Search alternatives:
method optimization » lead optimization (Expand Search), path optimization (Expand Search), feature optimization (Expand Search)
cell optimization » field optimization (Expand Search), wolf optimization (Expand Search), lead optimization (Expand Search)
based method » based methods (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
method optimization » lead optimization (Expand Search), path optimization (Expand Search), feature optimization (Expand Search)
cell optimization » field optimization (Expand Search), wolf optimization (Expand Search), lead optimization (Expand Search)
based method » based methods (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
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The performance of classifiers.
Published 2024“…Subsequently, feature selection was conducted using ANOVA and binary Particle Swarm Optimization (PSO). During the analysis phase, the discriminative power of the selected features was evaluated using machine learning classification algorithms. …”
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AUC sensitivity of APDCA to the sparse control parameter <i>k</i> under 5-fold cross-validation.
Published 2025Subjects: -
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AUC values under different combinations of regularization parameters <i>λ</i> and .
Published 2025Subjects: -
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Top 10 QKI–AS Event Associations Predicted by APDCA and Their Evidence in OncoSplicing.
Published 2025Subjects: -
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Table1_Identification of a ferroptosis-related gene signature predicting recurrence in stage II/III colorectal cancer based on machine learning algorithms.XLSX
Published 2023“…</p><p>Methods: Ferroptosis-related genes were retrieved from the FerrDb and KEGG databases. …”
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113
Inferring Gene Regulatory Networks Using the Improved Markov Blanket Discovery Algorithm
Published 2023“…This work mainly focuses on the following aspects: (1) On the basis of the IPC-MB and DPI, we presented a novel feature selection method called the improved MB discovery algorithm (IMBDA), which can accurately identify direct and indirect regulatory genes when inferring networks. (2) Isolated genes were properly processed by the IDS to optimize the network structure. (3) The performance of IMBDANET was assessed with extensive experiments. …”
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Inferring Gene Regulatory Networks Using the Improved Markov Blanket Discovery Algorithm
Published 2023“…<ul><li><a href="https://link.springer.com/article/10.1007/s12539-021-00478-9#auth-Wei-Liu-Aff1-Aff2" target="_blank">Wei Liu</a>, </li><li><a href="https://link.springer.com/article/10.1007/s12539-021-00478-9#auth-Yi-Jiang-Aff1" target="_blank">Yi Jiang</a>, </li><li><a href="https://link.springer.com/article/10.1007/s12539-021-00478-9#auth-Li-Peng-Aff3" target="_blank">Li Peng</a>, </li><li><a href="https://link.springer.com/article/10.1007/s12539-021-00478-9#auth-Xingen-Sun-Aff1" target="_blank">Xingen Sun</a>, </li><li><a href="https://link.springer.com/article/10.1007/s12539-021-00478-9#auth-Wenqing-Gan-Aff1" target="_blank">Wenqing Gan</a>, </li><li><a href="https://link.springer.com/article/10.1007/s12539-021-00478-9#auth-Qi-Zhao-Aff4" target="_blank">Qi Zhao</a> </li><li><a href="https://link.springer.com/article/10.1007/s12539-021-00478-9#auth-Huanrong-Tang-Aff1" target="_blank">Huanrong Tang</a></li></ul><p dir="ltr">A novel network inference method based on the improved MB discovery algorithm, IMBDANET, was proposed for improving gene regulatory networks. …”
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Simulated Design–Build–Test–Learn Cycles for Consistent Comparison of Machine Learning Methods in Metabolic Engineering
Published 2023“…Simultaneous optimization of a large number of pathway genes often leads to combinatorial explosions. …”
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<i>OptRAM</i>: <i>In-silico</i> strain design via integrative regulatory-metabolic network modeling
Published 2019“…To address challenges in metabolic engineering, computational strain optimization algorithms based on genome-scale metabolic models have increasingly been used to aid in overproducing products of interest. …”
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DataSheet1_Identification of a ferroptosis-related gene signature predicting recurrence in stage II/III colorectal cancer based on machine learning algorithms.DOCX
Published 2023“…</p><p>Methods: Ferroptosis-related genes were retrieved from the FerrDb and KEGG databases. …”
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