Wednesday, July 16, 2025 7/16/2025

Adaptive evolutionary inference frameworks for understudied populations using generative neural networks

Award Number: R15HG011528
ORGANIZATION: NATIONAL HUMAN GENOME RESEARCH INSTITUTE
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 12/18/2020
PERIOD OF PERFORMANCE END DATE: 05/31/2027

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Adaptive evolutionary inference frameworks for understudied populations using generative neural networks - PROJECT SUMMARY In population genetics, deep neural networks have largely replaced traditional approaches such as approximate Bayesian computation (ABC) and other summary statistic-based methods. However, there has been a lack of exploration and comparison of different architectures and input representation of genetic data. Additionally, interpreting trained neural networks and their predictions remains largely unexplored in this field. In this project we will develop new inference frameworks based on transformers, and compare these approaches with existing methodology. We will focus on the challenging task of joint inference, where a locus-specific forces such as natural selection or per site, per haplotype admixture are confounded by demographic history. We will create interpretability frameworks that allow researchers to understand what deep learning methods are learning at multiple scales. Local interpretability will explain network output on the genetic region level, while global interpretability focuses on individual network components such as convolutional filters or fully connected layers. Our interpretability methods will allow us to generate not just predictions and parameter estimates, but higher-level scientific insight for diverse human populations. Taken together, outcomes from our results will guide researchers toward the best networks for their inference tasks, quantify evolutionary processes in admixed populations, and illuminate the reasoning behind network predictions.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2025 ( Subtotal = $0 )
2025	2024	THE CORPORATION OF HAVERFORD COLLEGE	370 W LANCASTER AVE	HAVERFORD	PA	19041	MONTGOMERY	USA	Human Genome Research	001	2	3/4/2025	COMPETING CONTINUATION	$59,025
2025	2021	THE CORPORATION OF HAVERFORD COLLEGE	370 W LANCASTER AVE	HAVERFORD	PA	19041	MONTGOMERY	USA	Human Genome Research	000	1	3/4/2025	NEW	-$59,025
														Subtotal = $0

Issue Date FY: 2024 ( Subtotal = $350,141 )
2024	2024	THE CORPORATION OF HAVERFORD COLLEGE	370 W LANCASTER AVE	HAVERFORD	PA	19041	MONTGOMERY	USA	Human Genome Research	002	2	6/6/2024	COMPETING CONTINUATION	$350,141
2024	2021	THE CORPORATION OF HAVERFORD COLLEGE	370 W LANCASTER AVE	HAVERFORD	PA	19041	MONTGOMERY	USA	Human Genome Research	000	1	12/12/2023	NEW	$0
2024	2021	THE CORPORATION OF HAVERFORD COLLEGE	370 W LANCASTER AVE	HAVERFORD	PA	19041	MONTGOMERY	USA	Human Genome Research	001	1	5/31/2024	NEW	$0
														Subtotal = $350,141

Issue Date FY: 2021 ( Subtotal = $432,494 )
2021	2021	CORPORATION OF HAVERFORD COLLEGE, THE	370 LANCASTER AVE	HAVERFORD	PA	19041	MONTGOMERY	USA	Human Genome Research	000	1	12/18/2020	NEW	$389,243
2021	2021	CORPORATION OF HAVERFORD COLLEGE, THE	370 LANCASTER AVE	HAVERFORD	PA	19041	MONTGOMERY	USA	Human Genome Research	001	1	2/9/2021	NEW	$43,251
														Subtotal = $432,494

Grand Total All Awards = $782,635

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Adaptive evolutionary inference frameworks for understudied populations using generative neural networks

Award Number: R15HG011528

ORGANIZATION: NATIONAL HUMAN GENOME RESEARCH INSTITUTE

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

PERIOD OF PERFORMANCE START DATE: 12/18/2020

PERIOD OF PERFORMANCE END DATE: 05/31/2027

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