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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

Phylogenomics Identifies a New Major Subgroup of Apicomplexans, Marosporida class nov., with Extreme Apicoplast Genome Reduction.

TL;DR: A new lineage of apicomplexans is proposed, which is sister to the Coccidia and Hematozoa and proposes the class Marosporida class nov, and adds a new complexity to the models of stepwise reductive evolution of genome structure and organelle function in these parasites.
Journal ArticleDOI

The sugary-type isoamylase gene from rice and Aegilops tauschii: characterization and comparison with maize and Arabidopsis

TL;DR: Three distinct Sugary-type cDNA sequences were isolated from the wheat endosperm that are likely to correspond to the products of the three genomes and demonstrate that there are three types of isoamylase sequences in plants: those containing 18 exons (the Sugary -type iso amylase gene), those containing 21 exons, and those containing only 1 exon.
Journal ArticleDOI

The Arabidopsis thaliana peptide deformylase 1 protein is localized to both mitochondria and chloroplasts

TL;DR: This work fused full length At DEF1 and 2 proteins with GFP for transient expression studies using onion epidermal cells and photosynthetically active tobacco leaves and found that a single N-terminal sequence that targets a protein to both organelles is termed an ambiguous presequence and both AtDEF1 and At DEF2 have such sequences for dual organellar localization.
Journal ArticleDOI

The Arabidopsis thaliana CUTA gene encodes an evolutionarily conserved copper binding chloroplast protein

TL;DR: Analysis of cDNA clones and RT-PCR with total mRNA revealed alternative splicing of AtCUTA by retention of an intron, and the sequence of AtCutAp encoded by the fully spliced transcript suggests that the precursor consists of three domains: an N-terminal chloroplast transit sequence of 70 residues, followed by a domain with prokaryotic signal-sequence-like characteristics and finally the most conserved C-terminals.
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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