Understanding sequence similarity and framework analysis between centromere proteins using computational biology.
Certain mysteries pointing toward their recruitment pathways, cell cycle regulation mechanisms, spindle checkpoint assembly, and chromosome segregation process are considered the centre of attraction in cancer research. In modern times, with the established databases, ranges of computational platforms have provided a platform to examine almost all the physiological and biochemical evidences in disease-associated phenotypes. Using existing computational methods, we have utilized the amino acid residues to understand the similarity within the evolutionary variance of different associated centromere proteins. This study related to sequence similarity, protein-protein networking, co-expression analysis, and evolutionary trajectory of centromere proteins will speed up the understanding about centromere biology and will create a road map for upcoming researchers who are initiating their work of clinical sequencing using centromere proteins.
Medical Biotechnology Division, School of Biosciences and Technology, VIT University, Vellore, 632014, Tamil Nadu, India, georgepriyadoss@vit.ac.in.
C George Priya
CG
Doss
Chiranjib
C
Chakrabarty
C
C
Debajyoti
S
S
Debottam
D000595:Amino Acid Sequence; D002503:Centromere / Q000378:metabolism*; D019295:Computational Biology; D019143:Evolution, Molecular; D005786:Gene Expression Regulation; D006801:Humans; D008969:Molecular Sequence Data; D009687:Nuclear Proteins / Q000737:chemistry* / Q000235:genetics / Q000378:metabolism; D010802:Phylogeny; D060066:Protein Interaction Maps; D016415:Sequence Alignment
D009687:Nuclear Proteins