Automated processing of raw DNA sequence data
Michael C. Wendl, Ian Korf, Asif Chinwalla, LaDeana W. Hillier
- 发表年份
- 2001
- 引用次数
- 4
摘要
Present-day DNA sequencing techniques have evolved considerably from their early beginnings. A modern sequencing project is essentially an assembly-line environment and is therefore improved and accelerated by the degree to which slow and error-prone manual steps can be replaced by reliable and accurate automatic ones. For hardware, this typically means expanding the use of robotics, for example, to execute the multitude of micro-volume fluid transfers that occur for each of the samples processed in a project. Likewise, automated software replaces manual processing and analysis steps for samples wherever possible. In this article, we focus on one particular aspect of software: the automated handling of raw DNA data. Specifically, we discuss a number of critical software algorithms and components and how they have been woven into a framework for largely hands-off processing of Human Genome Project data at the Genome Sequencing Center. These data represent about 25% of the total public human sequencing project.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Fractional Differential Equations
Igor Podlubný
2025
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991