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Computational and biological approach to understand the 3′ UTR-mediated posttranscriptional regulation of alfalfa cytosolic glutamine synthetase genes

Computational and biological approach to understand the 3′ ...

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2nd International Conference on Bioinformatics and Computational Biology 2010, BICoB 2010

作者： Simon, Bindu Sengupta-Gopalan, Champa Yelavarthi, Pavan K. Ranjan, Desh Graduate Program in Molecular Biology New Mexico State University Las Cruces NM 88003 United States Dept. of Plant and Environmental Sciences New Mexico State University Las Cruces NM 88003 United States Department of Computer Science New Mexico State University Las Cruces NM 88003 United States Department of Computer Science Old Dominion University Norfolk VA 23529 United States

ISBN: (纸本)9781617381119

Glutamine synthetase (GS) is a key enzyme in nitrogen metabolism in plants. One of the GS isoforms in plants, GS1, is transcriptionally regulated. Our recent studies show that a soybean GS1, Gmglnβ 1, gene is posttranscriptionally regulated by its 3′UTR. It is of interest to know if the 3′UTR-mediated posttranscriptional regulation of GS1 genes is a universal phenomenon or is it limited to Gmglnβ 1 gene only. The 3′UTR-mediated posttranscriptional regulation of alfalfa GS1 genes (MsGS100 and MsGS13) was investigated using both computational and biological approaches. For our first set of study, we used CisFind, a software tool that identifies unextendable common patterns among sequences, to analyze the 3′UTRs of GS1 genes. CisFind analysis of the 3′UTRs showed that the 3′UTR of MsGS100 shared common putative cis-element motifs with the Gmglnβ 1 3′UTR whereas these elements were absent in the 3′UTR of MsGS13 gene. The computational results were verified using transgenic approach, and the results confirmed the computational analysis. The 3′UTR of MsGS 100 plays a similar role as the 3′UTR of Gmglnβ 1 gene in posttranscriptional regulation of a reporter gene while the 3′UTR of the MsGS13 does not. CisFind, was also used in analyzing the region in the 3′UTR of MsGS13 that could be responsible for its nodule enhanced expression (by detecting putative cis-elements that are overrepresented in the 3′UTR of nodule-enhanced GS1 genes).

关键词： Amino acids

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A scalable method for detecting multiple loci associated with traits using TF-IDF weighting and association rule mining

A scalable method for detecting multiple loci associated wit...

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IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)

作者： Sunwon Lee Jaewoo Kang Junho Oh Department of Graduate Program in Bioinformatics Korea University Seoul South Korea Department of Computer Science and Engineering Korea University Seoul South Korea

The recent advance in SNP genotyping has made a significant contribution to reduction of the costs for large-scale genotyping. The development also has dramatically increased the size of the SNP genotype data. The increase of the volume of the data, however, has posed a huge obstacle to the conventional analysis techniques that are typically vulnerable to the high-dimensionality problem. To address the issue, we propose a method that exploits two well-tested models: the document-term model and the transaction analysis model. The proposed method consists of two phases. In the first phase, we reduce the dimensions of the SNP genotype data by extracting significant SNPs through transformation of the data in lieu of the document-term model. In the second phase, we discover the association rules that signify the relations between the SNPs and the traits, through the application of the transactional analysis in the reduced-dimension genotype data. We validated the discovered rules through the literature survey. Experiments were also carried out using the HGDP panel data provided by the Foundation Jean Dausset-CEPH, which prove the validity of our new method for identifying appropriate dimensional reduction and associations of multiple SNPs and traits.

关键词： Association rules Data models Analytical models Diseases Asia Context

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computer Security Aspects in Industrial Instrumentation and Measurements

Computer Security Aspects in Industrial Instrumentation and ...

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IEEE Instrumentation & Measurement Technology Conference

作者： M. Lazzaroni V. Piuri C. Maziero Dipartimento di Tecnologie dell'Informazione Universita degli Studi di Milano Graduate Program in Computer Science Pontifical Catholic University of Parana

ISBN: (纸本)9781424428328;9781424428335

Industrial Control Systems (ICS), formerly isolated proprietary systems, are giving place to highly-connected systems, implemented using widespread operating systems and network protocols on public networks. Such standardization trend opens the door to security threats previously restricted to the corporate and personal computing areas. This paper presents how the main concepts of security in conventional computing systems can be exploited in dependability aspects of ICS, and presents some considerations on how security aspects of a standard-based could be applied to a typical control board used in industrial applications involving measurement.

关键词： Security Safety Availability Dependability Industrial measurement

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Optimization of the holder image descriptor using a genetic algorithm 10

Optimization of the holder image descriptor using a genetic ...

