optimization-based algorithm Search Results


growth-based optimization (gbo) algorithms  (Greiner Bio)
90
Greiner Bio growth-based optimization (gbo) algorithms
Comparison of the performance and total vascular tree volume with different number of processors when generating 5003 terminal segments using a <t> growth-based optimization </t> (GBO) algorithm
Growth Based Optimization (Gbo) Algorithms, supplied by Greiner Bio, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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a multidirectional optimum ecotope-based algorithm [amoeba] statistics  (Ecotope Inc)
90
Ecotope Inc a multidirectional optimum ecotope-based algorithm [amoeba] statistics
Comparison of the performance and total vascular tree volume with different number of processors when generating 5003 terminal segments using a <t> growth-based optimization </t> (GBO) algorithm
A Multidirectional Optimum Ecotope Based Algorithm [Amoeba] Statistics, supplied by Ecotope Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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multi-chromosome coding-based genetic algorithm  (Gurobi Optimization)
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Gurobi Optimization multi-chromosome coding-based genetic algorithm
Comparison of the performance and total vascular tree volume with different number of processors when generating 5003 terminal segments using a <t> growth-based optimization </t> (GBO) algorithm
Multi Chromosome Coding Based Genetic Algorithm, supplied by Gurobi Optimization, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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ant colony optimization-based image segmentation algorithm  (Changbai Mountain Tourism Co Ltd)
90
Changbai Mountain Tourism Co Ltd ant colony optimization-based image segmentation algorithm
Comparison of the performance and total vascular tree volume with different number of processors when generating 5003 terminal segments using a <t> growth-based optimization </t> (GBO) algorithm
Ant Colony Optimization Based Image Segmentation Algorithm, supplied by Changbai Mountain Tourism Co Ltd, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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hardware-based optimizations for the pairhmm algorithm in haplotypecaller  (Broad Institute Inc)
90
Broad Institute Inc hardware-based optimizations for the pairhmm algorithm in haplotypecaller
Churchill enables rapid secondary analysis and variant calling with GATK <t>HaplotypeCaller</t> using cloud computing resources. Analysis of raw sequence data for a single human genome sequence dataset (30× coverage) was compared using Churchill and bcbio-nextgen, with both pipelines utilizing BWA-MEM for alignment and GATK HaplotypeCaller for variant detection and genotyping. (A) CPU utilization on a single r3.8xlarge AWS EC2 instance (32 cores) was monitored throughout the analysis process and demonstrated that Churchill improved resource utilization (94%) when compared with bcbio-nextgen (57%), enabling the entire analysis to be completed in under 12 hours with a single instance. (B) Unlike bcbio-nextgen, Churchill enables all steps of the analysis process to be efficiently scaled across multiple compute nodes, resulting in significantly reduced run times. With 16 AWS EC2 instances the entire analysis could be completed in 104 minutes, with the variant calling and genotyping with GATK HaplotypeCaller stage taking only 24 minutes of the total run time.
Hardware Based Optimizations For The Pairhmm Algorithm In Haplotypecaller, supplied by Broad Institute Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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swarm intelligence  (BioMimetic Therapeutics)
90
BioMimetic Therapeutics swarm intelligence
Churchill enables rapid secondary analysis and variant calling with GATK <t>HaplotypeCaller</t> using cloud computing resources. Analysis of raw sequence data for a single human genome sequence dataset (30× coverage) was compared using Churchill and bcbio-nextgen, with both pipelines utilizing BWA-MEM for alignment and GATK HaplotypeCaller for variant detection and genotyping. (A) CPU utilization on a single r3.8xlarge AWS EC2 instance (32 cores) was monitored throughout the analysis process and demonstrated that Churchill improved resource utilization (94%) when compared with bcbio-nextgen (57%), enabling the entire analysis to be completed in under 12 hours with a single instance. (B) Unlike bcbio-nextgen, Churchill enables all steps of the analysis process to be efficiently scaled across multiple compute nodes, resulting in significantly reduced run times. With 16 AWS EC2 instances the entire analysis could be completed in 104 minutes, with the variant calling and genotyping with GATK HaplotypeCaller stage taking only 24 minutes of the total run time.
Swarm Intelligence, supplied by BioMimetic Therapeutics, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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whale optimization algorithm based fopi controllers  (Statcom Co Ltd)
90
Statcom Co Ltd whale optimization algorithm based fopi controllers
Churchill enables rapid secondary analysis and variant calling with GATK <t>HaplotypeCaller</t> using cloud computing resources. Analysis of raw sequence data for a single human genome sequence dataset (30× coverage) was compared using Churchill and bcbio-nextgen, with both pipelines utilizing BWA-MEM for alignment and GATK HaplotypeCaller for variant detection and genotyping. (A) CPU utilization on a single r3.8xlarge AWS EC2 instance (32 cores) was monitored throughout the analysis process and demonstrated that Churchill improved resource utilization (94%) when compared with bcbio-nextgen (57%), enabling the entire analysis to be completed in under 12 hours with a single instance. (B) Unlike bcbio-nextgen, Churchill enables all steps of the analysis process to be efficiently scaled across multiple compute nodes, resulting in significantly reduced run times. With 16 AWS EC2 instances the entire analysis could be completed in 104 minutes, with the variant calling and genotyping with GATK HaplotypeCaller stage taking only 24 minutes of the total run time.
Whale Optimization Algorithm Based Fopi Controllers, supplied by Statcom Co Ltd, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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gradient-based optimization algorithms  (Lawrence Livermore National Security LLC)
90
Lawrence Livermore National Security LLC gradient-based optimization algorithms
