtual Q&A sessions in which all attendees, irrespective of expertise and background, are encouraged to participate. Topics of interest within genomics cover the full spectrum of basic and clinical research. The workshop will also focus on the ethical aspects of ML applications to genomics data. ML scientists without any connection to genomics are as welcome to join as those already applying their analytical methods to genomic data.

The NHGRI Genomic Data Science Working Group of the National Advisory Council for Human Genome Research hosted the Machine Learning in Genomics virtual workshop on April 13 - April 14, 2021.

Day 1 Agenda | Day 2 Agenda

Organizing Committee

ML_Genomics_Workshop_ExecutiveSummary.pdf (251.02 KB)

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Machine Learning in Genomics: Tools, Resources, Clinical Applications and Ethics day1 Day 1 Agenda

All slides are in PDF format

April 13, 2021
11:00 a.m. – 5:00 p.m. EDT
11:00 a.m. - Welcome
Co-chairs:
Trey Ideker, Ph.D. , University of California San Diego
Mark Craven, Ph.D. , University of Wisconsin

Speaker:
Eric Green, M.D., Ph.D. , Director, National Human Genome Research Institute
Keynote Session: What are the opportunities and challenges for ML in genomics research?

Moderator:
Shannon McWeeney, Ph.D. , Oregon Health and Sciences University
11:10 a.m. - Eric Topol, M.D. , Scripps Research

TOPOL_NHGRI_Presentation1.pdf (54.45 MB)

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11:40 a.m. - Brad Malin, Ph.D. , Vanderbilt University Medical Center

Malin_Genomic_Challenges_v2.pdf (8.29 MB)

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12:10 p.m. - Q&A Session
12:40 p.m. - Break
Session 1: Algorithm development and machine learning approaches in genomics

Moderators:
Trey Ideker, Ph.D. , University of California San Diego
Anthony Philippakis, M.D., Ph.D. , Broad Institute
1:00 p.m. - Jian Peng, Ph.D. , University of Illinois at Urbana-Champaign

MLGW_Peng.pdf (7.27 MB)

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1:25 p.m. - Sara Mathieson, Ph.D. , Haverford College

Mathieson_NIH_talk.pdf (6.41 MB)

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1:50 p.m. - Christina Leslie Ph.D. , Memorial Sloan-Kettering Cancer Center

Leslie_nhgri-ml-workshop-mar2021_0.pdf (49.97 MB)

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2:15 p.m. - Q&A Session
2:45 p.m. - Break
Session 2: Ethical, Legal and Social Implications (ELSI) of machine learning in genomics

Moderators:
Dave Kaufman, Ph.D. , NHGRI
Eimear Kenny, Ph.D. , Icahn School of Medicine at Mount Sinai
3:10 p.m. - Pamela Sankar, Ph.D. , University of Pennsylvania

Sankar_NHGRI.pdf (153.46 KB)

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3:35 p.m. - Varoon Mathur , AI Now Institute

VaroonMathur-NHGRI_Machine_Learning_2021.pdf (8.07 MB)

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4:00 p.m. - Danton Char, M.D. , Stanford University

Danton_Char_ML.pdf (3.61 MB)

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4:25 p.m. - Q&A Session
4:55 p.m. - Day 1 Wrap-up

Co-chairs:
Trey Ideker, Ph.D. , University of California San Diego
Mark Craven, Ph.D. , University of Wisconsin
5:00 p.m. - Adjourn

day2 Day 2 Agenda

All slides are in PDF format

April 14, 2021
11:00 a.m. – 4:00 p.m. EDT
11:00 a.m. - Day 2 Opening

Co-chairs:
Trey Ideker, Ph.D. , University of California San Diego
Mark Craven, Ph.D. , University of Wisconsin
Session 3: Data and resource needs for machine learning in genomics

Moderators:
Christina Leslie, Ph.D. , Memorial Sloan Kettering Cancer Center
Mark Craven, Ph.D. , University of Wisconsin
11:10 a.m. - Alexis Battle, Ph.D ., Johns Hopkins University

NHGRI_Battle_2021.pdf (13 MB)

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11:35 a.m. - Anshul Kundaje, Ph.D. , Stanford University

2021-Kundaje-NHGRI-ML4Genomics.pdf (15.16 MB)

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12:00 p.m. - Gregory Cooper, M.D., Ph.D. , University of Pittsburgh

NHGRI_GCooper_ML.pdf (2.61 MB)

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12:25 p.m. - Q&A Session
12:55 p.m. - Break
Session 4: Machine learning in clinical genomics

Moderators:
Casey Overby Taylor, Ph.D. , Johns Hopkins University
Eric Boerwinkle, Ph.D. , University of Texas Health Science Center
2:00 p.m. - Su-In Lee, Ph.D. , University of Washington

ML-for-ClinicalGenomics-Lee-shared.pdf (7.63 MB)

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2:25 p.m. - Sriram Sankararaman, Ph.D. , University of California Los Angeles

NHGRI_Sankararaman-ML.pdf (6.01 MB)

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2:50 p.m. - Russ Altman, M.D., Ph.D. , Stanford University

nhgri-altman.pdf (23.02 MB)

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3:15 p.m. - Q&A Session
3:45 p.m. - Day 2 Wrap-up

Co-chairs:
Trey Ideker, Ph.D. , University of California San Diego
Mark Craven, Ph.D. , University of Wisconsin
4:00 p.m. - Adjourn