@article {Sanak2020203,
	title = {MARCO Gene Variations and Their Association with Cardiovascular Diseases Development: An In-Silico Analysis},
	journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
	volume = {12108 LNBI},
	year = {2020},
	note = {cited By 0},
	pages = {203-212},
	abstract = {Cardiovascular diseases (CVDs) represent the leading cause of morbidity and mortality in both developed and developing countries. They have complex etiology, influenced by several risk factors including the genetic component. The genetic variations were shown to be highly associated with different CVD forms, in this objective we proceeded to analyze the Macrophage Receptor with Collagen structure gene (MARCO), we performed an in-silico study with a genomic functional analysis, to evaluate the mutations{\textquoteright} effects on the proteins{\textquoteright} structures and functionalities. Indeed, we used dbSNP to retrieve single nucleotide polymorphisms (SNPs) of MARCO gene. We proceeded then to a filtration and a stability analysis using several bioinformatics tools to evaluate the most deleterious variations. Moreover we predicted the 3D structures of the encoded proteins by MARCO gene, which was validated using PROCHECK. Then we analyzed and visualize the proteins{\textquoteright} 3D structures. The extraction of the human MARCO gene SNPs revealed that dbSNP contains more than 14000 SNPs. The filtration process revealed the variations G241V and G262W to be the most deleterious SNPs, indeed, I-Mutant and DUET showed decreased protein stability. The validation using PROCHECK revealed a total of 89.9\% MARCO protein residues to be in the favored region. As conclusion, our results let suggesting that G241V and G262W variations can cause alteration in the proteins{\textquoteright} structures and functions. Hence, to improve the health management, screening precariously these variants, can be useful as model for CVD diagnosis and helpful in pharmacogenomics. {\textcopyright} Springer Nature Switzerland AG 2020.},
	keywords = {Bioinformatics, Bioinformatics tools, Biomedical engineering, Cardio-vascular disease, Cardiology, Collagen structure, Developing countries, Diagnosis, Diseases, Filtration process, Genes, Genetic components, Genetic variation, Health management, Proteins, Single nucleotide polymorphisms},
	doi = {10.1007/978-3-030-45385-5_19},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085196738\&doi=10.1007\%2f978-3-030-45385-5_19\&partnerID=40\&md5=1df531cdc3510e8747834a13a996b1b1},
	author = {Sanak, K. and Azzouzi, M. and Abik, M. and Radouani, F.}
}
