Recommendations for Bioinformatic Tools in lncRNA Research
Publikation: Bidrag til tidsskrift › Review › Forskning › fagfællebedømt
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Recommendations for Bioinformatic Tools in lncRNA Research. / Distefano, Rebecca; Ilieva, Mirolyuba; Rennie, Sarah; Uchida, Shizuka.
I: Current Bioinformatics, Bind 19, Nr. 1, 2024, s. 14-20.Publikation: Bidrag til tidsskrift › Review › Forskning › fagfællebedømt
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TY - JOUR
T1 - Recommendations for Bioinformatic Tools in lncRNA Research
AU - Distefano, Rebecca
AU - Ilieva, Mirolyuba
AU - Rennie, Sarah
AU - Uchida, Shizuka
N1 - Publisher Copyright: © 2024 Bentham Science Publishers.
PY - 2024
Y1 - 2024
N2 - Long non-coding RNAs (lncRNAs) typically refer to non-protein coding RNAs that are longer than 200 nucleotides. Historically dismissed as junk DNA, over two decades of research have re-vealed that lncRNAs bind to other macromolecules (e.g., DNA, RNA, and/or proteins) to modulate signaling pathways and maintain organism viability. Their discovery has been significantly aided by the development of bioinformatics tools in recent years. However, the diversity of tools for lncRNA discovery and functional prediction can present a challenge for researchers, especially bench scientists and cli-nicians. This Perspective article aims to navigate the current landscape of bioinformatic tools suitable for both protein-coding and lncRNA genes. It aims to provide a guide for bench scientists and clinicians to select the appropriate tools for their research questions and experimental designs.
AB - Long non-coding RNAs (lncRNAs) typically refer to non-protein coding RNAs that are longer than 200 nucleotides. Historically dismissed as junk DNA, over two decades of research have re-vealed that lncRNAs bind to other macromolecules (e.g., DNA, RNA, and/or proteins) to modulate signaling pathways and maintain organism viability. Their discovery has been significantly aided by the development of bioinformatics tools in recent years. However, the diversity of tools for lncRNA discovery and functional prediction can present a challenge for researchers, especially bench scientists and cli-nicians. This Perspective article aims to navigate the current landscape of bioinformatic tools suitable for both protein-coding and lncRNA genes. It aims to provide a guide for bench scientists and clinicians to select the appropriate tools for their research questions and experimental designs.
KW - Bioinformatics
KW - gene expression
KW - lncRNA
KW - RNA-seq
KW - screening
KW - tools
U2 - 10.2174/1574893618666230707103956
DO - 10.2174/1574893618666230707103956
M3 - Review
AN - SCOPUS:85185474639
VL - 19
SP - 14
EP - 20
JO - Current Bioinformatics
JF - Current Bioinformatics
SN - 1574-8936
IS - 1
ER -
ID: 384492157