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12th Annual Genetic and Evolutionary Computation Conference, GECCO-2010

作者： Trujillo, Leonardo Legrand, Pierrick Olague, Gustavo Pérez, Cynthia Instituto Tecnológico de Tijuana Computer Science Graduate Program Tijuana B.C Mexico Université Victor Segalen Bordeaux 2 ALEA Team UMR CNRS 5251 France Evo Visión Project CICESE Research Center Ensenada B.C Mexico

ISBN: (纸本)9781450300728

Local image features can provide the basis for robust and invariant recognition of objects and scenes. Therefore, compact and distinctive representations of local shape and appearance has become invaluable in modern computer vision. In this work, we study a local descriptor based on the Holder exponent, a measure of signal regularity. The proposal is to find an optimal number of dimensions for the descriptor using a genetic algorithm (GA). To guide the GA search, fitness is computed based on the performance of the descriptor when applied to standard region matching problems. This criterion is quantified using the F-Measure, derived from recall and precision analysis. Results show that it is possible to reduce the size of the canonical Holder descriptor without degrading the quality of its performance. In fact, the best descriptor found through the GA search is nearly 70% smaller and achieves similar performance on standard tests. Copyright 2010 ACM.

关键词： Genetic algorithms

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Accelerating the Shuffled Frog Leaping algorithm by parallel implementations in FPGAs

Accelerating the Shuffled Frog Leaping algorithm by parallel...

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2010 IEEE 5th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2010

作者： Muñoz, Daniel M. Llanos, Carlos H. Dos S. Coelho, Leandro Ayala-Rincón, Mauricio Department of Mechanical Engineering Automation and Control Group/GRACG University of Brasilia Brasilia D.F. Brazil Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Parana Curitiba Parana Brazil Department of Computer Science and Mathematics University of Brasilia Brasilia D.F. Brazil

ISBN: (纸本)9781424464388

Meta-heuristics are efficient techniques for solving large scale optimization problems in which traditional mathematical techniques are impractical or provide sub-optimal solutions. The Shuffled Frog Leaping algorithm (SFLA) is a stochastic iterative method, bio-inspired on the memetic evolution of a group of frogs when seeking for food, which combines the social behavior-based of the particle swarm optimization technique (PSO) and the global information exchange of memetic algorithms. However, the SFLA algorithm suffers on large execution times, being this problem clearly evident when solving complex optimization problems for embedded applications. This drawback can be overcome by exploiting the parallel capabilities of the SFLA. This paper proposes a hardware parallel implementation of the SFLA algorithm (HPSFLA) using FPGAs (Field programmable gate Arrays) and the efficient floating-point arithmetic. The proposed architecture allows the SFLA to improve the functionality of the algorithm as well as to decrease the execution times by implementing parallel frogs and parallel memeplexes. Three well-known benchmark problems have been used to validate the implemented algorithm and simulation results demonstrate that the HPSFLA speeds-up by factors of 362, 727 and 211 a C-code implementation using an embedded microprocessor for the Sphere, Rastrigin and Rosenbrock benchmarks problems, respectively. Synthesis, simulation and execution time results demonstrate the effectiveness of the proposed HPSFLA architecture for embedded optimization systems. © 2010 IEEE.

关键词： Global optimization

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A fuzzy inference system to determine the number of clones in the clonal selection algorithm

A fuzzy inference system to determine the number of clones i...

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World Congress on Nature & Biologically Inspired Computing (NaBIC)

作者： Luiz Antonio Carraro Leandro Nunes de Castro Angelita Maria de Ré Computer and Informatics Faculty & Graduate Program in Electrical Engineering Mackenzie University São Paulo Brazil Computer Science Department State University of West-Center Parana Guarapuava Brazil

Artificial Immune Systems (AISs) are composed of techniques inspired by immunology. The clonal selection principle ensures the organism adaptation to fight invading antigens by an immune response activated by the binding of antigens and antibodies. As an immune response can be elicited even when the binding between an antigen and an antibody is not perfect, an approximate binding might suffice, and a Fuzzy Logic mechanism might be the most appropriate mechanism to control such process. This paper presents a novel hybrid model based on concepts of Immune and Fuzzy Systems with applications to pattern recognition problems. The preliminary results obtained here suggest the proposed model is a promising pattern recognition tool.

关键词： Variable speed drives Animals

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Photonic crystal defects with increased surface area for improved refractive index sensing

Photonic crystal defects with increased surface area for imp...

