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 *

184 related articles for article (PubMed ID: 31151025)

  • 1. THPep: A machine learning-based approach for predicting tumor homing peptides.
    Shoombuatong W; Schaduangrat N; Pratiwi R; Nantasenamat C
    Comput Biol Chem; 2019 Jun; 80():441-451. PubMed ID: 31151025
    [TBL] [Abstract][Full Text] [Related]  

  • 2. HemoPred: a web server for predicting the hemolytic activity of peptides.
    Win TS; Malik AA; Prachayasittikul V; S Wikberg JE; Nantasenamat C; Shoombuatong W
    Future Med Chem; 2017 Mar; 9(3):275-291. PubMed ID: 28211294
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Computational approach for designing tumor homing peptides.
    Sharma A; Kapoor P; Gautam A; Chaudhary K; Kumar R; Chauhan JS; Tyagi A; Raghava GP
    Sci Rep; 2013; 3():1607. PubMed ID: 23558316
    [TBL] [Abstract][Full Text] [Related]  

  • 4. iBitter-SCM: Identification and characterization of bitter peptides using a scoring card method with propensity scores of dipeptides.
    Charoenkwan P; Yana J; Schaduangrat N; Nantasenamat C; Hasan MM; Shoombuatong W
    Genomics; 2020 Jul; 112(4):2813-2822. PubMed ID: 32234434
    [TBL] [Abstract][Full Text] [Related]  

  • 5. KELM-CPPpred: Kernel Extreme Learning Machine Based Prediction Model for Cell-Penetrating Peptides.
    Pandey P; Patel V; George NV; Mallajosyula SS
    J Proteome Res; 2018 Sep; 17(9):3214-3222. PubMed ID: 30032609
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Meta-iAVP: A Sequence-Based Meta-Predictor for Improving the Prediction of Antiviral Peptides Using Effective Feature Representation.
    Schaduangrat N; Nantasenamat C; Prachayasittikul V; Shoombuatong W
    Int J Mol Sci; 2019 Nov; 20(22):. PubMed ID: 31731751
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Prediction of anti-inflammatory proteins/peptides: an insilico approach.
    Gupta S; Sharma AK; Shastri V; Madhu MK; Sharma VK
    J Transl Med; 2017 Jan; 15(1):7. PubMed ID: 28057002
    [TBL] [Abstract][Full Text] [Related]  

  • 8. UMPred-FRL: A New Approach for Accurate Prediction of Umami Peptides Using Feature Representation Learning.
    Charoenkwan P; Nantasenamat C; Hasan MM; Moni MA; Manavalan B; Shoombuatong W
    Int J Mol Sci; 2021 Dec; 22(23):. PubMed ID: 34884927
    [TBL] [Abstract][Full Text] [Related]  

  • 9. iQSP: A Sequence-Based Tool for the Prediction and Analysis of Quorum Sensing Peptides via Chou's 5-Steps Rule and Informative Physicochemical Properties.
    Charoenkwan P; Schaduangrat N; Nantasenamat C; Piacham T; Shoombuatong W
    Int J Mol Sci; 2019 Dec; 21(1):. PubMed ID: 31861928
    [TBL] [Abstract][Full Text] [Related]  

  • 10. NL MIND-BEST: a web server for ligands and proteins discovery--theoretic-experimental study of proteins of Giardia lamblia and new compounds active against Plasmodium falciparum.
    González-Díaz H; Prado-Prado F; Sobarzo-Sánchez E; Haddad M; Maurel Chevalley S; Valentin A; Quetin-Leclercq J; Dea-Ayuela MA; Teresa Gomez-Muños M; Munteanu CR; José Torres-Labandeira J; García-Mera X; Tapia RA; Ubeira FM
    J Theor Biol; 2011 May; 276(1):229-49. PubMed ID: 21277861
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Correlation and prediction of gene expression level from amino acid and dipeptide composition of its protein.
    Raghava GP; Han JH
    BMC Bioinformatics; 2005 Mar; 6():59. PubMed ID: 15773999
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Designing of peptides with desired half-life in intestine-like environment.
    Sharma A; Singla D; Rashid M; Raghava GP
    BMC Bioinformatics; 2014 Aug; 15(1):282. PubMed ID: 25141912
    [TBL] [Abstract][Full Text] [Related]  

  • 13. PAAP: a web server for predicting antihypertensive activity of peptides.
    Win TS; Schaduangrat N; Prachayasittikul V; Nantasenamat C; Shoombuatong W
    Future Med Chem; 2018 Aug; 10(15):1749-1767. PubMed ID: 30039980
    [TBL] [Abstract][Full Text] [Related]  

  • 14. TargetAntiAngio: A Sequence-Based Tool for the Prediction and Analysis of Anti-Angiogenic Peptides.
    Laengsri V; Nantasenamat C; Schaduangrat N; Nuchnoi P; Prachayasittikul V; Shoombuatong W
    Int J Mol Sci; 2019 Jun; 20(12):. PubMed ID: 31212918
    [TBL] [Abstract][Full Text] [Related]  

  • 15. PIP-EL: A New Ensemble Learning Method for Improved Proinflammatory Peptide Predictions.
    Manavalan B; Shin TH; Kim MO; Lee G
    Front Immunol; 2018; 9():1783. PubMed ID: 30108593
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Machine learning study of classifiers trained with biophysiochemical properties of amino acids to predict fibril forming Peptide motifs.
    Kumaran Nair SS; Subba Reddy NV; Hareesha KS
    Protein Pept Lett; 2012 Sep; 19(9):917-23. PubMed ID: 22486618
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A machine learning based method for the prediction of secretory proteins using amino acid composition, their order and similarity-search.
    Garg A; Raghava GP
    In Silico Biol; 2008; 8(2):129-40. PubMed ID: 18928201
    [TBL] [Abstract][Full Text] [Related]  

  • 18. CAPTURE: Comprehensive anti-cancer peptide predictor with a unique amino acid sequence encoder.
    Ghafoor H; Asim MN; Ibrahim MA; Ahmed S; Dengel A
    Comput Biol Med; 2024 Jun; 176():108538. PubMed ID: 38759585
    [TBL] [Abstract][Full Text] [Related]  

  • 19. ProInflam: a webserver for the prediction of proinflammatory antigenicity of peptides and proteins.
    Gupta S; Madhu MK; Sharma AK; Sharma VK
    J Transl Med; 2016 Jun; 14(1):178. PubMed ID: 27301453
    [TBL] [Abstract][Full Text] [Related]  

  • 20. In silico approaches for designing highly effective cell penetrating peptides.
    Gautam A; Chaudhary K; Kumar R; Sharma A; Kapoor P; Tyagi A; ; Raghava GP
    J Transl Med; 2013 Mar; 11():74. PubMed ID: 23517638
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.