Evaluation of text-mining systems for biology: overview of the Second BioCreative community challenge. - Wikidata - wikimedia - TriplyDB

Evaluation of text-mining systems for biology: overview of the Second BioCreative community challenge.

Evaluation of text-mining systems for biology: overview of the Second BioCreative community challenge.

http://www.wikidata.org/entity/Q34844839

about

Biomedical discovery acceleration, with applications to craniofacial development Event-based text mining for biology and functional genomics Biomedical relation extraction: from binary to complex Weakly supervised learning of biomedical information extraction from curated data ChemSpot: a hybrid system for chemical named entity recognition Overview of the ID, EPI and REL tasks of BioNLP Shared Task 2011 Micropublications: a semantic model for claims, evidence, arguments and annotations in biomedical communications Biocuration workflows and text mining: overview of the BioCreative 2012 Workshop Track II Mining the pharmacogenomics literature--a survey of the state of the art Automatic extraction of angiogenesis bioprocess from text Full text and figure display improves bioscience literature search neXtA5: accelerating annotation of articles via automated approaches in neXtProt Overview of the interactive task in BioCreative V Interpretation of the consequences of mutations in protein kinases: combined use of bioinformatics and text mining.Layout-aware text extraction from full-text PDF of scientific articles.Large-scale event extraction from literature with multi-level gene normalization.Jointly creating digital abstracts: dealing with synonymy and polysemy Word add-in for ontology recognition: semantic enrichment of scientific literature.eGIFT: mining gene information from the literature.Disambiguating the species of biomedical named entities using natural language parsers.Discriminative and informative features for biomolecular text mining with ensemble feature selection.The structural and content aspects of abstracts versus bodies of full text journal articles are different.Finding abbreviations in biomedical literature: three BioC-compatible modules and four BioC-formatted corpora.Assisting manual literature curation for protein-protein interactions using BioQRator Biblio-MetReS: a bibliometric network reconstruction application and server.pubmed2ensembl: a resource for mining the biological literature on genes Exploring species-based strategies for gene normalization.Benchmarking of the 2010 BioCreative Challenge III text-mining competition by the BioGRID and MINT interaction databases.Classifying protein-protein interaction articles using word and syntactic features.Overview of the BioCreative III Workshop.BioCreative III interactive task: an overview Soft tagging of overlapping high confidence gene mention variants for cross-species full-text gene normalization.Extracting semantically enriched events from biomedical literature.Using text to build semantic networks for pharmacogenomics.Literature curation of protein interactions: measuring agreement across major public databases Prioritizing PubMed articles for the Comparative Toxicogenomic Database utilizing semantic information.Mining biomarker information in biomedical literature.BioC: a minimalist approach to interoperability for biomedical text processing A CRF-based system for recognizing chemical entity mentions (CEMs) in biomedical literature Assessment of NER solutions against the first and second CALBC Silver Standard Corpus

