Daniel L. Cook

Queensland University of Technology

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John H. Gennari

University of Washington

Maxwell L. Neal

Infectious Disease Research Institute

Leslie S. Satin

University of Michigan–Ann Arbor

José L. V. Mejino

University of Washington

Ian R. Sweet

University of Washington

Brian E. Carlson

University of Michigan–Ann Arbor

Daniel Porte

University of California, San Diego

Christopher T. Thompson

Medical College of Wisconsin

William F. Hopkins

Stanford University

C. N. Hales

University of Cambridge

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University of Washington

Seattle University

University of Washington Medical Center

United States Department of Veterans Affairs

Stanford University

University of Auckland

European Bioinformatics Institute

University of Cambridge

Geriatric Research Education and Clinical Center

Google (United States)

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Intracellular ATP directly blocks K+ channels in pancreatic B-cells

Nature (1984)

Daniel L. Cook Nicholas M. Hales

10.1038/311271a0

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Citations (1,202)

The Ontology of Physics for Biology

Daniel L. Cook John H. Gennari Maxwell L. Neal

This book introduces semantic representations of multiscale, multidomain physiological systems that link to qualitative reasoning and to quantitative analysis of biophysical processes in health and disease. Two major public health problems, diabetes and hypertension, serve as use-cases to illustrate the depth and rigor of such representations for logical inference and quantitative analysis. Central to this approach is the Ontology of Physics for Biology (OPB) that formally represents the foundations of classical physics and engineering system dynamics that are the basis for our understanding of biomedical entities, processes, and functional relationships. Furthermore, we introduce OPB-based software for annotating and abstracting available biosimulation models for reuse, recombination, and for archiving of physics-based biomedical knowledge. We have formalized and leveraged physics-based biological knowledge as a working view of physiology and biophysics from three distinct perspectives: (1) biologists and biomedical investigators, (2) biophysicists and bioengineers, and (3) biomedical ontologists and informaticists. We present a logical and intuitive semantics of classical physics as a tool for mediating and translating biophysical knowledge among biomedical domains. Daniel L. Cook, MD, PhD John H. Gennari, PhD Maxwell L. Neal, PhD

10.1201/9780429469961

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Citations (0)

Biomedical Information and Data Resources

CRC Press eBooks (2023)

Daniel L. Cook John H. Gennari Maxwell L. Neal

10.1201/9780429469961-2

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Biomedical Challenges

CRC Press eBooks (2023)

Daniel L. Cook John H. Gennari Maxwell L. Neal

10.1201/9780429469961-1

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Citations (1)

Systematic screening of potential β-cell imaging agents

Biochemical and Biophysical Research Communications (2004)

Ian R. Sweet Daniel L. Cook Åke Lernmark Carla J. Greenbaum Angela R. Wallen

Biodistribution

Tolbutamide

BETA (programming language)

Imaging agent

10.1016/j.bbrc.2003.12.182

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Citations (105)

Pancreatic B cells are bursting, but how?

Trends in Neurosciences (1991)

Daniel L. Cook Leslie S. Satin William F. Hopkins

Bursting

Pancreatic Islets

10.1016/0166-2236(91)90033-q

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Citations (78)

Modeling stochastic gene expression: Implications for haploinsufficiency

Proceedings of the National Academy of Sciences (1998)

Daniel L. Cook Anthony N. Gerber Stephen J. Tapscott

There is increasing recognition that stochastic processes regulate highly predictable patterns of gene expression in developing organisms, but the implications of stochastic gene expression for understanding haploinsufficiency remain largely unexplored. We have used simulations of stochastic gene expression to illustrate that gene copy number and expression deactivation rates are important variables in achieving predictable outcomes. In gene expression systems with non-zero expression deactivation rates, diploid systems had a higher probability of uninterrupted gene expression than haploid systems and were more successful at maintaining gene product above a very low threshold. Systems with relatively rapid expression deactivation rates (unstable gene expression) had more predictable responses to a gradient of inducer than systems with slow or zero expression deactivation rates (stable gene expression), and diploid systems were more predictable than haploid, with or without dosage compensation. We suggest that null mutations of a single allele in a diploid organism could decrease the probability of gene expression and present the hypothesis that some haploinsufficiency syndromes might result from an increased susceptibility to stochastic delays of gene initiation or interruptions of gene expression.

Haploinsufficiency

Gene dosage

Null allele

10.1073/pnas.95.26.15641

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Citations (244)

Representing physiological processes and their participants with PhysioMaps

Journal of Biomedical Semantics (2013)

Daniel L. Cook Maxwell L. Neal Robert Hoehndorf Georgios V. Gkoutos John H. Gennari

As the number and size of biological knowledge resources for physiology grows, researchers need improved tools for searching and integrating knowledge and physiological models. Unfortunately, current resources-databases, simulation models, and knowledge bases, for example-are only occasionally and idiosyncratically explicit about the semantics of the biological entities and processes that they describe.We present a formal approach, based on the semantics of biophysics as represented in the Ontology of Physics for Biology, that divides physiological knowledge into three partitions: structural knowledge, process knowledge and biophysical knowledge. We then computationally integrate these partitions across multiple structural and biophysical domains as computable ontologies by which such knowledge can be archived, reused, and displayed. Our key result is the semi-automatic parsing of biosimulation model code into PhysioMaps that can be displayed and interrogated for qualitative responses to hypothetical perturbations.Strong, explicit semantics of biophysics can provide a formal, computational basis for integrating physiological knowledge in a manner that supports visualization of the physiological content of biosimulation models across spatial scales and biophysical domains.

10.1186/2041-1480-4-s1-s2

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Citations (12)

The oral hypoglycemie agent, U‐56324, inhibits the activity of ATP‐sensitive potassium channels in cell‐free membrane patches from cultured mouse pancreatic B‐cells

FEBS Letters (1990)

William F. Hopkins Sahba Fatherazi Daniel L. Cook

U‐56324, a hypoglycemic agent derived from nicotinic acid, inhibited the activity of ATP‐sensitive potassium channels in excised patches from mouse pancreatic B‐cells. The effect of U‐56324 on channel activity was reversible and concentration‐dependent while it had no effect on single channel conductance. The positional isomer, U‐59588, which has relatively little hypoglycemic activity, had no effect on channel properties. U‐56324, at the same concentrations, had no effect on calcium‐activated potassium channels. The basis for the potentially antidiabetic properties of U‐56324 may therefore be due to direct and specific inhibition of ATP‐sensitive potassium channels.

Calcium-activated potassium channel

10.1016/0014-5793(90)80818-4

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Citations (5)

Bridging biological ontologies and biosimulation: the ontology of physics for biology.

PubMed (2008)

Daniel L. Cook José L. V. Mejino Maxwell L. Neal John H. Gennari

We introduce and define the Ontology of Physics for Biology (OPB), a reference ontology of physical principles that bridges the gap between bioinformat-ics modeling of biological structures and the bio-simulation modeling of biological processes. Where-as modeling anatomical entities is relatively well-studied, representing the physics-based semantics of biosimulation and biological processes remains an open research challenge. The OPB bridges this semantic gap-linking the semantics of biosimulation mathematics to structural bio-ontologies. Our design of the OPB is driven both by theory and pragmatics: we have applied systems dynamics theory to build an ontology with pragmatic use for annotating biosimulation models.

Open Biomedical Ontologies

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Citations (34)