10 resultados para semi binary based feature detectordescriptor

em National Center for Biotechnology Information - NCBI


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Detection of loss of heterozygosity (LOH) by comparison of normal and tumor genotypes using PCR-based microsatellite loci provides considerable advantages over traditional Southern blotting-based approaches. However, current methodologies are limited by several factors, including the numbers of loci that can be evaluated for LOH in a single experiment, the discrimination of true alleles versus "stutter bands," and the use of radionucleotides in detecting PCR products. Here we describe methods for high throughput simultaneous assessment of LOH at multiple loci in human tumors; these methods rely on the detection of amplified microsatellite loci by fluorescence-based DNA sequencing technology. Data generated by this approach are processed by several computer software programs that enable the automated linear quantitation and calculation of allelic ratios, allowing rapid ascertainment of LOH. As a test of this approach, genotypes at a series of loci on chromosome 4 were determined for 58 carcinomas of the uterine cervix. The results underscore the efficacy, sensitivity, and remarkable reproducibility of this approach to LOH detection and provide subchromosomal localization of two regions of chromosome 4 commonly altered in cervical tumors.

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Elucidating the genetic basis of human phenotypes is a major goal of contemporary geneticists. Logically, two fundamental and contrasting approaches are available, one that begins with a phenotype and concludes with the identification of a responsible gene or genes; the other that begins with a gene and works toward identifying one or more phenotypes resulting from allelic variation of it. This paper provides a conceptual overview of phenotype-based vs. gene-based procedures with emphasis on gene-based methods. A key feature of a gene-based approach is that laboratory effort first is devoted to developing an assay for mutations in the gene under regard; the assay then is applied to the evaluation of large numbers of unrelated individuals with a variety of phenotypes that are deemed potentially resulting from alleles at the gene. No effort is directed toward chromosomally mapping the loci responsible for the phenotypes scanned. Example is made of my laboratory’s successful use of a gene-based approach to identify genes causing hereditary diseases of the retina such as retinitis pigmentosa. Reductions in the cost and improvements in the speed of scanning individuals for DNA sequence anomalies may make a gene-based approach an efficient alternative to phenotype-based approaches to correlating genes with phenotypes.

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Vaccinia uses actin-based motility for virion movement in host cells, but the specific protein components have yet to be defined. A cardinal feature of Listeria and Shigella actin-based motility is the involvement of vasodilator-stimulated phosphoprotein (VASP). This essential adapter recognizes and binds to actin-based motility 1 (ABM-1) consensus sequences [(D/E)FPPPPX(D/E), X = P or T] contained in Listeria ActA and in the p90 host-cell vinculin fragment generated by Shigella infection. VASP, in turn, provides the ABM-2 sequences [XPPPPP, X = G, P, L, S, A] for binding profilin, an actin-regulatory protein that stimulates actin filament assembly. Immunolocalization using rabbit anti-VASP antibody revealed that VASP concentrates behind motile virions in HeLa cells. Profilin was also present in these actin-rich rocket tails, and microinjection of 10 μM (intracellular) ABM-2 peptide (GPPPPP)3 blocked vaccinia actin-based motility. Vinculin did not colocalize with VASP on motile virions and remained in focal adhesion contacts; however, another ABM-1-containing host protein, zyxin, was concentrated at the rear of motile virions. We also examined time-dependent changes in the location of these cytoskeletal proteins during vaccinia infection. VASP and zyxin were redistributed dramatically several hours before the formation of actin rocket tails, concentrating in the viral factories of the perinuclear cytoplasm. Our findings underscore the universal involvement of ABM-1 and ABM-2 docking sites in actin-based motility of Listeria, Shigella, and now vaccinia.

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We introduce a method of functionally classifying genes by using gene expression data from DNA microarray hybridization experiments. The method is based on the theory of support vector machines (SVMs). SVMs are considered a supervised computer learning method because they exploit prior knowledge of gene function to identify unknown genes of similar function from expression data. SVMs avoid several problems associated with unsupervised clustering methods, such as hierarchical clustering and self-organizing maps. SVMs have many mathematical features that make them attractive for gene expression analysis, including their flexibility in choosing a similarity function, sparseness of solution when dealing with large data sets, the ability to handle large feature spaces, and the ability to identify outliers. We test several SVMs that use different similarity metrics, as well as some other supervised learning methods, and find that the SVMs best identify sets of genes with a common function using expression data. Finally, we use SVMs to predict functional roles for uncharacterized yeast ORFs based on their expression data.

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The association of a particular mitochondrial DNA (mtDNA) mutation with different clinical phenotypes is a well-known feature of mitochondrial diseases. A simple genotype–phenotype correlation has not been found between mutation load and disease expression. Tissue and intercellular mosaicism as well as mtDNA copy number are thought to be responsible for the different clinical phenotypes. As disease expression of mitochondrial tRNA mutations is mostly in postmitotic tissues, studies to elucidate disease mechanisms need to be performed on patient material. Heteroplasmy quantitation and copy number estimation using small patient biopsy samples has not been reported before, mainly due to technical restrictions. In order to resolve this problem, we have developed a robust assay that utilizes Molecular Beacons to accurately quantify heteroplasmy levels and determine mtDNA copy number in small samples carrying the A8344G tRNALys mutation. It provides the methodological basis to investigate the role of heteroplasmy and mtDNA copy number in determining the clinical phenotypes.

