Gene identification: Classical and computational intelligence approaches

被引:19
|
作者
Bandyopadhyay, Sanghantitra [1 ,4 ,5 ,6 ]
Maulik, Ujjwal [2 ,4 ,5 ]
Roy, Debadyuti [3 ]
机构
[1] Indian Stat Inst, Machine Intelligence Unit, Kolkata 700108, India
[2] Jadavpur Univ, Dept Comp Sci & Engn, Kolkata 700032, India
[3] Univ Michigan, Dept Stat, Ann Arbor, MI 48109 USA
[4] Univ Maryland, Baltimore, MD 21201 USA
[5] Fraunhofer Inst AiS, St Augustin, Germany
[6] Tsinghua Univ, Beijing 100084, Peoples R China
关键词
bioinformatics; case-based reasoning; decision tree; gene finding; genetic algorithms (GAs); neural networks;
D O I
10.1109/TSMCC.2007.906066
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Automatic identification of genes has been an actively researched area of bioinformatics. Compared to earlier attempts for finding genes, the recent techniques are significantly more accurate and reliable. Many of the current gene-finding methods employ computational intelligence techniques that are known to be more robust when dealing with uncertainty and imprecision. In this paper, a detailed survey on the existing classical and computational intelligence based methods for gene identification is carried out. This includes a brief description of the classical and computational intelligence methods before discussing their applications to gene finding. In addition, a long list of available gene finders is compiled. For the convenience of the readers, the list is enhanced by mentioning their corresponding Web sites and commenting on the general approach adopted. An extensive bibliography is provided. Finally, some limitations of the current approaches and future directions are discussed.
引用
收藏
页码:55 / 68
页数:14
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