
Lindley Darden
· Research Professor, PhilosophyVerifiedUniversity of Maryland, College Park · Classics
Active 1976–2023
About
Lindley Darden (PhD, University of Chicago) is a Professor of Philosophy and an affiliate in the Department of History and in the Behavior, Evolution, Ecology, and Systematics (BEES) Concentration Area, the Computational Biology, Bioinformatics and Genomics (CBBG) Concentration Area, and the Molecular & Cellular Biology (MOCB) of the Biological Sciences Graduate Program (BISI). She is a philosopher of science and a historian of biology. Her research focuses on reasoning in scientific change, specifically investigating the conceptual aspects of discovery of biological mechanisms from the nineteenth through the twenty-first century, such as evolutionary and genetic mechanisms. She views the development of scientific knowledge as progressing through iterative cycles of construction, evaluation, and revision of hypotheses. Her work also explores the implications of such discoveries for science education, medicine, and environmental policy. Her current research area involves computational methods for aiding the discovery of molecular biological and disease mechanisms.
Research topics
- Computer Science
- Information Retrieval
- Mathematics
- Physics
- Programming language
- Engineering
- Thermodynamics
- Data Mining
- World Wide Web
- Mechanical engineering
- Geography
- Environmental science
- Quantum mechanics
- Meteorology
Selected publications
PSA volume 89 issue 2 Cover and Front matter
Philosophy of Science · 2022
- Computer Science
- Computer Science
- Physics
An abstract is not available for this content so a preview has been provided. As you have access to this content, a full PDF is available via the ‘Save PDF’ action button.
The Quarterly Review of Biology · 2022-05-18
review1st authorCorrespondingPSA volume 88 issue 4 Cover and Front matter
Philosophy of Science · 2021
- Computer Science
- Computer Science
- Environmental science
An abstract is not available for this content so a preview has been provided. As you have access to this content, a full PDF is available via the ‘Save PDF’ action button.
The Quarterly Review of Biology · 2021-05-19
review1st authorCorrespondingPSA volume 88 issue 5 Cover and Front matter
Philosophy of Science · 2021-12-01 · 1 citations
articleOpen accessAn abstract is not available for this content so a preview has been provided. As you have access to this content, a full PDF is available via the ‘Save PDF’ action button.
MecCog: a knowledge representation framework for genetic disease mechanism
Bioinformatics · 2021 · 4 citations
- Computer Science
- Computer Science
- Information Retrieval
MOTIVATION: Experimental findings on genetic disease mechanisms are scattered throughout the literature and represented in many ways, including unstructured text, cartoons, pathway diagrams and network graphs. Integration and structuring of such mechanistic information greatly enhances its utility. RESULTS: MecCog is a graphical framework for building integrated representations (mechanism schemas) of mechanisms by which a genetic variant causes a disease phenotype. A MecCog mechanism schema displays the propagation of system perturbations across stages of biological organization, using graphical notations to symbolize perturbed entities and activities, hyperlinked evidence tagging, a mechanism ontology and depiction of knowledge gaps, ambiguities and uncertainties. The web platform enables a user to construct, store, publish, browse, query and comment on schemas. MecCog facilitates the identification of potential biomarkers, therapeutic intervention sites and critical future experiments. AVAILABILITY AND IMPLEMENTATION: The MecCog framework is freely available at http://www.meccog.org. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
PSA volume 87 issue 4 Cover and Front matter
Philosophy of Science · 2020-09-18
articleOpen accessAn abstract is not available for this content so a preview has been provided. As you have access to this content, a full PDF is available via the ‘Save PDF’ action button.
