Year: 2013
Type: editorial
Abstract: All of the 3.2 billion base pairs in the entire human genome have been sequenced in this project.The Human Genome Project is a revolutionizing biological and medical research [2].However, it was just the starting point for us to understand the function of our genome.Extraordinary amount of information generated from the Human Genome Project needed to be analyzed accurately and efficiently.Also several powerful genome-wide detection tools such as genotyping micro arrays and tiling microarrays have been developed based on genetic information from the Human Genome Project.Nowadays, the analysis of huge amount of data from these high throughput tools is still very challenging [3].Bioinformatics, an interdisciplinary field that involves biology, computer science mathematics and statistics, provides various algorithms or programs to collect, analyze, store and integrate genetic information from the Human Genome Project and other genome-wide studies.Development of algorithms that enable efficient analysis of different types of information is one of the main goals of bioinformatics.Many algorithms were widely used for genome research including prediction of gene function, identification of genomic regions involved in gene regulation, dissection of molecular evolution, and modeling of alternative splicing.This special issue provides a snapshot of the applications of some bioinformatics algorithms in genome research and some genome-wide studies including the genome-wide association studies (GWAS) [4] and the next generation sequencing (NGS).This special issue starts with a review by Drs.Gengxin Li and Hongjian Zhu, which gives an introduction to the linear mixed models dealing with sample structure in GWAS.GWAS could identify the genetic variants such as single nucleotide polymorphism (SNP) contributing to complex traits or diseases in a genome-wide scale.GWAS has the potential to find novel disease-related genes because it investigates all human genes in the whole genome instead of specific genes or chromosome regions [4].GWAS have
Source: The Open Bioinformatics Journal
Author: Feng Cheng
Institution: University of South Florida
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: diamond
OpenAlex ID: W2050038067