Optimising chemical named entity recognition with pre-processing analytics, knowledge-rich features and heuristics

Journal of Cheminformatics

Volumn 7, Issue , 2015, Pages

  Batista Navarro, Riza ^a,b   Rak, Rafal ^a   Ananiadou, Sophia ^a  

^a UNIVERSITY OF MANCHESTER   (United Kingdom)

^b UNIVERSITY OF THE PHILIPPINES   (Philippines)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84946131442     PISSN: None     EISSN: 17582946     Source Type: Journal    
DOI: 10.1186/1758-2946-7-S1-S6     Document Type: Article

References (49)

1. Davis AP, Wiegers TC, Johnson RJ, Lay JM, Lennon-Hopkins K, Saraceni-Richards C, Sciaky D, Murphy CG, Mattingly CJ: Text mining effectively scores and ranks the literature for improving chemical-gene-disease curation at the comparative toxicogenomics database. PLoS ONE 2013, 8(4):58201.
2. Kolářik C, Hofmann-Apitius M: Linking Chemical and Biological Information with Natural Language Processing. In Chemical Information Mining Banville DL 2009, Chap 7:123-150.
3. Segura-Bedmar I, Martínez P, de Pablo-Sánchez C: Extracting drug-drug interactions from biomedical texts. BMC Bioinformatics 2010, 11(S-5):9.
4. Deftereos SN, Andronis C, Friedla EJ, Persidis A, Persidis A: Drug repurposing and adverse event prediction using high-throughput literature analysis. Wiley interdisciplinary reviews. Systems biology and medicine 2011, 3(3):323-34.
5. Li C, Liakata M, Rebholz-Schuhmann D: Biological network extraction from scientific literature: state of the art and challenges. Briefings in Bioinformatics 2013.
6. Banville DL: Mining chemical structural information from the drug literature. Drug Discovery Today 2006, 11(1):35-42.
7. Vazquez M, Krallinger M, Leitner F, Valencia A: Text mining for drugs and chemical compounds: Methods, tools and applications. Molecular Informatics 2011, 30(6-7):506-519.
8. Gurulingappa H, Mudi A, Toldo L, Hofmann-Apitius M, Bhate J: Challenges in mining the literature for chemical information. RSC Adv 2013, 16194-16211.
9. Grego T, Pesquita C, Bastos HP, Couto FM: Chemical Entity Recognition and Resolution to ChEBI. ISRN Bioinformatics 2012, 2012:9.
10. Corbett P, Batchelor C, Teufel S: Annotation of chemical named entities. Proceedings of the Workshop on BioNLP 2007: Biological, Translational, and Clinical Language Processing. BioNLP '07 Association for Computational Linguistics, Stroudsburg, PA, USA; 2007, 57-64.
11. Chemistry Using Text Annotations. [http://nactem.ac.uk/cheta], Accessed: October 2013.
12. Rebholz-Schuhmann D, Yepes J, Jose A, Van Mulligen EM, Kang N, Kors J, Milward D, Corbett P, Buyko E, Beisswanger E, Hahn U: CALBC silver standard corpus. Journal of Bioinformatics and Computational Biology 2010, 8(1):163-79.
13. Kolářik C, Klinger R, Friedrich CM, Hofmann-Apitius M, Fluck J: Chemical names: Terminological resources and corpora annotation. Proceedings of the Workshop on Building and Evaluating Resources for Biomedical Text Mining. LREC 2008, 51-58.
14. Fraunhofer SCAI Corpora for Chemical Entity Recognition. [http://www.scai.fraunhofer.de/chem-corpora.html], Accessed: October 2013.
15. Corbett P, Copestake A: Cascaded classifiers for confidence-based chemical named entity recognition. BMC Bioinformatics 2008, 9(Suppl 11):4.
16. Rocktäschel T, Weidlich M, Leser U: ChemSpot: a hybrid system for chemical named entity recognition. Bioinformatics 2012, 28(12):1633-1640.
