Restoration process via Algorithm 1. by Dilber Uzun Ozsahin (18320075)

Subjects: “…Cell Biology…”

Restoration process via Algorithm 1. by Dilber Uzun Ozsahin (18320075)

Subjects: “…Cell Biology…”

Restoration process via Algorithm 1. by Dilber Uzun Ozsahin (18320075)

Subjects: “…Cell Biology…”

Restoration process via Algorithm 1. by Dilber Uzun Ozsahin (18320075)

Subjects: “…Cell Biology…”

Restoration process via Algorithm 1. by Dilber Uzun Ozsahin (18320075)

Subjects: “…Cell Biology…”

Results of community detection from phosphoproteomics-derived networks. by Celia De Los Angeles Colomina Basanta (16437798)

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TTK and PI3K/AKT/mTOR pathway inhibitors impact common phosphorylation pathways. by Celia De Los Angeles Colomina Basanta (16437798)

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Additional information on the compounds used. by Celia De Los Angeles Colomina Basanta (16437798)

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Summary statistics for strictly negative z-scores. by Celia De Los Angeles Colomina Basanta (16437798)

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Identification of canonical and non-canonical kinases in PI3K/AKT networks. by Celia De Los Angeles Colomina Basanta (16437798)

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Convergence curves of the investigated algorithms. by Ziad M. Ali (12516532)

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S2 Dataset - by Ryu B. Lippmann (14797597)

“…<div><p>Production of cultivated resources require additional planning that takes growth time into account. We formulate a mathematical programming model to determine the optimal location and sizing of growth facilities, impacted by resource survival rate as a function of its growth time. …”

S1 Dataset - by Ryu B. Lippmann (14797597)

“…<div><p>Production of cultivated resources require additional planning that takes growth time into account. We formulate a mathematical programming model to determine the optimal location and sizing of growth facilities, impacted by resource survival rate as a function of its growth time. …”

Completion times for different algorithms. by Jianbin Zheng (587000)

“…In the context of intelligent manufacturing, there is still significant potential for improving the productivity of riveting and welding tasks in existing H-beam riveting and welding work cells. In response to the multi-agent system of the H-beam riveting and welding work cell, a recurrent multi-agent proximal policy optimization algorithm (rMAPPO) is proposed to address the multi-agent scheduling problem in the H-beam processing. …”

The average cumulative reward of algorithms. by Jianbin Zheng (587000)

“…In the context of intelligent manufacturing, there is still significant potential for improving the productivity of riveting and welding tasks in existing H-beam riveting and welding work cells. In response to the multi-agent system of the H-beam riveting and welding work cell, a recurrent multi-agent proximal policy optimization algorithm (rMAPPO) is proposed to address the multi-agent scheduling problem in the H-beam processing. …”

Image_1_Depression Classification Using Frequent Subgraph Mining Based on Pattern Growth of Frequent Edge in Functional Magnetic Resonance Imaging Uncertain Network.pdf by Yao Li (154923)

“…Therefore, considering these problems, we propose an approximate frequent subgraph mining algorithm based on pattern growth of frequent edge (unFEPG) for uncertain brain networks and a novel discriminative feature selection method based on statistical index (dfsSI) to perform graph mining and selection. …”

Image_2_Depression Classification Using Frequent Subgraph Mining Based on Pattern Growth of Frequent Edge in Functional Magnetic Resonance Imaging Uncertain Network.pdf by Yao Li (154923)

“…Therefore, considering these problems, we propose an approximate frequent subgraph mining algorithm based on pattern growth of frequent edge (unFEPG) for uncertain brain networks and a novel discriminative feature selection method based on statistical index (dfsSI) to perform graph mining and selection. …”

Table_2_Depression Classification Using Frequent Subgraph Mining Based on Pattern Growth of Frequent Edge in Functional Magnetic Resonance Imaging Uncertain Network.docx by Yao Li (154923)

“…Therefore, considering these problems, we propose an approximate frequent subgraph mining algorithm based on pattern growth of frequent edge (unFEPG) for uncertain brain networks and a novel discriminative feature selection method based on statistical index (dfsSI) to perform graph mining and selection. …”

Table_1_Depression Classification Using Frequent Subgraph Mining Based on Pattern Growth of Frequent Edge in Functional Magnetic Resonance Imaging Uncertain Network.docx by Yao Li (154923)

“…Therefore, considering these problems, we propose an approximate frequent subgraph mining algorithm based on pattern growth of frequent edge (unFEPG) for uncertain brain networks and a novel discriminative feature selection method based on statistical index (dfsSI) to perform graph mining and selection. …”

Study proposed algorithm. by Ainhoa Pérez-Guerrero (21377457)

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