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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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Journal ArticleDOI

Isolation and functional analysis of the glycerol permease activity of two new nodulin-like intrinsic proteins from salt stressed roots of the halophyte Atriplex nummularia

TL;DR: Proper functional expression of AnNIP proteins in yeast needed the removal of the unique hydrophilic N-terminal domain of both proteins, which did not show to be necessary for their transport activities.
Journal ArticleDOI

Characterization of the NADP malic enzyme gene family in the facultative, single-cell C 4 monocot Hydrilla verticillata

TL;DR: The hypothesis that a NADP-ME isoform with specific and unusual regulatory properties facilitates the functioning of the single-cell C4 system in H. verticillata is supported.
Journal ArticleDOI

Molecular characterization and regulation of formate dehydrogenase in Arabidopsis thaliana

Rong Li, +2 more
- 01 Jul 2001 - 
TL;DR: The identification of an Arabidopsis FDH cDNA, as well as studies of the molecular characterization and regulation of the enzyme inArabidopsis, are reported.
Journal ArticleDOI

Genome-Wide Identification of Glyoxalase Genes in Medicago truncatula and Their Expression Profiling in Response to Various Developmental and Environmental Stimuli

TL;DR: This study revealed that MtGLYI-4, Mt GLYII-6, and MtDJ-1A are the constitutive members with a high level of expression at all 17 analyzed tissues; while MtGLyI-1, MtGlyoxalaseI-11, MtGLYSI-5, MountGlyXI-7, and MountGLY II-13 showed tissue-specific expression.
Journal ArticleDOI

The analysis of the ChlI 1 and ChlI 2 genes using acifluorfen-resistant mutant of Arabidopsis thaliana.

TL;DR: Comparison of the amino acid sequence of CHLI 1 and CHLI 2 encoded in the genome of aci5 and wild type revealed alterations of the C-terminal end which are suggested to be responsible for the decreased ability ofCHLI 2 to participate in the formation of the CHLI ring-like structure of the Mg chelatase complex.
References
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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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