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ncRNA
Special Issues
Bioinformatics Softwares and Databases for Non-coding RNA Research 2.0
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Bioinformatics Softwares and Databases for Non-coding RNA Research 2.0

A special issue of Non-Coding RNA (ISSN 2311-553X).

Deadline for manuscript submissions: closed (15 March 2021) | Viewed by 16581

Special Issue Editor

Prof. Dr. Y-h. Taguchi

E-Mail Website
Guest Editor
Department of Physics, Chuo University, Tokyo 112-8551, Japan
Interests: bioinformatics; tensor decomposition; feature selection
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Recently, non-coding RNAs have attracted more and more attention from researchers, as they have been found to affect a wider range of biological processes than previously believed. Other than miRNAs that are already known to contribute to many biological processes, including disease and developments, more recently identified non-coding RNAs, e.g., lncRNAs and circRNAs, have begun to serve as the focus of various scientific studies, especially the interaction between these newly identified non-coding RNAs and others, e.g., mRNAs, proteins, and miRNAs, which has been discovered to play critical roles on various biological aspects. Since it is very difficult to confirm the interaction between them because of the large number of potential combinations, computational approaches are more desirable. However, and in spite of the urgency of this need, not a large enough number of bioinformatics tools as well as databases of these non-coding RNAs is available.

In this Special Issue, we encourage researchers to submit papers on the following topics, but not limited to them:

  • Bioinformatics tools and databases of interaction between non-coding RNAs and others;
  • Bioinformatics tools and databases for biomarker identification for diseases with non-coding RNAs;
  • Bioinformatics tools and databases for non-coding RNAs as therapy and drug targets;
  • Bioinformatics tools and databases for regulation of transcription by non-coding RNA;
  • Bioinformatics tools and databases epigenetics affected by non-coding RNAs.

Prof. Dr. Y-h. Taguchi
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Non-Coding RNA is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (3 papers)

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Research

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19 pages, 4398 KiB  
Article
DANSR: A Tool for the Detection of Annotated and Novel Small RNAs
by Jin Zhang, Abdallah M. Eteleeb, Emily B. Rozycki, Matthew J. Inkman, Amy Ly, Russell E. Scharf, Kay Jayachandran, Bradley A. Krasnick, Thomas Mazur, Nicole M. White, Ryan C. Fields and Christopher A. Maher
Non-Coding RNA 2022, 8(1), 9; https://doi.org/10.3390/ncrna8010009 - 13 Jan 2022
Viewed by 3381
Abstract
Existing small noncoding RNA analysis tools are optimized for processing short sequencing reads (17–35 nucleotides) to monitor microRNA expression. However, these strategies under-represent many biologically relevant classes of small noncoding RNAs in the 36–200 nucleotides length range (tRNAs, snoRNAs, etc.). To address this, [...] Read more.
Existing small noncoding RNA analysis tools are optimized for processing short sequencing reads (17–35 nucleotides) to monitor microRNA expression. However, these strategies under-represent many biologically relevant classes of small noncoding RNAs in the 36–200 nucleotides length range (tRNAs, snoRNAs, etc.). To address this, we developed DANSR, a tool for the detection of annotated and novel small RNAs using sequencing reads with variable lengths (ranging from 17–200 nt). While DANSR is broadly applicable to any small RNA dataset, we applied it to a cohort of matched normal, primary, and distant metastatic colorectal cancer specimens to demonstrate its ability to quantify annotated small RNAs, discover novel genes, and calculate differential expression. DANSR is available as an open source tool. Full article
(This article belongs to the Special Issue Bioinformatics Softwares and Databases for Non-coding RNA Research 2.0)
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18 pages, 3088 KiB  
Article
FuncPEP: A Database of Functional Peptides Encoded by Non-Coding RNAs
by Mihnea P. Dragomir, Ganiraju C. Manyam, Leonie Florence Ott, Léa Berland, Erik Knutsen, Cristina Ivan, Leonard Lipovich, Bradley M. Broom and George A. Calin
Non-Coding RNA 2020, 6(4), 41; https://doi.org/10.3390/ncrna6040041 - 23 Sep 2020
Cited by 41 | Viewed by 6488
Abstract
Non-coding RNAs (ncRNAs) are essential players in many cellular processes, from normal development to oncogenic transformation. Initially, ncRNAs were defined as transcripts that lacked an open reading frame (ORF). However, multiple lines of evidence suggest that certain ncRNAs encode small peptides of less [...] Read more.
Non-coding RNAs (ncRNAs) are essential players in many cellular processes, from normal development to oncogenic transformation. Initially, ncRNAs were defined as transcripts that lacked an open reading frame (ORF). However, multiple lines of evidence suggest that certain ncRNAs encode small peptides of less than 100 amino acids. The sequences encoding these peptides are known as small open reading frames (smORFs), many initiating with the traditional AUG start codon but terminating with atypical stop codons, suggesting a different biogenesis. The ncRNA-encoded peptides (ncPEPs) are gradually becoming appreciated as a new class of functional molecules that contribute to diverse cellular processes, and are deregulated in different diseases contributing to pathogenesis. As multiple publications have identified unique ncPEPs, we appreciated the need for assembling a new web resource that could gather information about these functional ncPEPs. We developed FuncPEP, a new database of functional ncRNA encoded peptides, containing all experimentally validated and functionally characterized ncPEPs. Currently, FuncPEP includes a comprehensive annotation of 112 functional ncPEPs and specific details regarding the ncRNA transcripts that encode these peptides. We believe that FuncPEP will serve as a platform for further deciphering the biologic significance and medical use of ncPEPs. The link for FuncPEP database can be found at the end of the Introduction Section. Full article
(This article belongs to the Special Issue Bioinformatics Softwares and Databases for Non-coding RNA Research 2.0)
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Review

