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.


Pubmed for Handhelds

PUBMED FOR HANDHELDS

Journal Abstract Search

193 related items for PubMed ID: 30255784

  • 1. Optimal selection of molecular descriptors for antimicrobial peptides classification: an evolutionary feature weighting approach.
    Beltran JA, Aguilera-Mendoza L, Brizuela CA.
    BMC Genomics; 2018 Sep 24; 19(Suppl 7):672. PubMed ID: 30255784
    [Abstract] [Full Text] [Related]

  • 2. Computer-based analysis, visualization, and interpretation of antimicrobial peptide activities.
    Mikut R.
    Methods Mol Biol; 2010 Sep 24; 618():287-99. PubMed ID: 20094871
    [Abstract] [Full Text] [Related]

  • 3. AMAP: Hierarchical multi-label prediction of biologically active and antimicrobial peptides.
    Gull S, Shamim N, Minhas F.
    Comput Biol Med; 2019 Apr 24; 107():172-181. PubMed ID: 30831306
    [Abstract] [Full Text] [Related]

  • 4. Antimicrobial peptide similarity and classification through rough set theory using physicochemical boundaries.
    Boone K, Camarda K, Spencer P, Tamerler C.
    BMC Bioinformatics; 2018 Dec 06; 19(1):469. PubMed ID: 30522443
    [Abstract] [Full Text] [Related]

  • 5. Quantitative sequence-activity modeling of antimicrobial hexapeptides using a segmented principal component strategy: an approach to describe and predict activities of peptide drugs containing L/D and unnatural residues.
    Yousefinejad S, Bagheri M, Moosavi-Movahedi AA.
    Amino Acids; 2015 Jan 06; 47(1):125-34. PubMed ID: 25323737
    [Abstract] [Full Text] [Related]

  • 6. Methods for building quantitative structure-activity relationship (QSAR) descriptors and predictive models for computer-aided design of antimicrobial peptides.
    Taboureau O.
    Methods Mol Biol; 2010 Jan 06; 618():77-86. PubMed ID: 20094859
    [Abstract] [Full Text] [Related]

  • 7. QSAR modeling and computer-aided design of antimicrobial peptides.
    Jenssen H, Fjell CD, Cherkasov A, Hancock RE.
    J Pept Sci; 2008 Jan 06; 14(1):110-4. PubMed ID: 17847019
    [Abstract] [Full Text] [Related]

  • 8. Short linear cationic antimicrobial peptides: screening, optimizing, and prediction.
    Hilpert K, Fjell CD, Cherkasov A.
    Methods Mol Biol; 2008 Jan 06; 494():127-59. PubMed ID: 18726572
    [Abstract] [Full Text] [Related]

  • 9. PhytAMP: a database dedicated to antimicrobial plant peptides.
    Hammami R, Ben Hamida J, Vergoten G, Fliss I.
    Nucleic Acids Res; 2009 Jan 06; 37(Database issue):D963-8. PubMed ID: 18836196
    [Abstract] [Full Text] [Related]

  • 10. Desirability-based multi-criteria virtual screening of selective antimicrobial cyclic β-hairpin cationic peptidomimetics.
    Cruz-Monteagudo M, Romero Y, Cordeiro MN, Borges F.
    Curr Pharm Des; 2013 Jan 06; 19(12):2148-63. PubMed ID: 23016843
    [Abstract] [Full Text] [Related]

  • 11. Optimization of antibacterial peptides by genetic algorithms and cheminformatics.
    Fjell CD, Jenssen H, Cheung WA, Hancock RE, Cherkasov A.
    Chem Biol Drug Des; 2011 Jan 06; 77(1):48-56. PubMed ID: 20942839
    [Abstract] [Full Text] [Related]

  • 12. QSAR modeling of the antimicrobial activity of peptides as a mathematical function of a sequence of amino acids.
    Toropova MA, Veselinović AM, Veselinović JB, Stojanović DB, Toropov AA.
    Comput Biol Chem; 2015 Dec 06; 59 Pt A():126-30. PubMed ID: 26454621
    [Abstract] [Full Text] [Related]

  • 13. Antimicrobial polymers as synthetic mimics of host-defense peptides.
    Kuroda K, Caputo GA.
    Wiley Interdiscip Rev Nanomed Nanobiotechnol; 2013 Dec 06; 5(1):49-66. PubMed ID: 23076870
    [Abstract] [Full Text] [Related]

  • 14. Application of 'HESH' descriptors for the structure-activity relationships of antimicrobial peptides.
    Shu M, Jiang Y, Yang L, Wu Y, Mei H, Li Z.
    Protein Pept Lett; 2009 Dec 06; 16(2):143-9. PubMed ID: 19200037
    [Abstract] [Full Text] [Related]

  • 15. Handcrafted versus non-handcrafted (self-supervised) features for the classification of antimicrobial peptides: complementary or redundant?
    García-Jacas CR, García-González LA, Martinez-Rios F, Tapia-Contreras IP, Brizuela CA.
    Brief Bioinform; 2022 Nov 19; 23(6):. PubMed ID: 36215083
    [Abstract] [Full Text] [Related]

  • 16. Predicting Antimicrobial Peptides by Using Increment of Diversity with Quadratic Discriminant Analysis Method.
    Feng P, Wang Z, Yu X.
    IEEE/ACM Trans Comput Biol Bioinform; 2019 Nov 19; 16(4):1309-1312. PubMed ID: 28212093
    [Abstract] [Full Text] [Related]

  • 17. Coupling molecular dynamics simulations with experiments for the rational design of indolicidin-analogous antimicrobial peptides.
    Tsai CW, Hsu NY, Wang CH, Lu CY, Chang Y, Tsai HH, Ruaan RC.
    J Mol Biol; 2009 Sep 25; 392(3):837-54. PubMed ID: 19576903
    [Abstract] [Full Text] [Related]

  • 18. Design of novispirin antimicrobial peptides by quantitative structure-activity relationship.
    Taboureau O, Olsen OH, Nielsen JD, Raventos D, Mygind PH, Kristensen HH.
    Chem Biol Drug Des; 2006 Jul 25; 68(1):48-57. PubMed ID: 16923026
    [Abstract] [Full Text] [Related]

  • 19. iAMP-2L: a two-level multi-label classifier for identifying antimicrobial peptides and their functional types.
    Xiao X, Wang P, Lin WZ, Jia JH, Chou KC.
    Anal Biochem; 2013 May 15; 436(2):168-77. PubMed ID: 23395824
    [Abstract] [Full Text] [Related]

  • 20. Optimizing antimicrobial host defense peptides.
    Sahl HG.
    Chem Biol; 2006 Oct 15; 13(10):1015-7. PubMed ID: 17052605
    [Abstract] [Full Text] [Related]

    Page: [Next] [New Search]
    of 10.