NLM IRP Seminar Schedule
UPCOMING SEMINARS
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May 7, 2024 OPEN
TBD -
May 9, 2024 Pascal Mutz
The Riboviria protein structurome expands virus protein annotation and highlights protein relations -
May 14, 2024 Stanley Liang
TBD -
May 16, 2024 Diego Salazar
TBD -
May 21, 2024 Ziynet Kesimoglu
TBD
RECENT SEMINARS
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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 -
April 11, 2024 Sergey Shmakov
Comprehensive survey of the TnpB RNA-guided nucleases
Scheduled Seminars on Feb. 8, 2022
Contact NLM_IRP_Seminar_Scheduling@mail.nih.gov with questions about this seminar.
Abstract:
Previous studies on biomedical relation extraction (RE) typically focus on extracting binary relations between two entities from a single sentence. However, complex inter-sentence relations involving multiple entity pairs, such as drug-protein and protein-disease, are commonly seen in the biomedical literature. In this talk, I will first introduce the characteristics of sentence-level RE and use the BioCreative VII DrugProt task to showcase a general text classification framework for sentence-level RE. The second part will introduce a new document-level dataset called BioRED, which covers six concept types (cell line, chemical, disease, gene, species, and variant) and eight relation pairs (e.g., chemical-disease, chemical-gene, chemical-chemical) in 600 MEDLINE abstracts. In total, BioRED consists of 20,000 entity and 6,000 relation annotations. The BioRED dataset is currently being used for developing and evaluating state-of-the-art relation extraction methods at the LitCoin natural language processing (NLP) challenge.