The role of ontologies in biological and biomedical research: A functional perspective

Briefings in Bioinformatics

Volumn 16, Issue 6, 2015, Pages 1069-1080

  Hoehndorf, Robert ^a   Schofield, Paul N ^b   Gkoutos, Georgios V ^c  

^a KING ABDULLAH UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Saudi Arabia)

^b UNIVERSITY OF CAMBRIDGE   (United Kingdom)

^c ABERYSTWYTH UNIVERSITY   (United Kingdom)

Author keywords

Data integration; Datamining; Ontology; SemanticWeb

Indexed keywords

BIOLOGY; BIOMEDICINE; DATA MINING; LEARNING; MEDICAL RESEARCH; ONTOLOGY; INTERNET; MACHINE LEARNING;

BIOMEDICAL RESEARCH; DATA MINING; INTERNET; MACHINE LEARNING;

EID: 84954318068     PISSN: 14675463     EISSN: 14774054     Source Type: Journal    
DOI: 10.1093/bib/bbv011     Document Type: Article

References (139)

1. Ashburner M, Ball CA, Blake JA, et al. Gene ontology: tool for the unification of biology. Nat Genet 2000;25:25-29.
2. Smith B, Ashburner M, Rosse C, et al. The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration. Nat Biotech 2007;25:1251-5.
3. Musen MA, Noy NF, Shah NH, et al. The National Center for Biomedical Ontology. J Am Med Inform Assoc 2012;19: 190-5.
4. Gruber TR, Olsen G. An ontology for engineering mathematics in principles of knowledge representation and reasoning. In: J Doyle, P Torasso, E Sandewall (eds). Proceedings of the 4th International Conference (KR '94):Bonn, Germany, May 24-27, 1994. Morgan Kaufmann Publishers, Burlington, Massachusetts, USA, 1994, 258-69.
5. Gruber TR. Toward principles for the design of ontologies used for knowledge sharing. Int J Hum Comput Stud 1995; 43(5/6):907-28.
6. Guarino N. Formal ontology and information systems. In: N Guarino (ed). Proceedings of the 1st International Conference on Formal Ontologies in Information Systems. Amsterdam, Netherlands: IOS Press, 1998, 3-15.
7. Smith B, Williams J, Schulze-Kremer S. The ontology of the gene ontology. AMIA Annu Symp Proc 2003;2003:609-13.
8. Baader F, Calvanese D, McGuinness D, et al. The Description Logic Handbook: Theory, Implementation and Applications. Cambridge University Press, 2003.
9. Heller B, Herre H. Ontological categories in GOL. Axiomathes 2004;14:57-76.
10. Herre H, Loebe F. A meta-ontological architecture for foundational ontologies. In: On the Move to Meaningful Internet Systems 2005: CoopIS, DOA, and ODBASE. Springer Verlag, Heidelberg, Germany, 2005, 1398-415.
11. Kumar A, Smith B. In: A Günter, R Kruse, B Neumann (eds). KI2003: Advances in AI. 2003, 135-48.
12. Bada M, Stevens R, Goble C, et al. A short study on the success of the Gene Ontology. Web Semant 2004;1:235-40.
13. Bodenreider O, Stevens R. Bio-ontologies: current trends and future directions. Brief Bioinform 2006;7:256-74.
14. Smith B. Ontology (Science). In: Proceeding of the 2008 conference on Formal Ontology in Information Systems: Proceedings of the Fifth International Conference (FOIS 2008). IOS Press, Amsterdam, The Netherlands, 2008, 21-35.
15. Merrill GH. Ontological realism: methodology or misdirection? Appl Ontol 2010;5:79-108.
16. Berners-Lee T, Hendler J, Lassila O, et al. The Semantic Web. Sci Am 2001;284:28-37.
17. Ruttenberg A, Courtot M, Mungall CJ. OBO Foundry Identifier Policy. 2013. http://www.obofoundry.org/id-_policy.shtml (2 November 2014 date last accessed).
18. Cimino JJ. Desiderata for controlled medical vocabularies in the twenty-first century. Methods Inf Med 1998;37:394-403.
19. Stevens R, Hull D. Separating Concepts from Labels. 2010. http://ontogenesis.knowledgeblog.org/818
20. Rosse C, Mejino JLV. A reference ontology for biomedical informatics: the foundational model of anatomy. J Biomed Inform 2003;36:478-500.
