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algorithm python » algorithm within (Expand Search), algorithms within (Expand Search), algorithm both (Expand Search)
python function » protein function (Expand Search)
co functional » cog functional (Expand Search), go functional (Expand Search), low functional (Expand Search)
algorithm co » algorithm _ (Expand Search), algorithm b (Expand Search), algorithm a (Expand Search)
algorithm cl » algorithm _ (Expand Search), algorithm b (Expand Search), algorithm a (Expand Search)
cl function » l function (Expand Search), cell function (Expand Search), cep function (Expand Search)
algorithm python » algorithm within (Expand Search), algorithms within (Expand Search), algorithm both (Expand Search)
python function » protein function (Expand Search)
co functional » cog functional (Expand Search), go functional (Expand Search), low functional (Expand Search)
algorithm co » algorithm _ (Expand Search), algorithm b (Expand Search), algorithm a (Expand Search)
algorithm cl » algorithm _ (Expand Search), algorithm b (Expand Search), algorithm a (Expand Search)
cl function » l function (Expand Search), cell function (Expand Search), cep function (Expand Search)
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Python implementation from Symplectic decomposition from submatrix determinants
Published 2021“…Python implementation of the algorithm and demonstration of how to use the functions.…”
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Overview of the CoRE-ATAC framework.
Published 2021“…In the final step, CoRE-ATAC classifies <i>cis</i>-REs into 4 functional classes: promoter, enhancer, insulator, and other.…”
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GraSPy: an Open Source Python Package for Statistical Connectomics
Published 2019“…We developed GraSPy, an open-source Python toolkit for statistical inference on graphs. …”
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Development of the CO<sub>2</sub> Adsorption Model on Porous Adsorbent Materials Using Machine Learning Algorithms
Published 2024“…In this research study, we created a data set and collected data points from porous adsorbents (2789) from 21 published papers, including carbon-based, porous polymers, metal–organic frameworks (MOFs), and zeolites, to understand their characteristics for CO<sub>2</sub> adsorption. Different machine learning (ML) algorithms, such as NN, MLP-GWO, XGBoost, RF, DT, and SVM, have been applied to display the CO<sub>2</sub> adsorption performance as a function of characteristics and adsorption isotherm parameters. …”
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Modular architecture design of PyNoetic showing all its constituent functions.
Published 2025Subjects: -
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