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within function » fibrin function (Expand Search), protein function (Expand Search), catenin function (Expand Search)
python function » protein function (Expand Search)
algorithm gene » algorithm where (Expand Search), algorithm etc (Expand Search), algorithm pre (Expand Search)
within function » fibrin function (Expand Search), protein function (Expand Search), catenin function (Expand Search)
python function » protein function (Expand Search)
algorithm gene » algorithm where (Expand Search), algorithm etc (Expand Search), algorithm pre (Expand Search)
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Identification and functional analysis of hub genes.
Published 2025“…(B) PPI network visualized using Cytoscape software. (C, D) Top 10 hub genes identified using the Maximal Clique Centrality (MCC) algorithm; darker colors indicate higher centrality within the PPI network. …”
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<b>Opti2Phase</b>: Python scripts for two-stage focal reducer
Published 2025“…</li></ul><p dir="ltr">The scripts rely on the following Python packages. Where available, repository links are provided:</p><ol><li><b>NumPy</b>, version 1.22.1</li><li><b>SciPy</b>, version 1.7.3</li><li><b>PyGAD</b>, version 3.0.1 — https://pygad.readthedocs.io/en/latest/#</li><li><b>bees-algorithm</b>, version 1.0.2 — https://pypi.org/project/bees-algorithm</li><li><b>KrakenOS</b>, version 1.0.0.19 — https://github.com/Garchupiter/Kraken-Optical-Simulator</li><li><b>matplotlib</b>, version 3.5.2</li></ol><p dir="ltr">All scripts are modular and organized to reflect the design stages described in the manuscript.…”
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Core genes were selected through PPI analysis based on three algorithms.
Published 2024“…<b>(B)</b> The priority of the top 10 genes was evaluated through MNC, which identifies clusters of protein nodes that are more functionally connected to each other and selects the central proteins within the cluster. …”
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Multimodal reference functions.
Published 2025“…We performed comparative analyses against other methodologies across various functions and public datasets to assess their effectiveness. …”
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The convergence curves of the test functions.
Published 2025“…We performed comparative analyses against other methodologies across various functions and public datasets to assess their effectiveness. …”
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Single-peaked reference functions.
Published 2025“…We performed comparative analyses against other methodologies across various functions and public datasets to assess their effectiveness. …”
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Test results of multimodal benchmark functions.
Published 2025“…We performed comparative analyses against other methodologies across various functions and public datasets to assess their effectiveness. …”
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Fixed-dimensional multimodal reference functions.
Published 2025“…We performed comparative analyses against other methodologies across various functions and public datasets to assess their effectiveness. …”
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Test results of multimodal benchmark functions.
Published 2025“…We performed comparative analyses against other methodologies across various functions and public datasets to assess their effectiveness. …”
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Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results
Published 2025“…This algorithm conducts a series of procedures: (1) fragmentation of the molecules into functional groups from SMILES, (2) calculation of activity coefficients under predetermined temperature and mole fraction conditions by employing universal quasi-chemical functional group activity coefficient (UNIFAC) model, and (3) regression of NRTL model parameters by employing UNIFAC model simulation results in the differential evolution algorithm (DEA) and Nelder–Mead method (NMM). …”
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EFGs: A Complete and Accurate Implementation of Ertl’s Functional Group Detection Algorithm in RDKit
Published 2025“…In this paper, a new RDKit/Python implementation of the algorithm is described, that is both accurate and complete. …”
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FAR-1: A Fast Integer Reduction Algorithm Compared to Collatz and Half-Collatz
Published 2025Subjects: -
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GSEA Analysis of Differentially Expressed Genes in High and Low-Risk Groups.
Published 2025Subjects: