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Open AccessJournal ArticleDOI

ChloroP, a neural network-based method for predicting chloroplast transit peptides and their cleavage sites.

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TLDR
An analysis of 715 Arabidopsis thaliana sequences from SWISS‐PROT suggests that the ChloroP method should be useful for the identification of putative transit peptides in genome‐wide sequence data.
Abstract
We present a neural network based method (ChloroP) for identifying chloroplast transit peptides and their cleavage sites. Using cross-validation, 88% of the sequences in our homology reduced training set were correctly classified as transit peptides or nontransit peptides. This performance level is well above that of the publicly available chloroplast localization predictor PSORT. Cleavage sites are predicted using a scoring matrix derived by an automatic motif-finding algorithm. Approximately 60% of the known cleavage sites in our sequence collection were predicted to within +/-2 residues from the cleavage sites given in SWISS-PROT. An analysis of 715 Arabidopsis thaliana sequences from SWISS-PROT suggests that the ChloroP method should be useful for the identification of putative transit peptides in genome-wide sequence data. The ChloroP predictor is available as a web-server at http://www.cbs.dtu.dk/services/ChloroP/.

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Cloning and functional characterization of the maize carotenoid isomerase and β-carotene hydroxylase genes and their regulation during endosperm maturation

TL;DR: Cloned cDNAs encoding the enzymes carotenoid isomerase (CRTISO) and β-carotene hydroxylase (BCH) were cloned using endosperm mRNA isolated from inbred line B73 to gain further insight into the partly-characterized carotanoid biosynthetic pathway in corn.
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Human Lsg1 defines a family of essential GTPases that correlates with the evolution of compartmentalization.

TL;DR: Comparison of localization and siRNA datasets suggests that all members of the YlqF Related GTPase (YRG) family are essential GTPases that have increased in number as the compartmentalization of the eukaryotic cell and the ribosome biogenesis pathway have evolved.
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REP27, a Tetratricopeptide Repeat Nuclear-Encoded and Chloroplast-Localized Protein, Functions in D1/32-kD Reaction Center Protein Turnover and Photosystem II Repair from Photodamage

TL;DR: Elucidation of the PSII repair mechanism may reveal the occurrence of hitherto unknown regulatory and catalytic reactions for the selective in situ replacement of specific proteins from within multiprotein complexes.
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Subcellular location prediction of proteins using support vector machines with alignment of block sequences utilizing amino acid composition

TL;DR: This paper proposes a novel and general predicting method by combining techniques for sequence alignment and feature vectors based on amino acid composition which is considered to be useful for subcellular location prediction of newly-discovered proteins.
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Functional characterization and hormonal regulation of the PHEOPHYTINASE gene LpPPH controlling leaf senescence in perennial ryegrass.

TL;DR: In this paper, the functional roles and hormonal regulation of a gene encoding pheophytin pheophorbide hydrolyase (PPH) that catabolizes chlorophyll degradation during leaf senescence in perennial grass species were determined.
References
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Journal ArticleDOI

A mathematical theory of communication

TL;DR: This final installment of the paper considers the case where the signals or the messages or both are continuously variable, in contrast with the discrete nature assumed until now.
Book ChapterDOI

Learning internal representations by error propagation

TL;DR: This chapter contains sections titled: The Problem, The Generalized Delta Rule, Simulation Results, Some Further Generalizations, Conclusion.
Journal ArticleDOI

Identification of prokaryotic and eukaryotic signal peptides and prediction of their cleavage sites.

TL;DR: A new method for the identification of signal peptides and their cleavage sites based on neural networks trained on separate sets of prokaryotic and eukaryotic sequence that performs significantly better than previous prediction schemes and can easily be applied on genome-wide data sets.

SHORT COMMUNICATION Identification of prokaryotic and eukaryotic signal peptides and prediction of their cleavage sites

TL;DR: In this paper, a new method for the identification of in performance compared with the weight matrix method signal peptides and their cleavage sites based on neural (Arrigo et al., 1991; Ladunga et al, 1991; Schneider and networks trained on separate sets of prokaryotic and eukaryotic sequence.
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