Preprint Review Version 1 Preserved in Portico This version is not peer-reviewed

A Survey of Techniques Leveraging miRNA as Biomarkers for Generalized and Type Specific Cancer Diagnosis.

Version 1 : Received: 31 August 2020 / Approved: 1 September 2020 / Online: 1 September 2020 (11:42:35 CEST)

How to cite: Banerjee, A.; Bose, S.; Das, C. A Survey of Techniques Leveraging miRNA as Biomarkers for Generalized and Type Specific Cancer Diagnosis.. Preprints 2020, 2020090013. https://doi.org/10.20944/preprints202009.0013.v1 Banerjee, A.; Bose, S.; Das, C. A Survey of Techniques Leveraging miRNA as Biomarkers for Generalized and Type Specific Cancer Diagnosis.. Preprints 2020, 2020090013. https://doi.org/10.20944/preprints202009.0013.v1

Abstract

MicroRNAs are used as biomarkers for classification of cancer subtypes since certain miRNAs are differentially expressed in normal and patient samples. Moreover, miRNAs target mRNAs and can heavily influence Gene Expressions. Thus, deregulation of miRNAs is linked to various disorders. Thus, miRNAs can be used for prognosis and developing personalized health solutions for patients. Given the importance of miRNAs, there has been substantial work done in the field. In this paper, recent works in the field of using miRNAs expressions of patients were considered. A total of 20 papers were surveyed which utilized feature selection ensembles, fuzzy logic as well as deep learning. 10 papers have been reported which offer insight into how miRNAs can be utilized for subtype-specific or generalized cancer diagnosis.

Keywords

MicroRNA Expression; Feature Selection; Cancer Diagnosis; Fuzzy Logic; Co-Learning

Subject

Medicine and Pharmacology, Oncology and Oncogenics

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