P2860

Q21092567-7E8E84E6-FF05-4A27-8BE3-836AFD7E3711 Q26823739-52FF3A81-3F9B-4671-9A1F-D370871B4979 Q27013607-8095E592-A674-4097-B156-45BF67B68746 Q27319562-6224BBB8-4B8F-4E7F-BC6C-10201FA000ED Q27907444-B43E1AC3-302C-4AD3-BC06-3F604363872B Q28480715-79500E93-A529-4051-9850-601EF2049E49 Q28631063-C658D169-83EA-4A1B-9CF7-5C38AFEF8302 Q28711453-402DCD74-2D69-4966-B53E-8B4AE0174169 Q28728833-E7AE1B41-00BC-4A7E-8E8E-B1E8035ADA3B Q28744578-1F2DF685-AF90-443D-B628-40D0B6B5C221 Q28752580-DEFDF422-B697-4A03-BD02-220BDADBA79D Q28831410-FF2BBB85-F9DB-40ED-A277-A192B22E710F Q30002351-26659058-7F78-4B8E-A598-1094567CD7AE Q30422192-844D3F60-0C0F-4890-9A7C-971738AB9007 Q30485494-2ABE49E6-1B9B-401D-A260-BBA7E6CDDE73 Q30486109-57780326-E125-4CA5-B1C0-9D9098D273A0 Q30530773-449645A1-A84A-4448-B3C4-838BB1F876F6 Q33533996-A1AEDB41-5768-41DF-823E-F2D3FF44DE05 Q33652931-079FB055-A4A5-4C7D-AED9-B720A558C08E Q33686341-115496D9-7B23-447C-B174-454C23AB8036 Q33686663-AF9C3F98-03E3-46F7-B70D-57A5C4DE80B2 Q33709943-FDA00F81-EEF1-4259-A71D-59768BBDFC3E Q33733629-B49E48DA-C2CB-40B9-8215-6D323A2A1861 Q33928865-96CC17F1-FEE1-4C1D-B96B-BACE41A97792 Q34041057-613438A3-FBE3-48DF-A9EF-4D9D4FE7B7A5 Q34042833-7B5B812A-C65D-49E3-BF64-6959C4A4DAEE Q34090329-D54CC57D-65D7-45C2-B75E-5928266C4978 Q34094010-186ACBB8-C315-4535-90F5-66515B27AB96 Q34094071-734C50E4-4C15-45BC-A4FD-E4201FD8F5E7 Q34094362-0375D50B-2361-4E5B-AB02-6BB11FEF7E74 Q34094645-3248532B-76D9-42D3-9C00-52B6B5C602E2 Q34094730-E850CBE3-3F5F-40B9-93FE-24AD5F9FB3D9 Q34278985-19F9BB6D-B5FC-4BB1-B705-32EADA0110A3 Q34349222-D57BC421-21FC-4D3A-AFE2-A2502B892B86 Q34447723-89925211-ABDB-43C7-8E0C-634F6FAF68B0 Q34480409-EA605FBD-BE44-4CD5-9C2F-EC878BAD7A37 Q34515256-4A2E4BFD-23E7-4FD1-8EAD-781CE190364C Q34992074-4D02BB5F-B59C-40E5-95CB-9F15FCDA9BF0 Q35092873-B3D2EFE7-C5A5-4A1A-8BCE-520F64963615 Q35617469-AC8302EB-B4AC-412D-BDE6-55A7D3591D50

P2860

Evaluation of text-mining systems for biology: overview of the Second BioCreative community challenge.

http://www.wikidata.org/entity/Q34844839

description

2008 nî lūn-bûn

@nan

2008 թուականի Սեպտեմբերին հրատարակուած գիտական յօդուած

@hyw

2008 թվականի սեպտեմբերին հրատարակված գիտական հոդված

@hy

2008年の論文

@ja

2008年論文

@yue

2008年論文

@zh-hant

2008年論文

@zh-hk

2008年論文

@zh-mo

2008年論文

@zh-tw

2008年论文

@wuu

name

Evaluation of text-mining syst ...... oCreative community challenge.

@ast

Evaluation of text-mining syst ...... oCreative community challenge.

@en

Evaluation of text-mining syst ...... oCreative community challenge.

@nl

type

label

Evaluation of text-mining syst ...... oCreative community challenge.

@ast

Evaluation of text-mining syst ...... oCreative community challenge.

@en

Evaluation of text-mining syst ...... oCreative community challenge.

@nl

prefLabel

Evaluation of text-mining syst ...... oCreative community challenge.

@ast

Evaluation of text-mining syst ...... oCreative community challenge.

@en

Evaluation of text-mining syst ...... oCreative community challenge.

