Search alternatives:
mode » made (Expand Search)
model » madel (Expand Search)
Showing 1,161 - 1,180 results of 1,414 for search '((((mode OR model) OR ((model OR model) OR model)) OR model) OR more) screening algorithm', query time: 0.22s Refine Results
  1. 1161

    Integrative machine learning and molecular simulation approaches identify GSK3β inhibitors for neurodegenerative disease therapy by Hassan H. Alhassan

    Published 2025-07-01
    “…Among all models, the Random Forest (RF) algorithm had the best prediction accuracy, with a value of 0.6832 on the test set and 0.7432 on the training set, and was employed to screen the target library of 11,032 phytochemicals. …”
    Get full text
    Article
  2. 1162

    Systematic elucidation of the effective constituents and potential mechanisms of Scrophulariae Radix against neoplasm based on LC-MS, network pharmacology, and molecular docking ap... by Shu-jie Yu, Xiao-bin Kong, Xin Jin, Meng-yi Shan, Gang Cheng, Pei-lu Wang, Wen-long Li, Pei-yuan Zhao, Yun-jie Sheng, Bing-qian He, Qi Shi, Hua-qiang Li, Qi-ming Zhao, Lu-ping Qin, Lu-ping Qin, Xiong-yu Meng, Xiong-yu Meng

    Published 2025-07-01
    “…As a result, the material–liquid ratio was significantly reduced from 100 g/mL to 32 g/mL, and the extraction efficiency was 1.332%, which was close to the predicted value of 1.346% in the response surface method, indicating that the algorithm model had a good fit. Next, a total of 738 compounds, including 161 terpenoids, 144 phenolic acids, 51 alkaloids, 24 flavonoids, 34 saccharides, 32 lignans and coumarins, 45 amino acids and derivatives, 23 organic acids, 134 lipids, 22 nucleotides and derivatives, and 59 other ingredients, were characterized from Scrophulariae Radix based on the accurate precursor and product ions, retention time, standards, fragmentation patterns, and previous publications. …”
    Get full text
    Article
  3. 1163

    Genome-wide identification and expression analysis of phytochrome gene family in Aikang58 wheat (Triticum aestivum L.) by Zhu Yang, Zhu Yang, Wenjie Kan, Wenjie Kan, Ziqi Wang, Caiguo Tang, Yuan Cheng, Yuan Cheng, Dacheng Wang, Dacheng Wang, Yameng Gao, Lifang Wu, Lifang Wu

    Published 2025-01-01
    “…Additionally, the least absolute shrinkage and selection operator (LASSO) regression algorithm in machine learning was used to screen transcription factors such as bHLH, WRKY, and MYB that influenced the expression of TaAkPHY genes. …”
    Get full text
    Article
  4. 1164

    The Place of Local Field Potentials in Deep Brain Stimulation Programming for Parkinson’s Disease: A Review by Chun Him Shelton Leung, Hugh D. Simpson, Dominic Thyagarajan

    Published 2025-01-01
    “…Results: Analyzing LFPs clearly has the potential to assist or streamline DBS programming in clinical practice, but there are knowledge gaps and challenges to overcome, especially in the utilization of intraoperative LFPs. Conclusions: More research is required to compare different algorithms that utilize LFPs in DBS programming to identify a simple, practical and time-saving algorithm incorporating reliable LFP biomarkers that will enhance the DBS programming experience for both patients and clinicians.…”
    Get full text
    Article
  5. 1165

    Application of GPR Underground Pipeline Detection Technology in Urban Complex Geological Environments by Xiaoqiang Liang, Da Hu, Yongsuo Li, Yunyi Zhang, Xian Yang

    Published 2022-01-01
    “…To address different kinds of complex conditions, this experiment in the present paper takes ground penetrating radar as the research basis and uses a self-correction and screening algorithm to innovatively detect underground pipelines. …”
    Get full text
    Article
  6. 1166

    A comparative study between Near-Infrared (NIR) spectrometer and High-Performance Liquid Chromatography (HPLC) on the sensitivity and specificity. by Elisa M Maffioli, Chimezie Anyakora

    Published 2025-01-01
    “…While these devices hold great potential, regulators should require more independent evaluations of various drug formulations before implementing them in real-world settings. …”
    Get full text
    Article
  7. 1167
  8. 1168

    The two ends of the spectrum: comparing chronic schizophrenia and premorbid latent schizotypy by actigraphy by Szandra László, Ádám Nagy, József Dombi, Emőke Adrienn Hompoth, Emese Rudics, Zoltán Szabó, András Dér, András Búzás, Zsolt János Viharos, Anh Tuan Hoang, Vilmos Bilicki, István Szendi

    Published 2025-05-01
    “…By applying model-explaining tools to the well-performing models, we could conclude the movement patterns and characteristics of the groups. …”
    Get full text
    Article
  9. 1169

    A cross-sectional study of evaluating cervical spondylotic myelopathy based on gait and plantar pressures by Xuhong Zhang, Zichuan Wu, Hanlin Song, Aochen Xu, Junbin Liu, Junzhe Sheng, Baifeng Sun, Min Qi, Chen Xu, Yang Liu

    Published 2025-06-01
    “…Although previous studies have objectively assessed CSM-specific gait patterns using motion cameras as well as mechanical platforms, these methods have limitations such as limited metrics that can be analyzed or inconvenience for simple screening. Therefore, there is a need to develop effective screening methods. …”
    Get full text
    Article
  10. 1170

