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algorithm python » algorithm within (Expand Search), algorithms within (Expand Search), algorithm both (Expand Search)
python function » protein function (Expand Search)
algorithm pre » algorithm where (Expand Search), algorithm used (Expand Search), algorithm from (Expand Search)
pre function » spread function (Expand Search), sphere function (Expand Search), three function (Expand Search)
algorithm 1 » algorithm _ (Expand Search), algorithms _ (Expand Search), algorithm 8217 (Expand Search)
1 function » _ function (Expand Search), a function (Expand Search)
algorithm python » algorithm within (Expand Search), algorithms within (Expand Search), algorithm both (Expand Search)
python function » protein function (Expand Search)
algorithm pre » algorithm where (Expand Search), algorithm used (Expand Search), algorithm from (Expand Search)
pre function » spread function (Expand Search), sphere function (Expand Search), three function (Expand Search)
algorithm 1 » algorithm _ (Expand Search), algorithms _ (Expand Search), algorithm 8217 (Expand Search)
1 function » _ function (Expand Search), a function (Expand Search)
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The ALO algorithm optimization flowchart.
Published 2024“…The average running time of the proposed algorithm in Sphere function and Griebank function was 2.67s and 1.64s, respectively. …”
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The IALO algorithm solution flowchart.
Published 2024“…The average running time of the proposed algorithm in Sphere function and Griebank function was 2.67s and 1.64s, respectively. …”
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Objective functions (i.e., RMSEs) and time of optimization for different population sizes of the used algorithms.
Published 2023“…<p>Objective functions (i.e., RMSEs) and time of optimization for different population sizes of the used algorithms.…”
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Algorithm pseudocode.
Published 2025“…The experimental results show that the proposed method enhances the image with a PCQI of 1.033, an IQE of 0.610, an IQM of 1.830, and an information entropy higher than 0.7. …”
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Glioblastoma multiforme (GBM) pathway modules identified by the netboxr package from cancer genomics alteration data without the use of pre-defined gene sets.
Published 2020“…For more detailed understanding users should also inspect the function of the genes contained in the modules. In this glioblastoma example, the largest module (M1, light orange background) contains genes related to the PIK3 pathway and functions related to AKT signaling (also known as “PKB signaling” in the GO Gene Ontology). …”
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Efficient algorithms to discover alterations with complementary functional association in cancer
Published 2019“…We provide analytic evidence of the effectiveness of UNCOVER in finding high-quality solutions and show experimentally that UNCOVER finds sets of alterations significantly associated with functional targets in a variety of scenarios. In particular, we show that our algorithms find sets which are better than the ones obtained by the state-of-the-art method, even when sets are evaluated using the statistical score employed by the latter. …”
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Revisiting the “satisfaction of spatial restraints” approach of MODELLER for protein homology modeling
Published 2019“…This program implements the “modeling by satisfaction of spatial restraints” strategy and its core algorithm has not been altered significantly since the early 1990s. …”
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