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Entity Linking for Biomedical Literature

Jin Guang Zheng, Daniel Howsmon, Boliang Zhang, Juergen Hahn, Deborah McGuinness, James Hendler, Heng Ji
2014 Proceedings of the ACM 8th International Workshop on Data and Text Mining in Bioinformatics - DTMBIO '14  
inference approach to link entities from unstructured full texts of biomedical literature to 300 ontologies.  ...  The Entity Linking (EL) task links entity mentions from an unstructured document to entities in a knowledge base.  ...  Conclusions We have developed an effective Entity Linking system to automatically identify and link prominent mentions in unstructured biomedical literature to ontologies.  ... 
doi:10.1145/2665970.2665974 dblp:conf/cikm/ZhengHZHMHJ14 fatcat:hrsnminpmfgunpwlz2eifjxxpy

Entity linking for biomedical literature

Jin G Zheng, Daniel Howsmon, Boliang Zhang, Juergen Hahn, Deborah McGuinness, James Hendler, Heng Ji
2015 BMC Medical Informatics and Decision Making  
inference approach to link entities from unstructured full texts of biomedical literature to 300 ontologies.  ...  The Entity Linking (EL) task links entity mentions from an unstructured document to entities in a knowledge base.  ...  Conclusions We have developed an effective Entity Linking system to automatically identify and link prominent mentions in unstructured biomedical literature to ontologies.  ... 
doi:10.1186/1472-6947-15-s1-s4 pmid:26045232 pmcid:PMC4460707 fatcat:e5pwxes7tvgofewecbxiufvlzi

MBlab: Molecular Biodiversity Laboratory [chapter]

Corrado Loglisci, Annalisa Appice, Michelangelo Ceci, Donato Malerba, Floriana Esposito
2011 Communications in Computer and Information Science  
Our contribution is the design of computational solutions for the analysis of biomedical documents and images.  ...  Technologies in available biomedical repositories do not yet provide adequate mechanisms to support the understanding and analysis of the stored content.  ...  , Feature Selection in Fig. 2 . 2 Mining Temporal Links from Biomedical Literature (left) -Pattern Discovery for Semantic Role Labeling in Biomedical Literature (right) M.  ... 
doi:10.1007/978-3-642-27302-5_18 fatcat:semakj3pm5d3xbn43rc672crti

LINKING BIOMEDICAL INFORMATION THROUGH TEXT MINING: SESSION INTRODUCTION

K. BRETONNEL COHEN, OLIVIER BODENREIDER, LYNETTE HIRSCHMAN
2005 Biocomputing 2006  
This session is focused on text mining applications that link information from the biomedical literature to the growing array of structured resources available to researchers, such as protein databases  ...  Many of the systems discussed in these earlier sessions focused on recognition of biomedical entities and relations in order to provide effective indexing into the literature.  ...  Taken together, these two tasks demonstrate that it is possible to link the literature to specific entities and to specific concepts.  ... 
doi:10.1142/9789812701626_0001 fatcat:idrwqvbmtrgwfbhbkneijgqaui

PosMed: A Biomedical Entity Prioritisation Tool Based on Statistical Inference over Literature and the Semantic Web

Norio Kobayashi, Yuko Makita, Manabu Ishii, Akihiro Matsushima, Yoshiki Mochizuki, Koji Doi, Koro Nishikata, David Gifford, Terue Takatsuki, Hiroshi Masuya, Tetsuro Toyoda
2013 Workshop on Semantic Web Applications and Tools for Life Sciences  
links over multiple biomedical documents.  ...  Positional MEDLINE (PosMed) is a web application that quickly prioritises biomedical entities such as genes and diseases based on statistical significance of associations between these and a user-specified  ...  However, because the task of generating semantic links for our biomedical knowledge is too expensive, and such knowledge is described by a vast amount of human-readable biomedical literature, this semantic  ... 
dblp:conf/swat4ls/KobayashiMIMMDNGTMT13 fatcat:bziatuqfizhwddqkh77rpeivx4