21. Munn K, Smith B (eds). Applied Ontology: An Introduction, 1st edn. Ontos Verlag, Heusenstamm, Germany, 2009.
22. Burgun A, Bodenreider O, Jacquelinet C. Issues in the classification of disease instances with ontologies. Stud Health Technol Inform 2005;116:695-700.
23. Grau B, Horrocks I, Motik B, et al. OWL 2: the next step for OWL. Web Semant 2008;6:309-322.
24. Baader F. The Description Logic Handbook: Theory, Implementation and Applications. Cambridge University Press, 2003.
25. Horrocks I, Kutz O, Sattler U. The even more irresistible SROIQ. In: P Doherty, J Mylopoulos, CA Welty (eds). KR. Palo Alto, California, USA: AAAI Press, 2006, 57-67.
26. Motik B, Grau BC, Horrocks I, et al. OWL 2 Web Ontology Language: Profiles Recommendation. World Wide Web Consortium (W3C), Cambridge, Massachusetts, USA, 2009.
27. Horrocks I. OBO Flat File Format Syntax and Semantics and Mapping to OWL Web Ontology Language. University of Manchester, 2007. http://www.cs.man.ac.uk/~horrocks/obo/
28. Henkin L, Suppes P, Tarski A. The axiomatic method with special reference to geometry and physics. In: Proceedings of an International Symposium Held at the University of California, Berkeley, December 26, 1957-January 4, 1958. North-Holland Publishing Co, Amsterdam, 1959.
29. Stevens R, Stevens M. A family history knowledge base using OWL 2. In: C Dolbear, A Ruttenberg, U, Sattler. OWLED, Vol. 432. Aachen, Germany: CEUR-WS.org, 2008.
30. Barwise J. Model-Theoretic Logics (Perspectives in Mathematical Logic). Springer, Heidelberg, Germany, 1985.
31. Hoehndorf R, Batchelor C, Bittner T, et al. The RNA Ontology (RNAO): an ontology for integrating RNA sequence and structure data. Appl Ontol 2011;6:53-89.
32. Grenon P. BFO in a Nutshell: A Bi-categorial Axiomatization of BFO and Comparison with DOLCE. IFOMIS Report 06/2003. Institute for Formal Ontology and Medical Information Science (IFOMIS), University of Leipzig, Leipzig, Germany, 2003.
33. Eilbeck K, Lewis SE, Mungall CJ, et al. The sequence ontology: a tool for the unification of genome annotations. Genome Biol 2005;6:R44.
34. Hoehndorf R, Kelso J, Herre H. The ontology of biological sequences. BMC Bioinformatics 2009;10:377+.
35. Hoehndorf R, Oellrich A, Dumontier M, et al. Relations as patterns: bridging the gap between OBO and OWL. BMC Bioinformatics 2010;11:441+.
36. Schulz S, Hahn U. Part-whole representation and reasoning in formal biomedical ontologies. Artif Intell Med 2005;34: 179-200.
37. Smith B, Ceusters W, Klagges B, et al. Relations in biomedical ontologies. Genome Biol 2004;6:R46.
38. The Gene Ontology Consortium. Gene ontology annotations and resources. Nucleic Acids Res 2013;41:D530-5.
39. Ciccarese P, Ocana M, Garcia Castro L, et al. An open annotation ontology for science on web 3.0. J Biomed Semantics 2011; 2:S4.
40. Lingutla N, Preece J, Todorovic S, et al. AISO: annotation of image segmentswith ontologies. J Biomed Semantics 2014;5:50.
41. Chibucos MC, Mungall CJ, Balakrishnan R, et al. Standardized description of scientific evidence using the Evidence Ontology (ECO). Database 2014;2014:pii: bau075.
42. Belhajjame K, Cheney J, Corsar D, et al. PROV-O: The PROV Ontology. 2012. http://www.w3.org/TR/prov-o/
43. Ciccarese P, Ocana M, Clark T. Open semantic annotation of scientific publications using DOMEO. J Biomed Semantics 2012;3:S1.
44. Sanderson R, Ciccarese P, de Sompel HV. Designing the W3C open annotation data model. CoRR 2013;abs/1304.6709.
45. Hirschman L, Burns GAPC, Krallinger M, et al. Text mining for the biocuration workflow. Database 2012;2012:bas020.
46. Müller HM, Kenny EE, Sternberg PW. Textpresso: an ontology- based information retrieval and extraction system for biological literature. PLoS Biol 2004;2:e309+.
