A comprehensive assessment of N-terminal signal peptides prediction methods
نویسندگان
چکیده
منابع مشابه
Prediction of signal peptides in archaea.
Computational prediction of signal peptides (SPs) and their cleavage sites is of great importance in computational biology; however, currently there is no available method capable of predicting reliably the SPs of archaea, due to the limited amount of experimentally verified proteins with SPs. We performed an extensive literature search in order to identify archaeal proteins having experimental...
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We describe improvements of the currently most popular method for prediction of classically secreted proteins, SignalP. SignalP consists of two different predictors based on neural network and hidden Markov model algorithms, where both components have been updated. Motivated by the idea that the cleavage site position and the amino acid composition of the signal peptide are correlated, new feat...
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The peptide hormones contained within the sequence of proopiomelanocortin (POMC) have diverse roles ranging from pigmentation to regulation of adrenal function to control of our appetite. It is generally acknowledged to be the archetypal hormone precursor, and as its biology has been unravelled, so too have many of the basic principles of hormone biosynthesis and processing. This short review f...
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MOTIVATION Pair-wise residue-residue contacts in proteins can be predicted from both threading templates and sequence-based machine learning. However, most structure modeling approaches only use the template-based contact predictions in guiding the simulations; this is partly because the sequence-based contact predictions are usually considered to be less accurate than that by threading. With t...
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Recently, neural networks have been applied to a widening range of problems in molecular biology. An area particularly suited to neural-network methods is the identification of protein sorting signals and the prediction of their cleavage sites, as these functional units are encoded by local, linear sequences of amino acids rather than global 3D structures.
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ژورنال
عنوان ژورنال: BMC Bioinformatics
سال: 2009
ISSN: 1471-2105
DOI: 10.1186/1471-2105-10-s15-s2