Index of papers in PLOS Comp. Biol. that mention
  • computational time
Mei Zhan, Matthew M. Crane, Eugeni V. Entchev, Antonio Caballero, Diana Andrea Fernandes de Abreu, QueeLim Ch’ng, Hang Lu
Discussion
In comparison with direct calculation of all features in a single layer of classification, the two-layer architecture employed in this work reduced average total computational time by a factor of two (S7 Fig).
Discussion
In this case, the computational time savings associated with the two-layer architecture increases with the complexity of the second-layer relationships and can result in large, roughly sixfold speed improvements in the case of two cell pair identification (88 Fig).
Results
This two-tier scheme allows significant reduction in computational time .
Supporting Information
Computational time savings associated with two-layer classification architecture for head versus tail detection.
Supporting Information
Computational time savings associated with two-layer classification architecture for cell identification.
computational time is mentioned in 5 sentences in this paper.
Topics mentioned in this paper:
Sébastien Giguère, François Laviolette, Mario Marchand, Denise Tremblay, Sylvain Moineau, Xinxia Liang, Éric Biron, Jacques Corbeil
Abstract
Unfortunately, once the model is learned, selecting peptides having the greatest predicted bioactivity often requires a prohibitive amount of computational time .
Author Summary
Indeed, applying the model to every peptides would take an astronomical amount of computer time .
Author Summary
Therefore, given a model, is it possible to determine, using reasonable computational time , the peptide that has the best properties and chance for success?
Introduction
I n-silico predictions are faster and cheaper than in-vitro assays, however, predicting the bioactivity of all possible peptide to select the most bioactive ones would require a prohibitive amount of computational time .
computational time is mentioned in 4 sentences in this paper.
Topics mentioned in this paper:
Christiaan A. de Leeuw, Joris M. Mooij, Tom Heskes, Danielle Posthuma
Computational performance
Although INRICH and ALIGATOR show comparable computation times at their lowest SNP p-value cutoff, the need to repeat the analysis at multiple cutoffs means the total analysis for both takes considerably longer.
Computational performance
The low MAGMA computation times are largely due to the choice of statistical model.
Computational performance
Note however that the permutation-based SNP-wise analyses in MAGMA also show very reasonable computation times .
Discussion
However, even the permutation-based SNP-wise models implemented in MAGMA outperformed their equivalents in other software and yielded very reasonable computation times .
computational time is mentioned in 4 sentences in this paper.
Topics mentioned in this paper:
Jérôme R. D. Soiné, Christoph A. Brand, Jonathan Stricker, Patrick W. Oakes, Margaret L. Gardel, Ulrich S. Schwarz
Model for the soft elastic substrate
In order to save computation time , but still keep a high local resolution, local mesh refinement is applied to the top surface.
Optimization
As this is expensive in terms of computation time , the numerical work is parallelized using the boost thread library [50].
Optimization
The computation time on 8 cores of current Intel i7 processors is on the order of 15 minutes per iteration step.
computational time is mentioned in 3 sentences in this paper.
Topics mentioned in this paper:
Oren E. Livne, Lide Han, Gorka Alkorta-Aranburu, William Wentworth-Sheilds, Mark Abney, Carole Ober, Dan L. Nicolae
Cross Validation
We then masked the framework genotypes of the 1,317 individuals whose genomes were not sequenced, imputed the framework genotypes, and calculated the concordance between the imputed and true genotypes over a sample of 53,861 framework SNVs (sorted by base-pair position, every 5th framework SNV was picked instead of using all SNVs to save computing time ).
Discussion
PRIMAL can be applied to other founder populations or to large families to provide accurate and nearly complete genotype coverage for relatively very small cost and minimal computation time .
Pedigree-based Imputation
Finding and indexing IBD segments into cliques takes the majority of computing time in the PRIMAL pipeline.
computational time is mentioned in 3 sentences in this paper.
Topics mentioned in this paper: