Abstract

According to the central dogma of Biology it was commonly accepted that most of the genetic information was transacted by proteins. Recent experimental techniques revealed that the majority of mammalian genomes and other complex organisms are in fact transcribed into non-coding RNAs. Typically, non-coding RNAs are small nucleotide sequences that are not transcribed into proteins and have a profound regulatory role. Present advances in computational biosciences linked their abnormal functionality to many diseases and re-stated the principles of basic therapeutic strategies. The effective identification of non-coding RNAs and their biological role emerges as a new and challenging bioinformatics problem. ncRNAclass ( http://biotools.ceid.upatras.gr/ncrnaclass/ ) is a web platform that allows for efficient computation of a set of features that can describe effectively the broad class of non-coding RNAs. Moreover, it enables the calculation of features that include information about the targeting behavior of miRNAs. The tool operates under a user-friendly interface and its pilot implementation incorporates prediction models for the well-known class of microRNAs and for prediction their mRNA targets. The prediction models are based on two novel evolutionary Machine Learning algorithms that achieve very high classification performance in comparison with existing methods. The platform is also equipped with a data warehouse, with manually curated sequences, that enables fast information retrieval and data mining utilities.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.