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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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iLoc-Plant: a multi-label classifier for predicting the subcellular localization of plant proteins with both single and multiple sites

TL;DR: iLoc-Plant is a new predictor developed that can be used to deal with the systems containing both single- and multiple-location plant proteins and may become a useful bioinformatics tool for Molecular Cell Biology, Proteomics, Systems Biology, and Drug Development.
Journal ArticleDOI

Homologs of plant PsbP and PsbQ proteins are necessary for regulation of photosystem ii activity in the cyanobacterium Synechocystis 6803.

TL;DR: Findings indicate that both PsbP and PsbQ proteins are regulators that are necessary for the biogenesis of optimally active PSII in Synechocystis 6803, and that five extrinsic PSII proteins are present in cyanobacteria, two of which have been lost during the evolution of green plants.
Journal ArticleDOI

HECTAR: A method to predict subcellular targeting in heterokonts

TL;DR: The HECTAR method is able to predict the subcellular localisation of heterokont proteins with high accuracy and efficiently predicts the sub cellular localisations of proteins from cryptophytes, a group that is phylogenetically close to the heterokents.
Journal ArticleDOI

A Chloroplastic UDP-Glucose Pyrophosphorylase from Arabidopsis Is the Committed Enzyme for the First Step of Sulfolipid Biosynthesis

TL;DR: The identification of a novel gene, UDP-glucose pyrophosphorylase3 (UGP3), required for sulfolipid biosynthesis is described, and a comparative genomics study on UGP3 homologs across different plant species suggested the structural and functional conservation of the proteins and, thus, a committing role for U GP3 in sulfolIPid synthesis.
Journal ArticleDOI

Isolation and Characterization of Homogentisate Phytyltransferase Genes from Synechocystis sp. PCC 6803 and Arabidopsis

TL;DR: Evidence that antisense expression of HPT1 in Arabidopsis resulted in reduced seed tocopherol levels, whereas seed-specific sense expression resulted in increased seed toCopherol Levels is presented.
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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