Showing 1 - 20 results of 15,845 for search '(( algorithm within functional ) OR ((( algorithm python function ) OR ( algorithm a function ))))', query time: 0.58s Refine Results
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    <b>Opti2Phase</b>: Python scripts for two-stage focal reducer by Morgan Najera (21540776)

    Published 2025
    “…</p><p dir="ltr">The package includes:</p><ul><li>Scripts for first-order analysis, third-order modeling, optimization using a Physically Grounded Merit Function (PGMF), and RMS-based refinement.…”
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    An expectation-maximization algorithm for finding noninvadable stationary states. by Robert Marsland (8616483)

    Published 2020
    “…<i>(b)</i> Metabolic byproducts move the relevant unperturbed state from <b>R</b><sup>0</sup> (gray ‘x’) to (black ‘x’), which is itself a function of the current environmental conditions. …”
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    EFGs: A Complete and Accurate Implementation of Ertl’s Functional Group Detection Algorithm in RDKit by Gonzalo Colmenarejo (650249)

    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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    Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results by Se-Hee Jo (20554623)

    Published 2025
    “…A Python-based algorithm was developed for estimating the nonrandom two-liquid (NRTL) model parameters of aqueous binary systems in a straightforward manner from simplified molecular-input line-entry specification (SMILES) strings of substances in a system. …”
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    Algorithmic assessment reveals functional implications of GABRD gene variants linked to idiopathic generalized epilepsy by Ayla Arslan (17943365)

    Published 2024
    “…</p> <p>The study employs a combination of in silico algorithms to analyze 82 variants of unknown clinical significance of GABRD gene sourced from the ClinVar database. …”
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    Route for bays29 output by ABSQL algorithm. by Jin Zhang (53297)

    Published 2023
    “…DSRABSQL builds upon the Q-learning (QL) algorithm. Considering its problems of slow convergence and low accuracy, four strategies within the QL framework are designed first: the weighting function-based reward matrix, the power function-based initial Q-table, a self-adaptive <i>ε-beam</i> search strategy, and a new Q-value update formula. …”
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