Classification of Long Noncoding RNAs by k-mer Content
| Autor: | J. Mauro Calabrese, Daniel Sprague, Jessime M. Kirk |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
0303 health sciences
Computational Biology Sequence alignment Computational biology Biology Long non-coding RNA Article 03 medical and health sciences 0302 clinical medicine k-mer Protein Binding Motif Cluster Analysis RNA Long Noncoding Nucleotide Motifs Unsupervised clustering 030217 neurology & neurosurgery Algorithms 030304 developmental biology Protein Binding |
| Zdroj: | Methods Mol Biol Methods in Molecular Biology ISBN: 9781071611579 |
| ISSN: | 1940-6029 |
| Popis: | K-mer based comparisons have emerged as powerful complements to BLAST-like alignment algorithms, particularly when the sequences being compared lack direct evolutionary relationships. In this chapter, we describe methods to compare k-mer content between groups of long noncoding RNAs (lncRNAs), to identify communities of lncRNAs with related k-mer contents, to identify the enrichment of protein-binding motifs in lncRNAs, and to scan for domains of related k-mer contents in lncRNAs. Our step-by-step instructions are complemented by Python code deposited in Github. Though our chapter focuses on lncRNAs, the methods we describe could be applied to any set of nucleic acid sequences. |
| Databáze: | OpenAIRE |
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