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Sequence retriever for known, discovered, and user-specified molecular fragments
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science and Engineering.
2016 (English)In: 10TH INTERNATIONAL CONFERENCE ON PRACTICAL APPLICATIONS OF COMPUTATIONAL BIOLOGY & BIOINFORMATICS / [ed] Fdez-Riverola F.,De Paz J.F.,Rocha M.P.,Mayo F.J.D.,Mohamad M.S., Springer, 2016, Vol. 477, 51-58 p.Conference paper (Refereed)
Abstract [en]

Typically, biological and chemical data are sequential, for example, as in genomic sequences or as in diverse chemical formats, such as InChI or SMILES. That poses a major problem for computational analysis, since the majority of the methods for data mining and prediction were developed to work on feature vectors. To address this challenge, a functionality of a Statistical Adapter has been proposed recently. It automatically converts parsable sequential input into feature vectors. During the conversion, insights are gained into the problem via finding regions of interest in the sequence and the level of abstraction for their representation, and the feature vectors are filled with the counts of interesting sequence fragments,-finally, making it possible to benefit from powerful vectorbased methods. For this submission, the Sequence Retriever has been added to the Adapter. While the Adapter performs the conversion: sequence → vector with the counts of interesting molecular fragments, the Retriever performs the mapping: molecular fragment → sequences from the database that contain this fragment.

Place, publisher, year, edition, pages
Springer, 2016. Vol. 477, 51-58 p.
Series
Advances in Intelligent Systems and Computing, ISSN 2194-5357 ; 477
Keyword [en]
Bioactivity; Bioinformatics; Data mining, Computational analysis; Genomic sequence; Level of abstraction; Molecular fragments; Parsing; Regions of interest; Sequence retrieval; Vector-based methods, Vectors
National Category
Bioinformatics (Computational Biology)
Identifiers
URN: urn:nbn:se:bth-13193DOI: 10.1007/978-3-319-40126-3_6ISI: 000389591300006ScopusID: 2-s2.0-84976340337ISBN: 9783319401256 (print)OAI: oai:DiVA.org:bth-13193DiVA: diva2:1012409
Conference
International Conference on Practical Applications of Computational Biology and Bioinformatics (PACBB), Sevilla; Spain
Available from: 2016-10-03 Created: 2016-10-03 Last updated: 2017-01-05Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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