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Philipp Cimiano | Matthias Hartung | Matthias Zwick | Roman Klinger | Hendrik ter Horst | Roman Klinger | P. Cimiano | Matthias Hartung | Hendrik ter Horst | M. Zwick
[1] Teruyoshi Hishiki,et al. Extraction of Gene-Disease Relations from Medline Using Domain Dictionaries and Machine Learning , 2005, Pacific Symposium on Biocomputing.
[2] Núria Queralt-Rosinach,et al. DisGeNET: a discovery platform for the dynamical exploration of human diseases and their genes , 2015, Database J. Biol. Databases Curation.
[3] Martin Hofmann-Apitius,et al. Named Entity Recognition with Combinations of Conditional Random Fields , 2007 .
[4] P. Kemmeren,et al. A new web-based data mining tool for the identification of candidate genes for human genetic disorders , 2003, European Journal of Human Genetics.
[5] David S. Wishart,et al. Nucleic Acids Research Polysearch: a Web-based Text Mining System for Extracting Relationships between Human Diseases, Genes, Mutations, Drugs Polysearch: a Web-based Text Mining System for Extracting Relationships between Human Diseases, Genes, Mutations, Drugs and Metabolites , 2008 .
[6] Corinna Cortes,et al. Support-Vector Networks , 1995, Machine Learning.
[7] Hendrik ter Horst,et al. Ranking of disease gene associations from large corpora of scientific publications , 2015 .
[8] Yan Teng,et al. Upregulation of heat shock protein 27 confers resistance to actinomycin D‐induced apoptosis in cancer cells , 2013, The FEBS journal.
[9] Zhiyong Lu,et al. An improved corpus of disease mentions in PubMed citations , 2012, BioNLP@HLT-NAACL.
[10] Changqin Quan,et al. Gene-disease association extraction by text mining and network analysis , 2014, Louhi@EACL.
[11] Joyce A. Mitchell,et al. Improving Literature Based Discovery Support by Genetic Knowledge Integration , 2003, MIE.
[12] Dragomir R. Radev,et al. Identifying gene-disease associations using centrality on a literature mined gene-interaction network , 2008, ISMB.
[13] Udo Hahn,et al. High-performance gene name normalization with GENO , 2009, Bioinform..
[14] Philipp Cimiano,et al. Towards Gene Recognition from Rare and Ambiguous Abbreviations using a Filtering Approach , 2014, BioNLP@ACL.
[15] Janos X. Binder,et al. DISEASES: Text mining and data integration of disease–gene associations , 2014, bioRxiv.
[16] Dennis M. Wilkinson,et al. A method for finding communities of related genes , 2004, Proceedings of the National Academy of Sciences of the United States of America.
[17] P. McHugh,et al. Pharmacogenetics, Kinetics, and Dynamics for Personalized Medicine by DF Kisor, MD Kane, JN Talbot and JE Sprague , 2016 .
[18] Jonathan D. Wren,et al. Knowledge discovery by automated identification and ranking of implicit relationships , 2004, Bioinform..
[19] Nora Husain,et al. The NIH genetic testing registry: a new, centralized database of genetic tests to enable access to comprehensive information and improve transparency , 2012, Nucleic Acids Res..
[20] Hinrich Schütze,et al. Introduction to information retrieval , 2008 .
[21] Neil R. Smalheiser,et al. Undiscovered Public Knowledge: A Ten-Year Update , 1996, KDD.
[22] R. A. Leibler,et al. On Information and Sufficiency , 1951 .
[23] Jari Björne,et al. Extracting Complex Biological Events with Rich Graph-Based Feature Sets , 2009, BioNLP@HLT-NAACL.
[24] Jari Björne,et al. Large-Scale Event Extraction from Literature with Multi-Level Gene Normalization , 2013, PloS one.
[25] Hitoshi Isahara,et al. Chinese Named Entity Recognition with Conditional Random Fields , 2006, SIGHAN@COLING/ACL.
[26] T. Tatusova,et al. Entrez Gene: gene-centered information at NCBI , 2010, Nucleic Acids Res..
[27] Hisham Al-Mubaid,et al. A New Text Mining Approach for Finding Protein-to-Disease Associations , 2005 .