Mapreduce Based Approach to Longest Common Subsequence in Biosequences (Paperback)
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MapReduce Based Approach to Longest Common Subsequence in BioSequences
DE PB NW RPISBN: 9783659680502 bzw. 3659680508, in Deutsch, LAP Lambert Academic Publishing, Taschenbuch, neu, Nachdruck.
Von Händler/Antiquariat, AHA-BUCH GmbH [51283250], Einbeck, Germany.
This item is printed on demand - Print on Demand Titel. Neuware - The Longest Common Subsequence(LCS) identification of biological sequences has significant applications in bioinformatics. Due to the emerging growth in bioinformatics applications, new biological sequences with longer length have been used for processing, making it great challenge for sequential LCS algorithms. Few parallel LCS algorithms have been proposed but their efficiency and effectiveness are not satisfactory with increasing complexity and size of biological data. To overcome limitations of existing LCS algorithms and considering MapReduce programming model as promising technology for cost effective high performance parallel computing, MapReduce based parallel algorithm for LCS has been developed. This approach adopts the concepts of successor tables, identical character pairs, successor tree and traversal of successor tree to find Longest Common Subsequence. The hadoop framework is used for the realization of MapReduce model. 56 pp. Englisch.
This item is printed on demand - Print on Demand Titel. Neuware - The Longest Common Subsequence(LCS) identification of biological sequences has significant applications in bioinformatics. Due to the emerging growth in bioinformatics applications, new biological sequences with longer length have been used for processing, making it great challenge for sequential LCS algorithms. Few parallel LCS algorithms have been proposed but their efficiency and effectiveness are not satisfactory with increasing complexity and size of biological data. To overcome limitations of existing LCS algorithms and considering MapReduce programming model as promising technology for cost effective high performance parallel computing, MapReduce based parallel algorithm for LCS has been developed. This approach adopts the concepts of successor tables, identical character pairs, successor tree and traversal of successor tree to find Longest Common Subsequence. The hadoop framework is used for the realization of MapReduce model. 56 pp. Englisch.
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MapReduce Based Approach to Longest Common Subsequence in BioSequences
DE NWISBN: 9783659680502 bzw. 3659680508, in Deutsch, neu.
Lieferung aus: Deutschland, zzgl. Versandkosten.
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MapReduce Based Approach to Longest Common Subsequence in BioSequences (2015)
EN PB NWISBN: 9783659680502 bzw. 3659680508, in Englisch, 56 Seiten, LAP Lambert Academic Publishing, Taschenbuch, neu.
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Von Händler/Antiquariat, Book Depository US.
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Von Händler/Antiquariat, Book Depository US.
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MapReduce Based Approach to Longest Common Subsequence in BioSequences
EN NWISBN: 9783659680502 bzw. 3659680508, in Englisch, OmniScriptum GmbH & Co. KG, OmniScriptum GmbH & Co. KG, neu.
Lieferung aus: Vereinigte Staaten von Amerika, zzgl. Versandkosten, Free Shipping on eligible orders over $25.
Bohara Jnaneshwar, Joshi Shashidhar Ram, Paperback, English-language edition, Pub by OmniScriptum GmbH & Co. KG.
Bohara Jnaneshwar, Joshi Shashidhar Ram, Paperback, English-language edition, Pub by OmniScriptum GmbH & Co. KG.
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MapReduce Based Approach to Longest Common Su . 9783659680502 | dpd Versand
DE NWISBN: 9783659680502 bzw. 3659680508, in Deutsch, neu.
Lieferung aus: Deutschland, Lieferart: Free, Lieferung: Weltweit, Artikelstandort: 37574 Einbeck,Deutschland, Versandkostenfrei.
Von Händler/Antiquariat, aha-buch - AHA-BUCH.
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Von Händler/Antiquariat, aha-buch - AHA-BUCH.
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