SMEpred workbench: A web server for predicting efficacy of chemicallymodified siRNAs.

ABSTRACT: Chemical modifications have been extensively exploited to circumvent shortcomings in therapeutic applications of small interfering RNAs (siRNAs). However, experimental designing and testing of these siRNAs or chemically modified siRNAs (cm-siRNAs) involves enormous resources. Therefore, in-silico intervention in designing cm-siRNAs would be of utmost importance. We developed SMEpred workbench to predict the efficacy of normal siRNAs as well as cm-siRNAs using 3031 heterogeneous cm-siRNA sequences from siRNAmod database. These include 30 frequently used chemical modifications on different positions of either siRNA strand. Support Vector Machine (SVM) was employed to develop predictive models utilizing various sequence features namely mono-, di-nucleotide composition, binary pattern and thei

SUBMITTER: Dar SA 

PROVIDER: S-EPMC5100349 | biostudies-literature | 2016 Nov

REPOSITORIES: biostudies-literature