HSplice: A hybrid approach for predicting 5' splicing junctions
About HSplice
Run HSplice

HSplice can be used for the prediction of donor splice sites, mainly in vertebrtes, in eukaryotic gene. Initially, the positional, dependency and compositional features are extracted by using both positive and negative dataset. Important features are then selected out of all the features. The selected features are then used as input in support vector machine for the prediction of true and false splice sites. The server has been trained with human, cattle and fish splice site datasets. The user has to supply only the test sequence (at least two) in FASTA format to run this server.

Please Cite:

Meher, P. K., Sahu, T. K., Rao, A. R. and Wahi, S. D. (2016). Identification of donor splice sites using support vector machine: a computational approach based on positional, compositional and dependency features. Algorithms for Molecular Biology11(1), 1-12.

Team: Prabina Kumar Meher, Tanmaya Kumar Sahu, A. R. Rao and S. D. Wahi

Contact: meherprabin@yahoo.com; tanmayabioinfo@gmail.com; rao.cshl.work@gmail.com

Technical Assisted By: Jai Bhagwan; jai.kharb@icar.gov.in

Indian Agricultural Statistics Research Institute, (ICAR), Library Avenue, New Delhi - 110012