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A neural network-based tool, TargetP, for large-scale subcellular location prediction of newly identified proteins has been developed. Using N-terminal sequence information only, it discriminates between proteins destined for the mitochondrion, the chloroplast, the secretory pathway, and "other" localizations with a success rate of 85% (plant) or 90%(More)
We have developed 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. The method performs significantly better than previous prediction schemes and can easily be applied on genome-wide data sets. Discrimination between cleaved signal(More)
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(More)
We have developed an entirely sequence-based method that identifies and integrates relevant features that can be used to assign proteins of unknown function to functional classes, and enzyme categories for enzymes. We show that strategies for the elucidation of protein function may benefit from a number of functional attributes that are more directly(More)
Prediction of protein sorting signals from the sequence of amino acids has great importance in the field of proteomics today. Recently, the growth of protein databases, combined with machine learning approaches, such as neural networks and hidden Markov models, have made it possible to achieve a level of reliability where practical use in, for example(More)
Recently, a new protein translocation pathway, the twin-arginine translocation (TAT) pathway, has been identified in both bacteria and chloroplasts. To study the possible competition between the TAT- and the well-characterized Sec translocon-dependent pathways in Escherichia coli, we have fused the TorA TAT-targeting signal peptide to the Sec-dependent(More)
OBJECTIVE To calculate the incidence of and determine possible risk factors for dementia in PD. BACKGROUND Dementia has important clinical consequences for patients with PD and their caregivers, but the incidence is unknown. METHODS A population-based cohort of nondemented patients with PD (n = 171) from the county of Rogaland, Norway, was assessed at(More)
OBJECTIVE To develop criteria for disease activity in systemic sclerosis (SSc) that are valid, reliable, and easy to use. METHODS Investigators from 19 European centres completed a standardised clinical chart for a consecutive number of patients with SSc. Three protocol management members blindly evaluated each chart and assigned a disease activity score(More)
BACKGROUND Mesorectal excision for rectal cancer has resulted in local recurrence rates of 3-11 per cent compared with up to 38 per cent after conventional methods. The results of a prospective Danish study with a historical control group are presented. METHODS Three hundred and eleven patients with a mobile rectal cancer had mesorectal excision with(More)
OBJECTIVES The prevalence of dementia has been estimated in several countries and a meta-analysis has shown moderate and severe dementia in people aged 65 years and older to be between 4% and 6%. The Odense study is aiming to estimate the prevalence and incidence of dementia and to identify risk factors. MATERIAL AND METHODS A total of 3346 persons,(More)