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Computational maps are of central importance to a neuronal representation of the outside world. In a map, neighboring neurons respond to similar sensory features. A well studied example is the computational map of interaural time differences (ITDs), which is essential to sound localization in a variety of species and allows resolution of ITDs of the order of 10 μs. Nevertheless, it is unclear how such an orderly representation of temporal features arises. We address this problem by modeling the ontogenetic development of an ITD map in the laminar nucleus of the barn owl. We show how the owl's ITD map can emerge from a combined action of homosynaptic spike-based Hebbian learning and its propagation along the presynaptic axon. In spike-based Hebbian learning, synaptic strengths are modified according to the timing of pre- and postsynaptic action potentials. In unspecific axonal learning, a synapse's modification gives rise to a factor that propagates along the presynaptic axon and affects the properties of synapses at neighboring neurons. Our results indicate that both Hebbian learning and its presynaptic propagation are necessary for map formation in the laminar nucleus, but the latter can be orders of magnitude weaker than the former. We argue that the algorithm is important for the formation of computational maps, when, in particular, time plays a key role.

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As the number of protein folds is quite limited, a mode of analysis that will be increasingly common in the future, especially with the advent of structural genomics, is to survey and re-survey the finite parts list of folds from an expanding number of perspectives. We have developed a new resource, called PartsList, that lets one dynamically perform these comparative fold surveys. It is available on the web at http://bioinfo.mbb.yale.edu/partslist and http://www.partslist.org. The system is based on the existing fold classifications and functions as a form of companion annotation for them, providing ‘global views’ of many already completed fold surveys. The central idea in the system is that of comparison through ranking; PartsList will rank the approximately 420 folds based on more than 180 attributes. These include: (i) occurrence in a number of completely sequenced genomes (e.g. it will show the most common folds in the worm versus yeast); (ii) occurrence in the structure databank (e.g. most common folds in the PDB); (iii) both absolute and relative gene expression information (e.g. most changing folds in expression over the cell cycle); (iv) protein–protein interactions, based on experimental data in yeast and comprehensive PDB surveys (e.g. most interacting fold); (v) sensitivity to inserted transposons; (vi) the number of functions associated with the fold (e.g. most multi-functional folds); (vii) amino acid composition (e.g. most Cys-rich folds); (viii) protein motions (e.g. most mobile folds); and (ix) the level of similarity based on a comprehensive set of structural alignments (e.g. most structurally variable folds). The integration of whole-genome expression and protein–protein interaction data with structural information is a particularly novel feature of our system. We provide three ways of visualizing the rankings: a profiler emphasizing the progression of high and low ranks across many pre-selected attributes, a dynamic comparer for custom comparisons and a numerical rankings correlator. These allow one to directly compare very different attributes of a fold (e.g. expression level, genome occurrence and maximum motion) in the uniform numerical format of ranks. This uniform framework, in turn, highlights the way that the frequency of many of the attributes falls off with approximate power-law behavior (i.e. according to V–b, for attribute value V and constant exponent b), with a few folds having large values and most having small values.

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Theories of image segmentation suggest that the human visual system may use two distinct processes to segregate figure from background: a local process that uses local feature contrasts to mark borders of coherent regions and a global process that groups similar features over a larger spatial scale. We performed psychophysical experiments to determine whether and to what extent the global similarity process contributes to image segmentation by motion and color. Our results show that for color, as well as for motion, segmentation occurs first by an integrative process on a coarse spatial scale, demonstrating that for both modalities the global process is faster than one based on local feature contrasts. Segmentation by motion builds up over time, whereas segmentation by color does not, indicating a fundamental difference between the modalities. Our data suggest that segmentation by motion proceeds first via a cooperative linking over space of local motion signals, generating almost immediate perceptual coherence even of physically incoherent signals. This global segmentation process occurs faster than the detection of absolute motion, providing further evidence for the existence of two motion processes with distinct dynamic properties.

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We have developed a specific and sensitive nucleic acid amplification assay that is suitable for routine gene detection. The assay is based on a novel molecular genetic strategy in which two different RNA probes are hybridized to adjacent positions on a target nucleic acid and then ligated to form an amplifiable reporter RNA. The reporter RNA is then replicated up to a hundred billion-fold in a 30-min isothermal reaction that signals the presence of the target. The assay can detect fewer than 100 nucleic acid molecules; it provides quantitative results over a wide range of target concentrations and it employs a universal format that can detect any infectious agent.

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Leukotriene A4 (LTA4) hydrolase [7E,9E,11Z,14Z)-(5S,6S)-5,6-epoxyicosa-7,9 ,11,14-tetraenoate hydrolase; EC 3.3.2.6] is a bifunctional zinc metalloenzyme which converts LTA4 into the chemotactic agent leukotriene B4 (LTB4). Suicide inactivation, a typical feature of LTA4 hydrolase/aminopeptidase, occurs via an irreversible, apparently mechanism-based, covalent binding of LTA4 to the protein in a 1:1 stoichiometry. Differential lysine-specific peptide mapping of unmodified and suicide-inactivated LTA4 hydrolase has been used to identify a henicosapeptide, encompassing the amino acid residues 365-385 of human LTA4 hydrolase, which is involved in the binding of LTA4, LTA4 methyl ester, and LTA4 ethyl ester to the native enzyme. A modified form of this peptide, generated by lysine-specific digestion of LTA4 hydrolase inactivated by LTA4 ethyl ester, could be isolated for complete Edman degradation. The sequence analysis revealed a gap at position 14, which shows that binding of the leukotriene epoxide had occurred via Tyr-378 in LTA4 hydrolase. Inactivation of the epoxide hydrolase and the aminopeptidase activity was accompanied by a proportionate modification of the peptide. Furthermore, both enzyme inactivation and peptide modification could be prevented by preincubation of LTA4 hydrolase with the competitive inhibitor bestatin, which demonstrates that the henicosapeptide contains functional elements of the active site(s). It may now be possible to clarify the molecular mechanisms underlying suicide inactivation and epoxide hydrolysis by site-directed mutagenesis combined with structural analysis of the lipid molecule, covalently bound to the peptide.