Nassef Mohammad (8 results)

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Taschenbuch. Condition: Neu. Exploring the Referentially-compressed Genomes | Advantages and Challenges | Mohammad Nassef (u. a.) | Taschenbuch | 108 S. | Englisch | 2015 | LAP LAMBERT Academic Publishing | EAN 9783659791123 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]b…od[dot]de | Anbieter: preigu.

Language: English
Published by LAP LAMBERT Academic Publishing Okt 2015 2015
- Softcover
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Modern genome sequencing technologies produce enormous amount of data daily. Biologists in turn are keen to precisely explore this genomic data in order to discover effective patterns that have a real impact on the function and evol…ution of living creatures. Therefore, it becomes very critical to professionally store this data in order to efficiently explore it in a frequent manner. Reference-based Compression algorithms (RbCs) efficiently compress the sequenced genomes by mainly storing their differences with respect to a reference genome. Therefore, RbCs give amazing compression ratios compared to the traditional compression algorithms. However, in order to explore a compressed genome, it has to be totally decompressed, wasting both time and storage. By avoiding their complete decompression, the compressed genomes can be explored by performing partial decompressions at specific regions, gaining a significant reduction in runtime, memory, and storage consumption. Moreover, the complete decompression of a compressed genome can be performed more efficiently through successive partial decompressions. 108 pp. Englisch.

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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Nassef MohammadDr. Mohammad Nassef is a lecturer at department of Computer Science, Faculty of Computers and Information, Cairo University, Egypt. He is interested in the research areas of Bioinformatic…s and Parallel Computing. This .

Language: English
Published by LAP LAMBERT Academic Publishing Okt 2015 2015
- Softcover
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Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Modern genome sequencing technologies produce enormous amount of data daily. Biologists in turn are keen to precisely explore this genomic data in order to discover effective patterns that have a real impact on the function and evolutio…n of living creatures. Therefore, it becomes very critical to professionally store this data in order to efficiently explore it in a frequent manner. Reference-based Compression algorithms (RbCs) efficiently compress the sequenced genomes by mainly storing their differences with respect to a reference genome. Therefore, RbCs give amazing compression ratios compared to the traditional compression algorithms. However, in order to explore a compressed genome, it has to be totally decompressed, wasting both time and storage. By avoiding their complete decompression, the compressed genomes can be explored by performing partial decompressions at specific regions, gaining a significant reduction in runtime, memory, and storage consumption. Moreover, the complete decompression of a compressed genome can be performed more efficiently through successive partial decompressions.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 108 pp. Englisch.

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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Modern genome sequencing technologies produce enormous amount of data daily. Biologists in turn are keen to precisely explore this genomic data in order to discover effective patterns that have a real impact on the function and evolution… of living creatures. Therefore, it becomes very critical to professionally store this data in order to efficiently explore it in a frequent manner. Reference-based Compression algorithms (RbCs) efficiently compress the sequenced genomes by mainly storing their differences with respect to a reference genome. Therefore, RbCs give amazing compression ratios compared to the traditional compression algorithms. However, in order to explore a compressed genome, it has to be totally decompressed, wasting both time and storage. By avoiding their complete decompression, the compressed genomes can be explored by performing partial decompressions at specific regions, gaining a significant reduction in runtime, memory, and storage consumption. Moreover, the complete decompression of a compressed genome can be performed more efficiently through successive partial decompressions.