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New Computational Systems Biology Methods for Modeling Gene Regulatory Circuits

Award Number: R35GM128717
ORGANIZATION: NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 08/01/2018
PERIOD OF PERFORMANCE END DATE: 01/31/2029

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New Computational Systems Biology Methods for Modeling Gene Regulatory Circuits - Project Summary/Abstract Title: New Computational Systems Biology Methods for Modeling Gene Regulatory Circuits One of the biggest challenges in biology is to elucidate complex gene interactions and networks for the purpose of developing interventions in human disease. Particularly important are those gene networks that control cellular state transitions (e.g., replicative to quiescent, epithelial to mesenchymal, etc.). Thanks to the emergence of next-generation sequencing technology, rich data resources are available for mapping gene regulatory interactions. However, the field still lacks a systems-level understanding of how genes in a network collectively perform their functions and control cellular state transitions, information that is critical for informed clinical intervention. The PI’s long-term goal is to design effective computer-aided strategies for predicting therapeutic interventions by integrating knowledge of gene regulatory networks, genomics data from patients, and systems- biology model simulations. So far, numerous computational methods have been developed to infer and model gene regulatory networks. However, they typically suffer from the following issues. First, current approaches are still ineffective to choose an appropriate set of genes and regulatory interactions in a network to model. Current approaches infer regulatory relationships based on association of gene expression signals, but generally don't also consider whether an inferred gene regulatory network can operate as a functional dynamical system driving expected transitions between the network states. Second, traditional mathematical modeling is hard to be applied systematically to large systems, because many kinetic parameters are unmeasurable directly from experiments, especially in vivo. The parameter uncertainty and the potential risk of overfitting in large systems have limited the predictive power of systems biology. To address these issues, the PI’s research program will develop a suite of computational systems biology algorithms to construct and model high-quality core regulatory circuits driving cellular state transitions. We have recently developed enhanced ensemble-based mathematical modeling algorithms for simulating network behaviors without the need of detailed kinetic parameters. This advance has allowed an integrated top-down and bottom-up systems-biology modeling, as evident from the PI’s recently developed network reconstruction and modeling method NetAct and network coarse-graining algorithm SacoGraci. The PI’s research program will further advance novel technologies of ensemble-based modeling and their applications to optimize high-quality systems-biology models that capture cellular state transitions. The algorithms will be benchmarked and refined using in-silico simulated data, publicly available omics data sets, and data from collaborations, with a focus on cell differentiation in developmental processes and state transitions in oncogenesis. Success of the research program will result in a comprehensive toolkit that will unveil the gene regulatory mechanism of cellular state transitions. The algorithmic development is expected to have a broad impact on not only basic research in systems biology but also shed light on therapeutic intervention in genomic medicine.


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 = $360,000 )
2025	2025	NORTHEASTERN UNIVERSITY	360 HUNTINGTON AVE	BOSTON	MA	02115	SUFFOLK	USA	Biomedical Research and Research Training	002	7	1/16/2025	NON-COMPETING CONTINUATION	$360,000
2025	2024	NORTHEASTERN UNIVERSITY	360 HUNTINGTON AVE	BOSTON	MA	02115	SUFFOLK	USA	Biomedical Research and Research Training	000	6	11/14/2024	COMPETING CONTINUATION	$0
2025	2022	NORTHEASTERN UNIVERSITY	360 HUNTINGTON AVE	BOSTON	MA	02115	SUFFOLK	USA	Biomedical Research and Research Training	001	5	12/31/2024	NON-COMPETING CONTINUATION	$0
														Subtotal = $360,000

Issue Date FY: 2024 ( Subtotal = $399,479 )
2024	2024	NORTHEASTERN UNIVERSITY	360 HUNTINGTON AVE	BOSTON	MA	02115	SUFFOLK	USA	Biomedical Research and Research Training	000	6	1/3/2024	COMPETING CONTINUATION	$399,479
														Subtotal = $399,479

Issue Date FY: 2022 ( Subtotal = $392,500 )
2022	2022	NORTHEASTERN UNIVERSITY	360 HUNTINGTON AVE	BOSTON	MA	02115	SUFFOLK	USA	Biomedical Research and Research Training	000	5	9/7/2022	NON-COMPETING CONTINUATION	$392,500
														Subtotal = $392,500

Issue Date FY: 2021 ( Subtotal = $347,500 )
2021	2021	NORTHEASTERN UNIVERSITY	360 HUNTINGTON AVE	BOSTON	MA	02115	SUFFOLK	USA	Biomedical Research and Research Training	003	4	7/22/2021	NON-COMPETING CONTINUATION	$392,500
2021	2020	NORTHEASTERN UNIVERSITY	360 HUNTINGTON AVE	BOSTON	MA	02115	SUFFOLK	USA	Biomedical Research and Research Training	000	3	11/24/2020	CHANGE OF GRANTEE / TRAINING INSTITUTION / AWARDING INSTITUTION	-$45,000
2021	2020	NORTHEASTERN UNIVERSITY	360 HUNTINGTON AVE	BOSTON	MA	02115	SUFFOLK	USA	Biomedical Research and Research Training	002	3	3/17/2021	CHANGE OF GRANTEE / TRAINING INSTITUTION / AWARDING INSTITUTION	$35,503
2021	2019	THE JACKSON LABORATORY	600 MAIN ST	BAR HARBOR	ME	04609	HANCOCK	USA	Biomedical Research and Research Training	001	2	3/17/2021	NON-COMPETING CONTINUATION	-$35,503
														Subtotal = $347,500

Issue Date FY: 2020 ( Subtotal = $437,500 )
2020	2020	NORTHEASTERN UNIVERSITY	360 HUNTINGTON AVE	BOSTON	MA	02115	SUFFOLK	USA	Biomedical Research and Research Training	000	3	9/23/2020	CHANGE OF GRANTEE / TRAINING INSTITUTION / AWARDING INSTITUTION	$437,500
2020	2019	THE JACKSON LABORATORY	600 MAIN ST	BAR HARBOR	ME	04609	HANCOCK	USA	Biomedical Research and Research Training	001	2	9/24/2020	NON-COMPETING CONTINUATION	$0
														Subtotal = $437,500

Issue Date FY: 2019 ( Subtotal = $437,500 )
2019	2019	THE JACKSON LABORATORY	600 MAIN ST	BAR HARBOR	ME	04609	HANCOCK	USA	Biomedical Research and Research Training	000	2	7/30/2019	NON-COMPETING CONTINUATION	$437,500
														Subtotal = $437,500

Issue Date FY: 2018 ( Subtotal = $437,500 )
2018	2018	THE JACKSON LABORATORY	600 MAIN ST	BAR HARBOR	ME	04609	HANCOCK	USA	Biomedical Research and Research Training	000	1	7/30/2018	NEW	$437,500
														Subtotal = $437,500

Grand Total All Awards = $2,811,979

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New Computational Systems Biology Methods for Modeling Gene Regulatory Circuits

Award Number: R35GM128717

ORGANIZATION: NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

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

PERIOD OF PERFORMANCE START DATE: 08/01/2018

PERIOD OF PERFORMANCE END DATE: 01/31/2029

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