Title :
Identification of promoter through stochastic approach
Author :
Jabid, Taskeed ; Anwar, Firoz ; Baker, Syed Murtuza ; Shoyaib, Mohammad
Author_Institution :
East West Univ., Dhaka
Abstract :
Analysis of a gene sequence, which is transcribed into RNA and then translated into protein, is a difficult task. If this could be achieved, it would make possible better understand how the organisms are developed from DNA information. The behavior of gene is highly influenced by promoter sequences residing upstream or downstream of the Transcription Start Site (TSS). The promoter recognition process is a part of the complex process where genes interact with each other over time and actually regulates the whole working process of a cell. This paper attempts to develop an efficient algorithm that can successfully distinguish promoters and non promoters by analyzing statistical data. A learning model is developed from the known dataset to predict the unknown ones.
Keywords :
biology computing; data analysis; identification; statistical analysis; stochastic processes; DNA information; Transcription Start Site; algorithm; deoxyribonucleic acid; gene sequence; learning model; promoter recognition process; promoter sequence; statistical data analysis; stochastic approach; Biological information theory; DNA; Data analysis; Hidden Markov models; Organisms; Proteins; RNA; Sequences; Stochastic processes; Support vector machines; DNA; Promoter; Support Vector Machine (SVM); Transcriptional Start Site (TSS);
Conference_Titel :
Computer and information technology, 2007. iccit 2007. 10th international conference on
Conference_Location :
Dhaka
Print_ISBN :
978-1-4244-1550-2
Electronic_ISBN :
978-1-4244-1551-9
DOI :
10.1109/ICCITECHN.2007.4579366