MecCog: A knowledge representation framework for genetic disease mechanism
bioRxiv (Cold Spring Harbor Laboratory) · 2020 · 1 citations
- Computer Science
- Computer Science
- Information Retrieval
ABSTRACT Motivation Experimental findings on genetic disease mechanisms are scattered throughout the literature and represented in many ways, including unstructured text, cartoons, pathway diagrams, and network graphs. Integration and structuring of such mechanistic information will greatly enhance its utility. Results MecCog is a graphical framework for building integrated representations (mechanism schemas) of mechanisms by which a genetic variant causes a disease phenotype. A MecCog mechanism schema displays the propagation of system perturbations across stages of biological organization, using graphical notations to symbolize perturbed entities and activities, hyperlinked evidence tagging, a mechanism ontology, and depiction of knowledge gaps, ambiguities, and uncertainties. The web platform enables a user to construct, store, publish, browse, query, and comment on schemas. MecCog facilitates the identification of potential biomarkers, therapeutic intervention sites, and critical future experiments. Availability and Implementation The MecCog framework is freely available at http://www.meccog.org . Contact jmoult@umd.edu Supplementary information Supplementary material is available at Bioinformatics online.
2018-09-11
book-chapter1st authorCorrespondingGenetics studies the problem of heredity, namely why offspring resemble their parents. The field emerged in 1900 with the rediscovery of the 1865 work of Gregor Mendel. William Bateson called the new field ‘genetics’ in 1905, and W. Johannsen used the term ‘gene’ in 1909. By analysing data about patterns of inheritance of characters, such as yellow and green peas, Mendelian geneticists infer the number and type of hypothetical genes. The major components of the theory of the gene, which proposed the model of genes as beads on a string, were in place by the 1920s. In the 1930s, the field of population genetics emerged from the synthesis of results from Mendelian genetics with Darwinian natural selection. Population geneticists study the distribution of genes in the gene pool of a population and changes caused by selection and other factors. The 1940s and 1950s saw the development of molecular genetics, which investigates problems about gene reproduction, mutation and function at the molecular level. Philosophical issues arise: the question about the evidence for the reality of hypothetical genes, and the status of Mendel’s laws, given that they are not universal generalizations. Debates have occurred about the nature of the relation between Mendelian and molecular genetics. Population genetics provides the perspective of the gene as the unit of selection in evolutionary theory. Molecular genetics and its accompanying technologies raise ethical issues about humans’ genetic information, such as the issue of privacy of information about one’s genome and the morality of changing a person’s genes. The nature–nurture debate involves the issue of genetic determinism, the extent to which genes control human traits and behaviour.
Harnessing formal concepts of biological mechanism to analyze human disease
PLoS Computational Biology · 2018-12-26 · 21 citations
editorialOpen access1st authorMechanism is a widely used concept in biology. In 2017, more than 10% of PubMed abstracts used the term. Therefore, searching for and reasoning about mechanisms is fundamental to much of biomedical research, but until now there has been almost no computational infrastructure for this purpose. Recent work in the philosophy of science has explored the central role that the search for mechanistic accounts of biological phenomena plays in biomedical research, providing a conceptual basis for representing and analyzing biological mechanism. The foundational categories for components of mechanisms-entities and activities-guide the development of general, abstract types of biological mechanism parts. Building on that analysis, we have developed a formal framework for describing and representing biological mechanism, MecCog, and applied it to describing mechanisms underlying human genetic disease. Mechanisms are depicted using a graphical notation. Key features are assignment of mechanism components to stages of biological organization and classes; visual representation of uncertainty, ignorance, and ambiguity; and tight integration with literature sources. The MecCog framework facilitates analysis of many aspects of disease mechanism, including the prioritization of future experiments, probing of gene-drug and gene-environment interactions, identification of possible new drug targets, personalized drug choice, analysis of nonlinear interactions between relevant genetic loci, and classification of diseases based on mechanism.
Frequent coauthors
- 124 shared
Michela Massimi
- 124 shared
John Dupré
University of Exeter
- 122 shared
John D. Norton
- 122 shared
Brian Skyrms
- 122 shared
Geoffrey Hellman
Cambridge University Press
- 120 shared
Helen E. Longino
University of Exeter
- 120 shared
Alex Rosenberg
Case Western Reserve University
- 120 shared
James Woodward
University of Pittsburgh
Education
Ph.D.
University of Chicago
Awards & honors
- Fellow of the American Association of the Advancement of Sci…
- Distinguished Scholar/Teacher of the University of Maryland…
- President of the International Society for History, Philosop…
- Visiting Professor at the Centre Cavailles for History and P…
- Clark-Way-Harrison Visiting Professor at Washington Universi…
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