miRDetect: A combinatorial approach for automated detection of novel miRNA precursors from plant EST data using homology and Random Forest classification.

Ayachit, Garima; Pandya, Himanshu; Das, Jayashankar

Ayachit, Garima; Pandya, Himanshu; Das, Jayashankar.

Affiliation

Ayachit G; Department of Botany, Bioinformatics and Climate Change, Gujarat University, Ahmedabad, India.
Pandya H; Department of Botany, Bioinformatics and Climate Change, Gujarat University, Ahmedabad, India. Electronic address: hapandya@gmail.com.
Das J; Centre for Genomics & Biomedical Informatics, IMS and SUM Hospital, Siksha "O" Anusandhan University (Deemed to be), K8, Kalinga Nagar, Bhubaneswar, Odisha 751003, India. Electronic address: jayashankardas@soa.ac.in.

Genomics ; 112(5): 3201-3206, 2020 09.

Article in En | MEDLINE | ID: mdl-32380232

Subject(s)

MicroRNAs/chemistry; RNA Precursors/chemistry; RNA, Plant/chemistry; Sequence Analysis, RNA/methods; Expressed Sequence Tags; Machine Learning; Sequence Homology, Nucleic Acid; Software

Key words

EST; Machine learning; Novel precursor; Pipeline; Plant; miRNA

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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: RNA Precursors / Sequence Analysis, RNA / RNA, Plant / MicroRNAs Type of study: Clinical_trials / Diagnostic_studies / Prognostic_studies Language: En Journal: Genomics Journal subject: GENETICA Year: 2020 Document type: Article Affiliation country: India Country of publication: United States

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