The CALBC RDF Triple Store: retrieval over large literature content [article]

Samuel Croset, Christoph Grabmüller, Chen Li, Silvestras Kavaliauskas, Dietrich Rebholz-Schuhmann
2010 arXiv   pre-print
Integration of the scientific literature into a biomedical research infrastructure requires the processing of the literature, identification of the contained named entities (NEs) and concepts, and to represent  ...  RDF Triple Store enables querying the scientific literature and bioinformatics resources at the same time for evidence of genetic causes, such as drug targets and disease involvement.  ...  The lexical resource serves as a complete term repository for the biomedical domain and enables disambiguation of entity types.  ... 
arXiv:1012.1650v1 fatcat:gmd6wycjyrblhbix7vnzuvvciq

Improving classification of low-resource COVID-19 literature by using Named Entity Recognition

Oscar Lithgow-Serrano, Joseph Cornelius, Vani Kanjirangat, Carlos-Francisco Méndez-Cruz, Fabio Rinaldi
2021 Genomics & Informatics  
We processed the literature with OntoGene's Biomedical Entity Recogniser (OGER) and used the resulting identified Named Entities (NE) and their links to major biological databases as extra input features  ...  During the 7th Biomedical Linked Annotation Hackathon (BLAH7) hackathon, we performed experiments to explore the use of named-entity-recognition (NER) to improve the classification.  ...  Acknowledgments We are grateful to the organizer of the Biomedical Linked Annotation Hackathon 2021 for the opportunity to work collaboratively on this project and share it with the other participants.  ... 
doi:10.5808/gi.21018 pmid:34638169 fatcat:73x63betlzdjhdqd5nwt4bnwt4

Biomedical Text Link Prediction for Drug Discovery: A Case Study with COVID-19

Kevin McCoy, Sateesh Gudapati, Lawrence He, Elaina Horlander, David Kartchner, Soham Kulkarni, Nidhi Mehra, Jayant Prakash, Helena Thenot, Sri Vivek Vanga, Abigail Wagner, Brandon White (+1 others)
2021 Pharmaceutics  
A link prediction model was developed using the complex heterogeneous biomedical knowledge graph, SemNet, to predict missing links in biomedical literature for drug discovery.  ...  The link prediction algorithm guided identification and ranking of repurposed drug candidates for SARS-CoV-2 primarily by text mining biomedical literature from previous coronaviruses, including SARS and  ...  However, similar text mining and artificial intelligence tools can be adapted to identify new links in the biomedical literature.  ... 
doi:10.3390/pharmaceutics13060794 pmid:34073456 pmcid:PMC8230210 fatcat:na32tnt62jcwxomlk6pger6sdq

MeDetect: Domain Entity Annotation in Biomedical References Using Linked Open Data

Li Tian, Weinan Zhang, Haofen Wang, Chenyang Wu, Yuan Ni, Feng Cao, Yong Yu
2012 International Semantic Web Conference  
In this paper, we propose a knowledge-incentive approach based on LOD for entity annotation in the biomedical field.  ...  The number of entities and the number of properties describing semantic relationships between entities within the linked data cloud are very large.  ...  We implement a prototype system MeDetect to demonstrate our approach for domain entity annotation for biomedical references.  ... 
dblp:conf/semweb/TianZWWNCY12 fatcat:uif7h4kmzvhclfdgrzxq5xwdsy

Darling: A Web Application for Detecting Disease-Related Biomedical Entity Associations with Literature Mining

Evangelos Karatzas, Fotis A. Baltoumas, Ioannis Kasionis, Despina Sanoudou, Aristides G. Eliopoulos, Theodosios Theodosiou, Ioannis Iliopoulos, Georgios A. Pavlopoulos
2022 Biomolecules  
Finding, exploring and filtering frequent sentence-based associations between a disease and a biomedical entity, co-mentioned in disease-related PubMed literature, is a challenge, as the volume of publications  ...  records, and generates an interactive biomedical entity association network.  ...  The ever-increasing amount of literature is posing numerous challenges for bioscientists, as parsing these texts and extracting associations among biomedical entities is neither easy nor trivial.  ... 
doi:10.3390/biom12040520 pmid:35454109 pmcid:PMC9028073 fatcat:xyygpexpebe65iaga3z2hddeay

