Machine Learning Applications in Bioinformatics

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F12%3A00196365" target="_blank" >RIV/68407700:21230/12:00196365 - isvavai.cz</a>

Výsledek na webu

<a href="http://itat.ics.upjs.sk/proceedings/ITAT2012%20-%20CEUR%20Proceedings%20-%20tlacova%20verzia.pdf" target="_blank" >http://itat.ics.upjs.sk/proceedings/ITAT2012%20-%20CEUR%20Proceedings%20-%20tlacova%20verzia.pdf</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Machine Learning Applications in Bioinformatics

Popis výsledku v původním jazyce

Bioinformatics is a field of study dealing with methods for storing, retrieving and analyzing gene and protein oriented biological data. High-throughput technologies like DNA sequencing or microarrays allow researchers to obtain large volumes of heterogeneous and mutually interacting data. Analysis and understanding of these data provides a natural application field for machine leasing algorithms. At the same time, bioinformatics is a scientific branch of such analytical complexity, data variety and abundance that it motivates further development of specialized learning algorithms such as co-clustering or multiple sequence alignment. This paper provides a brief overview of the topics and works discussed during my talk on machine learning applications in bioinformatics. The talk starts with a preview of fundamental bioinformatics analytical tasks solved by machine learning algorithms mentioning a few success stories. The second part summarizes the recent bioinformatics research carried

Název v anglickém jazyce

Machine Learning Applications in Bioinformatics

Popis výsledku anglicky

Bioinformatics is a field of study dealing with methods for storing, retrieving and analyzing gene and protein oriented biological data. High-throughput technologies like DNA sequencing or microarrays allow researchers to obtain large volumes of heterogeneous and mutually interacting data. Analysis and understanding of these data provides a natural application field for machine leasing algorithms. At the same time, bioinformatics is a scientific branch of such analytical complexity, data variety and abundance that it motivates further development of specialized learning algorithms such as co-clustering or multiple sequence alignment. This paper provides a brief overview of the topics and works discussed during my talk on machine learning applications in bioinformatics. The talk starts with a preview of fundamental bioinformatics analytical tasks solved by machine learning algorithms mentioning a few success stories. The second part summarizes the recent bioinformatics research carried

Druh

D - Stať ve sborníku

CEP obor

JC - Počítačový hardware a software

OECD FORD obor

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Projekt

<a href="/cs/project/GAP202%2F12%2F2032" target="_blank" >GAP202/12/2032: Predikce vlastností bílkovin prostorovým statistickým relačním strojovým učením</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2012

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of Conference on Theory and Practice of information Technologies

ISBN

978-80-971144-0-4

ISSN

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e-ISSN

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Počet stran výsledku

2

Strana od-do

1-2

Název nakladatele

Univerzita P. J. Šafárika

Místo vydání

Košice

Místo konání akce

Belianské Tatry

Datum konání akce

17. 9. 2012

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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