Earticle

초록

영어

Identification of the disease-causal genomic variants that alter human phenotypes, particularly those that lead to diseases, is the central goal of human genetics studies. In the past decade, genome-wide studies have identified several hundreds of common variants associated with complex human diseases and traits. Despite these successes, most of the common variants only have a small individual contribution to the estimated heritability underlying common diseases and traits. Many explanations for these missing heritabilities have been suggested, including rare variants, structural variants, regulatory variants, and epigenetic variants. Recent advances in high-throughput technologies have provided an opportunity to construct comprehensive maps of genetic variation, including the several million single nucleotide variants, thousands of small insertion or deletion events, and thousands of structural variants, in both the protein-coding and noncoding regions of the human genome without time and cost limitations. The present review describes current bioinformatics tools for identifying deleterious variants in protein-coding regions based on the evolutionary and functional constraints of human proteins.

목차

Abstract
 1. Introduction
 2. Predicting Deleterious nsSNPs Based on Evolutionary Constraints
 3. Structural and Functional Constraints in Deleterious nsSNPs
 4. Realizing the Identification of Disease-Causal Variants by Using Bioinformatics Tools
 5. Conclusions
 References

키워드

저자

• Youngmahn Han [ Korea Institute of Science and Technology Information ]
• Insung Ahn [ Korea Institute of Science and Technology Information ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Bio-Science and Bio-Technology

• 간기

  격월간

• pISSN

  2233-7849

• 수록기간

  2009~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605