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Advances in Diagnostics: Applications of Nucleic Acids and Their Analogs

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Genetics and Genomics".

Deadline for manuscript submissions: 30 June 2024 | Viewed by 789

Special Issue Editors


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Guest Editor
Institute of Crystallography, Consiglio Nazionale delle Ricerche, Monterotondo Stazione, 00015 Rome, Italy
Interests: oligonucleotides; oxidative DNA damage; DNA repair; diagnostic; biomarkers
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Institute of Crystallography, Consiglio Nazionale delle Ricerche, Monterotondo Stazione, 00015 Rome, Italy
Interests: DNA repair; mitochondrial dysfunction; oxidative stress; aging; neurodegenerative diseases
Special Issues, Collections and Topics in MDPI journals

E-Mail Website
Guest Editor
Institute of Crystallography, Consiglio Nazionale delle Ricerche, Monterotondo Stazione, 00015 Rome, Italy
Interests: design and synthesis of PNA; miRNAs; therapeutics; diagnostic; biomarkers; cancer
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue explores the dynamic landscape of nucleic acids and their analogs in diagnostic breakthroughs, elucidating their pivotal role in pushing the boundaries of molecular diagnostics. Amidst the evolving field of genetic and epigenetic analyses, this collection delves into the multifaceted applications of nucleic acids, uncovering their potential to revolutionize disease diagnosis. Contributions within this issue span diverse areas, including the utilization of biomarkers for early cancer detection, the integration of CRISPR-based technologies in precision medicine and the exploration of novel nucleic acid analogs for enhanced diagnostic sensitivity. Additionally, the issue explores the intersection of artificial intelligence and nucleic acid diagnostics, showcasing innovative strategies to decipher complex genomic data. The combination of these sub-topics collectively unlocks diagnostic frontiers, offering a comprehensive perspective on the power of nucleic acid in shaping the future of diagnostic medicine. 

Dr. Annalisa Masi
Dr. Barbara Pascucci
Dr. Maria Moccia
Guest Editors

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. International Journal of Molecular Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. There is an Article Processing Charge (APC) for publication in this open access journal. For details about the APC please see here. 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

  • nucleic acids
  • PNAs
  • ASOs
  • aptamers
  • CRISPR
  • biomarkers

Published Papers (1 paper)

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Research

16 pages, 4245 KiB  
Article
CrnnCrispr: An Interpretable Deep Learning Method for CRISPR/Cas9 sgRNA On-Target Activity Prediction
by Wentao Zhu, Huanzeng Xie, Yaowen Chen and Guishan Zhang
Int. J. Mol. Sci. 2024, 25(8), 4429; https://doi.org/10.3390/ijms25084429 - 17 Apr 2024
Viewed by 596
Abstract
CRISPR/Cas9 is a powerful genome-editing tool in biology, but its wide applications are challenged by a lack of knowledge governing single-guide RNA (sgRNA) activity. Several deep-learning-based methods have been developed for the prediction of on-target activity. However, there is still room for improvement. [...] Read more.
CRISPR/Cas9 is a powerful genome-editing tool in biology, but its wide applications are challenged by a lack of knowledge governing single-guide RNA (sgRNA) activity. Several deep-learning-based methods have been developed for the prediction of on-target activity. However, there is still room for improvement. Here, we proposed a hybrid neural network named CrnnCrispr, which integrates a convolutional neural network and a recurrent neural network for on-target activity prediction. We performed unbiased experiments with four mainstream methods on nine public datasets with varying sample sizes. Additionally, we incorporated a transfer learning strategy to boost the prediction power on small-scale datasets. Our results showed that CrnnCrispr outperformed existing methods in terms of accuracy and generalizability. Finally, we applied a visualization approach to investigate the generalizable nucleotide-position-dependent patterns of sgRNAs for on-target activity, which shows potential in terms of model interpretability and further helps in understanding the principles of sgRNA design. Full article
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