Bioinformatics Usage, Application and Challenges to Detect Human Genetic Diseases (Mini Review)

Zahraa Isam Jameel¹

Section:Review Paper, Product Type: Journal-Paper
Vol.10 , Issue.5 , pp.59-67, Oct-2023

Online published on Oct 31, 2023

Copyright © Zahraa Isam Jameel . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
Bioinformatics is a field that combines computational methods with biology, explicitly focusing on macromolecules. It uses informatics techniques to analyze and structure vast information about these molecules. The data above have been generated by extensive molecular biology initiatives, including but not limited to large-scale projects involving genome sequencing, gene expression analysis, and investigations into genomics, proteomics, and protein-protein interactions. Precision healthcare programs are being widely implemented globally to enhance individualized patient care. The detection and management of genetic illnesses have seen notable advancements, primarily due to the growing availability of affordable and accurate sequencing data. The data above are derived from extensive molecular biology initiatives, including but not limited to large-scale programs focused on genome sequencing, gene expression analysis, genomics analysis, proteomics analysis, and protein-protein interaction study. In recent years, the field of bioinformatics has witnessed notable progressions. The progress in sequencing technology has resulted in a substantial augmentation in the quantity of genetic data produced. As a result, the establishment of approaches that can efficiently and promptly evaluate this data poses a substantial obstacle in the realm of bioinformatics research. This study aims to present a succinct summary of the most recent advancements in bioinformatics approaches that can be used in the domain of personalized medicine. To effectively leverage the potential of personalized medicine, it is imperative to embrace four innovative techniques. This paper will explore the obstacles and potential solutions related to the identification of predictive genetic biomarkers and genetic variations in patients. Moreover, it will tackle the anticipated future bioinformatics issues within this domain.

Key-Words / Index Term :
Bioinformatics, Computer Science, DNA, Genetic Disease, Network Biology, Protein

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