Showing 121 - 140 results of 156 for search '(( final sample processing optimization algorithm ) OR ( binary a codon optimization algorithm ))', query time: 0.45s Refine Results
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    Three conditions of gas explosion. by Hongxia Li (493545)

    Published 2023
    “…Then, a training set is randomly selected from known coal mine samples, and the training sample set is processed and analyzed using Matlab software. …”
  5. 125

    S1 Data - by Hongxia Li (493545)

    Published 2023
    “…Then, a training set is randomly selected from known coal mine samples, and the training sample set is processed and analyzed using Matlab software. …”
  6. 126

    Principles for selecting evaluation indicators. by Hongxia Li (493545)

    Published 2023
    “…Then, a training set is randomly selected from known coal mine samples, and the training sample set is processed and analyzed using Matlab software. …”
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  10. 130

    Data_Sheet_1_Dried shiitake mushroom grade recognition using D-VGG network and machine vision.docx by Li Wang (15202)

    Published 2023
    “…In this study, a comprehensive method to solve this problem is provided, including image acquisition, preprocessing, dataset creation, and grade recognition. The osprey optimization algorithm (OOA) is used to improve the computational efficiency of Otsu’s threshold binarization and obtain complete mushroom contours samples efficiently. …”
  11. 131

    Environmental DNA metabarcoding to monitor tropical reef fishes in Santa Marta by camille albouy (3800893)

    Published 2021
    “…After this step, we analyzed each data set sample individually before merging the taxon list for the final ecological analysis. …”
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    A new GEE-based App called “Crop Mapper” for crop mapping by Anonymous During Peer Review (16029755)

    Published 2023
    “…</p> <p>The crop maps will be derived using the Random Forest machine learning algorithm and monthly gap-free Landsat Sentinel-2 time series data that was evaluated to be optimal and well documented in this paper. …”
  14. 134

    Data Sheet 1_Immunogenic cell death-related genes as prognostic biomarkers and therapeutic insights in uterine corpus endometrial carcinoma: an integrative bioinformatics analysis.... by Tianfei Yi (10971822)

    Published 2025
    “…</p>Methods<p>The ICD score was assessed using single-sample gene set enrichment analysis (ssGSEA). Differentially expressed genes (DEGs) were identified from transcriptomic data processed with the "DESeq2" R package. …”
  15. 135

    <b>AI for imaging plant stress in invasive species </b>(dataset from the article https://doi.org/10.1093/aob/mcaf043) by Erola Fenollosa (20977421)

    Published 2025
    “…</i>, 2023</a>) (<a href="#sup1" target="_blank">Supplementary Data S2</a>). The final proposed betalain extraction procedure in the cape fig used 300 mg of frozen leaf samples ground with a mixer mill and homogenized with 0.5 mL of 50 % MeOH (aq.) and mixed for 20 min with a vortex. …”
  16. 136

    Akt1 prodigiosin docking and dynamic molecular by Fares ELGHALI (18467655)

    Published 2024
    “…Long-range electrostatic interactions were calculated using the particle-mesh Ewald (PME) algorithm, with a real space cutoff of 1.2 nm. (8) Initial Velocities Assignment: Initial velocities of particles were assigned based on Maxwell distributions to set the system in motion. (9) Molecular Dynamics Simulation: tow simulations have been performed between 10 and 100 nanosecond (ns) with sampling of each 5 ns, MD simulation was conducted to observe and analyze the system's behavior over an extended period. (10) Analysis: Various parameters including root mean square deviations (RMSD), residue root means square fluctuation (RMSF), number of hydrogen bonds (HB), radius of gyration (Rg) were calculated to analyze the system's dynamics and interactions. …”
  17. 137

    Data_Sheet_1_Metagenomic Geolocation Prediction Using an Adaptive Ensemble Classifier.PDF by Samuel Anyaso-Samuel (10671576)

    Published 2021
    “…In each instance, we observed that the component classifiers performed differently, whereas the ensemble classifier consistently yielded optimal performance. Finally, we predicted the source cities of mystery samples provided by the organizers. …”
  18. 138

    Data Sheet 2_Analysis and validation of serum biomarkers in brucellosis patients through proteomics and bioinformatics.xlsx by Xiao Li (107004)

    Published 2025
    “…Introduction<p>This study aims to utilize proteomics, bioinformatics, and machine learning algorithms to identify diagnostic biomarkers in the serum of patients with acute and chronic brucellosis</p>Methods<p>Proteomic analysis was conducted on serum samples from patients with acute and chronic brucellosis, as well as from healthy controls. …”
  19. 139

    Data Sheet 3_Analysis and validation of serum biomarkers in brucellosis patients through proteomics and bioinformatics.docx by Xiao Li (107004)

    Published 2025
    “…Introduction<p>This study aims to utilize proteomics, bioinformatics, and machine learning algorithms to identify diagnostic biomarkers in the serum of patients with acute and chronic brucellosis</p>Methods<p>Proteomic analysis was conducted on serum samples from patients with acute and chronic brucellosis, as well as from healthy controls. …”
  20. 140

    Data Sheet 1_Analysis and validation of serum biomarkers in brucellosis patients through proteomics and bioinformatics.xlsx by Xiao Li (107004)

    Published 2025
    “…Introduction<p>This study aims to utilize proteomics, bioinformatics, and machine learning algorithms to identify diagnostic biomarkers in the serum of patients with acute and chronic brucellosis</p>Methods<p>Proteomic analysis was conducted on serum samples from patients with acute and chronic brucellosis, as well as from healthy controls. …”