Text mining for biology - the way forward: opinions from leading scientists - Wikidata - wikimedia - TriplyDB

Text mining for biology - the way forward: opinions from leading scientists

Text mining for biology - the way forward: opinions from leading scientists

http://www.wikidata.org/entity/Q28756933

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Open PHACTS: semantic interoperability for drug discovery Weakly supervised learning of biomedical information extraction from curated data Text mining for literature review and knowledge discovery in cancer risk assessment and research Bioinformatics for personal genome interpretation Integrative computational biology for cancer research Text mining and manual curation of chemical-gene-disease networks for the comparative toxicogenomics database (CTD)Enhancing navigation in biomedical databases by community voting and database-driven text classification Improved mutation tagging with gene identifiers applied to membrane protein stability prediction Layout-aware text extraction from full-text PDF of scientific articles.Mining locus tags in PubMed Central to improve microbial gene annotation.RLIMS-P 2.0: A Generalizable Rule-Based Information Extraction System for Literature Mining of Protein Phosphorylation Information Improving accuracy for identifying related PubMed queries by an integrated approach.Word add-in for ontology recognition: semantic enrichment of scientific literature.Concept-based query expansion for retrieving gene related publications from MEDLINE.Identifying overrepresented concepts in gene lists from literature: a statistical approach based on Poisson mixture model Assisting manual literature curation for protein-protein interactions using BioQRator Overview of the BioCreative III Workshop.Chapter 9: Analyses using disease ontologies The Lexicon Builder Web service: Building Custom Lexicons from two hundred Biomedical Ontologies.Chapter 15: disease gene prioritization.Review of biological network data and its applications.Open semantic annotation of scientific publications using DOMEO.The BioC-BioGRID corpus: full text articles annotated for curation of protein-protein and genetic interactions Towards precision medicine: advances in computational approaches for the analysis of human variants The Evidence and Conclusion Ontology (ECO): Supporting GO Annotations.Mapping annotations with textual evidence using an scLDA model.Integrative bioinformatics analysis of proteins associated with the cardiorenal syndrome A text mining approach to detect mentions of protein glycosylation in biomedical text.Caipirini: using gene sets to rank literature.

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P2860

Text mining for biology - the way forward: opinions from leading scientists

http://www.wikidata.org/entity/Q28756933

description

2008 nî lūn-bûn

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2008 թուականին հրատարակուած գիտական յօդուած

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2008 թվականին հրատարակված գիտական հոդված

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2008年の論文

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2008年論文

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2008年論文

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2008年論文

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2008年論文

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2008年論文

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2008年论文

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name

Text mining for biology - the way forward: opinions from leading scientists

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Text mining for biology - the way forward: opinions from leading scientists

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Text mining for biology--the way forward: opinions from leading scientists

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label

Text mining for biology - the way forward: opinions from leading scientists

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Text mining for biology - the way forward: opinions from leading scientists

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Text mining for biology--the way forward: opinions from leading scientists

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Text mining for biology - the way forward: opinions from leading scientists

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Text mining for biology - the way forward: opinions from leading scientists

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Text mining for biology--the way forward: opinions from leading scientists

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GB-2008-9-S2-S7

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Text mining for biology - the way forward: opinions from leading scientists

@en

P2093

Aaron Cohen

http://www.w3.org/2001/XMLSchema#string

Alfonso Valencia

http://www.w3.org/2001/XMLSchema#string

Frank Gannon

http://www.w3.org/2001/XMLSchema#string

Hagit Shatkay

http://www.w3.org/2001/XMLSchema#string

Les Grivell

http://www.w3.org/2001/XMLSchema#string

Seán I O'Donoghue

http://www.w3.org/2001/XMLSchema#string

Udo Hahn

http://www.w3.org/2001/XMLSchema#string

P2860

Will a biological database be different from a biological journal?

STRING 7--recent developments in the integration and prediction of protein interactions

PreBIND and Textomy--mining the biomedical literature for protein-protein interactions using a support vector machine

Facts from text--is text mining ready to deliver?

Which gene did you mean?

CAFASP-1: critical assessment of fully automated structure prediction methods

A gene network for navigating the literature

Key biology databases go wiki

SherLoc: high-accuracy prediction of protein subcellular localization by integrating text and protein sequence data

Assessing computational tools for the discovery of transcription factor binding sites

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gb-2008-9-s2-s7

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scholarly article

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10.1186/GB-2008-9-S2-S7

http://www.w3.org/2001/XMLSchema#string

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P433

Suppl 2

http://www.w3.org/2001/XMLSchema#string

P478

9 Suppl 2

http://www.w3.org/2001/XMLSchema#string

P50

Dietrich Rebholz-Schuhmann

Lars Juhl Jensen

Lynette Hirschman

Martin Krallinger

Christian Blaschke

Manuel C. Peitsch

Judith A. Blake

Casey M Bergman

P577

2008-01-01T00:00:00Z

http://www.w3.org/2001/XMLSchema#dateTime

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51434170

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1051866282

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18834498

http://www.w3.org/2001/XMLSchema#string

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2559991

http://www.w3.org/2001/XMLSchema#string