NLM IRP Seminar Schedule
UPCOMING SEMINARS
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May 14, 2024 Stanley Liang
Knowledge-driven Latent Diffusion For COVID-19 Pneumonia Radiology Pattern Synthesis -
May 21, 2024 Ziynet Kesimoglu
TBD -
May 23, 2024 Leslie Ronish
TBD -
May 28, 2024 Harutyun Saakyan
TBD -
May 30, 2024 Deepak Gupta
TBD
RECENT SEMINARS
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May 9, 2024 Pascal Mutz
The Riboviria protein structurome expands virus protein annotation and highlights protein relations -
May 2, 2024 OPEN
TBD -
April 30, 2024 Wenya Rowe
The conformal central charge of the spin-1/2 XX model derived from long-chain asymptotics -
April 25, 2024 Ermin Hodzic
Condition-Aware Cell Type Deconvolution of Bulk Tissues -
April 16, 2024 Jaya Srivastava
Regulatory plasticity of the human genome
Scheduled Seminars on March 1, 2023
Contact NLM_IRP_Seminar_Scheduling@mail.nih.gov with questions about this seminar.
Abstract:
Understanding biological networks and how alterations in those networks drive human disease is key to novel treatment strategies. I will give an overview of several methods and resources focused on understanding complex diseases through the lens of network biology. A major topic will be the development and application of the Pathway Commons (PC) molecular interaction resource. PC is based on community-generated formats and ontologies for the representation of biological data (i.e., the Biological Pathway Exchange format and the Systems Biology Graphical Notation). More recent PC development has broadened into areas of crowdsourcing and natural language processing in order to scale with the increase of scientific publishing. I will also cover the use of PC in the creation of drug resistance prediction algorithms and the interpretation of experimental results in the context of biological networks. Additionally, I will discuss work done in collaboration with the National Cancer Institute (NCI) and National Center for Advancing Translational Sciences (NCATS) to structure large data collections. This work helps bridge experimental model systems and patient data for the development of predictive drug response models and the identification of biomarkers and biological process signatures relevant to treatment decisions.