47. Dowell KG, McAndrews-Hill MS, Hill DP, et al. Integrating text mining into the MGI biocuration workflow. Database (Oxford) 2009;2009:bap019
48. Dahdul WM, BalhoffJP, Engeman J, et al. Evolutionary characters, phenotypes and ontologies: curating data from the systematic biology literature. PLoS One 2010;5:e10708.
49. BalhoffJ, Dahdul W, Dececchi T, et al. Annotation of phenotypic diversity: decoupling data curation and ontology curation using Phenex. J Biomed Semantics 2014;5:45.
50. Gaudet P, Livstone MS, Lewis SE, et al. Phylogenetic-based propagation of functional annotations within the Gene Ontology consortium. Brief Bioinform 2011;12:449-62.
51. Mabee P, BalhoffJP, Dahdul WM, et al. 500,000 fish phenotypes: the new informatics landscape for evolutionary and developmental biology of the vertebrate skeleton. J Appl Ichthyol 2012;28:300-5.
52. Brown SDM, Moore MW. Towards an encyclopaedia of mammalian gene function: the International Mouse Phenotyping Consortium. Dis Model Mech 2012;5:289-292.
53. Beck T, Morgan H, Blake A, et al. Practical application of ontologies to annotate and analyse large scale raw mouse phenotype data. BMC Bioinformatics 2009;10:S2+.
54. Koscielny G, Yaikhom G, Iyer V, et al. The International Mouse Phenotyping Consortium Web Portal, a unified point of access for knockout mice and related phenotyping data. Nucleic Acids Res 2014;42:D802-9.
55. Carbon S, Ireland A, Mungall CJ, et al. AmiGO: online access to ontology and annotation data. Bioinformatics 2009;25:288-9.
56. Doms A, Schroeder M. GoPubMed: exploring PubMed with the Gene Ontology. Nucleic Acids Res 2005;33:783-6.
57. Rebholz-Schuhmann D, Oellrich A, Hoehndorf R. Text-mining solutions for biomedical research: enabling integrative biology. Nat Rev Genet 2012;13:829-39.
58. Jonquet C, Shah NH, Musen MA. The open biomedical annotator. Summit Translat Bioinforma 2009;2009:56-60.
59. Ghazvinian A, Noy NF, Musen MA. Creating mappings for ontologies in biomedicine: simple methods work. AMIA Annu Symp Proc 2009;2009:198-202.
60. Mao Y, Van Auken K, Li D, et al. Overview of the gene ontology task at BioCreative IV. Database 2014;2014:bau086.
61. Van Driel MA, Bruggeman J, Vriend G, et al. A text-mining analysis of the human phenome. Eur J Hum Genet 2006;14: 535-42.
62. Zhou X, Menche J, Barabási A-L, et al. Human symptoms- disease network. Nat Commun 2014;5:4212.
63. Campillos M, Kuhn M, Gavin ACC, et al. Drug target identification using side-effect similarity. Science 2008;321:263-6.
64. Kuhn M, Campillos M, Letunic I, et al. A side effect resource to capture phenotypic effects of drugs. Mol Syst Biol 2010;6:343.
65. Percha B, Garten Y, Altman RB. Discovery and explanation of drug-drug interactions via text mining. Pac Symp Biocomput 2012;2012:410-21.
66. Oellrich A, Gkoutos GV, Hoehndorf R, et al. Quantitative comparison of mapping methods between Human and Mammalian Phenotype Ontology. J Biomed Semantics 2012; 3:S1.
67. Hoehndorf R, Schofield PN, Gkoutos GV. An integrative, translational approach to understanding rare and orphan genetically based diseases. Interface Focus 2013;3: 20120055.
68. Rebholz-Schuhmann D, Kim JH, Yan Y, et al. Evaluation and cross-comparison of lexical entities of biological interest (LexEBI). PLoS One 2013;8:e75185.
69. Funk C, Baumgartner W, Garcia B, et al. Large-scale biomedical concept recognition: an evaluation of current automatic annotators and their parameters. BMC Bioinformatics 2014; 15:59.
70. Hunter L, Lu Z, Firby J, et al. OpenDMAP: an open source, ontology-driven concept analysis engine, with applications to capturing knowledge regarding protein transport, protein interactions and cell-type-specific gene expression. BMC Bioinformatics 2008;9:78.
