Bird Eye View of Protein Subcellular Localization Prediction

被引:16
作者
Kumar, Ravindra [1 ]
Dhanda, Sandeep Kumar [2 ]
机构
[1] NCI, Biometr Res Program, Div Canc Treatment & Diag, NIH, 9609 Med Ctr Dr, Rockville, MD 20850 USA
[2] St Jude Childrens Res Hosp, Dept Oncol, Memphis, TN 38105 USA
来源
LIFE-BASEL | 2020年 / 10卷 / 12期
关键词
protein localization; signal peptide-based method; sequence compositional information-based method; machine learning based method; integrated method; AMINO-ACID-COMPOSITION; SIGNAL PEPTIDES; NETWORK; SYSTEM; PSORT;
D O I
10.3390/life10120347
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Proteins are made up of long chain of amino acids that perform a variety of functions in different organisms. The activity of the proteins is determined by the nucleotide sequence of their genes and by its 3D structure. In addition, it is essential for proteins to be destined to their specific locations or compartments to perform their structure and functions. The challenge of computational prediction of subcellular localization of proteins is addressed in various in silico methods. In this review, we reviewed the progress in this field and offered a bird eye view consisting of a comprehensive listing of tools, types of input features explored, machine learning approaches employed, and evaluation matrices applied. We hope the review will be useful for the researchers working in the field of protein localization predictions.
引用
收藏
页码:1 / 18
页数:18
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