title: RNA-SSPT: RNA Secondary Structure Prediction Tools.
abstract: The prediction of RNA structure is useful for understanding evolution for both in silico and in vitro studies. Physical methods like NMR studies to predict RNA secondary structure are expensive and difficult. Computational RNA secondary structure prediction is easier. Comparative sequence analysis provides the best solution. But secondary structure prediction of a single RNA sequence is challenging. RNA-SSPT is a tool that computationally predicts secondary structure of a single RNA sequence. Most of the RNA secondary structure prediction tools do not allow pseudoknots in the structure or are unable to locate them. Nussinov dynamic programming algorithm has been implemented in RNA-SSPT. The current studies shows only energetically most favorable secondary structure is required and the algorithm modification is also available that produces base pairs to lower the total free energy of the secondary structure. For visualization of RNA secondary structure, NAVIEW in C language is used and modified in C# for tool requirement. RNA-SSPT is built in C# using Dot Net 2.0 in Microsoft Visual Studio 2005 Professional edition. The accuracy of RNA-SSPT is tested in terms of Sensitivity and Positive Predicted Value. It is a tool which serves both secondary structure prediction and secondary structure visualization purposes.
authors.affiliation: Department of Bioinformatics and Biotechnology, G C University, Faisalabad, Pakistan.
authors.forename: Freed
authors.initials: F
authors.lastname: Ahmad
authors.forename: Shahid
authors.initials: S
authors.lastname: Mahboob
authors.forename: Tahsin
authors.initials: T
authors.lastname: Gulzar
authors.forename: Salah U
authors.initials: SU
authors.lastname: Din
authors.forename: Tanzeela
authors.initials: T
authors.lastname: Hanif
authors.forename: Hifza
authors.initials: H
authors.lastname: Ahmad
authors.forename: Muhammad
authors.initials: M
authors.lastname: Afzal
keywords: C#; Nussinov algorithm; RNA secondary structure prediction; dot net