71. Shah N, Bhatia N, Jonquet C, et al. Comparison of concept recognizers for building the Open Biomedical Annotator. BMC Bioinformatics 2009;10(Suppl 9):S14.
72. Sirin E, Parsia B, Grau BC, et al. Pellet: a practical OWL-DL reasoner. Web Semant 2007;5:51-3.
73. Motik B, Shearer R, Horrocks I. Hypertableau reasoning for description logics. J Artif Intell Res 2009;36:165-228.
74. Kazakov Y, Krötzsch M, Simancik F. The incredible ELK. J Autom Reason 2014;53:1-61.
75. Steigmiller A, Liebig T, Glimm B. Konclude: system description. Web Semant 2014:27.
76. Bail S, Glimm B, Jiménez-Ruiz E, et al. (eds). ORE 2014: OWL Reasoner Evaluation Workshop. CEUR Workshop Proceedings 1207. CEUR-WS.org, Aachen, Germany, 2014.
77. Hoehndorf R, Dumontier M, Oellrich A, et al. A common layer of interoperability for biomedical ontologies based on OWL EL. Bioinformatics 2011;27:1001-8.
78. Rector AL. Modularisation of domain ontologies implemented in description logics and related formalisms including OWL in K-CAP '03. In: Proceedings of the 2nd International Conference on Knowledge Capture. ACM Press, New York, NY, 2003, 121-8.
79. Jiménez-Ruiz E, Grau BC, Sattler U, et al. English. In: S Bechhofer, M Hauswirth, J Hoffmann, et al. (eds). The Semantic Web: Research and Applications. Springer, Berlin, Heidelberg, 2008, 185-199.
80. Horridge M, Bechhofer S, Noppens O. Igniting the OWL 1.1 Touch Paper: The OWL API. In: Proceedings of OWLED 2007: Third International Workshop on OWL Experiences and Directions. 2007. CEUR-WS.org, Aachen, Germany.
81. Noppens O, Luther M, Liebig T. The OWLlink API: Teaching OWL Components a Common Protocol. In: E Sirin, K Clark (eds). Proceedings of the 7th International Workshop on OWL: Experiences and Directions (OWLED 2010), Vol. 614 of CEUR Workshop Proceedings, 2010. http://ceur-_ws.org.
82. Noy NF, Sintek M, Decker S, et al. Creating semantic web contents with protege-2000. IEEE Intell Syst 2001;16:60-71.
83. Hoehndorf R, Dumontier M, Gennari JH, et al. Integrating systems biology models and biomedical ontologies. BMC Syst Biol 2011;5:124+.
84. Lenzerini M, Console M. Data quality in ontology-based data access: the case of consistency. In: Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence 2014, 1020-6. AAAI Press, Palo Alto, California, USA.
85. Tao C, Song D, Sharma D, et al. Semantator: semantic annotator for converting biomedical text to linked data. J Biomed Inform 2013;46:882-93.
86. Demir E, CaryMP, Paley S, et al. The BioPAX community standard for pathway data sharing. Nat Biotechnol 2010;28:935-42.
87. Wolstencroft K, Lord P, Tabernero L, et al. Protein classification using ontology classification. Bioinformatics 2006;22:e530-8.
88. Egaña M, Rector A, Stevens R, et al. Applying ontology design patterns in bio-ontologies. In: A Gangemi, J Euzenat (eds). Knowledge Engineering: Practice and Patterns, Vol. 5268 of Lecture Notes in Computer Science. 2008, 7-16.
89. Hoehndorf R, Dumontier M, Oellrich A, et al. Interoperability between biomedical ontologies through relation expansion, upper-level ontologies and automatic reasoning. PLOS One 2011;6:e22006.
90. Mungall C, Gkoutos G, Smith C, et al. Integrating phenotype ontologies across multiple species. Genome Biol 2010;11:R2. doi:10.1186/gb-2010-11-1-r2, R2+ (2010).
91. Washington NL, Haendel MA, Mungall CJ, et al. Linking human diseases to animal models using ontology-based phenotype annotation. PLoS Biol 2009;7:e1000247.
92. Mungall C, Torniai C, Gkoutos G, et al. Uberon, an integrative multi-species anatomy ontology. Genome Biol 2012;13:R5.
93. Hoehndorf R, Oellrich A, Rebholz-Schuhmann D. Interoperability between phenotype and anatomy ontologies. Bioinformatics 2010;26:3112-18.
