HUDÍK, Tomáš and Matej LEXA. Segmentation of texts and biological sequences into lexical and structural units using a machine-learning approach. In Proceedings of the 1st International Summer School on Computational Biology. Brno: L. Dušek, L., J. Hřebíček, L. Jarkovský, 2005, p. 50-56, 8 pp. ISBN 80-210-3907-8.
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Basic information
Original name Segmentation of texts and biological sequences into lexical and structural units using a machine-learning approach
Name in Czech Segmentácia textov a biologických sekvencií do lexikálnych a štrukturálnych jednotiek použitím metód strojového učenia
Authors HUDÍK, Tomáš (703 Slovakia, guarantor) and Matej LEXA (703 Slovakia).
Edition Brno, Proceedings of the 1st International Summer School on Computational Biology, p. 50-56, 8 pp. 2005.
Publisher L. Dušek, L., J. Hřebíček, L. Jarkovský
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher Czech Republic
Confidentiality degree is not subject to a state or trade secret
WWW URL
RIV identification code RIV/00216224:14330/05:00014589
Organization unit Faculty of Informatics
ISBN 80-210-3907-8
Keywords in English machine learning ; segmentation; I-sites
Tags I-sites, machine learning, segmentation
Changed by Changed by: Mgr. Tomáš Hudík, učo 55775. Changed: 31/1/2006 12:00.
Abstract
Results demonstrate that segmentation problems in the linguistic domain and protein sequence domain are similar and can be treated with similar computational tools. From our point of view protein sequences contain segments that are analogical to words in natural language.
Abstract (in Czech)
Výsledky ukazujú, že problém segmentácie v oblasti lingvistiky a proteínových sekvencií sú podobné a môžu sa spracovávať podobnými výpočtovými nástrojmi. Z nášho pohľadu proteínové sekvencie obsahujú segmenty podobné slovám v prirodzenom jazyku.
Links
MSM 143300003, plan (intention)Name: Interakce člověka s počítačem, dialogové systémy a asistivní technologie
Investor: Ministry of Education, Youth and Sports of the CR, Human-computer interaction, dialog systems and assistive technologies
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