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Comparative analysis of protein-coding and long non-coding transcripts based on RNA sequence features. / Volkova, Oxana A.; Kondrakhin, Yury V.; Kashapov, Timur A. et al.

In: Journal of Bioinformatics and Computational Biology, Vol. 16, No. 2, 1840013, 01.04.2018.

Research output: Contribution to journalArticlepeer-review

Harvard

Volkova, OA, Kondrakhin, YV, Kashapov, TA & Sharipov, RN 2018, 'Comparative analysis of protein-coding and long non-coding transcripts based on RNA sequence features', Journal of Bioinformatics and Computational Biology, vol. 16, no. 2, 1840013. https://doi.org/10.1142/S0219720018400139

APA

Volkova, O. A., Kondrakhin, Y. V., Kashapov, T. A., & Sharipov, R. N. (2018). Comparative analysis of protein-coding and long non-coding transcripts based on RNA sequence features. Journal of Bioinformatics and Computational Biology, 16(2), [1840013]. https://doi.org/10.1142/S0219720018400139

Vancouver

Volkova OA, Kondrakhin YV, Kashapov TA, Sharipov RN. Comparative analysis of protein-coding and long non-coding transcripts based on RNA sequence features. Journal of Bioinformatics and Computational Biology. 2018 Apr 1;16(2):1840013. doi: 10.1142/S0219720018400139

Author

Volkova, Oxana A. ; Kondrakhin, Yury V. ; Kashapov, Timur A. et al. / Comparative analysis of protein-coding and long non-coding transcripts based on RNA sequence features. In: Journal of Bioinformatics and Computational Biology. 2018 ; Vol. 16, No. 2.

BibTeX

@article{3d107234358d4d7b9aa0582cae917d4b,
title = "Comparative analysis of protein-coding and long non-coding transcripts based on RNA sequence features",
abstract = "RNA plays an important role in the intracellular cell life and in the organism in general. Besides the well-established protein coding RNAs (messenger RNAs, mRNAs), long non-coding RNAs (lncRNAs) have gained the attention of recent researchers. Although lncRNAs have been classified as non-coding, some authors reported the presence of corresponding sequences in ribosome profiling data (Ribo-seq). Ribo-seq technology is a powerful experimental tool utilized to characterize RNA translation in cell with focus on initiation (harringtonine, lactimidomycin) and elongation (cycloheximide). By exploiting translation starts obtained from the Ribo-seq experiment, we developed a novel position weight matrix model for the prediction of translation starts. This model allowed us to achieve 96% accuracy of discrimination between human mRNAs and lncRNAs. When the same model was used for the prediction of putative ORFs in RNAs, we discovered that the majority of lncRNAs contained only small ORFs (≤300nt) in contrast to mRNAs.",
keywords = "discriminant analysis, human lncRNAs, Human mRNAs, IPSmatrix algorithm, position weight matrix approach, small ORFs, MOUSE, MUSCLE, GENE-REGULATION, TRANSLATION, CONSERVATION, DYNAMICS, PREDICTIONS, ARABIDOPSIS, REVEALS, Protein Biosynthesis, Open Reading Frames, Ribosomes/genetics, Computational Biology/methods, Proteins/genetics, RNA, Messenger/genetics, 3' Untranslated Regions, Algorithms, Sequence Analysis, RNA, 5' Untranslated Regions, RNA, Long Noncoding",
author = "Volkova, {Oxana A.} and Kondrakhin, {Yury V.} and Kashapov, {Timur A.} and Sharipov, {Ruslan N.}",
note = "Publisher Copyright: {\textcopyright} 2018 World Scientific Publishing Europe Ltd.",
year = "2018",
month = apr,
day = "1",
doi = "10.1142/S0219720018400139",
language = "English",
volume = "16",
journal = "Journal of Bioinformatics and Computational Biology",
issn = "0219-7200",
publisher = "World Scientific Publishing Co. Pte Ltd",
number = "2",

}

RIS

TY - JOUR

T1 - Comparative analysis of protein-coding and long non-coding transcripts based on RNA sequence features

AU - Volkova, Oxana A.

AU - Kondrakhin, Yury V.

AU - Kashapov, Timur A.

AU - Sharipov, Ruslan N.

N1 - Publisher Copyright: © 2018 World Scientific Publishing Europe Ltd.

PY - 2018/4/1

Y1 - 2018/4/1

N2 - RNA plays an important role in the intracellular cell life and in the organism in general. Besides the well-established protein coding RNAs (messenger RNAs, mRNAs), long non-coding RNAs (lncRNAs) have gained the attention of recent researchers. Although lncRNAs have been classified as non-coding, some authors reported the presence of corresponding sequences in ribosome profiling data (Ribo-seq). Ribo-seq technology is a powerful experimental tool utilized to characterize RNA translation in cell with focus on initiation (harringtonine, lactimidomycin) and elongation (cycloheximide). By exploiting translation starts obtained from the Ribo-seq experiment, we developed a novel position weight matrix model for the prediction of translation starts. This model allowed us to achieve 96% accuracy of discrimination between human mRNAs and lncRNAs. When the same model was used for the prediction of putative ORFs in RNAs, we discovered that the majority of lncRNAs contained only small ORFs (≤300nt) in contrast to mRNAs.

AB - RNA plays an important role in the intracellular cell life and in the organism in general. Besides the well-established protein coding RNAs (messenger RNAs, mRNAs), long non-coding RNAs (lncRNAs) have gained the attention of recent researchers. Although lncRNAs have been classified as non-coding, some authors reported the presence of corresponding sequences in ribosome profiling data (Ribo-seq). Ribo-seq technology is a powerful experimental tool utilized to characterize RNA translation in cell with focus on initiation (harringtonine, lactimidomycin) and elongation (cycloheximide). By exploiting translation starts obtained from the Ribo-seq experiment, we developed a novel position weight matrix model for the prediction of translation starts. This model allowed us to achieve 96% accuracy of discrimination between human mRNAs and lncRNAs. When the same model was used for the prediction of putative ORFs in RNAs, we discovered that the majority of lncRNAs contained only small ORFs (≤300nt) in contrast to mRNAs.

KW - discriminant analysis

KW - human lncRNAs

KW - Human mRNAs

KW - IPSmatrix algorithm

KW - position weight matrix approach

KW - small ORFs

KW - MOUSE

KW - MUSCLE

KW - GENE-REGULATION

KW - TRANSLATION

KW - CONSERVATION

KW - DYNAMICS

KW - PREDICTIONS

KW - ARABIDOPSIS

KW - REVEALS

KW - Protein Biosynthesis

KW - Open Reading Frames

KW - Ribosomes/genetics

KW - Computational Biology/methods

KW - Proteins/genetics

KW - RNA, Messenger/genetics

KW - 3' Untranslated Regions

KW - Algorithms

KW - Sequence Analysis, RNA

KW - 5' Untranslated Regions

KW - RNA, Long Noncoding

UR - http://www.scopus.com/inward/record.url?scp=85046857488&partnerID=8YFLogxK

U2 - 10.1142/S0219720018400139

DO - 10.1142/S0219720018400139

M3 - Article

C2 - 29739305

AN - SCOPUS:85046857488

VL - 16

JO - Journal of Bioinformatics and Computational Biology

JF - Journal of Bioinformatics and Computational Biology

SN - 0219-7200

IS - 2

M1 - 1840013

ER -

ID: 13360772