@nl

P1433

Q34844839-9CB68331-18B6-462C-94D7-46486B836297

P1476

Q34844839-9EBC3B69-A16E-4E11-9C77-00F900558019

P2093

Q34844839-079ED076-A5D9-4F61-AA6A-0D09F3363142

Q34844839-A6B1B908-74D2-45A9-80CA-64735F46F13A

Q34844839-BB095DAC-725A-4F3D-9AD4-457EAB41036B

Q34844839-CED927BA-E46D-4031-AA87-B6E9E0CE2D9C

Q34844839-D775D458-EE97-4966-8071-46757FBB1178

Q34844839-F163A2FB-C6BC-453A-A2B5-963F652033C5

P2860

Q34844839-24D63E39-6FBE-4338-9C38-523F3C76DFBD

Q34844839-3404E92B-33A5-46E7-9995-18601AB445F0

Q34844839-4E9FCC0E-A6B8-4732-B4D1-5AA7DB321A34

Q34844839-568DD269-D7B4-4735-8800-3A4AD23ABB2E

Q34844839-628D15AC-5EC3-4397-8CF2-23C6EB05ECD2

Q34844839-6E384821-B73E-4153-9379-9807CE0363EB

Q34844839-833DB417-7707-4B87-B108-2C166266BE79

Q34844839-8E3B68B1-C49B-4979-B3D3-1CCC8347568D

Q34844839-90516053-B9EC-4EF3-AF8A-FEDFBB1C4D0E

Q34844839-A09A95F3-8F6B-4FE0-A13A-C628F2C8B6F3

P2888

Q34844839-BA629E9F-D561-439E-BEEE-615505C744FF

P304

Q34844839-21CD6732-E95D-45FC-9206-CF12E266E151

P31

Q34844839-C0DB9FAC-2D3E-4153-9B7A-BC0E9574E122

P356

Q34844839-DBF32A2B-34EE-43E8-916B-7244ECEB6229

P478

Q34844839-F8E3B4CA-3A73-48DB-A23E-B29CA4F68571

P50

Q34844839-21EE59F4-727F-4181-8059-F070068CA412

Q34844839-C6FA925D-4790-439B-84FE-87655F8931DA

P577

Q34844839-AD345AF1-EBE6-4793-B25C-D0D636C6D9EC

P5875

Q34844839-09533B24-C24B-44FB-8DF7-D69C41A07D14

P6179

Q34844839-56778CED-6EA6-4724-9BFD-D80C85164CD6

P698

Q34844839-C6DC8CF0-37F8-4307-AD81-15D880BAC41A

P932

Q34844839-341B5DF2-8F12-444D-8C45-A9FAD86AC359

P356

GB-2008-9-S2-S1

P1433

P1476

Evaluation of text-mining syst ...... oCreative community challenge.

@en

P2093

Alexander Morgan

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

John Wilbur

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

Larry Smith

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

Lorraine Tanabe

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

Lynette Hirschman

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

Martin Krallinger

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

P2860

Overview of BioCreAtIvE: critical assessment of information extraction for biology

EGASP: the human ENCODE Genome Annotation Assessment Project

Protein alchemy: changing beta-sheet into alpha-helix

Overview of BioCreAtIvE task 1B: normalized gene lists

Evaluation of BioCreAtIvE assessment of task 2

BioCreAtIvE task 1A: gene mention finding evaluation

Assessment of predictions submitted for the CASP7 function prediction category.

Evaluation of text data mining for database curation: lessons learned from the KDD Challenge Cup.

Evaluation and comparison of mammalian subcellular localization prediction methods.

MINT and IntAct contribute to the Second BioCreative challenge: serving the text-mining community with high quality molecular interaction data.

P2888

gb-2008-9-s2-s1

P304

S1

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

P31

scholarly article

P356

10.1186/GB-2008-9-S2-S1

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

P478

9 Suppl 2

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

P50

Alfonso Valencia

Florian Leitner

P577

2008-09-01T00:00:00Z

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

P5875

51434159

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

P6179

1013181865

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

P698

18834487

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

P932

2559980

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