Book chapter ยท Journal article
Predicting Subcellular Localization of Proteins by Bioinformatic Algorithms
Department of Systems Biology, Technical University of Denmark1
Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark2
Functional Human Variation, Center for Biological Sequence Analysis, Department of Systems Biology, Technical University of Denmark3
When predicting the subcellular localization of proteins from their amino acid sequences, there are basically three approaches: signal-based, global property-based, and homology-based. Each of these has its advantages and drawbacks, and it is important when comparing methods to know which approach was used.
Various statistical and machine learning algorithms are used with all three approaches, and various measures and standards are employed when reporting the performances of the developed methods. This chapter presents a number of available methods for prediction of sorting signals and subcellular localization, but rather than providing a checklist of which predictors to use, it aims to function as a guide for critical assessment of prediction methods.
Language: | English |
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Publisher: | Springer |
Year: | 2015 |
Pages: | 129-158 |
Series: | Current Topics in Microbiology and Immunology |
ISBN: | 3319560123 , 331956014X , 331956014x , 9783319560120 and 9783319560144 |
ISSN: | 21969965 and 0070217x |
Types: | Book chapter and Journal article |
DOI: | 10.1007/82_2015_5006 |
ORCIDs: | Nielsen, Henrik |