Churchill enables rapid secondary analysis and variant calling with GATK <t>HaplotypeCaller</t> using cloud computing resources. Analysis of raw sequence data for a single human genome sequence dataset (30× coverage) was compared using Churchill and bcbio-nextgen, with both pipelines utilizing BWA-MEM for alignment and GATK HaplotypeCaller for variant detection and genotyping. (A) CPU utilization on a single r3.8xlarge AWS EC2 instance (32 cores) was monitored throughout the analysis process and demonstrated that Churchill improved resource utilization (94%) when compared with bcbio-nextgen (57%), enabling the entire analysis to be completed in under 12 hours with a single instance. (B) Unlike bcbio-nextgen, Churchill enables all steps of the analysis process to be efficiently scaled across multiple compute nodes, resulting in significantly reduced run times. With 16 AWS EC2 instances the entire analysis could be completed in 104 minutes, with the variant calling and genotyping with GATK HaplotypeCaller stage taking only 24 minutes of the total run time.
Gradient Based Optimization Algorithms, supplied by Lawrence Livermore National Security LLC, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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ant colony optimization based memetic algorithm  (IEEE Access)
90
IEEE Access ant colony optimization based memetic algorithm
Churchill enables rapid secondary analysis and variant calling with GATK <t>HaplotypeCaller</t> using cloud computing resources. Analysis of raw sequence data for a single human genome sequence dataset (30× coverage) was compared using Churchill and bcbio-nextgen, with both pipelines utilizing BWA-MEM for alignment and GATK HaplotypeCaller for variant detection and genotyping. (A) CPU utilization on a single r3.8xlarge AWS EC2 instance (32 cores) was monitored throughout the analysis process and demonstrated that Churchill improved resource utilization (94%) when compared with bcbio-nextgen (57%), enabling the entire analysis to be completed in under 12 hours with a single instance. (B) Unlike bcbio-nextgen, Churchill enables all steps of the analysis process to be efficiently scaled across multiple compute nodes, resulting in significantly reduced run times. With 16 AWS EC2 instances the entire analysis could be completed in 104 minutes, with the variant calling and genotyping with GATK HaplotypeCaller stage taking only 24 minutes of the total run time.
Ant Colony Optimization Based Memetic Algorithm, supplied by IEEE Access, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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heuristic algorithm based optimal power flow model incorporating stochastic renewable energy sources  (IEEE Access)
90
IEEE Access heuristic algorithm based optimal power flow model incorporating stochastic renewable energy sources
Churchill enables rapid secondary analysis and variant calling with GATK <t>HaplotypeCaller</t> using cloud computing resources. Analysis of raw sequence data for a single human genome sequence dataset (30× coverage) was compared using Churchill and bcbio-nextgen, with both pipelines utilizing BWA-MEM for alignment and GATK HaplotypeCaller for variant detection and genotyping. (A) CPU utilization on a single r3.8xlarge AWS EC2 instance (32 cores) was monitored throughout the analysis process and demonstrated that Churchill improved resource utilization (94%) when compared with bcbio-nextgen (57%), enabling the entire analysis to be completed in under 12 hours with a single instance. (B) Unlike bcbio-nextgen, Churchill enables all steps of the analysis process to be efficiently scaled across multiple compute nodes, resulting in significantly reduced run times. With 16 AWS EC2 instances the entire analysis could be completed in 104 minutes, with the variant calling and genotyping with GATK HaplotypeCaller stage taking only 24 minutes of the total run time.
Heuristic Algorithm Based Optimal Power Flow Model Incorporating Stochastic Renewable Energy Sources, supplied by IEEE Access, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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adaptive genetic algorithm based multi-objective optimization for photovoltaic cell design parameter extraction  (Chennai Corporation)
90
Chennai Corporation adaptive genetic algorithm based multi-objective optimization for photovoltaic cell design parameter extraction
Churchill enables rapid secondary analysis and variant calling with GATK <t>HaplotypeCaller</t> using cloud computing resources. Analysis of raw sequence data for a single human genome sequence dataset (30× coverage) was compared using Churchill and bcbio-nextgen, with both pipelines utilizing BWA-MEM for alignment and GATK HaplotypeCaller for variant detection and genotyping. (A) CPU utilization on a single r3.8xlarge AWS EC2 instance (32 cores) was monitored throughout the analysis process and demonstrated that Churchill improved resource utilization (94%) when compared with bcbio-nextgen (57%), enabling the entire analysis to be completed in under 12 hours with a single instance. (B) Unlike bcbio-nextgen, Churchill enables all steps of the analysis process to be efficiently scaled across multiple compute nodes, resulting in significantly reduced run times. With 16 AWS EC2 instances the entire analysis could be completed in 104 minutes, with the variant calling and genotyping with GATK HaplotypeCaller stage taking only 24 minutes of the total run time.
Adaptive Genetic Algorithm Based Multi Objective Optimization For Photovoltaic Cell Design Parameter Extraction, supplied by Chennai Corporation, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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continuous gradient-based optimization algorithm  (CONTINUUS Pharma)
90
CONTINUUS Pharma continuous gradient-based optimization algorithm
Churchill enables rapid secondary analysis and variant calling with GATK <t>HaplotypeCaller</t> using cloud computing resources. Analysis of raw sequence data for a single human genome sequence dataset (30× coverage) was compared using Churchill and bcbio-nextgen, with both pipelines utilizing BWA-MEM for alignment and GATK HaplotypeCaller for variant detection and genotyping. (A) CPU utilization on a single r3.8xlarge AWS EC2 instance (32 cores) was monitored throughout the analysis process and demonstrated that Churchill improved resource utilization (94%) when compared with bcbio-nextgen (57%), enabling the entire analysis to be completed in under 12 hours with a single instance. (B) Unlike bcbio-nextgen, Churchill enables all steps of the analysis process to be efficiently scaled across multiple compute nodes, resulting in significantly reduced run times. With 16 AWS EC2 instances the entire analysis could be completed in 104 minutes, with the variant calling and genotyping with GATK HaplotypeCaller stage taking only 24 minutes of the total run time.
Continuous Gradient Based Optimization Algorithm, supplied by CONTINUUS Pharma, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Image Search Results


