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LION LBD: a literature-based discovery system for cancer biology
MOTIVATION: The overwhelming size and rapid growth of the biomedical literature make it impossible for scientists to read all studies related to their work, potentially leading to missed connections and wasted time and resources. Literature-based discovery (LBD) aims to alleviate these issues by ide...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6499247/ https://www.ncbi.nlm.nih.gov/pubmed/30304355 http://dx.doi.org/10.1093/bioinformatics/bty845 |
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author | Pyysalo, Sampo Baker, Simon Ali, Imran Haselwimmer, Stefan Shah, Tejas Young, Andrew Guo, Yufan Högberg, Johan Stenius, Ulla Narita, Masashi Korhonen, Anna |
author_facet | Pyysalo, Sampo Baker, Simon Ali, Imran Haselwimmer, Stefan Shah, Tejas Young, Andrew Guo, Yufan Högberg, Johan Stenius, Ulla Narita, Masashi Korhonen, Anna |
author_sort | Pyysalo, Sampo |
collection | PubMed |
description | MOTIVATION: The overwhelming size and rapid growth of the biomedical literature make it impossible for scientists to read all studies related to their work, potentially leading to missed connections and wasted time and resources. Literature-based discovery (LBD) aims to alleviate these issues by identifying implicit links between disjoint parts of the literature. While LBD has been studied in depth since its introduction three decades ago, there has been limited work making use of recent advances in biomedical text processing methods in LBD. RESULTS: We present LION LBD, a literature-based discovery system that enables researchers to navigate published information and supports hypothesis generation and testing. The system is built with a particular focus on the molecular biology of cancer using state-of-the-art machine learning and natural language processing methods, including named entity recognition and grounding to domain ontologies covering a wide range of entity types and a novel approach to detecting references to the hallmarks of cancer in text. LION LBD implements a broad selection of co-occurrence based metrics for analyzing the strength of entity associations, and its design allows real-time search to discover indirect associations between entities in a database of tens of millions of publications while preserving the ability of users to explore each mention in its original context in the literature. Evaluations of the system demonstrate its ability to identify undiscovered links and rank relevant concepts highly among potential connections. AVAILABILITY AND IMPLEMENTATION: The LION LBD system is available via a web-based user interface and a programmable API, and all components of the system are made available under open licenses from the project home page http://lbd.lionproject.net. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-6499247 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-64992472019-05-07 LION LBD: a literature-based discovery system for cancer biology Pyysalo, Sampo Baker, Simon Ali, Imran Haselwimmer, Stefan Shah, Tejas Young, Andrew Guo, Yufan Högberg, Johan Stenius, Ulla Narita, Masashi Korhonen, Anna Bioinformatics Original Papers MOTIVATION: The overwhelming size and rapid growth of the biomedical literature make it impossible for scientists to read all studies related to their work, potentially leading to missed connections and wasted time and resources. Literature-based discovery (LBD) aims to alleviate these issues by identifying implicit links between disjoint parts of the literature. While LBD has been studied in depth since its introduction three decades ago, there has been limited work making use of recent advances in biomedical text processing methods in LBD. RESULTS: We present LION LBD, a literature-based discovery system that enables researchers to navigate published information and supports hypothesis generation and testing. The system is built with a particular focus on the molecular biology of cancer using state-of-the-art machine learning and natural language processing methods, including named entity recognition and grounding to domain ontologies covering a wide range of entity types and a novel approach to detecting references to the hallmarks of cancer in text. LION LBD implements a broad selection of co-occurrence based metrics for analyzing the strength of entity associations, and its design allows real-time search to discover indirect associations between entities in a database of tens of millions of publications while preserving the ability of users to explore each mention in its original context in the literature. Evaluations of the system demonstrate its ability to identify undiscovered links and rank relevant concepts highly among potential connections. AVAILABILITY AND IMPLEMENTATION: The LION LBD system is available via a web-based user interface and a programmable API, and all components of the system are made available under open licenses from the project home page http://lbd.lionproject.net. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2019-05-01 2018-10-09 /pmc/articles/PMC6499247/ /pubmed/30304355 http://dx.doi.org/10.1093/bioinformatics/bty845 Text en © The Author(s) 2018. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Papers Pyysalo, Sampo Baker, Simon Ali, Imran Haselwimmer, Stefan Shah, Tejas Young, Andrew Guo, Yufan Högberg, Johan Stenius, Ulla Narita, Masashi Korhonen, Anna LION LBD: a literature-based discovery system for cancer biology |
title | LION LBD: a literature-based discovery system for cancer biology |
title_full | LION LBD: a literature-based discovery system for cancer biology |
title_fullStr | LION LBD: a literature-based discovery system for cancer biology |
title_full_unstemmed | LION LBD: a literature-based discovery system for cancer biology |
title_short | LION LBD: a literature-based discovery system for cancer biology |
title_sort | lion lbd: a literature-based discovery system for cancer biology |
topic | Original Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6499247/ https://www.ncbi.nlm.nih.gov/pubmed/30304355 http://dx.doi.org/10.1093/bioinformatics/bty845 |
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