Cross-ontological analytics: Combining associative and hierarchical relations in the gene ontologies to assess gene product similarity

C. Posse, Antonio Sanfilippo, B. Gopalan, R. Riensche, N. Beagley, B. Baddeley

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

Gene and gene product similarity is a fundamental diagnostic measure in analyzing biological data and constructing predictive models for functional genomics. With the rising influence of the gene ontologies, two complementary approaches have emerged where the similarity between two genes/gene products is obtained by comparing gene ontology (GO) annotations associated with the gene/gene products. One approach captures GO-based similarity in terms of hierarchical relations within each gene ontology. The other approach identifies GO-based similarity in terms of associative relations across the three gene ontologies. We propose a novel methodology where the two approaches can be merged with ensuing benefits in coverage and accuracy.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages871-878
Number of pages8
Volume3992 LNCS - II
DOIs
Publication statusPublished - 2006
Externally publishedYes
EventICCS 2006: 6th International Conference on Computational Science - Reading
Duration: 28 May 200631 May 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3992 LNCS - II
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

OtherICCS 2006: 6th International Conference on Computational Science
CityReading
Period28/5/0631/5/06

Fingerprint

Gene Ontology
Ontology
Genes
Gene
Molecular Sequence Annotation
Functional Genomics
Predictive Model
Genomics
Annotation
Similarity
Diagnostics
Coverage
Methodology

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

Cite this

Posse, C., Sanfilippo, A., Gopalan, B., Riensche, R., Beagley, N., & Baddeley, B. (2006). Cross-ontological analytics: Combining associative and hierarchical relations in the gene ontologies to assess gene product similarity. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3992 LNCS - II, pp. 871-878). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3992 LNCS - II). https://doi.org/10.1007/11758525_116

Cross-ontological analytics : Combining associative and hierarchical relations in the gene ontologies to assess gene product similarity. / Posse, C.; Sanfilippo, Antonio; Gopalan, B.; Riensche, R.; Beagley, N.; Baddeley, B.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3992 LNCS - II 2006. p. 871-878 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3992 LNCS - II).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Posse, C, Sanfilippo, A, Gopalan, B, Riensche, R, Beagley, N & Baddeley, B 2006, Cross-ontological analytics: Combining associative and hierarchical relations in the gene ontologies to assess gene product similarity. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 3992 LNCS - II, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 3992 LNCS - II, pp. 871-878, ICCS 2006: 6th International Conference on Computational Science, Reading, 28/5/06. https://doi.org/10.1007/11758525_116
Posse C, Sanfilippo A, Gopalan B, Riensche R, Beagley N, Baddeley B. Cross-ontological analytics: Combining associative and hierarchical relations in the gene ontologies to assess gene product similarity. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3992 LNCS - II. 2006. p. 871-878. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/11758525_116
Posse, C. ; Sanfilippo, Antonio ; Gopalan, B. ; Riensche, R. ; Beagley, N. ; Baddeley, B. / Cross-ontological analytics : Combining associative and hierarchical relations in the gene ontologies to assess gene product similarity. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 3992 LNCS - II 2006. pp. 871-878 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
@inproceedings{c771de14031a41f4bd916d787733cc6b,
title = "Cross-ontological analytics: Combining associative and hierarchical relations in the gene ontologies to assess gene product similarity",
abstract = "Gene and gene product similarity is a fundamental diagnostic measure in analyzing biological data and constructing predictive models for functional genomics. With the rising influence of the gene ontologies, two complementary approaches have emerged where the similarity between two genes/gene products is obtained by comparing gene ontology (GO) annotations associated with the gene/gene products. One approach captures GO-based similarity in terms of hierarchical relations within each gene ontology. The other approach identifies GO-based similarity in terms of associative relations across the three gene ontologies. We propose a novel methodology where the two approaches can be merged with ensuing benefits in coverage and accuracy.",
author = "C. Posse and Antonio Sanfilippo and B. Gopalan and R. Riensche and N. Beagley and B. Baddeley",
year = "2006",
doi = "10.1007/11758525_116",
language = "English",
isbn = "3540343814",
volume = "3992 LNCS - II",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "871--878",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

}

TY - GEN

T1 - Cross-ontological analytics

T2 - Combining associative and hierarchical relations in the gene ontologies to assess gene product similarity

AU - Posse, C.

AU - Sanfilippo, Antonio

AU - Gopalan, B.

AU - Riensche, R.

AU - Beagley, N.

AU - Baddeley, B.

PY - 2006

Y1 - 2006

N2 - Gene and gene product similarity is a fundamental diagnostic measure in analyzing biological data and constructing predictive models for functional genomics. With the rising influence of the gene ontologies, two complementary approaches have emerged where the similarity between two genes/gene products is obtained by comparing gene ontology (GO) annotations associated with the gene/gene products. One approach captures GO-based similarity in terms of hierarchical relations within each gene ontology. The other approach identifies GO-based similarity in terms of associative relations across the three gene ontologies. We propose a novel methodology where the two approaches can be merged with ensuing benefits in coverage and accuracy.

AB - Gene and gene product similarity is a fundamental diagnostic measure in analyzing biological data and constructing predictive models for functional genomics. With the rising influence of the gene ontologies, two complementary approaches have emerged where the similarity between two genes/gene products is obtained by comparing gene ontology (GO) annotations associated with the gene/gene products. One approach captures GO-based similarity in terms of hierarchical relations within each gene ontology. The other approach identifies GO-based similarity in terms of associative relations across the three gene ontologies. We propose a novel methodology where the two approaches can be merged with ensuing benefits in coverage and accuracy.

UR - http://www.scopus.com/inward/record.url?scp=33746582286&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33746582286&partnerID=8YFLogxK

U2 - 10.1007/11758525_116

DO - 10.1007/11758525_116

M3 - Conference contribution

AN - SCOPUS:33746582286

SN - 3540343814

SN - 9783540343813

VL - 3992 LNCS - II

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 871

EP - 878

BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

ER -