94. Subramanian A, Tamayo P, Mootha VK, et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci USA 2005;102:15545-50.
95. Pesquita C, Faria D, Falcao AO, et al. Semantic similarity in biomedical ontologies. PLoS Comput Biol 2009;5:e1000443. DOI:10.1371/journal.pcbi.1000443, e1000443.
96. Guzzi PH, Mina M, Guerra C, et al. Semantic similarity analysis of protein data: assessment with biological features and issues. Brief Bioinform 2011;13:569-85.
97. Benabderrahmane S, Smail-Tabbone M, Poch O, et al. IntelliGO: a new vector-based semantic similarity measure including annotation origin. BMC Bioinformatics 2010;11:588.
98. Köhler S, Schulz MH, Krawitz P, et al. Clinical diagnostics in human genetics with semantic similarity searches in ontologies. Am J Hum Genet 2009;85:457-64.
99. Hoehndorf R, Schofield PN, Gkoutos GV. PhenomeNET: a whole-phenome approach to disease gene discovery. Nucleic Acids Res 2011;39:e119.
100. Schlicker A, Albrecht M. FunSimMat update: new features for exploring functional similarity. Nucleic Acids Res 2010;38: D244-8.
101. Ferreira JD, Couto FM. Semantic similarity for automatic classification of chemical compounds. PLoS Comput Biol 2010; 6:e1000937.
102. Radivojac P, Clark WT, Oron TR, et al. A large-scale evaluation of computational protein function prediction. Nat Meth 2013;10:221-7.
103. Melvin I, Ie E, Kuang R, et al. SVM-Fold: a tool for discriminative multi-class protein fold and superfamily recognition. BMC Bioinformatics 2007;8:S2.
104. Sokolov A, Funk C, Graim K, et al. Combining heterogeneous data sources for accurate functional annotation of proteins. BMC Bioinformatics 2013;14:S10.
105. Cozzetto D, Buchan D, Bryson K, et al. Protein function prediction by massive integration of evolutionary analyses and multiple data sources. BMC Bioinformatics 2013;14:S1.
106. Lan L, Djuric N, Guo Y, et al. MS-kNN: protein function prediction by integrating multiple data sources. BMC Bioinformatics 2013;14:S8.
107. Sokolov A, Ben-Hur A. Hierarchical classification of gene ontology terms using the GOStruct method. J Bioinform Comput Biol 2010;8:357-76.
108. Skowron A, Wang H, Wojna A, et al. Multimodal classification: case studies. In: JF Peters, A Skowron (eds). Transactions on Rough Sets V. Springer-Verlag, Berlin, Heidelberg, 2006, 224-39.
109. Huang J, Dang J, Borchert GM, et al. OMIT: dynamic, semiautomated ontology development for the microRNA domain. PLoS One 2014;9:e100855.
110. Abeyruwan S, Vempati UD, Kucuk-McGinty H, et al. Evolving BioAssay Ontology (BAO): modularization, integration and applications. J Biomed Semantics 2014;5:S5.
111. Köhler S, Doelken SC, Ruef BJ, et al. Construction and accessibility of a cross-species phenotype ontology along with gene annotations for biomedical research. F1000Research 2013;2:30.
112. Vos R, Biserkov J, Balech B, et al. Enriched biodiversity data as a resource and service. Biodiversity Data J 2014;2:e1125.
113. Pathak J, Kiefer RC, Bielinski SJ, et al. Applying semantic web technologies for phenome-wide scan using an electronic health record linked Biobank. J Biomed Semantics 2012; 3:10.
114. Girdea M, Dumitriu S, Fiume M, et al. PhenoTips: patient phenotyping software for clinical and research use. Hum Mutat 2013;34:1057-65.
115. Denny JC. Chapter 13: Mining electronic health records in the genomics era. PLoS Comput Biol 2012;8:e1002823.
116. Zemojtel T, Köhler S, Mackenroth L, et al. Effective diagnosis of genetic disease by computational phenotype analysis of the disease-associated genome. Sci Transl Med 2014;6: 252ra123.
117. Hoehndorf R, Dumontier M, Gkoutos GV. Evaluation of research in biomedical ontologies. Brief Bioinform 2013;14: 696-712.
