Showing 241 - 260 results of 292 for search '(( algorithm brain function ) OR ( algorithm python function ))', query time: 0.24s Refine Results
  1. 241

    Data Sheet 2_Identification of novel gut microbiota-related biomarkers in cerebral hemorrhagic stroke.zip by Fengli Ye (22123540)

    Published 2025
    “…In vivo, FMT reduced hematoma volume and brain edema, improved neurological function, restored intestinal barrier proteins, decreased inflammatory cytokines, and downregulated hub gene expression.…”
  2. 242

    Data Sheet 1_Prefrontal meta-control incorporating mental simulation enhances the adaptivity of reinforcement learning agents in dynamic environments.pdf by JiHun Kim (20945054)

    Published 2025
    “…In addition, hippocampal function, particularly mental simulation capacity, proves essential in this adaptive process. …”
  3. 243

    Code and data for evaluating oil spill amount from text-form incident information by Yiming Liu (18823387)

    Published 2025
    “…These are separately stored in the folders “description” and “posts”.</p><h2>Algorithms for Evaluating Release Amount (RA)</h2><p dir="ltr">The algorithms are split into the following three notebooks based on their functions:</p><ol><li><b>"1_RA_extraction.ipynb"</b>:</li><li><ul><li>Identifies oil spill-related incidents from raw incident data.…”
  4. 244

    CSPP instance by peixiang wang (19499344)

    Published 2025
    “…</b></p><p dir="ltr">Its primary function is to create structured datasets that simulate container terminal operations, which can then be used for developing, testing, and benchmarking optimization algorithms (e.g., for yard stacking strategies, vessel stowage planning).…”
  5. 245

    Spatiotemporal Soil Erosion Dataset for the Yarlung Tsangpo River Basin (1990–2100) by peng xin (21382394)

    Published 2025
    “…Bias correction was conducted using a 25-year baseline (1990–2014), with adjustments made monthly to correct for seasonal biases. The corrected bias functions were then applied to adjust the years (2020–2100) of daily rainfall data using the "ibicus" package, an open-source Python tool for bias adjustment and climate model evaluation. …”
  6. 246

    Data Sheet 2_Characterization of the salivary microbiome in healthy individuals under fatigue status.docx by Xianhui Peng (14551488)

    Published 2025
    “…Bioinformatics analyses encompassed assessment of alpha and beta diversity, identification of differential taxa using Linear discriminant analysis Effect Size (LEfSe) with multi-method cross-validation, construction of microbial co-occurrence networks, and screening of fatigue-associated biomarker genera via the Boruta-SHAP algorithm. Microbial community phenotypes and potential functional pathways were predicted using BugBase and PICRUSt2, respectively.…”
  7. 247

    Table 3_Characterization of the salivary microbiome in healthy individuals under fatigue status.xlsx by Xianhui Peng (14551488)

    Published 2025
    “…Bioinformatics analyses encompassed assessment of alpha and beta diversity, identification of differential taxa using Linear discriminant analysis Effect Size (LEfSe) with multi-method cross-validation, construction of microbial co-occurrence networks, and screening of fatigue-associated biomarker genera via the Boruta-SHAP algorithm. Microbial community phenotypes and potential functional pathways were predicted using BugBase and PICRUSt2, respectively.…”
  8. 248

    Data Sheet 1_Characterization of the salivary microbiome in healthy individuals under fatigue status.docx by Xianhui Peng (14551488)

    Published 2025
    “…Bioinformatics analyses encompassed assessment of alpha and beta diversity, identification of differential taxa using Linear discriminant analysis Effect Size (LEfSe) with multi-method cross-validation, construction of microbial co-occurrence networks, and screening of fatigue-associated biomarker genera via the Boruta-SHAP algorithm. Microbial community phenotypes and potential functional pathways were predicted using BugBase and PICRUSt2, respectively.…”
  9. 249

    Table 5_Characterization of the salivary microbiome in healthy individuals under fatigue status.xlsx by Xianhui Peng (14551488)

    Published 2025
    “…Bioinformatics analyses encompassed assessment of alpha and beta diversity, identification of differential taxa using Linear discriminant analysis Effect Size (LEfSe) with multi-method cross-validation, construction of microbial co-occurrence networks, and screening of fatigue-associated biomarker genera via the Boruta-SHAP algorithm. Microbial community phenotypes and potential functional pathways were predicted using BugBase and PICRUSt2, respectively.…”
  10. 250

    Table 4_Characterization of the salivary microbiome in healthy individuals under fatigue status.xlsx by Xianhui Peng (14551488)

