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dc.contributor.authorKiron, Md. Ismail
dc.contributor.authorSumon, Md. Enamul Haque
dc.contributor.authorMourey, Jannatul Maksuda
dc.contributor.authorUllah, Md. Zayed
dc.date.accessioned2016-01-03T15:42:31Z
dc.date.available2016-01-03T15:42:31Z
dc.date.issued2015
dc.identifier.otherID 12101076
dc.identifier.otherID 15341034
dc.identifier.otherID14101270
dc.identifier.otherID 12101119
dc.identifier.urihttp://hdl.handle.net/10361/4664
dc.descriptionThis thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2015.en_US
dc.description.abstractIn this ever-fast running modern world of technologies, bioinformatics is not lagging behind. It is now possible to connect one’s smart phone to the huge database of bioinformatics where one can find thousands of gene and organism information in a few seconds. This project of an Android mobile application is another dimension that has been added to the features of smart phones. This mobile app will allow the researchers and the students in the field of bioinformatics to have access to the NCBI website’s BLAST protein sequences as well as the Blosum62 matrix used for the Smith-Waterman algorithm to identify and deduce similarities between sequences. Local alignment and global alignment features were selected for the application. Upon testing of the programming language Java was found to be the most optimal language. On the basis of time complexity, space complexity etc. Smith-Waterman and BLAST algorithms were chosen for the application. First the algorithms were implemented for the computer system using Java. This was done in two parts, firstly implementation of the algorithms and secondly parsing data from the database server. Gradually the program was incorporated into smart phone system. Finally, the application was evaluated in the smart phone system using both sequence input and accession ID input of protein sequences. The results obtained from the app in the smart phone system were compared to the existing computer system which proved that new system is providing the same results. In future this app will be expanded to other platforms of mobile operating systems and additional functions will be added.en_US
dc.language.isoenen_US
dc.publisherBRAC Universityen_US
dc.subjectComputer science and engineeringen_US
dc.subjectBLASTen_US
dc.subjectSmith-Watermanen_US
dc.subjectProtein sequenceen_US
dc.subjectAalignmenten_US
dc.subjectAndroiden_US
dc.subjectJavaen_US
dc.titleA mobile application on performing blast analysis and local alignmenten_US
dc.typeThesisen_US


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