Knowledge-based biomedical Data Science

Lawrence E. Hunter, Tobias Kuhn
2017 Data Science  
There are many ways in which a computational approach might act as if it knew something: for example, it might be able to answer a natural language question about a biomedical topic, or pass an exam; it  ...  After a brief survey of existing approaches to knowledge-based data science, this position paper argues that such research is ripe for expansion, and expanded application.  ...  Computational methods to identify semantically well-defined entities in the literature support further analysis that identifies links both among different documents in the literature (e.g.  ... 
doi:10.3233/ds-170001 pmid:30294517 pmcid:PMC6171523 fatcat:d5kjfs24nvdsne4mmzrdfb5wsq

Quantitative biomedical annotation using medical subject heading over-representation profiles (MeSHOPs)

Warren A Cheung, BF Ouellette, Wyeth W Wasserman
2012 BMC Bioinformatics  
Comparison of MeSHOPs allows entities to be related based on shared medical themes in their literature. A web interface is provided for generating and visualizing MeSHOPs.  ...  Distilling the essential biomedical themes for a topic of interest from the relevant literature is important to both understand the importance of related concepts and discover new relationships.  ...  Leon French, Paul Pavlidis and Raf Podowski for comments and discussion on the research and Joseph Yamada for help with the website. Funding  ... 
doi:10.1186/1471-2105-13-249 pmid:23017167 pmcid:PMC3564935 fatcat:kzqloymanvhihgtrd5swvp57em

MedMentions: A Large Biomedical Corpus Annotated with UMLS Concepts [article]

Sunil Mohan, Donghui Li
2019 arXiv   pre-print
To encourage research in Biomedical Named Entity Recognition and Linking, data splits for training and testing are included in the release, and a baseline model and its metrics for entity linking are also  ...  This paper presents the formal release of MedMentions, a new manually annotated resource for the recognition of biomedical concepts.  ...  Table 7 : 7 Entity linking metrics for the TaggerOne model on MedMentions ST21pv.  ... 
arXiv:1902.09476v1 fatcat:hcnfoaf4lnhf3jyjdm3emd5czu

Smart Searching System for Biomedical Information

Hong-Woo Chun, Chang-Hoo Jeong, Sa-Kwang Song, Yunsoo Choi, Sung-Pil Choi, Hanmin Jung
2012 International Conference on Biomedical Ontology  
Interactions between Biomedical entities provides meaningful information to detect and invent new drugs for diseases.  ...  This demonstration presents a smart searching system that provides various analysis tools for Biomedical interactions in whole PubMed.  ...  A semantic triple consists of two Biomedical entities and one verb, and two Biomedical entities are syntacticly a subject and an object for a verb appeared in a sentence.  ... 
dblp:conf/icbo/ChunJSCCJ12 fatcat:kou2fhd2endaph6tppnnc6yjlu

Knowledge-based Biomedical Data Science 2019 [article]

Tiffany J. Callahan, Ignacio J. Tripodi Computational Bioscience Program, Department of Pharmacology, University of Colorado Denver Anschutz Medical Campus
2019 arXiv   pre-print
Knowledge-based biomedical data science (KBDS) involves the design and implementation of computer systems that act as if they knew about biomedicine.  ...  Here we survey the progress in the last year in systems that use formally represented knowledge to address data science problems in both clinical and biological domains, as well as on approaches for creating  ...  entities, and entity types as nodes and citations, authorship, entity-linking, mention-mention, and entity-entity relations as edges.  ... 
arXiv:1910.06710v1 fatcat:kvz5k643zvhpdiq67blc2v33wi
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