NLM DIR Seminar Schedule
UPCOMING SEMINARS
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April 8, 2025 Jaya Srivastava
Leveraging a deep learning model to assess the impact of regulatory variants on traits and diseases -
April 15, 2025 Pascal Mutz
TBD -
April 18, 2025 Valentina Boeva, Department of Computer Science, ETH Zurich
Decoding tumor heterogeneity: computational methods for scRNA-seq and spatial omics -
April 22, 2025 Stanley Liang
TBD -
April 29, 2025 MG Hirsch
TBD
RECENT SEMINARS
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April 1, 2025 Roman Kogay
Horizontal transfer of bacterial operons into eukaryote genomes -
March 25, 2025 Yifan Yang
Adversarial Manipulation and Data Memorization in Large Language Models for Medicine -
March 11, 2025 Sofya Garushyants
Tmn – bacterial anti-phage defense system -
March 4, 2025 Sanasar Babajanyan
Evolution of antivirus defense in prokaryotes depending on the environmental virus load -
Feb. 25, 2025 Zhizheng Wang
GeneAgent: Self-verification Language Agent for Gene Set Analysis using Domain Databases
Scheduled Seminars on Jan. 18, 2022
Contact NLMDIRSeminarScheduling@mail.nih.gov with questions about this seminar.
Abstract:
Thermodynamic selection is an indirect competition between agents feeding on the same energy resource and obeying the laws of thermodynamics. We examine scenarios of this selection, where the agent is modeled as a heat-engine coupled to two thermal baths and extracting work from the high-temperature bath. The agents can apply different work-extracting strategies, e.g. the maximum power or the maximum efficiency. They can also have a fixed structure or be adaptive. Depending on whether the resource (i.e. the high-temperature bath) is infinite or finite, the fitness of the agent relates to the work-power or the total extracted work. These two selection scenarios lead to increasing or decreasing efficiencies of the work-extraction, respectively. We also show that certain general concepts of game-theory and ecology--the prisoner's dilemma and the maximal power principle--emerge from the thermodynamics of competing agents. We emphasize the role of adaptation in developing efficient work-extraction mechanisms.