RNAs in Biology
A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "RNA".
Deadline for manuscript submissions: 20 May 2024 | Viewed by 2662
Special Issue Editor
2. Department of Medicine, State University of New York at Buffalo, Buffalo, NY 14203, USA
3. New York State Center of Excellence in Bioinformatics and Life Sciences, State University of New York at Buffalo, Buffalo, NY 14203, USA
Interests: bioinformatics; genomics; gene regulation; miRNA; genetic variation
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
RNA has played a broad range of roles in cellular processes. These include controlling gene expression, transferring information from genomic DNA to protein molecules, mediating molecular interactions, and catalyzing chemical reactions. In the human genome, tens of thousands of RNA sequences do not translate into proteins but help regulate gene expression at transcriptional and post-transcription levels. Recent advances in genomic technologies have revealed that RNA-based gene regulation by different classes of non-coding RNAs is involved in almost every aspect of biology, including development, disease progression, and pathogenesis.
This Special Issue welcomes reviews and research articles on a broad range of RNA biology. We will consider manuscripts on topics including, but not limited to, studies on the ways RNAs influence gene expression, the characterization of function for different classes of RNAs in cellular development, the role of RNAs in disease, the functions of various types of non-coding RNAs, and especially the identification and characterization of the role of non-coding regulatory RNAs and their regulatory networks. We look forward to your contributions.
Dr. Zihua Hu
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. Genes is an international peer-reviewed open access monthly 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 2600 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.
Keywords
- regulatory RNAs
- non-coding RNAs
- RNA in disease and therapy
- RNA modifications, including editing
- RNA–RNA interactions, including microRNAs
- RNA in transcriptional and post-transcriptional regulation
- non-coding RNA in epigenetic regulation
Planned Papers
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
1. title: Hypergraph Learning with Restart-based Association Masking and DCE Loss for miRNA-Disease Prediction
Abstract: Accumulating scientific evidence highlights the pivotal role of miRNA-Disease association research in elucidating disease pathogenesis and developing innovative diagnostics . Consequently, accurately identifying disease-associated miRNAs has emerged as a prominent research topic in bioinformatics.Advances in Graph Neural Networks (GNNs) have catalyzed methodological breakthroughs in this field.However, existing methods are often affected by data noise and insufficient information utilization, limiting their predictive performance. To address this, we introduce PGCMDA, an innovative hypergraph learning framework that incorporates random walk with restart-based association masking and DCE Loss to infer miRNA-disease associations.PGCMDA starts by constructing multiple homogeneous similarity networks. A novel enhancement of our approach is the introduction of a restart-based random walk association masking strategy. By stochastically masking a subset of association data and integrating it with a GCN enhanced by an attention mechanism, this strategy enables better capture of key information, leading to improved information utilization and reduced impact of noisy data. Next, we build a miRNA-disease heterogeneous hypergraph and employ Graph Convolutional Networks (GCNs) to facilitate advanced information fusion and knowledge discovery. Lastly, We utilize the DCE Loss function to steer the training of the model, effectively addressing class imbalance and probability distribution discrepancies, thereby optimizing the model’s performance.To evaluate the performance of PGCMDA, comprehensive comparisons were conducted with state-of-the-art methods. Additionally, in-depth case studies on lung cancer and colorectal cancer were performed. The results demonstrate PGCMDA's outstanding performance across various metrics and its exceptional effectiveness in real-world application scenarios, highlighting the advantages and value of this method.
2. title: The evolution of pre-mrna splicing signals and modules across the tree of life.
