5 resultados para 3-D trunk image analysis

em National Center for Biotechnology Information - NCBI


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The database reported here is derived using the Combinatorial Extension (CE) algorithm which compares pairs of protein polypeptide chains and provides a list of structurally similar proteins along with their structure alignments. Using CE, structure–structure alignments can provide insights into biological function. When a protein of known function is shown to be structurally similar to a protein of unknown function, a relationship might be inferred; a relationship not necessarily detectable from sequence comparison alone. Establishing structure–structure relationships in this way is of great importance as we enter an era of structural genomics where there is a likelihood of an increasing number of structures with unknown functions being determined. Thus the CE database is an example of a useful tool in the annotation of protein structures of unknown function. Comparisons can be performed on the complete PDB or on a structurally representative subset of proteins. The source protein(s) can be from the PDB (updated monthly) or uploaded by the user. CE provides sequence alignments resulting from structural alignments and Cartesian coordinates for the aligned structures, which may be analyzed using the supplied Compare3D Java applet, or downloaded for further local analysis. Searches can be run from the CE web site, http://cl.sdsc.edu/ce.html, or the database and software downloaded from the site for local use.

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Three-week-old plants of two unrelated lines of maize (Zea mays L.) and their hybrid were submitted to progressive water stress for 10 d. Changes induced in leaf proteins were studied by two-dimensional electrophoresis and quantitatively analyzed using image analysis. Seventy-eight proteins out of a total of 413 showed a significant quantitative variation (increase or decrease), with 38 of them exhibiting a different expression in the two genotypes. Eleven proteins that increased by a factor of 1.3 to 5 in stressed plants and 8 proteins detected only in stressed plants were selected for internal amino acid microsequencing, and by similarity search 16 were found to be closely related to previously reported proteins. In addition to proteins already known to be involved in the response to water stress (e.g. RAB17 [Responsive to ABA]), several enzymes involved in basic metabolic cellular pathways such as glycolysis and the Krebs cycle (e.g. enolase and triose phosphate isomerase) were identified, as well as several others, including caffeate O-methyltransferase, the induction of which could be related to lignification.

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The discovery that the epsilon 4 allele of the apolipoprotein E (apoE) gene is a putative risk factor for Alzheimer disease (AD) in the general population has highlighted the role of genetic influences in this extremely common and disabling illness. It has long been recognized that another genetic abnormality, trisomy 21 (Down syndrome), is associated with early and severe development of AD neuropathological lesions. It remains a challenge, however, to understand how these facts relate to the pathological changes in the brains of AD patients. We used computerized image analysis to examine the size distribution of one of the characteristic neuropathological lesions in AD, deposits of A beta peptide in senile plaques (SPs). Surprisingly, we find that a log-normal distribution fits the SP size distribution quite well, motivating a porous model of SP morphogenesis. We then analyzed SP size distribution curves in genotypically defined subgroups of AD patients. The data demonstrate that both apoE epsilon 4/AD and trisomy 21/AD lead to increased amyloid deposition, but by apparently different mechanisms. The size distribution curve is shifted toward larger plaques in trisomy 21/AD, probably reflecting increased A beta production. In apoE epsilon 4/AD, the size distribution is unchanged but the number of SP is increased compared to apoE epsilon 3, suggesting increased probability of SP initiation. These results demonstrate that subgroups of AD patients defined on the basis of molecular characteristics have quantitatively different neuropathological phenotypes.