8 resultados para pruning algorithm

em National Center for Biotechnology Information - NCBI


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Neuronal connections are arranged topographically such that the spatial organization of neurons is preserved by their termini in the targets. During the development of topographic projections, axons initially explore areas much wider than the final targets, and mistargeted axons are pruned later. The molecules regulating these processes are not known. We report here that the ligands of the Eph family tyrosine kinase receptors may regulate both the initial outgrowth and the subsequent pruning of axons. In the presence of ephrins, the outgrowth and branching of the receptor-positive hippocampal axons are enhanced. However, these axons are induced later to degenerate. These observations suggest that the ephrins and their receptors may regulate topographic map formation by stimulating axonal arborization and by pruning mistargeted axons.

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We propose a general procedure for solving incomplete data estimation problems. The procedure can be used to find the maximum likelihood estimate or to solve estimating equations in difficult cases such as estimation with the censored or truncated regression model, the nonlinear structural measurement error model, and the random effects model. The procedure is based on the general principle of stochastic approximation and the Markov chain Monte-Carlo method. Applying the theory on adaptive algorithms, we derive conditions under which the proposed procedure converges. Simulation studies also indicate that the proposed procedure consistently converges to the maximum likelihood estimate for the structural measurement error logistic regression model.

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Fragile X syndrome arises from blocked expression of the fragile X mental retardation protein (FMRP). Golgi-impregnated mature cerebral cortex from fragile X patients exhibits long, thin, tortuous postsynaptic spines resembling spines observed during normal early neocortical development. Here we describe dendritic spines in Golgi-impregnated cerebral cortex of transgenic fragile X gene (Fmr1) knockout mice that lack expression of the protein. Dendritic spines on apical dendrites of layer V pyramidal cells in occipital cortex of fragile X knockout mice were longer than those in wild-type mice and were often thin and tortuous, paralleling the human syndrome and suggesting that FMRP expression is required for normal spine morphological development. Moreover, spine density along the apical dendrite was greater in the knockout mice, which may reflect impaired developmental organizational processes of synapse stabilization and elimination or pruning.

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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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There is a need for faster and more sensitive algorithms for sequence similarity searching in view of the rapidly increasing amounts of genomic sequence data available. Parallel processing capabilities in the form of the single instruction, multiple data (SIMD) technology are now available in common microprocessors and enable a single microprocessor to perform many operations in parallel. The ParAlign algorithm has been specifically designed to take advantage of this technology. The new algorithm initially exploits parallelism to perform a very rapid computation of the exact optimal ungapped alignment score for all diagonals in the alignment matrix. Then, a novel heuristic is employed to compute an approximate score of a gapped alignment by combining the scores of several diagonals. This approximate score is used to select the most interesting database sequences for a subsequent Smith–Waterman alignment, which is also parallelised. The resulting method represents a substantial improvement compared to existing heuristics. The sensitivity and specificity of ParAlign was found to be as good as Smith–Waterman implementations when the same method for computing the statistical significance of the matches was used. In terms of speed, only the significantly less sensitive NCBI BLAST 2 program was found to outperform the new approach. Online searches are available at http://dna.uio.no/search/

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We present a shape-recovery technique in two dimensions and three dimensions with specific applications in modeling anatomical shapes from medical images. This algorithm models extremely corrugated structures like the brain, is topologically adaptable, and runs in O(N log N) time, where N is the total number of points in the domain. Our technique is based on a level set shape-recovery scheme recently introduced by the authors and the fast marching method for computing solutions to static Hamilton-Jacobi equations.

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Frequencies of meiotic configurations in cytogenetic stocks are dependent on chiasma frequencies in segments defined by centromeres, breakpoints, and telomeres. The expectation maximization algorithm is proposed as a general method to perform maximum likelihood estimations of the chiasma frequencies in the intervals between such locations. The estimates can be translated via mapping functions into genetic maps of cytogenetic landmarks. One set of observational data was analyzed to exemplify application of these methods, results of which were largely concordant with other comparable data. The method was also tested by Monte Carlo simulation of frequencies of meiotic configurations from a monotelodisomic translocation heterozygote, assuming six different sample sizes. The estimate averages were always close to the values given initially to the parameters. The maximum likelihood estimation procedures can be extended readily to other kinds of cytogenetic stocks and allow the pooling of diverse cytogenetic data to collectively estimate lengths of segments, arms, and chromosomes.