An Algorithm for Template-Based Prediction of Secondary Structures of Individual RNA Sequences

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61388971%3A_____%2F17%3A00480493" target="_blank" >RIV/61388971:_____/17:00480493 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.3389/fgene.2017.00147" target="_blank" >http://dx.doi.org/10.3389/fgene.2017.00147</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3389/fgene.2017.00147" target="_blank" >10.3389/fgene.2017.00147</a>

Jazyk výsledku

angličtina

Název v původním jazyce

An Algorithm for Template-Based Prediction of Secondary Structures of Individual RNA Sequences

Popis výsledku v původním jazyce

While understanding the structure of RNA molecules is vital for deciphering their functions, determining RNA structures experimentally is exceptionally hard. At the same time, extant approaches to computational RNA structure prediction have limited applicability and reliability. In this paper we provide a method to solve a simpler yet still biologically relevant problem: prediction of secondary RNA structure using structure of different molecules as a template. Our method identifies conserved and unconserved subsequences within an RNA molecule. For conserved subsequences, the template structure is directly transferred into the generated structure and combined with de-novo predicted structure for the unconserved subsequences with low evolutionary conservation. The method also determines, when the generated structure is unreliable. The method is validated using experimentally identified structures. The accuracy of the method exceeds that of classical prediction algorithms and constrained prediction methods. This is demonstrated by comparison using large number of heterogeneous RNAs. The presented method is fast and robust, and useful for various applications requiring knowledge of secondary structures of individual RNA sequences.

Název v anglickém jazyce

An Algorithm for Template-Based Prediction of Secondary Structures of Individual RNA Sequences

Popis výsledku anglicky

While understanding the structure of RNA molecules is vital for deciphering their functions, determining RNA structures experimentally is exceptionally hard. At the same time, extant approaches to computational RNA structure prediction have limited applicability and reliability. In this paper we provide a method to solve a simpler yet still biologically relevant problem: prediction of secondary RNA structure using structure of different molecules as a template. Our method identifies conserved and unconserved subsequences within an RNA molecule. For conserved subsequences, the template structure is directly transferred into the generated structure and combined with de-novo predicted structure for the unconserved subsequences with low evolutionary conservation. The method also determines, when the generated structure is unreliable. The method is validated using experimentally identified structures. The accuracy of the method exceeds that of classical prediction algorithms and constrained prediction methods. This is demonstrated by comparison using large number of heterogeneous RNAs. The presented method is fast and robust, and useful for various applications requiring knowledge of secondary structures of individual RNA sequences.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10606 - Microbiology

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Frontiers in genetics

ISSN

1664-8021

e-ISSN

—

Svazek periodika

8

Číslo periodika v rámci svazku

OCT 10

Stát vydavatele periodika

CH - Švýcarská konfederace

Počet stran výsledku

11

Strana od-do

—

Kód UT WoS článku

000412633900001

EID výsledku v databázi Scopus

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