Analytical design of multi-threshold and high fan-in DNA-based logical sensors to profi le the pattern of MS microRNAs

Early detection of diseases is very important to increase the life quality and reduce the treatment cost for the patient. MicroRNAshave been introduced in recent years as an effi cient class of biomarkers for detecting the risky situation of many diseasessuch as cancers, Multiple sclerosis (MS), and...

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Bibliographic Details
Published inBiomedical engineering letters pp. 131 - 145
Main Authors Mercedeh Sanjabi, Ali Jahanian
Format Journal Article
LanguageEnglish
Published 대한의용생체공학회 01.05.2021
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ISSN2093-9868
2093-985X
DOI10.1007/s13534-021-00186-9

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Summary:Early detection of diseases is very important to increase the life quality and reduce the treatment cost for the patient. MicroRNAshave been introduced in recent years as an effi cient class of biomarkers for detecting the risky situation of many diseasessuch as cancers, Multiple sclerosis (MS), and heart attacks, and other diseases. Now, real-time PCR has been used to profi lethe microRNA expression, which is expensive, time-consuming, and has low accuracy. Most recently, DNA logic gates areused to detect the MicroRNA expression level that is more accurate and faster than previous methods. In this paper, weimproved the design of multi-threshold and multi-input DNA-based logic gates in response to specifi c microRNA (miRNA)inputs. The proposed design style can simultaneously recognize multiple miRNAs with diff erent rising and falling thresholds. The proposed structure in this paper is used to diagnose Multiple Sclerosis (MS) as a case study. We simulated this systemto understand its performance and compare it with other existing methods. The simulation results show the effi ciency ofthe proposed method in terms of accuracy, effi ciency, and speed. In this analysis, unwanted reactions, fault positive, and theprobability of generating the fi nal output using the formal method are investigated in depth. Finally, the proposed solutionsare improved based on the results of these analyses. The analytic approach of this paper helps to design the DNA-basedlogic gates for real diseases. KCI Citation Count: 0
ISSN:2093-9868
2093-985X
DOI:10.1007/s13534-021-00186-9