Title :
Recognizing transcription start site (TSS) of plant promoters
Author :
Loganantharaj, Raja
Author_Institution :
Center for Adv. Comput. Studies, Louisiana Univ., Lafayette, LA, USA
Abstract :
Discovering a promoter or promoters from a given DNA sequence is an active research area in bioinformatics. Many promoter detection algorithms use transcription binding sights and some core promoter elements such as CCAAT and TATA box, to determine the location of transcription start site. For the purpose of comparing the effectiveness of different algorithms, we consider transcription start site in isolation. We use annotated plant promoters for our experiments. We have compared the following algorithms for their effectiveness in detecting a TSS: position weighted matrix (PWM), naive Bayes, decision tree and artificial neural network.
Keywords :
DNA; belief networks; biology computing; botany; decision trees; learning (artificial intelligence); matrix algebra; neural nets; sequences; DNA sequence; artificial neural network; bioinformatics; core promoter elements; decision tree; naive Bayes; plant promoters; position weighted matrix; promoter detection algorithms; transcription binding sights; transcription start site; Artificial neural networks; Bioinformatics; DNA; Decision trees; Detection algorithms; Machine learning algorithms; Pulse width modulation; Sequences; Software tools; Testing;
Conference_Titel :
Information Technology: Coding and Computing, 2005. ITCC 2005. International Conference on
Print_ISBN :
0-7695-2315-3
DOI :
10.1109/ITCC.2005.240
