scholarly journals Efficient Serial and Parallel Algorithms for Selection of Unique Oligos in EST Databases

2013 ◽  
Vol 2013 ◽  
pp. 1-6
Author(s):  
Manrique Mata-Montero ◽  
Nabil Shalaby ◽  
Bradley Sheppard
Keyword(s):  
Parallel Algorithms ◽  
Human Genome ◽  
Search Problem ◽  
Brute Force ◽  
Est Database ◽  
New Genes ◽  
Brute Force Approach ◽  
New Algorithms ◽  
Selection Of

Obtaining unique oligos from an EST database is a problem of great importance in bioinformatics, particularly in the discovery of new genes and the mapping of the human genome. Many algorithms have been developed to find unique oligos, many of which are much less time consuming than the traditional brute force approach. An algorithm was presented by Zheng et al. (2004) which finds the solution of the unique oligos search problem efficiently. We implement this algorithm as well as several new algorithms based on some theorems included in this paper. We demonstrate how, with these new algorithms, we can obtain unique oligos much faster than with previous ones. We parallelize these new algorithms to further improve the time of finding unique oligos. All algorithms are run on ESTs obtained from a Barley EST database.

scholarly journals Combining metabolomic and transcriptomic approaches to assess and improve crop quality traits

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Delphine M. Pott ◽  
Sara Durán-Soria ◽  
Sonia Osorio ◽  
José G. Vallarino
Keyword(s):  
Quality Trait ◽  
Quality Traits ◽  
Crop Species ◽  
Breeding Programs ◽  
Crop Quality ◽  
Crop Varieties ◽  
New Genes ◽  
Technical Advances ◽  
Health Promoting ◽  
Selection Of

AbstractPlant quality trait improvement has become a global necessity due to the world overpopulation. In particular, producing crop species with enhanced nutrients and health-promoting compounds is one of the main aims of current breeding programs. However, breeders traditionally focused on characteristics such as yield or pest resistance, while breeding for crop quality, which largely depends on the presence and accumulation of highly valuable metabolites in the plant edible parts, was left out due to the complexity of plant metabolome and the impossibility to properly phenotype it. Recent technical advances in high throughput metabolomic, transcriptomic and genomic platforms have provided efficient approaches to identify new genes and pathways responsible for the extremely diverse plant metabolome. In addition, they allow to establish correlation between genotype and metabolite composition, and to clarify the genetic architecture of complex biochemical pathways, such as the accumulation of secondary metabolites in plants, many of them being highly valuable for the human diet. In this review, we focus on how the combination of metabolomic, transcriptomic and genomic approaches is a useful tool for the selection of crop varieties with improved nutritional value and quality traits.

scholarly journals Evolutionary design of optimal surface topographies for biomaterials

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Aliaksei Vasilevich ◽  
Aurélie Carlier ◽  
David A. Winkler ◽  
Shantanu Singh ◽  
Jan de Boer
Keyword(s):  
High Throughput Screening ◽  
Random Mutagenesis ◽  
Material Design ◽  
Fitness Assessment ◽  
Surface Topographies ◽  
Optimal Surface ◽  
Design Production ◽  
Brute Force Approach ◽  
Survival Of The Fittest ◽  
Selection Of

AbstractNatural evolution tackles optimization by producing many genetic variants and exposing these variants to selective pressure, resulting in the survival of the fittest. We use high throughput screening of large libraries of materials with differing surface topographies to probe the interactions of implantable device coatings with cells and tissues. However, the vast size of possible parameter design space precludes a brute force approach to screening all topographical possibilities. Here, we took inspiration from Nature to optimize materials surface topographies using evolutionary algorithms. We show that successive cycles of material design, production, fitness assessment, selection, and mutation results in optimization of biomaterials designs. Starting from a small selection of topographically designed surfaces that upregulate expression of an osteogenic marker, we used genetic crossover and random mutagenesis to generate new generations of topographies.

scholarly journals LHC physicists embrace brute-force approach to particle hunt

Nature ◽  
2018 ◽  
Vol 560 (7718) ◽  
pp. 293-294
Author(s):  
Davide Castelvecchi
Keyword(s):  
Brute Force ◽  
Brute Force Approach

scholarly journals Efficient Parameterized Word Matching Using Bit-Parallelism and Partitioning the Text

2016 ◽  
Vol 2 (2) ◽  
pp. 20
Author(s):  
Rajesh Prasad
Keyword(s):  
Experimental Results ◽  
Brute Force ◽  
White Space ◽  
Matching Problem ◽  
One To One ◽  
Brute Force Approach ◽  
Better Than

