loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Müşerref Duygu Saçar and Jens Allmer

Affiliation: Izmir Institute of Technology, Turkey

Keyword(s): miRNA, Ab Initio, miRNA Prediction, Comparison.

Related Ontology Subjects/Areas/Topics: Algorithms and Software Tools ; Bioinformatics ; Biomedical Engineering ; Data Mining and Machine Learning ; Sequence Analysis ; Transcriptomics

Abstract: MicroRNAs are small RNA sequences of 18-24 nucleotides in length, which serve as templates to drive post transcriptional gene silencing. The canonical microRNA pathway starts with transcription from DNA and is followed by processing by the Microprocessor complex, yielding a hairpin structure. This is then exported into the cytosol where it is processed by Dicer and next incorporated into the RNA induced silencing complex. All of these biogenesis steps add to the overall specificity of miRNA production and effect. Unfortunately, experimental detection of miRNAs is cumbersome and therefore computational tools are necessary. Homology-based miRNA prediction tools are limited by fast miRNA evolution and by the fact that they are template driven. Ab initio miRNA prediction methods have been proposed but they have not been analyzed competitively so that their relative performance is largely unknown. Here we implement the features proposed in four miRNA ab initio studies and evaluate them on two data sets. Using the features described in Bentwich 2008 leads to the highest accuracy but still does not provide enough confidence into the results to warrant experimental validation of all predictions in a larger genome like the human genome. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.226.226.158

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Saçar, M. and Allmer, J. (2013). Comparison of Four Ab Initio MicroRNA Prediction Tools. In Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms (BIOSTEC 2013) - BIOINFORMATICS; ISBN 978-989-8565-35-8; ISSN 2184-4305, SciTePress, pages 190-195. DOI: 10.5220/0004248201900195

@conference{bioinformatics13,
author={Müşerref Duygu Sa\c{C}ar. and Jens Allmer.},
title={Comparison of Four Ab Initio MicroRNA Prediction Tools},
booktitle={Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms (BIOSTEC 2013) - BIOINFORMATICS},
year={2013},
pages={190-195},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004248201900195},
isbn={978-989-8565-35-8},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms (BIOSTEC 2013) - BIOINFORMATICS
TI - Comparison of Four Ab Initio MicroRNA Prediction Tools
SN - 978-989-8565-35-8
IS - 2184-4305
AU - Saçar, M.
AU - Allmer, J.
PY - 2013
SP - 190
EP - 195
DO - 10.5220/0004248201900195
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic