948 resultados para Neural algorithm


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In the past decade, the amount of data in biological field has become larger and larger; Bio-techniques for analysis of biological data have been developed and new tools have been introduced. Several computational methods are based on unsupervised neural network algorithms that are widely used for multiple purposes including clustering and visualization, i.e. the Self Organizing Maps (SOM). Unfortunately, even though this method is unsupervised, the performances in terms of quality of result and learning speed are strongly dependent from the neuron weights initialization. In this paper we present a new initialization technique based on a totally connected undirected graph, that report relations among some intersting features of data input. Result of experimental tests, where the proposed algorithm is compared to the original initialization techniques, shows that our technique assures faster learning and better performance in terms of quantization error.

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Self-Organizing Map (SOM) algorithm has been extensively used for analysis and classification problems. For this kind of problems, datasets become more and more large and it is necessary to speed up the SOM learning. In this paper we present an application of the Simulated Annealing (SA) procedure to the SOM learning algorithm. The goal of the algorithm is to obtain fast learning and better performance in terms of matching of input data and regularity of the obtained map. An advantage of the proposed technique is that it preserves the simplicity of the basic algorithm. Several tests, carried out on different large datasets, demonstrate the effectiveness of the proposed algorithm in comparison with the original SOM and with some of its modification introduced to speed-up the learning.

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This paper presents a parallel genetic algorithm to the Steiner Problem in Networks. Several previous papers have proposed the adoption of GAs and others metaheuristics to solve the SPN demonstrating the validity of their approaches. This work differs from them for two main reasons: the dimension and the characteristics of the networks adopted in the experiments and the aim from which it has been originated. The reason that aimed this work was namely to build a comparison term for validating deterministic and computationally inexpensive algorithms which can be used in practical engineering applications, such as the multicast transmission in the Internet. On the other hand, the large dimensions of our sample networks require the adoption of a parallel implementation of the Steiner GA, which is able to deal with such large problem instances.

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The paper presents a design for a hardware genetic algorithm which uses a pipeline of systolic arrays. These arrays have been designed using systolic synthesis techniques which involve expressing the algorithm as a set of uniform recurrence relations. The final design divorces the fitness function evaluation from the hardware and can process chromosomes of different lengths, giving the design a generic quality. The paper demonstrates the design methodology by progressively re-writing a simple genetic algorithm, expressed in C code, into a form from which systolic structures can be deduced. This paper extends previous work by introducing a simplification to a previous systolic design for the genetic algorithm. The simplification results in the removal of 2N 2 + 4N cells and reduces the time complexity by 3N + 1 cycles.

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We advocate the use of systolic design techniques to create custom hardware for Custom Computing Machines. We have developed a hardware genetic algorithm based on systolic arrays to illustrate the feasibility of the approach. The architecture is independent of the lengths of chromosomes used and can be scaled in size to accommodate different population sizes. An FPGA prototype design can process 16 million genes per second.

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Capturing the pattern of structural change is a relevant task in applied demand analysis, as consumer preferences may vary significantly over time. Filtering and smoothing techniques have recently played an increasingly relevant role. A dynamic Almost Ideal Demand System with random walk parameters is estimated in order to detect modifications in consumer habits and preferences, as well as changes in the behavioural response to prices and income. Systemwise estimation, consistent with the underlying constraints from economic theory, is achieved through the EM algorithm. The proposed model is applied to UK aggregate consumption of alcohol and tobacco, using quarterly data from 1963 to 2003. Increased alcohol consumption is explained by a preference shift, addictive behaviour and a lower price elasticity. The dynamic and time-varying specification is consistent with the theoretical requirements imposed at each sample point. (c) 2005 Elsevier B.V. All rights reserved.

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The Wnt family of secreted signalling molecules controls a wide range of developmental processes in all metazoans. In this investigation we concentrate on the role that members of this family play during the development of (1) the somites and (2) the neural crest. (3) We also isolate a novel component of the Wnt signalling pathway called Naked cuticle and investigate the role that this protein may play in both of the previously mentioned developmental processes. (1) In higher vertebrates the paraxial mesoderm undergoes a mesenchymal-to-epithelial transformation to form segmentally organised structures called somites. Experiments have shown that signals originating from the ectoderm overlying the somites or from midline structures are required for the formation of the somites, but their identity has yet to be determined. Wnt6 is a good candidate as a somite epithelialisation factor from the ectoderm since it is expressed in this tissue. In this study we show that injection of Wnt6-producing cells beneath the ectoderm at the level of the segmental plate or lateral to the segmental plate leads to the formation of numerous small epithelial somites. We show that Wnts are indeed responsible for the epithelialisation of somites by applying Wnt antagonists which result in the segmental plate being unable to form somites. These results show that Wnt6, the only member of this family to be localised to the chick paraxial ectoderm, is able to regulate the development of epithelial somites and that cellular organisation is pivotal in the execution of the differentiation programmes. (2) The neural crest is a population of multipotent progenitor cells that arise from the neural ectoderm in all vertebrate embryos and form a multitude of derivatives including the peripheral sensory neurons, the enteric nervous system, Schwann cells, pigment cells and parts of the craniofacial skeleton. The induction of the neural crest relies on an ectodermally derived signal, but the identity of the molecule performing this role in amniotes is not known. Here we show that Wnt6, a protein expressed in the ectoderm, induces neural crest production. (3) The intracellular response to Wnt signalling depends on the choice of signalling cascade activated in the responding cell. Cells can activate either the canonical pathway that modulates gene expression to control cellular differentiation and proliferation, or the non-canonical pathway that controls cell polarity and movement (Pandur et al. 2002b). Recent work has identified the protein Naked cuticle as an intracellular switch promoting the non-canonical pathway at the expense of the canonical pathway. We have cloned chick Naked cuticle-1 (cNkd1) and demonstrate that it is expressed in a dynamic manner during early embryogenesis. We show that it is expressed in the somites and in particular regions where cells are undergoing movement. Lastly our study shows that the expression of cNkd1 is regulated by Wnt expression originating from the neural tube. This study provides evidence that non-canonical Wnt signalling plays a part in somite development.

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The neural crest is a multipotent embryonic cell population that arises from neural ectoderm and forms derivatives essential for vertebrate function. Neural crest induction requires an ectodermal signal, thought to be a Writ ligand, but the identity of the Wnt that performs this function in amniotes is unknown. Here, we demonstrate that Wnt6, derived from the ectoderm, is necessary for chick neural crest induction. Crucially, we also show that Wnt6 acts through the non-canonical pathway and not the beta-catenin-dependant pathway. Surprisingly, we found that canonical Wnt signaling inhibited neural crest production in the chick embryo. In light of studies in anamniotes demonstrating that canonical Wnt signaling induces neural crest, these results indicate a significant and novel change in the mechanism of neural crest induction during vertebrate evolution. These data also highlight a key role for noncanonical Wnt signaling in cell type specification from a stem population during development.

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We have developed a novel Hill-climbing genetic algorithm (GA) for simulation of protein folding. The program (written in C) builds a set of Cartesian points to represent an unfolded polypeptide's backbone. The dihedral angles determining the chain's configuration are stored in an array of chromosome structures that is copied and then mutated. The fitness of the mutated chain's configuration is determined by its radius of gyration. A four-helix bundle was used to optimise simulation conditions, and the program was compared with other, larger, genetic algorithms on a variety of structures. The program ran 50% faster than other GA programs. Overall, tests on 100 non-redundant structures gave comparable results to other genetic algorithms, with the Hill-climbing program running from between 20 and 50% faster. Examples including crambin, cytochrome c, cytochrome B and hemerythrin gave good secondary structure fits with overall alpha carbon atom rms deviations of between 5 and 5.6 Angstrom with an optimised hydrophobic term in the fitness function. (C) 2003 Elsevier Ltd. All rights reserved.

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The vertebrate Zic gene family encodes C2H2 zinc finger transcription factors closely related to the Gli proteins. Zic genes are expressed in multiple areas of developing vertebrate embryos, including the dorsal neural tube where they act as potent neural crest inducers. Here we describe the characterization of a Zic ortholog from the amphioxus Branchiostoma floridae and further describe the expression of a Zic ortholog from the ascidian Ciona intestinalis. Molecular phylogenetic analysis and sequence comparisons suggest the gene duplications that formed the vertebrate Zic family were specific to the vertebrate lineage. In Ciona maternal CiZic/Ci-macho1 transcripts are localized during cleavage stages by asymmetric cell division, whereas zygotic expression by neural plate cells commences during neurulation. The amphioxus Zic ortholog AmphiZic is expressed in dorsal mesoderm and ectoderm during gastrulation, before being eliminated first from midline cells and then from all neurectoderm during neurulation. After neurulation, expression is reactivated in the dorsal neural tube and dorsolateral somite. Comparison of CiZic and AmphiZic expression with vertebrate Zic expression leads to two main conclusions. First, Zic expression allows us to define homologous compartments between vertebrate and amphioxus somites, showing primitive subdivision of vertebrate segmented mesoderm. Second, we show that neural Zic expression is a chordate synapomorphy, whereas the precise pattern of neural expression has evolved differently on the different chordate lineages. Based on these observations we suggest that a change in Zic regulation, specifically the evolution of a dorsal neural expression domain in vertebrate neurulae, was an important step in the evolution of the neural crest.

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Liquid chromatography-mass spectrometry (LC-MS) datasets can be compared or combined following chromatographic alignment. Here we describe a simple solution to the specific problem of aligning one LC-MS dataset and one LC-MS/MS dataset, acquired on separate instruments from an enzymatic digest of a protein mixture, using feature extraction and a genetic algorithm. First, the LC-MS dataset is searched within a few ppm of the calculated theoretical masses of peptides confidently identified by LC-MS/MS. A piecewise linear function is then fitted to these matched peptides using a genetic algorithm with a fitness function that is insensitive to incorrect matches but sufficiently flexible to adapt to the discrete shifts common when comparing LC datasets. We demonstrate the utility of this method by aligning ion trap LC-MS/MS data with accurate LC-MS data from an FTICR mass spectrometer and show how hybrid datasets can improve peptide and protein identification by combining the speed of the ion trap with the mass accuracy of the FTICR, similar to using a hybrid ion trap-FTICR instrument. We also show that the high resolving power of FTICR can improve precision and linear dynamic range in quantitative proteomics. The alignment software, msalign, is freely available as open source.

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Previous functional imaging studies have shown that facilitated processing of a visual object on repeated, relative to initial, presentation (i.e., repetition priming) is associated with reductions in neural activity in multiple regions, including fusiforin/lateral occipital cortex. Moreover, activity reductions have been found, at diminished levels, when a different exemplar of an object is presented on repetition. In one previous study, the magnitude of diminished priming across exemplars was greater in the right relative to the left fusiform, suggesting greater exemplar specificity in the right. Another previous study, however, observed fusiform lateralization modulated by object viewpoint, but not object exemplar. The present fMRI study sought to determine whether the result of differential fusiform responses for perceptually different exemplars could be replicated. Furthermore, the role of the left fusiform cortex in object recognition was investigated via the inclusion of a lexical/semantic manipulation. Right fusiform cortex showed a significantly greater effect of exemplar change than left fusiform, replicating the previous result of exemplar-specific fusiform lateralization. Right fusiform and lateral occipital cortex were not differentially engaged by the lexical/semantic manipulation, suggesting that their role in visual object recognition is predominantly in the. C visual discrimination of specific objects. Activation in left fusiform cortex, but not left lateral occipital cortex, was modulated by both exemplar change and lexical/semantic manipulation, with further analysis suggesting a posterior-to-anterior progression between regions involved in processing visuoperceptual and lexical/semantic information about objects. The results are consistent with the view that the right fusiform plays a greater role in processing specific visual form information about objects, whereas the left fusiform is also involved in lexical/semantic processing. (C) 2003 Elsevier Science (USA). All rights reserved.

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It has been previously demonstrated that extensive activation in the dorsolateral temporal lobes associated with masking a speech target with a speech masker, consistent with the hypothesis that competition for central auditory processes is an important factor in informational masking. Here, masking from speech and two additional maskers derived from the original speech were investigated. One of these is spectrally rotated speech, which is unintelligible and has a similar (inverted) spectrotemporal profile to speech. The authors also controlled for the possibility of "glimpsing" of the target signal during modulated masking sounds by using speech-modulated noise as a masker in a baseline condition. Functional imaging results reveal that masking speech with speech leads to bilateral superior temporal gyrus (STG) activation relative to a speech-in-noise baseline, while masking speech with spectrally rotated speech leads solely to right STG activation relative to the baseline. This result is discussed in terms of hemispheric asymmetries for speech perception, and interpreted as showing that masking effects can arise through two parallel neural systems, in the left and right temporal lobes. This has implications for the competition for resources caused by speech and rotated speech maskers, and may illuminate some of the mechanisms involved in informational masking.