Literature DB >> 11928487

Mining MEDLINE: abstracts, sentences, or phrases?

J Ding1, D Berleant, D Nettleton, E Wurtele.   

Abstract

A growing body of works address automated mining of biochemical knowledge from digital repositories of scientific literature, such as MEDLINE. Some of these works use abstracts as the unit of text from which to extract facts. Others use sentences for this purpose, while still others use phrases. Here we compare abstracts, sentences, and phrases in MEDLINE using the standard information retrieval performance measures of recall, precision, and effectiveness, for the task of mining interactions among biochemical terms based on term co-occurrence. Results show statistically significant differences that can impact the choice of text unit.

Mesh:

Year:  2002        PMID: 11928487     DOI: 10.1142/9789812799623_0031

Source DB:  PubMed          Journal:  Pac Symp Biocomput        ISSN: 2335-6928


  44 in total

1.  NLP-based information extraction for managing the molecular biology literature.

Authors:  Bisharah Libbus; Thomas C Rindflesch
Journal:  Proc AMIA Symp       Date:  2002

2.  Bridging semantics and syntax with graph algorithms-state-of-the-art of extracting biomedical relations.

Authors:  Yuan Luo; Özlem Uzuner; Peter Szolovits
Journal:  Brief Bioinform       Date:  2016-02-05       Impact factor: 11.622

Review 3.  A Survey of Data Mining and Deep Learning in Bioinformatics.

Authors:  Kun Lan; Dan-Tong Wang; Simon Fong; Lian-Sheng Liu; Kelvin K L Wong; Nilanjan Dey
Journal:  J Med Syst       Date:  2018-06-28       Impact factor: 4.460

4.  Learning Inter-Sentence, Disorder-Centric, Biomedical Relationships from Medical Literature.

Authors:  Anton H van der Vegt; Guido Zuccon; Bevan Koopman
Journal:  AMIA Annu Symp Proc       Date:  2020-03-04

5.  A comprehensive benchmark of kernel methods to extract protein-protein interactions from literature.

Authors:  Domonkos Tikk; Philippe Thomas; Peter Palaga; Jörg Hakenberg; Ulf Leser
Journal:  PLoS Comput Biol       Date:  2010-07-01       Impact factor: 4.475

6.  ISDB: Interaction Sentence Database.

Authors:  Michael A Bauer; Robert E Belford; Jing Ding; Daniel Berleant
Journal:  BMC Res Notes       Date:  2010-05-03

7.  Identification and analysis of co-occurrence networks with NetCutter.

Authors:  Heiko Müller; Francesco Mancuso
Journal:  PLoS One       Date:  2008-09-10       Impact factor: 3.240

8.  Construction of an annotated corpus to support biomedical information extraction.

Authors:  Paul Thompson; Syed A Iqbal; John McNaught; Sophia Ananiadou
Journal:  BMC Bioinformatics       Date:  2009-10-23       Impact factor: 3.169

9.  A realistic assessment of methods for extracting gene/protein interactions from free text.

Authors:  Renata Kabiljo; Andrew B Clegg; Adrian J Shepherd
Journal:  BMC Bioinformatics       Date:  2009-07-28       Impact factor: 3.169

10.  Linguistic feature analysis for protein interaction extraction.

Authors:  Timur Fayruzov; Martine De Cock; Chris Cornelis; Veronique Hoste
Journal:  BMC Bioinformatics       Date:  2009-11-12       Impact factor: 3.169

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