Word matching problem is to find all the exact occurrences of a pattern P[0...m-1] in the text T[0...n-1], where P neither contains any white space nor preceded and followed by space. In the parameterized word matching problem, a given word P[0...m-1] is said to match with a sub-word t of the text T[0...n-1], if there exists a one-to-one correspondence between the symbols of P and the symbols of t. Exact Word Matching (EWM) problem has been previously solved by partitioning the text into number of tables in the pre-processing phase and then applying either brute force approach or fast hashing during the searching process. This paper presents an extension of EWM problem for parameterized word matching. It first split the text into number of tables in the pre-processing phase and then applying prev-encoding and bit-parallelism technique, Parameterized Shift-Or (PSO) during the searching phase. Experimental results show that this technique performs better than PSO.

scholarly journals A Hybrid Computational Intelligence based Technique for Automatic Cryptanalysis of Playfair Ciphers

2020 ◽  
Vol 70 (6) ◽  
pp. 612-618
Author(s):  
Maiya Din ◽  
Saibal K. Pal ◽  
S. K. Muttoo ◽  
Sushila Madan
Keyword(s):  
Computational Intelligence ◽  
Text Message ◽  
Search Space ◽  
Population Based ◽  
English Text ◽  
Hybrid Technique ◽  
Brute Force ◽  
Symmetric Key ◽  
Brute Force Approach ◽  
Multiple Particle

The Playfair cipher is a symmetric key cryptosystem-based on encryption of digrams of letters. The cipher shows higher cryptanalytic complexity compared to mono-alphabetic cipher due to the use of 625 different letter-digrams in encryption instead of 26 letters from Roman alphabets. Population-based techniques like Genetic algorithm (GA) and Swarm intelligence (SI) are more suitable compared to the Brute force approach for cryptanalysis of cipher because of specific and unique structure of its Key Table. This work is an attempt to automate the process of cryptanalysis using hybrid computational intelligence. Multiple particle swarm optimization (MPSO) and GA-based hybrid technique (MPSO-GA) have been proposed and applied in solving Playfair ciphers. The authors have attempted to find the solution key applied in generating Playfair crypts by using the proposed hybrid technique to reduce the exhaustive search space. As per the computed results of the MPSO-GA technique, correct solution was obtained for the Playfair ciphers of 100 to 200 letters length. The proposed technique provided better results compared to either GA or PSO-based technique. Furthermore, the technique was also able to recover partial English text message for short Playfair ciphers of 80 to 120 characters length.

scholarly journals Exploiting distant homologues for phasing through the generation of compact fragments, local fold refinement and partial solution combination

2018 ◽  
Vol 74 (4) ◽  
pp. 290-304 ◽  
Author(s):  
Claudia Millán ◽  
Massimo Domenico Sammito ◽  
Airlie J. McCoy ◽  
Andrey F. Ziem Nascimento ◽  
Giovanna Petrillo ◽  
...  
Keyword(s):  
Fragment Size ◽  
Sequence Similarity ◽  
Three Dimensional ◽  
Partial Solution ◽  
Molecular Replacement ◽  
Search Models ◽  
Full Structure ◽  
Phase Combination ◽  
Brute Force Approach ◽  
New Algorithms

Macromolecular structures can be solved by molecular replacement provided that suitable search models are available. Models from distant homologues may deviate too much from the target structure to succeed, notwithstanding an overall similar fold or even their featuring areas of very close geometry. Successful methods to make the most of such templates usually rely on the degree of conservation to select and improve search models.ARCIMBOLDO_SHREDDERuses fragments derived from distant homologues in a brute-force approach driven by the experimental data, instead of by sequence similarity. The new algorithms implemented inARCIMBOLDO_SHREDDERare described in detail, illustrating its characteristic aspects in the solution of new and test structures. In an advance from the previously published algorithm, which was based on omitting or extracting contiguous polypeptide spans, model generation now uses three-dimensional volumes respecting structural units. The optimal fragment size is estimated from the expected log-likelihood gain (LLG) values computed assuming that a substructure can be found with a level of accuracy near that required for successful extension of the structure, typically below 0.6 Å root-mean-square deviation (r.m.s.d.) from the target. Better sampling is attempted through model trimming or decomposition into rigid groups and optimization throughPhaser'sgyrerefinement. Also, after model translation, packing filtering and refinement, models are either disassembled into predetermined rigid groups and refined (gimblerefinement) orPhaser's LLG-guided pruning is used to trim the model of residues that are not contributing signal to the LLG at the target r.m.s.d. value. Phase combination among consistent partial solutions is performed in reciprocal space withALIXE. Finally, density modification and main-chain autotracing inSHELXEserve to expand to the full structure and identify successful solutions. The performance on test data and the solution of new structures are described.