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Conference on Lasers and Electro-Optics, CLEO 2010

作者： Kang, Christopher Christopher Phare Weiss, Sharon M. Vlasov, Yurii A. Assefa, Solomon Interdisciplinary Graduate Program in Materials Science Vanderbilt University Nashville TN 37235 United States Department of Physics and Astronomy Vanderbilt University Nashville TN 37235 United States Department of Electrical Engineering and Computer Science Vanderbilt University Tennessee 37235 United States IBM T.J. Watson Research Center Yorktown Heights NY 10536 United States

Photonic crystal cavities with tunable surface area via multiple-hole defects were investigated for increased resonance wavelength shifts upon exposure to variable-index analytes. Sensitivity was improved by 10% compa... 详细信息

ISBN: (纸本)9781557528896

关键词： Refractive index

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Photonic crystal defects with increased surface area for improved refractive index sensing

Photonic crystal defects with increased surface area for imp...

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Conference on Lasers and Electro-Optics

作者： Kang, Christopher Phare, Christopher Weiss, Sharon M. Vlasov, Yurii A. Assefa, Solomon Interdisciplinary Graduate Program in Materials Science Vanderbilt University Nashville TN 37235 United States Department of Physics and Astronomy Vanderbilt University Nashville TN 37235 United States Department of Electrical Engineering and Computer Science Vanderbilt University 37235 United States IBM. T.J. Watson Research Center Yorktown Heights NY 10536 United States

Photonic crystal cavities with tunable surface area via multiple-hole defects were investigated for increased resonance wavelength shins upon exposure to variable-index analytes. Sensitivity was improved by 10% compar... 详细信息

ISBN: (纸本)9781557528902

关键词： Surface defects

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Comparison between two FPGA implementations of the particle swarm optimization algorithm for high-performance embedded applications

Comparison between two FPGA implementations of the particle ...

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2010 IEEE 5th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2010

作者： Muñoz, Daniel M. Llanos, Carlos H. Dos S. Coelho, Leandro Ayala-Rincón, Mauricio Department of Mechanical Engineering Automation and Control Group/GRACO University of Brasilia Brasilia D.F. Brazil Industrial and Systems Engineering Graduate Program LAS/PPGPES Pontifical Catholic University of Parana Curitiba Parana Brazil Department of Computer Science and Mathematics University of Brasilia Brasilia D.F. Brazil

ISBN: (纸本)9781424464388

Particle Swarm Optimization (PSO) algorithms have been proposed to solve engineering problems that require to find an optimal point of operation. There are several embedded applications which requires to solve online optimization problems with a high performance. However, the PSO suffers on large execution times, and this fact becomes evident when using Reduced Instruction Set computer (RISC) microprocessors in which the operational frequencies are low in comparison with the high operational frequencies of traditional personal computers (PCs). This paper compares two hardware implementations of the parallel PSO algorithm using an efficient floating-point arithmetic which perform computations with large dynamic range and high precision. The full-parallel and the partially-parallel PSO architectures allow the parallel capabilities of the PSO to be exploited in order to decrease the running time. Three well-known benchmark test functions have been used to validate the hardware architectures and a comparison in terms of cost in logic area, quality of the solution and performance is reported. In addition, a comparison of the execution time between the hardware and two C-code software implementations, based on a Intel Core Duo at 1.6GHz and a embedded Microblaze microprocessor at 50MHz, are presented. © 2010 IEEE.

关键词： Global optimization

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Empirical Studies on Application of Genetic Algorithms and Ant Colony Optimization for Data Clustering

Empirical Studies on Application of Genetic Algorithms and A...

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computer science Society (SCCC) International Conference Chilean FLAGGED

作者： Thelma Elita Colanzi Wesley Klewerton Guez Assunção Aurora Trinidad Ramirez Pozo Ana Cristina B. Kochem Vendramin Diogo Augusto Barros Pereira Computer Science Postgraduate Program Federal University of Paraná (UFPR) Curitiba Paraná Brazil Graduate School of Electrical Engineering and Computer Science (CPGEI) Federal Technological University of Paraná (UTFPR) Curitiba Paraná Brazil Informatics Department (DAINF)

Cluster analysis is used in several research areas to classify data sets in groups by their similar characteristics. Metaheuristic-based techniques, such as Genetic Algorithms (GAs) and Ant Colony Optimization (ACO), have been applied in order to increase the clustering algorithm performance. GA and ACO-based clustering algorithms are capable of efficiently and automatically forming natural groups from a pre-defined number of clusters. This paper presents a GA and an ACO algorithm to the clustering problem. Both algorithms were refined using local search in order to improve the clustering accuracy. The results are compared on numeric UCI databases.

关键词： Clustering algorithms Search problems Equations Mathematical model Gallium Genetic algorithms Memetics

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