118. Dutkowski J, Kramer M, Surma MA, et al. A gene ontology inferred from molecular networks. Nat Biotechnol 2012;31: 38-45.
119. Verspoor K, Dvorkin D, Cohen KB, et al. Ontology quality assurance through analysis of term transformations. Bioinformatics 2009;25:i77-84.
120. Manola F, Miller E (eds). RDF Primer. World Wide Web Consortium, Cambridge, Massachusetts, USA, 2004.
121. Seaborne A, Prud'hommeaux E. SPARQL Query Language for RDF. W3C Recommendation (W3C, 2008). http://www.w3.org/TR/2008/REC-rdf-sparql-query-20080115/.
122. Heath T, Bizer C. Linked Data: Evolving the Web into a Global Data Space, 1st edn. San Rafael, California, USA: Morgan & Claypool, 2011.
123. Nelson SJ, Schopen M, Savage AG, et al. The MeSH translation maintenance system: Structure, interface design, and implementation. In Proceedings of the 11th World Congress on Medical Informatics. IOS Press, Amsterdam, 2004, 67-9.
124. Bodenreider O. The Unified Medical Language System (UMLS): integrating biomedical terminology. Nucleic Acids Res 2004;32, D267-70.
125. Cornet R, de Keizer N. Forty years of SNOMED: a literature review. BMC Med Inform Decis Mak 2008;8:S2.
126. Noy NF, Shah NH, Whetzel PL, et al. BioPortal: ontologies and integrated data resources at the click of a mouse. Nucleic Acids Res 2009;37:W170-3.
127. Whetzel P, Team, N. NCBO technology: powering semantically aware applications. J Biomed Semantics 2013;4:S8.
128. Xiang Z, Mungall CJ, Ruttenberg A, et al. Ontobee: a linked data server and browser for ontology terms. In: Proceedings of International Conference on Biomedical Ontology 2011, 279-81. CEUR-WS.org, Aachen, Germany.
129. Cote R, Jones P, Apweiler R, et al. The Ontology Lookup Service, a lightweight cross-platform tool for controlled vocabulary queries. BMC Bioinformatics 2006;7:97+
130. Tsarkov D, Horrocks I. FaCT++ description logic reasoner: system description. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Third International Joint Conference on Automated Reasoning, Seattle, USA. IJCAR 2006, Vol. 4130 LNAI. Springer Verlag, Heidelberg, Germany. 2006, 292-7.
131. Haarslev V, Hidde K, Möller R, et al. The RacerPro knowledge representation and reasoning system. Semantic Web J 2012;3: 267-77.
132. W3C. AllegroGraph RDFStore Web 3.0's Database. 2009. http://www.franz.com/agraph/allegrograph/
133. Thomas E, Pan JZ, Ren Y. TrOWL: tractable OWL 2 reasoning infrastructure. In: Proceeding of the Extended Semantic Web Conference (ESWC2010) Springer Verlag, Heidelberg, Germany, 2010.
134. Levin MK, Ruttenberg A, Masci AM, et al. owl_cpp, a C++ Library for Working with OWL Ontologies. In: O Bodenreider, ME Martone, A Ruttenberg (eds). Proceedings of the 2nd International Conference on Biomedical Ontology CEUR-WS.org, Aachen, Germany 2011, 40.
135. Croset S, Overington JP, Rebholz-Schuhmann D. Brain: biomedical knowledge manipulation. Bioinformatics 2013;29: 1238-9.
136. Bastian M, Heymann S, Jacomy M. Gephi: an open source software for exploring and manipulating networks. In: E Adar, M Hurst, T Finin, et al. (eds). International AAAI Conference on Weblogs and Social Media (ICWSM). Palo Alto, California, USA: The AAAI Press, 2009, 361-2.
137. Smoot ME, Ono K, Ruscheinski J, et al. Cytoscape 2.8: new features for data integration and network visualization. Bioinformatics 2011;27:431-2.
138. Harispe S, Ranwez S, Janaqi S, et al. The semantic measures library and toolkit: fast computation of semantic similarity and relatedness using biomedical ontologies. Bioinformatics 2014;30:740-2.
139. Hoehndorf R, Hancock JM, Hardy NW, et al. Analyzing gene expression data in mice with the Neuro Behavior Ontology. Mamm Genome 2014;25:32-40.