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182 related items for PubMed ID: 34528291

  • 1. ANOVA-particle swarm optimization-based feature selection and gradient boosting machine classifier for improved protein-protein interaction prediction.
    Mahapatra S, Sahu SS.
    Proteins; 2022 Feb; 90(2):443-454. PubMed ID: 34528291
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  • 4. Deep Neural Network and Extreme Gradient Boosting Based Hybrid Classifier for Improved Prediction of Protein-Protein Interaction.
    Mahapatra S, Gupta VR, Sahu SS, Panda G.
    IEEE/ACM Trans Comput Biol Bioinform; 2022 Feb; 19(1):155-165. PubMed ID: 33621179
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  • 6. Predicting protein-protein interactions by fusing various Chou's pseudo components and using wavelet denoising approach.
    Tian B, Wu X, Chen C, Qiu W, Ma Q, Yu B.
    J Theor Biol; 2019 Feb 07; 462():329-346. PubMed ID: 30452960
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  • 8. Sequence-Based Prediction with Feature Representation Learning and Biological Function Analysis of Channel Proteins.
    Chen Z, Jiao S, Zhao D, Hesham AE, Zou Q, Xu L, Sun M, Zhang L.
    Front Biosci (Landmark Ed); 2022 Jun 02; 27(6):177. PubMed ID: 35748253
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  • 11. RVMAB: Using the Relevance Vector Machine Model Combined with Average Blocks to Predict the Interactions of Proteins from Protein Sequences.
    An JY, You ZH, Meng FR, Xu SJ, Wang Y.
    Int J Mol Sci; 2016 May 18; 17(5):. PubMed ID: 27213337
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  • 13. Global protein-protein interaction networks in yeast saccharomyces cerevisiae and helicobacter pylori.
    Zandi F, Mansouri P, Goodarzi M.
    Talanta; 2023 Dec 01; 265():124836. PubMed ID: 37393709
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  • 14. Improved Prediction of Protein-Protein Interaction Mapping on Homo Sapiens by Using Amino Acid Sequence Features in a Supervised Learning Framework.
    Islam MM, Alam MJ, Ahmed FF, Hasan MM, Mollah MNH.
    Protein Pept Lett; 2021 Dec 01; 28(1):74-83. PubMed ID: 32520672
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  • 15. PreDTIs: prediction of drug-target interactions based on multiple feature information using gradient boosting framework with data balancing and feature selection techniques.
    Mahmud SMH, Chen W, Liu Y, Awal MA, Ahmed K, Rahman MH, Moni MA.
    Brief Bioinform; 2021 Sep 02; 22(5):. PubMed ID: 33709119
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  • 16. Improving protein-protein interactions prediction accuracy using XGBoost feature selection and stacked ensemble classifier.
    Chen C, Zhang Q, Yu B, Yu Z, Lawrence PJ, Ma Q, Zhang Y.
    Comput Biol Med; 2020 Aug 02; 123():103899. PubMed ID: 32768046
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  • 17. Accurate prediction of protein-protein interactions by integrating potential evolutionary information embedded in PSSM profile and discriminative vector machine classifier.
    Li ZW, You ZH, Chen X, Li LP, Huang DS, Yan GY, Nie R, Huang YA.
    Oncotarget; 2017 Apr 04; 8(14):23638-23649. PubMed ID: 28423569
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  • 18. Using Weighted Extreme Learning Machine Combined With Scale-Invariant Feature Transform to Predict Protein-Protein Interactions From Protein Evolutionary Information.
    Li J, Shi X, You ZH, Yi HC, Chen Z, Lin Q, Fang M.
    IEEE/ACM Trans Comput Biol Bioinform; 2020 Apr 04; 17(5):1546-1554. PubMed ID: 31940546
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  • 19. Explainable machine learning models based on multimodal time-series data for the early detection of Parkinson's disease.
    Junaid M, Ali S, Eid F, El-Sappagh S, Abuhmed T.
    Comput Methods Programs Biomed; 2023 Jun 04; 234():107495. PubMed ID: 37003039
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  • 20. Analysis of Hybrid Feature Optimization Techniques Based on the Classification Accuracy of Brain Tumor Regions Using Machine Learning and Further Evaluation Based on the Institute Test Data.
    Pal S, Singh RP, Kumar A.
    J Med Phys; 2024 Jun 04; 49(1):22-32. PubMed ID: 38828069
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