بدائل البحث:
algorithm python » algorithm within (توسيع البحث), algorithms within (توسيع البحث), algorithm both (توسيع البحث)
python function » protein function (توسيع البحث)
where function » sphere function (توسيع البحث), gene function (توسيع البحث), wave function (توسيع البحث)
algorithms fc » algorithms mc (توسيع البحث), algorithms _ (توسيع البحث), algorithms a (توسيع البحث)
fc function » _ function (توسيع البحث), a function (توسيع البحث), 1 function (توسيع البحث)
algorithm python » algorithm within (توسيع البحث), algorithms within (توسيع البحث), algorithm both (توسيع البحث)
python function » protein function (توسيع البحث)
where function » sphere function (توسيع البحث), gene function (توسيع البحث), wave function (توسيع البحث)
algorithms fc » algorithms mc (توسيع البحث), algorithms _ (توسيع البحث), algorithms a (توسيع البحث)
fc function » _ function (توسيع البحث), a function (توسيع البحث), 1 function (توسيع البحث)
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Brief sketch of the quasi-attraction/alignment algorithm.
منشور في 2023"…(D) A brief sketch of the avoidance algorithm. Upper: Each direction is extended to the repulsion area = {<b><i>r</i></b>||<b><i>r</i></b>| = <i>R</i>}, where is the minimal sphere cap that covers all points on . …"
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BOFdat: Generating biomass objective functions for genome-scale metabolic models from experimental data
منشور في 2019"…Despite its importance, no standardized computational platform is currently available to generate species-specific biomass objective functions in a data-driven, unbiased fashion. To fill this gap in the metabolic modeling software ecosystem, we implemented BOFdat, a Python package for the definition of a <b>B</b>iomass <b>O</b>bjective <b>F</b>unction from experimental <b>dat</b>a. …"
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166
Python code for a rule-based NLP model for mapping circular economy indicators to SDGs
منشور في 2025"…The package includes:</p><ul><li>The complete Python codebase implementing the classification algorithm</li><li>A detailed manual outlining model features, requirements, and usage instructions</li><li>Sample input CSV files and corresponding processed output files to demonstrate functionality</li><li>Keyword dictionaries for all 17 SDGs, distinguishing strong and weak matches</li></ul><p dir="ltr">These materials enable full reproducibility of the study, facilitate adaptation for related research, and offer transparency in the methodological framework.…"
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167
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168
Discovery of Protein Modifications Using Differential Tandem Mass Spectrometry Proteomics
منشور في 2021"…Termed SAMPEI for spectral alignment-based modified peptide identification, this open-source algorithm is designed for the discovery of functional protein and peptide signaling modifications, without prior knowledge of their identities. …"
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169
Discovery of Protein Modifications Using Differential Tandem Mass Spectrometry Proteomics
منشور في 2021"…Termed SAMPEI for spectral alignment-based modified peptide identification, this open-source algorithm is designed for the discovery of functional protein and peptide signaling modifications, without prior knowledge of their identities. …"
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170
Ms.FPOP: A Fast Exact Segmentation Algorithm with a Multiscale Penalty
منشور في 2024"…This penalty was proposed by Verzelen et al. and achieves optimal rates for changepoint detection and changepoint localization in a non-asymptotic scenario. Our proposed algorithm, Multiscale Functional Pruning Optimal Partitioning (Ms.FPOP), extends functional pruning ideas presented in Rigaill and Maidstone et al. to multiscale penalties. …"
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172
Performance of the three algorithms.
منشور في 2024"…<div><p>Disruptive events cause decreased functionality of transportation infrastructures and enormous financial losses. …"
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State Function-Based Correction: A Simple and Efficient Free-Energy Correction Algorithm for Large-Scale Relative Binding Free-Energy Calculations
منشور في 2025"…We present an efficient and straightforward State Function-based Correction (SFC) algorithm, which leverages the state function property of free energy without requiring cycle identification. …"
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Revisiting the “satisfaction of spatial restraints” approach of MODELLER for protein homology modeling
منشور في 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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Rosenbrock function losses for .
منشور في 2025"…This approach bridges the gap between model accuracy and optimization efficiency, offering a practical solution for optimizing non-differentiable machine learning models that can be extended to other tree-based ensemble algorithms. The method has been successfully applied to real-world steel alloy optimization, where it achieved superior performance while maintaining all metallurgical composition constraints.…"
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180
Rosenbrock function losses for .
منشور في 2025"…This approach bridges the gap between model accuracy and optimization efficiency, offering a practical solution for optimizing non-differentiable machine learning models that can be extended to other tree-based ensemble algorithms. The method has been successfully applied to real-world steel alloy optimization, where it achieved superior performance while maintaining all metallurgical composition constraints.…"