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20 pages, 880 KiB  
Review
A Survey of Current Resources to Study lncRNA-Protein Interactions
by Melcy Philip, Tyrone Chen and Sonika Tyagi
Non-Coding RNA 2021, 7(2), 33; https://doi.org/10.3390/ncrna7020033 - 08 Jun 2021
Cited by 15 | Viewed by 5679
Abstract
Phenotypes are driven by regulated gene expression, which in turn are mediated by complex interactions between diverse biological molecules. Protein–DNA interactions such as histone and transcription factor binding are well studied, along with RNA–RNA interactions in short RNA silencing of genes. In contrast, [...] Read more.
Phenotypes are driven by regulated gene expression, which in turn are mediated by complex interactions between diverse biological molecules. Protein–DNA interactions such as histone and transcription factor binding are well studied, along with RNA–RNA interactions in short RNA silencing of genes. In contrast, lncRNA-protein interaction (LPI) mechanisms are comparatively unknown, likely directed by the difficulties in studying LPI. However, LPI are emerging as key interactions in epigenetic mechanisms, playing a role in development and disease. Their importance is further highlighted by their conservation across kingdoms. Hence, interest in LPI research is increasing. We therefore review the current state of the art in lncRNA-protein interactions. We specifically surveyed recent computational methods and databases which researchers can exploit for LPI investigation. We discovered that algorithm development is heavily reliant on a few generic databases containing curated LPI information. Additionally, these databases house information at gene-level as opposed to transcript-level annotations. We show that early methods predict LPI using molecular docking, have limited scope and are slow, creating a data processing bottleneck. Recently, machine learning has become the strategy of choice in LPI prediction, likely due to the rapid growth in machine learning infrastructure and expertise. While many of these methods have notable limitations, machine learning is expected to be the basis of modern LPI prediction algorithms. Full article
(This article belongs to the Special Issue Bioinformatics Softwares and Databases for Non-coding RNA Research 2.0)
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