17. Hettne KM, Stierum RH, Schuemie MJ, Hendriksen PJM, Schijvenaars BJA, van Mulligen EM, Kleinjans J, Kors JA: A dictionary to identify small molecules and drugs in free text. Bioinformatics 2009, 25(22):2983-2991.
18. Lafferty JD, McCallum A, Pereira FCN: Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data. Proceedings of the Eighteenth International Conference on Machine Learning. ICML '01 Morgan Kaufmann Publishers Inc., San Francisco, CA, USA; 2001, 282-289.
19. Krallinger M, Leitner F, Rabal O, Vazquez M, Oyarzabal J, Valencia A: CHEMDNER: The drugs and chemical names extraction challenge. J Cheminform 2015, 7(Suppl 1):S1.
20. Krallinger M, Rabal O, Leitner F, Vazquez M, Salgado D, Lu Z, Leaman R, Lu Y, Ji D, Lowe DM, Sayle RA, Batista-Navarro RT, Rak R, Huber T, Rocktaschel T, Matos S, Campos D, Tang B, Xu H, Munkhdalai T, Ryu KH, Ramanan SV, Nathan S, Zitnik S, Bajec M, Weber L, Irmer M, Akhondi SA, Kors JA, Xu S, An X, Sikdar UK, Ekbal A, Yoshioka M, Dieb TM, Choi M, Verspoor K, Khabsa M, Giles CL, Liu H, Ravikumar KE, Lamurias A, Couto FM, Dai H, Tsai RT, Ata C, Can T, Usie A, Alves R, Segura-Bedmar I, Martinez P, Oryzabal J, Valencia A: The CHEMDNER corpus of chemicals and drugs and its annotation principles. J Cheminform 2015, 7(Suppl 1):S2.
21. Rak R, Batista-Navarro RT, Carter J, Rowley A, Ananiadou S: Processing biological literature with customizable web services supporting interoperable formats. Database 2014, 2014:064.
22. Batista-Navarro RTB, Rak R, Ananiadou S: Chemistry-specific features and heuristics for developing a CRF-based chemical named entity recogniser. Proceedings of the Fourth BioCreative Challenge Evaluation Workshop 2013, 2:55-59.
23. Nobata C, Dobson PD, Iqbal SA, Mendes P, Tsujii J, Kell DB, Ananiadou S: Mining metabolites: extracting the yeast metabolome from the literature. Metabolomics 2011, 7(1):94-101.
24. OSCAR4. [https://bitbucket.org/wwmm/oscar4/wiki/Home], Accessed: October 2013.
25. ChemSpot. [https://github.com/rockt/ChemSpot], Accessed: October 2013.
26. Hastings J, de Matos P, Dekker A, Ennis M, Harsha B, Kale N, Muthukrishnan V, Owen G, Turner S, Williams M, Steinbeck C: The ChEBI reference database and ontology for biologically relevant chemistry: enhancements for 2013. Nucleic Acids Research 2012.
27. Wishart DS, Knox C, Guo AC, Eisner R, Young N, Gautam B, Hau DD, Psychogios N, Dong E, Bouatra S, Mandal R, Sinelnikov I, Xia J, Jia L, Cruz JA, Lim E, Sobsey CA, Shrivastava S, Huang P, Liu P, Fang L, Peng J, Fradette R, Cheng D, Tzur D, Clements M, Lewis A, De Souza A, Zuniga A, Dawe M, Xiong Y, Clive D, Nazyrova A, Shaykhutdinov R, Li L, Vogel HJ, Forsythe I: HMDB: a knowledgebase for the human metabolome. Nucleic Acids Research 2009, 37(suppl 1):603-610.
28. NaCTeM Metabolite and Enzyme Corpus. [http://www.nactem.ac.uk/metabolite-corpus], Accessed: October 2013.
29. Grego T, Pęzik P, Couto FM, Rebholz-Schuhmann D: Identification of chemical entities in patent documents. Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part II: Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living. IWANN '09 Springer, Berlin, Heidelberg; 2009, 942-949.
30. Patents Gold Standard Annotations. [http://chebi.cvs.sourceforge.net/viewvc/chebi/chapati/patentsGoldStandard], Accessed: October 2013.
31. Herrero-Zazo M, Segura-Bedmar I, Martínez P, Declerck T: The ddi corpus: An annotated corpus with pharmacological substances and drug-drug interactions. Journal of Biomedical Informatics 2013, 46(5):914-920.
