A computing approach for biological sequences /
Mohammad Nassef Fattoh Abdelrahman
A computing approach for biological sequences / منهج حسابى للتسلسلات البيولوجية Mohammad Nassef Fattoh Abdelrahman ; Supervised Ibrahim Farag Abdelrahman , Amr Ahmed Anwar Ali Badr - Cairo : Mohammad Nassef Fattoh Abdelrahman , 2014 - 96 Leaves ; 30cm
Thesis (Ph.D.) - Cairo University - Faculty of Computers and Information - Department of Computer Science
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 (such as motifs and retro - transposons) 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. Many techniques have emerged to store genomes in the lowest possible space. Reference - based compression algorithms (RbCs) efficiently compress the sequenced genomes by mainly storing their differences with respect to another sequenced reference genome. Therefore, RbCs give very high 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
Genome partial decompression Referential compression algorithms Referentially compressed genomes
A computing approach for biological sequences / منهج حسابى للتسلسلات البيولوجية Mohammad Nassef Fattoh Abdelrahman ; Supervised Ibrahim Farag Abdelrahman , Amr Ahmed Anwar Ali Badr - Cairo : Mohammad Nassef Fattoh Abdelrahman , 2014 - 96 Leaves ; 30cm
Thesis (Ph.D.) - Cairo University - Faculty of Computers and Information - Department of Computer Science
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 (such as motifs and retro - transposons) 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. Many techniques have emerged to store genomes in the lowest possible space. Reference - based compression algorithms (RbCs) efficiently compress the sequenced genomes by mainly storing their differences with respect to another sequenced reference genome. Therefore, RbCs give very high 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
Genome partial decompression Referential compression algorithms Referentially compressed genomes