    Published 2025
    “…Bioinformatics analyses encompassed assessment of alpha and beta diversity, identification of differential taxa using Linear discriminant analysis Effect Size (LEfSe) with multi-method cross-validation, construction of microbial co-occurrence networks, and screening of fatigue-associated biomarker genera via the Boruta-SHAP algorithm. Microbial community phenotypes and potential functional pathways were predicted using BugBase and PICRUSt2, respectively.…”
  11. 251

    Table 2_Characterization of the salivary microbiome in healthy individuals under fatigue status.xlsx by Xianhui Peng (14551488)

    Published 2025
    “…Bioinformatics analyses encompassed assessment of alpha and beta diversity, identification of differential taxa using Linear discriminant analysis Effect Size (LEfSe) with multi-method cross-validation, construction of microbial co-occurrence networks, and screening of fatigue-associated biomarker genera via the Boruta-SHAP algorithm. Microbial community phenotypes and potential functional pathways were predicted using BugBase and PICRUSt2, respectively.…”
  12. 252

    Table 1_Characterization of the salivary microbiome in healthy individuals under fatigue status.xlsx by Xianhui Peng (14551488)

    Published 2025
    “…Bioinformatics analyses encompassed assessment of alpha and beta diversity, identification of differential taxa using Linear discriminant analysis Effect Size (LEfSe) with multi-method cross-validation, construction of microbial co-occurrence networks, and screening of fatigue-associated biomarker genera via the Boruta-SHAP algorithm. Microbial community phenotypes and potential functional pathways were predicted using BugBase and PICRUSt2, respectively.…”
  13. 253

    A computational-based search of natural product derived multi-target ligands for the management of Alzheimer’s and Parkinson’s disease using structure-based pharmacophore modelling... by N. Chhabra (22645522)

    Published 2025
    “…Additionally, density functional theory (DFT) studies provided insights into the electronic characteristics and reactivity of top hits. …”
  14. 254

    Data Sheet 3_Identification and validation of biomarkers associated with mitochondrial dysfunction and ferroptosis in rat spinal cord injury.csv by Jingliang Zhu (20889605)

    Published 2025
    “…Two machine learning algorithms, least absolute shrinkage and selection operator (LASSO) and Boruta, were employed to isolate SCI-associated feature genes. …”
  15. 255

    Data Sheet 2_Identification and validation of biomarkers associated with mitochondrial dysfunction and ferroptosis in rat spinal cord injury.csv by Jingliang Zhu (20889605)

    Published 2025
    “…Two machine learning algorithms, least absolute shrinkage and selection operator (LASSO) and Boruta, were employed to isolate SCI-associated feature genes. …”
  16. 256

    Data Sheet 1_Identification and validation of biomarkers associated with mitochondrial dysfunction and ferroptosis in rat spinal cord injury.csv by Jingliang Zhu (20889605)

    Published 2025
    “…Two machine learning algorithms, least absolute shrinkage and selection operator (LASSO) and Boruta, were employed to isolate SCI-associated feature genes. …”
  17. 257

    Data Sheet 4_Identification and validation of biomarkers associated with mitochondrial dysfunction and ferroptosis in rat spinal cord injury.csv by Jingliang Zhu (20889605)

    Published 2025
    “…Two machine learning algorithms, least absolute shrinkage and selection operator (LASSO) and Boruta, were employed to isolate SCI-associated feature genes. …”
  18. 258

    Data Sheet 1_Cerebral gray matter volume identifies healthy older drivers with a critical decline in driving safety performance using actual vehicles on a closed-circuit course.pdf by Handityo Aulia Putra (21430112)

    Published 2025
    “…Additional factors, such as neuronal connectivity assessed by functional MRI, may improve predictive accuracy. Nonetheless, MRI-based assessment of brain structure can enhance our understanding of the neural mechanisms underlying driving safety and inform strategies to prevent traffic accidents among older adults.…”
  19. 259

    Data Sheet 1_Multimodal fusion model for diagnosing mild cognitive impairment in unilateral middle cerebral artery steno-occlusive disease.docx by Ziyi Yuan (12959918)

    Published 2025
    “…Objectives<p>To propose a multimodal functional brain network (FBN) and structural brain network (SBN) topological feature fusion technique based on resting-state functional magnetic resonance imaging (rs-fMRI), diffusion tensor imaging (DTI), 3D-T1-weighted imaging (3D-T1WI), and demographic characteristics to diagnose mild cognitive impairment (MCI) in patients with unilateral middle cerebral artery (MCA) steno-occlusive disease.…”
  20. 260

    Code by Baoqiang Chen (21099509)

    Published 2025
    “…We implemented machine learning algorithms using the following R packages: rpart for Decision Trees, gbm for Gradient Boosting Machines (GBM), ranger for Random Forests, the glm function for Generalized Linear Models (GLM), and xgboost for Extreme Gradient Boosting (XGB). …”