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This review describes the sequence characteristics of N-terminal targeting signals from different organisms and sorting pathways. of special interest
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0030614959
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Identification of prokaryotic and eukaryotic signal peptides and prediction of their cleavage sites
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Neural networks are trained to identify signal peptides in prokaryotic and eukaryotic proteins. Sequence logos are calculated for signal peptides from different groups of organisms. of outstanding interest
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Nielsen H, Engelbrecht J, Brunak S, Von Heijne G. Identification of prokaryotic and eukaryotic signal peptides and prediction of their cleavage sites. Protein Eng. 10:1997;1-6 Neural networks are trained to identify signal peptides in prokaryotic and eukaryotic proteins. Sequence logos are calculated for signal peptides from different groups of organisms. of outstanding interest.
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Nielsen, H.1
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0029868212
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Defining a similarity threshold for a functional protein sequence pattern: The signal peptide cleavage site
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A method to exclude redundant or homologous entries from sets of sequences that contain a common, well defined feature, such as a proteolytic cleavage site is presented. of special interest
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Nielsen H, Engelbrecht J, Von Heijne G, Brunak S. Defining a similarity threshold for a functional protein sequence pattern: the signal peptide cleavage site. Proteins. 24:1996;165-177 A method to exclude redundant or homologous entries from sets of sequences that contain a common, well defined feature, such as a proteolytic cleavage site is presented. of special interest.
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Software that calculates and presents all the characteristics proposed to be important for mitochondrial targeting sequences is described. of special interest
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Claros MG. MitoProt, a Macintosh application for studying mitochondrial proteins. Comput Appl Biosci. 11:1995;441-447 Software that calculates and presents all the characteristics proposed to be important for mitochondrial targeting sequences is described. of special interest.
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0029915525
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A discriminant analysis is used to identify mitochondrial proteins. The final function is implemented in a software that can also be used to identify the targeting sequence. The advantage of this approach is the large number of parameters and sequences considered to elaborate the discriminant function, and the rules to infer the mitochondrial targeting sequence. of outstanding interest
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Claros MG, Vincens P. Computational method to predict mitochondrially imported proteins and their transit peptides. Eur J Biochem. 241:1996;779-786 A discriminant analysis is used to identify mitochondrial proteins. The final function is implemented in a software that can also be used to identify the targeting sequence. The advantage of this approach is the large number of parameters and sequences considered to elaborate the discriminant function, and the rules to infer the mitochondrial targeting sequence. of outstanding interest.
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