Protein-protein interaction network alignment using GPU

dc.contributor.advisor Bozkuş, Zeki en_US
dc.contributor.author Bozkuş, Zeki
dc.contributor.other Computer Engineering
dc.date.accessioned 2019-07-12T08:41:03Z en_US
dc.date.available 2019-07-12T08:41:03Z en_US
dc.date.issued 2016 en_US
dc.department Enstitüler, Lisansüstü Eğitim Enstitüsü, Bilgisayar Mühendisliği Ana Bilim Dalı en_US
dc.department-temp Kadir Has University : Graduate School of Science and Engineering: Computer Engineering en_US
dc.description.abstract The alignment of Protein-Protein interaction Networks is becoming an imperative phenomenon in Bio-informatics that leads to several vital results. These results can be used in numerous fields associated with Bio-informatics including the prediction/variation of evolutionary relationships finding cures for gene inflicted diseases (like cancer) and identifying probable therapies. However with the introduction of fast sequencing and other technologies that spawn large amounts of data for computing (since the proteins are very large in size and have many nodes and edges) limiting dynamics arise. These include performance scalability and time consumption. Recently CPU versions of the alignment procedures and computations have been introduced. However because of the large size of the proteins they are very time-consuming. Therefore in this thesis i propose a GPU version for performing the computations quickly and efficiently. This thesis is based on improving the efficiency of SPiNAL a polynomial time heuristic algorithm introduced by [1] that finds the similarities between pairs of PPi-Networks. in this thesis the sequential algorithm of SPiNAL is converted into a parallel algorithm using Heterogeneous Programming Library (HPL) that performs the computations in a massively parallel fashion on a single GPU with 448 thread processors a clock rate of 1.15 Giga Hertz and 6 Giga Bytes of DRAM. The modifications/enhancements to the algorithm result in a significant speedup as compared to the benchmark algorithms. en_US
dc.description.abstract The alignment of Protein-Protein Interaction Networks is becoming an imperative phenomenon in Bio-Informatics that leads to several vital results. These results can be used in numerous fields associated with Bio-Informatics including the prediction/variation of evolutionary relationships, finding cures for gene inflicted diseases (like cancer) and identifying probable therapies. However, with the introduction of fast sequencing and other technologies that spawn large amounts of data for computing (since the proteins are very large in size and have many nodes and edges), limiting dynamics arise. These include performance, scalability and time consumption. Recently, CPU versions of the alignment procedures and computations have been introduced. However, because of the large size of the proteins, they are very time-consuming. Therefore, in this thesis, I propose a GPU version for performing the computations quickly and efficiently. This thesis is based on improving the efficiency of SPINAL, a polynomial time heuristic algorithm introduced by [1] that finds the similarities between pairs of PPI-Networks. In this thesis, the sequential algorithm of SPINAL is converted into a parallel algorithm using Heterogeneous Programming Library (HPL) that performs the computations in a massively parallel fashion on a single GPU with 448 thread processors, a clock rate of 1.15 Giga Hertz and 6 Giga Bytes of DRAM. The modifications/enhancements to the algorithm result in a significant speedup as compared to the benchmark algorithms. en_US
dc.identifier.uri https://hdl.handle.net/20.500.12469/2463
dc.identifier.yoktezid 430110 en_US
dc.language.iso en en_US
dc.publisher Kadir Has Üniversitesi en_US
dc.relation.publicationcategory Tez en_US
dc.rights info:eu-repo/semantics/openAccess en_US
dc.subject Protein-protein interaction networks en_US
dc.subject Graphics Processing Unit en_US
dc.subject Scalable Protein Interaction Network Alignment en_US
dc.subject Parallel Programming en_US
dc.subject Heterogeneous Programming Library en_US
dc.subject Protein-Protein Etkileşim Ağı en_US
dc.subject Grafik İşleme Birimi en_US
dc.subject Ölçeklenebilir Protein Etkileşim Ağları Dizilemesi en_US
dc.subject Paralel Programlama en_US
dc.subject Heterojen Programlama Kütüphanesi en_US
dc.title Protein-protein interaction network alignment using GPU en_US
dc.type Master Thesis en_US
dspace.entity.type Publication
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