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Nucleic acid tests (NATs) are considered as gold standard in molecular diagnosis. To meet the demand for onsite, point-of-care, specific and sensitive, trace and genotype detection of pathogens and pathogenic variants, various types of NATs have been developed since the discovery of PCR. As alternatives to traditional NATs (e.g., PCR), isothermal nucleic acid amplification techniques (INAATs) such as LAMP, RPA, SDA, HDR, NASBA, and HCA were invented gradually. PCR and most of these techniques highly depend on efficient and optimal primer and probe design to deliver accurate and specific results. This chapter starts with a discussion of traditional NATs and INAATs in concert with the description of computational tools available to aid the process of primer/probe design for NATs and INAATs. Besides briefly covering nanoparticles-assisted NATs, a more comprehensive presentation is given on the role CRISPR-based technologies have played in molecular diagnosis. Here we provide examples of a few groundbreaking CRISPR assays that have been developed to counter epidemics and pandemics and outline CRISPR biology, highlighting the role of CRISPR guide RNA and its design in any successful CRISPR-based application. In this respect, we tabularize computational tools that are available to aid the design of guide RNAs in CRISPR-based applications. In the second part of our chapter, we discuss machine learning (ML)- and deep learning (DL)-based computational approaches that facilitate the design of efficient primer and probe for NATs/INAATs and guide RNAs for CRISPR-based applications. Given the role of microRNA (miRNAs) as potential future biomarkers of disease diagnosis, we have also discussed ML/DL-based computational approaches for miRNA-target predictions. Our chapter presents the evolution of nucleic acid-based diagnosis techniques from PCR and INAATs to more advanced CRISPR/Cas-based methodologies in concert with the evolution of deep learning (DL)- and machine learning (ml)-based computational tools in the most relevant application domains.

Original publication

DOI

10.1007/978-1-0716-4079-1_17

Type

Chapter

Publication Date

2025

Volume

2847

Pages

241 - 300

Keywords

CRISPR base editing, CRISPR off-target efficiency, CRISPR on-target efficiency, CRISPR prime editing, CRISPR-based diagnosis, CRISPR/Cas, CRISPR/Cas tools, Cas12, Cas13, Cas9, Deep learning, Genotyping, Guide RNA, HCR, HDA, LAMP, Machine learning, Molecular diagnosis, NASBA, Nanoparticles, Nucleic acid testing, PCR, Primer, Primer design, Primer-design-tools, Probe, RPA, SDA, miRNA, Humans, Deep Learning, CRISPR-Cas Systems, Molecular Diagnostic Techniques, Nucleic Acid Amplification Techniques, RNA, Machine Learning, Clustered Regularly Interspaced Short Palindromic Repeats