liu.seSearch for publications in DiVA
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Grouping Biological Data
Linköping University, Department of Computer and Information Science.
2006 (English)Independent thesis Basic level (professional degree), 20 points / 30 hpStudent thesis
Abstract [en]

Today, scientists in various biomedical fields rely on biological data sources in their research. Large amounts of information concerning, for instance, genes, proteins and diseases are publicly available on the internet, and are used daily for acquiring knowledge. Typically, biological data is spread across multiple sources, which has led to heterogeneity and redundancy.

The current thesis suggests grouping as one way of computationally managing biological data. A conceptual model for this purpose is presented, which takes properties specific for biological data into account. The model defines sub-tasks and key issues where multiple solutions are possible, and describes what approaches for these that have been used in earlier work. Further, an implementation of this model is described, as well as test cases which show that the model is indeed useful.

Since the use of ontologies is relatively new in the management of biological data, the main focus of the thesis is on how semantic similarity of ontological annotations can be used for grouping. The results of the test cases show for example that the implementation of the model, using Gene Ontology, is capable of producing groups of data entries with similar molecular functions.

Place, publisher, year, edition, pages
Institutionen för datavetenskap , 2006. , 81 p.
Keyword [en]
Biological Data, Grouping, Ontologies, Semantic Similarity
National Category
Bioinformatics (Computational Biology)
Identifiers
URN: urn:nbn:se:liu:diva-6327ISRN: LITH-IDA-EX--06/029--SEOAI: oai:DiVA.org:liu-6327DiVA: diva2:21763
Presentation
2006-04-21, Alan Turing, Hus E, Linköpings universitet, Linköping, 13:15
Uppsok
fysik/kemi/matematik
Supervisors
Examiners
Available from: 2006-05-23 Created: 2006-05-23

Open Access in DiVA

fulltext(1684 kB)439 downloads
File information
File name FULLTEXT01.pdfFile size 1684 kBChecksum SHA-1
601009f70c72697418ab95b28da28d125e5e7b1900b4a25864128029bbb9a9547c18411e
Type fulltextMimetype application/pdf

By organisation
Department of Computer and Information Science
Bioinformatics (Computational Biology)

Search outside of DiVA

GoogleGoogle Scholar
Total: 439 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 617 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf