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ISSN: 0974-7230

Journal of Computer Science & Systems Biology
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  • Research Article   
  • J Comput Sci Syst Biol 2019, Vol 12(2): 297
  • DOI: 10.4172/0974-7230.1000297

Mapping Chromosome Sequences of Several Primate on Variant Maps

Huaxian Zheng* and Jeffrey Zheng
School of Software, Yunnan University, Kunming, China
*Corresponding Author : Huaxian Zheng, School of Software, Yunnan University, Kunming, China, Tel: +8618388308955, Email: [email protected]

Received Date: Apr 03, 2019 / Accepted Date: Apr 15, 2019 / Published Date: Apr 22, 2019

Abstract

The chromosome is a carrier of genetic information. The number of somatic chromosomes in normal people is 23 pairs, and there have shapes and structures. It has been found that there are more than 100 kinds of chromosomal diseases caused by chromosomal abnormalities. Chromosome diseases can often cause miscarriage, congenital, congenital multiple malformations, cancer, etc. At present the research on chromosomal sequences has carried out. People have been looking for a suitable visualization model. In this type of visualization models, there is no problem of information degradation and data loss, and a complete chromosomal sequence distribution feature can be mapped. There are multiple sets of chromosomal sequences in species, and a comparative analysis is needed to find out some of the relationships between chromosomes in humans during evolution. In this paper, variant maps are used to illustrate the segmentation probability of the chromosome sequences of Homo sapiens and non-human primate species, distributions of different chromosomal sequence features are compared and analyzed by multiple two-dimension statistical probability maps.

Keywords: Chromosomal sequence; Probability measurement; Twodimension statistics; Probability maps

Citation: Huaxian Zheng, Jeffrey Zheng (2019) Mapping Chromosome Sequences of Several Primate on Variant Maps. J Comput Sci Syst Biol 12:35-41. Doi: 10.4172/0974-7230.1000297

Copyright: © 2019 Zheng H, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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