Jingbo Xia


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An Overview of the Active Gene Annotation Corpus and the BioNLP OST 2019 AGAC Track Tasks
Yuxing Wang | Kaiyin Zhou | Mina Gachloo | Jingbo Xia
Proceedings of The 5th Workshop on BioNLP Open Shared Tasks

The active gene annotation corpus (AGAC) was developed to support knowledge discovery for drug repurposing. Based on the corpus, the AGAC track of the BioNLP Open Shared Tasks 2019 was organized, to facilitate cross-disciplinary collaboration across BioNLP and Pharmacoinformatics communities, for drug repurposing. The AGAC track consists of three subtasks: 1) named entity recognition, 2) thematic relation extraction, and 3) loss of function (LOF) / gain of function (GOF) topic classification. The AGAC track was participated by five teams, of which the performance are compared and analyzed. The the results revealed a substantial room for improvement in the design of the task, which we analyzed in terms of “imbalanced data”, “selective annotation” and “latent topic annotation”.


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CRF-LSTM Text Mining Method Unveiling the Pharmacological Mechanism of Off-target Side Effect of Anti-Multiple Myeloma Drugs
Kaiyin Zhou | Sheng Zhang | Xiangyu Meng | Qi Luo | Yuxing Wang | Ke Ding | Yukun Feng | Mo Chen | Kevin Cohen | Jingbo Xia
Proceedings of the BioNLP 2018 workshop

Sequence labeling of biomedical entities, e.g., side effects or phenotypes, was a long-term task in BioNLP and MedNLP communities. Thanks to effects made among these communities, adverse reaction NER has developed dramatically in recent years. As an illuminative application, to achieve knowledge discovery via the combination of the text mining result and bioinformatics idea shed lights on the pharmacological mechanism research.

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Three Dimensions of Reproducibility in Natural Language Processing
K. Bretonnel Cohen | Jingbo Xia | Pierre Zweigenbaum | Tiffany Callahan | Orin Hargraves | Foster Goss | Nancy Ide | Aurélie Névéol | Cyril Grouin | Lawrence E. Hunter
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)