These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

185 related articles for article (PubMed ID: 33902446)

  • 21. Prediction of lysine propionylation sites using biased SVM and incorporating four different sequence features into Chou's PseAAC.
    Ju Z; He JJ
    J Mol Graph Model; 2017 Sep; 76():356-363. PubMed ID: 28763688
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Inspector: a lysine succinylation predictor based on edited nearest-neighbor undersampling and adaptive synthetic oversampling.
    Zhu Y; Jia C; Li F; Song J
    Anal Biochem; 2020 Mar; 593():113592. PubMed ID: 31968210
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Prediction of lysine crotonylation sites by incorporating the composition of k-spaced amino acid pairs into Chou's general PseAAC.
    Ju Z; He JJ
    J Mol Graph Model; 2017 Oct; 77():200-204. PubMed ID: 28886434
    [TBL] [Abstract][Full Text] [Related]  

  • 24. iLM-2L: A two-level predictor for identifying protein lysine methylation sites and their methylation degrees by incorporating K-gap amino acid pairs into Chou׳s general PseAAC.
    Ju Z; Cao JZ; Gu H
    J Theor Biol; 2015 Nov; 385():50-7. PubMed ID: 26254214
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Predicting S-nitrosylation proteins and sites by fusing multiple features.
    Qiu WR; Wang QK; Guan MY; Jia JH; Xiao X
    Math Biosci Eng; 2021 Oct; 18(6):9132-9147. PubMed ID: 34814339
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Prediction of lysine glutarylation sites by maximum relevance minimum redundancy feature selection.
    Ju Z; He JJ
    Anal Biochem; 2018 Jun; 550():1-7. PubMed ID: 29641975
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Prediction of lysine formylation sites using support vector machine based on the sample selection from majority classes and synthetic minority over-sampling techniques.
    Sohrawordi M; Hossain MA
    Biochimie; 2022 Jan; 192():125-135. PubMed ID: 34627982
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Predicting Citrullination Sites in Protein Sequences Using mRMR Method and Random Forest Algorithm.
    Zhang Q; Sun X; Feng K; Wang S; Zhang YH; Wang S; Lu L; Cai YD
    Comb Chem High Throughput Screen; 2017; 20(2):164-173. PubMed ID: 28029071
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Improvement of P300-Based Brain-Computer Interfaces for Home Appliances Control by Data Balancing Techniques.
    Lee T; Kim M; Kim SP
    Sensors (Basel); 2020 Sep; 20(19):. PubMed ID: 33003367
    [TBL] [Abstract][Full Text] [Related]  

  • 30. FCCCSR_Glu: a semi-supervised learning model based on FCCCSR algorithm for prediction of glutarylation sites.
    Ning Q; Qi Z; Wang Y; Deng A; Chen C
    Brief Bioinform; 2022 Nov; 23(6):. PubMed ID: 36168700
    [TBL] [Abstract][Full Text] [Related]  

  • 31. SMOTE for high-dimensional class-imbalanced data.
    Blagus R; Lusa L
    BMC Bioinformatics; 2013 Mar; 14():106. PubMed ID: 23522326
    [TBL] [Abstract][Full Text] [Related]  

  • 32. PLP_FS: prediction of lysine phosphoglycerylation sites in protein using support vector machine and fusion of multiple F_Score feature selection.
    Sohrawordi M; Hossain MA; Hasan MAM
    Brief Bioinform; 2022 Sep; 23(5):. PubMed ID: 35929355
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Structure-activity relationship-based chemical classification of highly imbalanced Tox21 datasets.
    Idakwo G; Thangapandian S; Luttrell J; Li Y; Wang N; Zhou Z; Hong H; Yang B; Zhang C; Gong P
    J Cheminform; 2020 Oct; 12(1):66. PubMed ID: 33372637
    [TBL] [Abstract][Full Text] [Related]  

  • 34. MLysPRED: graph-based multi-view clustering and multi-dimensional normal distribution resampling techniques to predict multiple lysine sites.
    Zuo Y; Hong Y; Zeng X; Zhang Q; Liu X
    Brief Bioinform; 2022 Sep; 23(5):. PubMed ID: 35953081
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Prediction of Citrullination Sites on the Basis of mRMR Method and SNN.
    Liu M; Liu G
    Comb Chem High Throughput Screen; 2019; 22(10):705-715. PubMed ID: 31782357
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Recognition of Protein Pupylation Sites by Adopting Resampling Approach.
    Li T; Chen Y; Li T; Jia C
    Molecules; 2018 Nov; 23(12):. PubMed ID: 30486421
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Predicting lysine lipoylation sites using bi-profile bayes feature extraction and fuzzy support vector machine algorithm.
    Ju Z; Wang SY
    Anal Biochem; 2018 Nov; 561-562():11-17. PubMed ID: 30218638
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Enhanced plasma protein carbonylation in patients with myelodysplastic syndromes.
    Hlaváčková A; Štikarová J; Pimková K; Chrastinová L; Májek P; Kotlín R; Čermák J; Suttnar J; Dyr JE
    Free Radic Biol Med; 2017 Jul; 108():1-7. PubMed ID: 28300669
    [TBL] [Abstract][Full Text] [Related]  

  • 39. iGlu_AdaBoost: Identification of Lysine Glutarylation Using the AdaBoost Classifier.
    Dou L; Li X; Zhang L; Xiang H; Xu L
    J Proteome Res; 2021 Jan; 20(1):191-201. PubMed ID: 33090794
    [TBL] [Abstract][Full Text] [Related]  

  • 40. A Synthetic Minority Oversampling Technique Based on Gaussian Mixture Model Filtering for Imbalanced Data Classification.
    Xu Z; Shen D; Kou Y; Nie T
    IEEE Trans Neural Netw Learn Syst; 2024 Mar; 35(3):3740-3753. PubMed ID: 35984792
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 10.