miREval 2.0: a web tool for simple microRNA prediction in genome sequences

Dadi Gao; Robert Middleton; John E. J. Rasko; William Ritchie

doi:10.1093/bioinformatics/btt545

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miREval 2.0: a web tool for simple microRNA prediction in genome sequences

Article de revue

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miREval 2.0: a web tool for simple microRNA prediction in genome sequences

Dadi Gao, Robert Middleton, John E. J. Rasko et William Ritchie

BIOINFORMATICS, Vol.29(24), pp.3225-3226

15/12/2013

DOI: https://doi.org/10.1093/bioinformatics/btt545

PMID: 24048357

Résumé

Biochemical Research Methods

Biochemistry & Molecular Biology

Biotechnology & Applied Microbiology

Computer Science

Computer Science, Interdisciplinary Applications

Life Sciences & Biomedicine

Mathematical & Computational Biology

Mathematics

Physical Sciences

Science & Technology

Statistics & Probability

Technology

Result: We have developed miREval 2.0, an online tool that can simultaneously search up to 100 sequences for novel microRNAs ( miRNAs) in multiple organisms. miREval 2.0 uses multiple published in silico approaches to detect miRNAs in sequences of interest. This tool can be used to discover miRNAs from DNA sequences or to validate candidates from sequencing data.

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Détails

Titre: miREval 2.0: a web tool for simple microRNA prediction in genome sequences
Créateurs - sans rôle: Dadi Gao - Univ Sydney, Centenary Inst, Bioinformat Lab, Sydney, NSW 2006, Australia
Robert Middleton - Univ Sydney, Centenary Inst, Bioinformat Lab, Sydney, NSW 2006, Australia
John E. J. Rasko - The University of Sydney
William Ritchie - Univ Sydney, Centenary Inst, Bioinformat Lab, Sydney, NSW 2006, Australia
Détails de publication: BIOINFORMATICS, Vol.29(24), pp.3225-3226
Éditeur: Oxford Univ Press
Nombre de pages: 2
Note de subvention: Rebecca L. Cooper Foundation 571156 / Australian National Health and Medical Research Council; National Health & Medical Research Council (NHMRC) of Australia 12/CDF/2-28 / Cancer Institute NSW Cell and Gene Trust [Cure The Future] 1006260 / Cancer Council NSW; Cancer Council New South Wales
Identifiants: 99139772109311
Unité académique: Institut de Génétique Humaine - IGH
Langue: English
Type de ressource: Journal article