Method and Verification for Material Calibration of the Chaboche Plasticity Model for Multiple Material Directions

2021 ◽  
Author(s):  
Charles R. Krouse ◽  
Grant O. Musgrove ◽  
Taewoan Kim ◽  
Seungmin Lee ◽  
Muhyoung Lee ◽  
...  
Keyword(s):  
Experimental Data ◽  
Kinematic Hardening ◽  
Material Model ◽  
Brute Force ◽  
Hardening Material ◽  
Material Constants ◽  
Automated Method ◽  
Chaboche Model ◽  
Multiple Material ◽  
Brute Force Approach

Abstract The Chaboche model is a well-validated non-linear kinematic hardening material model. This material model, like many models, depends on a set of material constants that must be calibrated for it to match the experimental data. Due to the challenge of calibrating these constants, the Chaboche model is often disregarded. The challenge with calibrating the Chaboche constants is that the most reliable method for doing the calibration is a brute force approach, which tests thousands of combinations of constants. Different sampling techniques and optimization schemes can be used to select different combinations of these constants, but ultimately, they all rely on iteratively selecting values and running simulations for each selected set. In the experience of the authors, such brute force methods require roughly 2,500 combinations to be evaluated in order to have confidence that a reasonable solution is found. This process is not efficient. It is time-intensive and labor-intensive. It requires long simulation times, and it requires significant effort to develop the accompanying scripts and algorithms that are used to iterate through combinations of constants and to calculate agreement. A better, more automated method exists for calibrating the Chaboche material constants. In this paper, the authors describe a more efficient, automated method for calibrating Chaboche constants. The method is validated by using it to calibrate Chaboche constants for an IN792 single-crystal material and a CM247 directionally-solidified material. The calibration results using the automated approach were compared to calibration results obtained using a brute force approach. It was determined that the automated method achieves agreeable results that are equivalent to, or supersede, results obtained using the conventional brute force method. After validating the method for cases that only consider a single material orientation, the automated method was extended to multiple off-axis calibrations. The Chaboche model that is available in commercial software, such as ANSYS, will only accept a single set of Chaboche constants for a given temperature. There is no published method for calibrating Chaboche constants that considers multiple material orientations. Therefore, the approach outlined in this paper was extended to include multiple material orientations in a single calibration scheme. The authors concluded that the automated approach can be used to successfully, accurately, and efficiently calibrate multiple material directions. The approach is especially well-suited when off-axis calibration must be considered concomitantly with longitudinal calibration. Overall, the automated Chaboche calibration method yielded results that agreed well with experimental data. Thus, the method can be used with confidence to efficiently and accurately calibrate the Chaboche non-linear kinematic hardening material model.

A Method for Solving Multi-Objective Optimization Problems Containing an Infinite Number of Parameterized Objectives

2020 ◽  
Author(s):  
Eliot Rudnick-Cohen
Keyword(s):  
Decision Making ◽  
Infinite Number ◽  
Optimization Problems ◽  
Pareto Frontier ◽  
Brute Force ◽  
Multi Objective Optimization ◽  
New Approach ◽  
Multi Objective ◽  
Brute Force Approach ◽  
Better Than

Abstract Multi-objective decision making problems can sometimes involve an infinite number of objectives. In this paper, an approach is presented for solving multi-objective optimization problems containing an infinite number of parameterized objectives, termed “infinite objective optimization”. A formulation is given for infinite objective optimization problems and an approach for checking whether a Pareto frontier is a solution to this formulation is detailed. Using this approach, a new sampling based approach is developed for solving infinite objective optimization problems. The new approach is tested on several different example problems and is shown to be faster and perform better than a brute force approach.

PARALLEL ALGORITHMS FOR CELLULAR MODELS SIMULATION

2007 ◽  
Vol 17 (03) ◽  
pp. 263-285
Author(s):  
SHAFAGH JAFER ◽  
GABRIEL A. WAINER
Keyword(s):  
Dynamic System ◽  
Parallel Algorithms ◽  
Modeling And Simulation ◽  
Formal Modeling ◽  
Frequency Model ◽  
Time Warp ◽  
Cellular Models ◽  
Simulation Engine ◽  
Original Time ◽  
New Algorithms

DEVS is a sound formal modeling and simulation (M&S) framework based on generic dynamic system concepts. Cell-DEVS is a formalism for cell-shaped models based on DEVS. This work presents a new simulation technique for execution of DEVS and Cell-DEVS models in parallel environments. These techniques are modifications to the original Time Warp mechanism offered by WARPED kernel. Time Warp functionalities are revised to include two new algorithms namely, Local Rollback Frequency Model (LRFM) and Global Rollback Frequency Model (GRFM). The resulting simulator is used as new simulation engine for CD++, an M&S toolkit that implements DEVS and Cell-DEVS theories. The results obtained allowed us to achieve considerable speedups due to the reductions that LRFM and GRFM protocols perform on number of rollbacks and anti-messages.

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