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algorithm api » algorithm ai (Expand Search), algorithm a (Expand Search), algorithm i (Expand Search)
api function » a function (Expand Search), i function (Expand Search), adl function (Expand Search)
algorithm python » algorithm within (Expand Search), algorithms within (Expand Search), algorithm both (Expand Search)
python function » protein function (Expand Search)
algorithm gene » algorithm where (Expand Search), algorithm etc (Expand Search), algorithm pre (Expand Search)
algorithm api » algorithm ai (Expand Search), algorithm a (Expand Search), algorithm i (Expand Search)
api function » a function (Expand Search), i function (Expand Search), adl function (Expand Search)
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The result of Wilcoxon signed-rand test.
Published 2022Subjects: “…evolutionary genetic algorithm…”
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The Simulation and optimization process of pipe diameter selection.
Published 2022Subjects: “…evolutionary genetic algorithm…”
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Optional pipe diameter and unit price of NYN.
Published 2022Subjects: “…evolutionary genetic algorithm…”
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Optional pipe diameter and unit price of HN.
Published 2022Subjects: “…evolutionary genetic algorithm…”
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BOFdat Step 3: Identifying species-specific metabolic end goals.
Published 2019“…(B) Schematic description of the effect of adding a biomass precursor on the prediction of gene essentiality in the model. A simplified metabolic network composed of two linear pathways is depicted with its corresponding stoichiometric matrix S, in which the objective function is presented in the blue column (<i>v</i><sub><i>obj</i></sub>). …”
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Practical rules for summing the series of the Tweedie probability density function with high-precision arithmetic
Published 2019“…With these practical rules, simple summation algorithms provide sufficiently robust results for the calculation of the density function and its definite integrals. …”
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Overview of the Cell2Spatial algorithm.
Published 2025Subjects: “…minimizing assignment algorithm…”
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DE genes detected by different DEA algorithms.
Published 2024“…Here, we compare 6 performance metrics on both simulated and real scRNA-seq datasets to assess the adaptability of 8 DEA approaches, with a particular emphasis on how well they function under small biological replications. Our findings suggest that DEA algorithms extended from bulk RNA-seq are still competitive under small biological replicate conditions, whereas the newly developed method DEF-scRNA-seq which is based on information entropy offers significant advantages. …”