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NLM DIR Seminar Schedule
UPCOMING SEMINARS
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Nov. 4, 2025 Mehdi Bagheri Hamaneh
TBD -
Nov. 13, 2025 Leslie Ronish
TBD -
Nov. 18, 2025 Ryan Bell
TBD -
Nov. 24, 2025 Mario Flores
AI Pipeline for Characterization of the Tumor Microenvironment -
Nov. 25, 2025 Jing Wang
TBD
RECENT SEMINARS
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Oct. 28, 2025 Won Gyu Kim
TBD -
Oct. 21, 2025 Yifan Yang
TBD -
Oct. 14, 2025 Devlina Chakravarty
TBD -
Oct. 9, 2025 Ziynet Nesibe Kesimoglu
TBD -
Oct. 7, 2025 Lana Yeganova
From Algorithms to Insights: Bridging AI and Topic Discovery for Large-Scale Biomedical Literature Analysis.
Scheduled Seminars on May 10, 2022
Contact NLMDIRSeminarScheduling@mail.nih.gov with questions about this seminar.
Abstract:
Wastewater-based epidemiology relies on the high-throughput sequencing (HTS) of pathogens from wastewater, and it has been widely applied during the SARS-CoV-2 pandemic. This approach has some advantages over conventional clinical-based epidemiology since it is a low-cost, non-invasive, and anonymous sampling opportunity that captures viral diversity from multiple symptomatic or asymptomatic individuals. However, there are challenges to the data analysis since viral sequences obtained are derived from multiple genomes. In this research, we have developed a bioinformatic framework to address some of those challenges, process the HTS data and detect the most likely variant of concern present in each location based on their defining single nucleotide variants, insertions, and deletions. In addition, we developed an approach to look at viral diversity at the community level using principal component analysis.