Learn to use the XplorMed software, a web-based tool which allows researchers to access a text-mining algorithm. Researchers can improve upon standard PubMed searches by mining abstracts for word frequencies and combinations. Learn to use the XplorMed tool as a means of discovery of new relationships, or as a method to more quickly find the most relevant articles by understanding the context of words of interest.
You will learn:
This tutorial is a part of the tutorial group Text-related tools. You might find the other tutorials in the group interesting:
PubMatrix: PubMatrix, an on-line tool for multiplex literature mining of the PubMed database.
iHOP: Information Hyperlinked Over Proteins text mining resource
STRING: known and predicted protein-protein interactions
Textpresso: Text-mining the biological literature
Gene Ontology: Gene Ontology controlled vocabularies in biology
GoMiner: Ascribe biological significance to large lists of genes by annotating them with their corresponding GO categories
Controlled Vocabularies: Standardized term lists that can enhance interactions with biological databases
DAVID: A tool that analyzes large lists of genes to provide biological meaning
Entrez Overview: Overview of NCBI's Entrez Search Resource
PubMed: PubMed access to biomedical research literature
Literature and Text Mining : Tools which are related to scientific literature. Repositories, query tools, and mining resources are included.
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Recent BioMed Central research articles citing this resource
Barbosa-Silva Adriano et al., PESCADOR, a web-based tool to assist text-mining of biointeractions extracted from PubMed queries. BMC Bioinformatics (2011) doi:10.1186/1471-2105-12-435
Sy Mohameth-François et al., User centered and ontology based information retrieval system for life sciences Semantic Web Applications and Tools for Life Sciences (SWAT4LS) 2010 Semantic Web Applications and Tools for Life Sciences (SWAT4LS) 2010. BMC Bioinformatics (2011) doi:10.1186/1471-2105-13-S1-S4
Tudor O Catalina et al., eGIFT: Mining Gene Information from the Literature. BMC Bioinformatics (2010) doi:10.1186/1471-2105-11-418
Dietze Heiko et al., GoWeb: a semantic search engine for the life science web Semantic Web Applications and Tools for Life Sciences, 2008 Semantic Web Applications and Tools for Life Sciences, 2008. BMC Bioinformatics (2009) doi:10.1186/1471-2105-10-S10-S7
Spasić Irena et al., Facilitating the development of controlled vocabularies for metabolomics technologies with text mining Proceedings of the 10 th Bio-Ontologies Special Interest Group Workshop 2007. Ten years past and looking to the future 10 th Bio-Ontologies Special Interest Group Workshop 2007. Ten years past and looking to the future. BMC Bioinformatics (2008) doi:10.1186/1471-2105-9-S5-S5