Comparison of the performance and total vascular tree volume with different number of processors when generating 5003 terminal segments using a growth-based optimization (GBO) algorithm

Journal: Biomechanics and Modeling in Mechanobiology

Article Title: Tissue-growth-based synthetic tree generation and perfusion simulation

doi: 10.1007/s10237-023-01703-8

Figure Lengend Snippet: Comparison of the performance and total vascular tree volume with different number of processors when generating 5003 terminal segments using a growth-based optimization (GBO) algorithm

Article Snippet: We performed the comparison study between the growth-based optimization (GBO) and constrained constructive optimization (CCO) algorithms for the generation of 567, 1189, 2369, and 5003 terminal segments and the execution time reduced by 8, 13, 20, and 26 folds, respectively.

Techniques: Comparison

Churchill enables rapid secondary analysis and variant calling with GATK HaplotypeCaller using cloud computing resources. Analysis of raw sequence data for a single human genome sequence dataset (30× coverage) was compared using Churchill and bcbio-nextgen, with both pipelines utilizing BWA-MEM for alignment and GATK HaplotypeCaller for variant detection and genotyping. (A) CPU utilization on a single r3.8xlarge AWS EC2 instance (32 cores) was monitored throughout the analysis process and demonstrated that Churchill improved resource utilization (94%) when compared with bcbio-nextgen (57%), enabling the entire analysis to be completed in under 12 hours with a single instance. (B) Unlike bcbio-nextgen, Churchill enables all steps of the analysis process to be efficiently scaled across multiple compute nodes, resulting in significantly reduced run times. With 16 AWS EC2 instances the entire analysis could be completed in 104 minutes, with the variant calling and genotyping with GATK HaplotypeCaller stage taking only 24 minutes of the total run time.

Journal: Genome Biology

Article Title: Churchill: an ultra-fast, deterministic, highly scalable and balanced parallelization strategy for the discovery of human genetic variation in clinical and population-scale genomics

doi: 10.1186/s13059-014-0577-x

Figure Lengend Snippet: Churchill enables rapid secondary analysis and variant calling with GATK HaplotypeCaller using cloud computing resources. Analysis of raw sequence data for a single human genome sequence dataset (30× coverage) was compared using Churchill and bcbio-nextgen, with both pipelines utilizing BWA-MEM for alignment and GATK HaplotypeCaller for variant detection and genotyping. (A) CPU utilization on a single r3.8xlarge AWS EC2 instance (32 cores) was monitored throughout the analysis process and demonstrated that Churchill improved resource utilization (94%) when compared with bcbio-nextgen (57%), enabling the entire analysis to be completed in under 12 hours with a single instance. (B) Unlike bcbio-nextgen, Churchill enables all steps of the analysis process to be efficiently scaled across multiple compute nodes, resulting in significantly reduced run times. With 16 AWS EC2 instances the entire analysis could be completed in 104 minutes, with the variant calling and genotyping with GATK HaplotypeCaller stage taking only 24 minutes of the total run time.

Article Snippet: In collaboration with Intel®, the Broad Institute recently developed a set of hardware-based optimizations for the PairHMM algorithm in HaplotypeCaller enabling them to reduce the time to analyze a single genome from three days to one day (a three-fold speedup).

Techniques: Variant Assay, Sequencing