ISMB/ECCB 2019 - Special Sessions
Monday, July 22 10:15 a.m. - 6:00 pm
Robert Leaman, National Library of Medicine, National Center for Biotechnology Information, United States
Lars Jensen, University of Copenhagen, Novo Nordisk Foundation Center for Protein Research, Denmark
Cecilia Arighi, University of Delaware, Delaware Biotechnology Institute, United States
Zhiyong Lu, National Library of Medicine, National Center for Biotechnology Information, United States
Text mining methods for biology and healthcare have matured significantly in recent years. The quality of text mining systems has improved considerably not only in terms of accuracy, but also in interoperability, scalability, and a lower barrier of entry for non-specialists. Much of current research in text mining is published as open source software, making state-of-the-art tools (e.g. PubTator) widely available. Moreover, the use of text mining methods to support other research in the biological and medical sciences has been increasing. Numerous databases use text mining — either to speed up curation (e.g. UniProt) or for directly integrating evidence (e.g. STRING) — and literature databases (e.g. PubMed) have a long history of using text mining techniques to improve search capabilities.
The previous BioLINK special interest group (SIG) successfully organized meetings at ISMB and collaborations with other SIGs for many years. Since the time that the BioLINK SIG was discontinued, however, biomedical text mining has advanced significantly. The use of textual genres outside of published literature has greatly expanded, including patents, drug labels, social media and, most notably, clinical records. At the same time, a number of new computational technologies have emerged that have led to improved accuracy, increased scalability and expanded the number of applications and use cases (e.g. accelerating drug discovery). Interest in text mining at ISMB has continued: ISMB has consistently published text mining research, even without a specific community of special interest (COSI).
Given the lack of a specific community of special interest (COSI), we propose a special session to be held at ISMB 2019 on Text Mining for Biology and Healthcare, to meet the increasing need/interests of computational biologists in such areas, and to bring together researchers that create text mining tools with researchers who currently use or are interested in using text mining tools to make new discoveries. The goal of the session is therefore to link at least two distinct audiences: those who are not text mining specialists, but who could use the results in their work (e.g., bioinformaticians and computational biologists), and biomedical text mining specialists who develop new methodologies to advance the state of the art. We therefore propose focusing on text mining use cases (concrete problems with scientific importance) in addition to methodology development.