32. Corpora for Drug-Drug Interaction Extraction. [http://labda.inf.uc3m.es/doku.php?id=en:labda-ddicorpus], Accessed: October 2013.
33. Wu H-Y, Karnik S, Subhadarshini A, Wang Z, Philips S, Han X, Chiang C, Liu L, Boustani M, Rocha L, Quinney S, Flockhart D, Li L: An integrated pharmacokinetics ontology and corpus for text mining. BMC Bioinformatics 2013, 14(1):35.
34. Pharmacokinetics Corpus. [http://rweb.compbio.iupui.edu/corpus], Accessed: October 2013.
35. Rak R, Rowley A, Black W, Ananiadou S: Argo: an integrative, interactive, text mining-based workbench supporting curation. Database : The Journal of Biological Databases and Curation 2012, 010.
36. Kolluru B, Hawizy L, Murray-Rust P, Tsujii J, Ananiadou S: Using workflows to explore and optimise named entity recognition for chemistry. PLoS ONE 2011, 6(5):20181.
37. Alias-I: LingPipe 4.1.0. [http://alias-i.com/lingpipe], Accessed: July 2013.
38. Cafetiere English Sentence Detector. [http://metashare.metanet4u.eu/repository/browse/u-compare-cafetiere-english-sentence-detector/aff1ddc0bc8911e1a404080027e73ea259aeca28412944ea97f7b2580a41caec/#], Accessed: October 2013.
39. Tsuruoka Y, Tateisi Y, Kim J-D, Ohta T, McNaught J, Ananiadou S, Tsujii J: Developing a Robust Part-of-Speech Tagger for Biomedical Text. In: Advances in Informatics - 10th Panhellenic Conference on Informatics. LNCS, Springer, Volos, Greece 2005, 3746:382-392.
40. Jessop DM, Adams SE, Willighagen EL, Hawizy L, Murray-Rust P: OSCAR4: a flexible architecture for chemical text-mining. Journal of Cheminformatics 2011, 3(1):41.
41. Okazaki N: CRFsuite: a fast implementation of Conditional Random Fields (CRFs).[http://www.chokkan.org/software/crfsuite], Accessed: July 2013.
42. Knox C, Law V, Jewison T, Liu P, Ly S, Frolkis A, Pon A, Banco K, Mak C, Neveu V, Djoumbou Y, Eisner R, Guo AC, Wishart DS: DrugBank 3.0: a comprehensive resource for 'omics' research on drugs. Nucleic acids research 2011, , 39 Database: 1035-41.
43. Davis AP, Murphy CG, Johnson R, Lay JM, Lennon-Hopkins K, Saraceni-Richards C, Sciaky D, King BL, Rosenstein MC, Wiegers TC, Mattingly CJ: The Comparative Toxicogenomics Database: update 2013. Nucleic Acids Research 2012.
44. Bolton EE, Wang Y, Thiessen PA, Bryant SH: PubChem: Integrated Platform of Small Molecules and Biological Activities. Annual Reports in Computational Chemistry 2008, 4.
45. American Chemical Society: Registry file basic name segment dictionary. Technical report 1993.
46. Schwartz AS, Hearst MA: A simple algorithm for identifying abbreviation definitions in biomedical text. Pacific Symposium on Biocomputing 2003, 451-462.
47. Segura-Bedmar I, Martínez P, Herrero Zazo M: SemEval-2013 Task 9: Extraction of Drug-Drug Interactions from Biomedical Texts (DDIExtraction 2013). Second Joint Conference on Lexical and Computational Semantics (∗SEM), Volume 2: Proceedings of the Seventh International Workshop on Semantic Evaluation (SemEval 2013) Association for Computational Linguistics, Atlanta, Georgia, USA; 2013, 341-350.
48. Cho H-C, Okazaki N, Miwa M, Tsujii J: NERsuite: a named entity recognition toolkit. [https://github.com/nlplab/nersuite], Accessed: July 2013.
49. Leitner F: BioCreative II.5 Evaluation Library. [http://www.biocreative.org/resources/biocreative-ii5/evaluation-library], Accessed: August 2013.