    Deciphering the role of cuproptosis in the development of intimal hyperplasia in rat carotid arteries using single cell analysis and machine learning techniques by Miao He, Hui Chen, Zhengli Liu, Boxiang Zhao, Xu He, Qiujin Mao, Jianping Gu, Jie Kong

    Published 2025-02-01
    “…Methods: We downloaded single-cell sequencing and bulk transcriptome data from the GEO database to screen for copper-growth-associated genes (CAGs) using machine-learning algorithms, including Random Forest and Support Vector Machine. …”
    Get full text
    Article
  11. 1171

    The Value of Subclinical Carotid Atherosclerosis for Primary Prevention of Cardiovascular Diseases. Review of the Main International Studies by E. K. Butina, E. V. Bochkareva

    Published 2016-11-01
    “…Measures for the prevention of cardiovascular diseases (CVD) are more effective if they are performed taking into account the risk factors of their development. …”
    Get full text
    Article
  12. 1172

    Shared pathogenic mechanisms linking obesity and idiopathic pulmonary fibrosis revealed by bioinformatics and in vivo validation by Linjie Chen, Haojie Chen, Zinan Chen, Kunyi Zhang, Hongsen Zhang, Jiahe Xu, Tongsheng Chen

    Published 2025-07-01
    “…Functional enrichment (GO/KEGG), protein-protein interaction (PPI) networks, and machine learning algorithms were applied to screen hub genes, validated by ROC curves. …”
    Get full text
    Article
  13. 1173
  14. 1174

    Prediction and validation of anoikis-related genes in neuropathic pain using machine learning. by Yufeng He, Ye Wei, Yongxin Wang, Chunyan Ling, Xiang Qi, Siyu Geng, Yingtong Meng, Hao Deng, Qisong Zhang, Xiaoling Qin, Guanghui Chen

    Published 2025-01-01
    “…We also used rats to construct an NP model and validated the analyzed hub genes using hematoxylin and eosin (H&E) staining, real-time polymerase chain reaction (PCR), and Western blotting assays.…”
    Get full text
    Article
  15. 1175

    Prognostic, oncogenic roles, and pharmacogenomic features of AMD1 in hepatocellular carcinoma by Youliang Zhou, Yi Zhou, Jiabin Hu, Yao Xiao, Yan Zhou, Liping Yu

    Published 2024-12-01
    “…Univariate Cox regression analysis and Pearson correlation were used to screen for AMD1-related genes (ARGs). Multidimensional bioinformatic algorithms were utilized to establish a risk score model for ARGs. …”
    Get full text
    Article
  16. 1176

    Identification of glucocorticoid-related genes in systemic lupus erythematosus using bioinformatics analysis and machine learning. by Yinghao Ren, Weiqiang Chen, Yuhao Lin, Zeyu Wang, Weiliang Wang

    Published 2025-01-01
    “…Furthermore, we utilized least absolute shrinkage and selection operator (LASSO) regression and Random Forest (RF) algorithms to screen for hub genes. We then validated the expression of these hub genes and constructed nomograms for further validation. …”
    Get full text
    Article
  17. 1177

    Fragmenstein: predicting protein–ligand structures of compounds derived from known crystallographic fragment hits using a strict conserved-binding–based methodology by Matteo P. Ferla, Rubén Sánchez-García, Rachael E. Skyner, Stefan Gahbauer, Jenny C. Taylor, Frank von Delft, Brian D. Marsden, Charlotte M. Deane

    Published 2025-01-01
    “…We show that an algorithmic approach (Fragmenstein) that ‘stitches’ the ligand atoms from this structural information together can provide more accurate and reliable predictions for protein–ligand complex conformation than general methods such as pharmacophore-constrained docking. …”
    Get full text
    Article
  18. 1178

    LABORATORY OF CLINICAL IMMUNOLOGY N.V. SKLIFOSOVSKY RESEARCH INSTITUTE FOR EMERGENCY MEDICINE (HISTORY AND PRESENT) by M. A. Godkov, G. V. Bulava

    Published 2016-03-01
    “…During 45 years of work of immunological service formed the algorithm of the adequate immunological screening was formed, number of innovative methods of diagnosis was developed, the ideology of post-test counseling of patients by immunologists was created, mathematical methods of storage, modeling and processing of research results was introduced. …”
    Get full text
    Article
  19. 1179

    Psychometric properties of the German version of the Traumatic Grief Inventory-Self Report Plus (TGI-SR+) by Julia Treml, Viktoria Schmidt, Elmar Braehler, Matthias Morfeld, Anette Kersting

    Published 2024-12-01
    “…Despite the same name, both versions of PGD differ in symptom count, content, and diagnostic algorithm. A single instrument to screen for both PGD diagnoses is critical for bereavement research and care. …”
    Get full text
    Article
  20. 1180

    Ways to predict interstitial lung disease in patients with systemic sclerosis: results of an observational study by D. V. Khorolsky, A. A. Klimenko, E. S. Pershina, N. M. Babadeva, A. A. Kondrashov, N. A. Shostak, E. P. Mikheeva, E. V. Zhilyaev

    Published 2023-08-01
    “…It is advisable to include these indicators in the algorithm for screening and monitoring patients with SSc.…”
    Get full text
    Article