Efficient computational model for identification of antitubercular peptides by integrating amino acid patterns and properties
暂无分享,去创建一个
[1] Chul-Su Yang,et al. Host-Directed Therapeutics as a Novel Approach for Tuberculosis Treatment. , 2017, Journal of microbiology and biotechnology.
[2] Gajendra P. S. Raghava,et al. AntiTbPdb: a knowledgebase of anti-tubercular peptides , 2018, Database J. Biol. Databases Curation.
[3] Hiroyuki Kurata,et al. PreAIP: Computational Prediction of Anti-inflammatory Peptides by Integrating Multiple Complementary Features , 2019, Front. Genet..
[4] Jinyan Li,et al. Computational Identification of Protein Pupylation Sites by Using Profile-Based Composition of k-Spaced Amino Acid Pairs , 2015, PloS one.
[5] Balachandran Manavalan,et al. Random Forest-Based Protein Model Quality Assessment (RFMQA) Using Structural Features and Potential Energy Terms , 2014, PloS one.
[6] Myeong Ok Kim,et al. iBCE-EL: A New Ensemble Learning Framework for Improved Linear B-Cell Epitope Prediction , 2018, Front. Immunol..
[7] John W. Wilson,et al. Extensively Drug-Resistant Tuberculosis: Principles of Resistance, Diagnosis, and Management. , 2016, Mayo Clinic proceedings.
[8] C. Hamilton,et al. RePORT International: Advancing Tuberculosis Biomarker Research Through Global Collaboration. , 2015, Clinical infectious diseases : an official publication of the Infectious Diseases Society of America.
[9] Rolf Apweiler,et al. The SWISS-PROT protein sequence database and its supplement TrEMBL in 2000 , 2000, Nucleic Acids Res..
[10] Shivendra K Chaurasiya. Tuberculosis: Smart manipulation of a lethal host , 2018, Microbiology and immunology.
[11] Hiroyuki Kurata,et al. Computational identification of protein S-sulfenylation sites by incorporating the multiple sequence features information. , 2017, Molecular bioSystems.
[12] Alfred Goldberg,et al. Lassomycin, a ribosomally synthesized cyclic peptide, kills mycobacterium tuberculosis by targeting the ATP-dependent protease ClpC1P1P2. , 2014, Chemistry & biology.
[13] Gajendra P. S. Raghava,et al. Prediction of Antitubercular Peptides From Sequence Information Using Ensemble Classifier and Hybrid Features , 2018, Front. Pharmacol..
[14] Suhair Sunoqrot,et al. The Cyclic Peptide Ecumicin Targeting ClpC1 Is Active against Mycobacterium tuberculosis In Vivo , 2014, Antimicrobial Agents and Chemotherapy.
[15] Hiroyuki Kurata,et al. GPSuc: Global Prediction of Generic and Species-specific Succinylation Sites by aggregating multiple sequence features , 2018, PloS one.
[16] Leyi Wei,et al. mAHTPred: a sequence-based meta-predictor for improving the prediction of anti-hypertensive peptides using effective feature representation , 2018, Bioinform..
[17] Dianjing Guo,et al. A systematic identification of species-specific protein succinylation sites using joint element features information , 2017, International journal of nanomedicine.
[18] Md. Nurul Haque Mollah,et al. NTyroSite: Computational Identification of Protein Nitrotyrosine Sites Using Sequence Evolutionary Features , 2018, Molecules.
[19] Hiroyuki Kurata,et al. iLBE for Computational Identification of Linear B-cell Epitopes by Integrating Sequence and Evolutionary Features , 2020, Genom. Proteom. Bioinform..
[20] Marcos Abdo Arbex,et al. Drogas antituberculose: interações medicamentosas, efeitos adversos e utilização em situações especiais - parte 1: fármacos de primeira linha , 2010 .
[21] A. Diacon,et al. C-Tb skin test to diagnose Mycobacterium tuberculosis infection in children and HIV-infected adults: A phase 3 trial , 2018, PloS one.
[22] Leo Breiman,et al. Random Forests , 2001, Machine Learning.
[23] Vladimir Vacic,et al. Two Sample Logo: a graphical representation of the differences between two sets of sequence alignments , 2006, Bioinform..
[24] M. Zasloff. Inducing endogenous antimicrobial peptides to battle infections. , 2006, Proceedings of the National Academy of Sciences of the United States of America.
[25] Hiroyuki Kurata,et al. A Comprehensive Review of In silico Analysis for Protein S-sulfenylation Sites. , 2018, Protein and peptide letters.
[26] Leyi Wei,et al. Meta-4mCpred: A Sequence-Based Meta-Predictor for Accurate DNA 4mC Site Prediction Using Effective Feature Representation , 2019, Molecular therapy. Nucleic acids.
[27] Hiroyuki Kurata,et al. Large-Scale Assessment of Bioinformatics Tools for Lysine Succinylation Sites , 2019, Cells.
[28] Hongping Wei,et al. Anti-Mycobacterial Peptides: From Human to Phage , 2015, Cellular Physiology and Biochemistry.
[29] Avinash Sonawane,et al. Antimicrobial peptides and proteins in mycobacterial therapy: current status and future prospects. , 2014, Tuberculosis.
[30] Gwang Lee,et al. AIPpred: Sequence-Based Prediction of Anti-inflammatory Peptides Using Random Forest , 2018, Front. Pharmacol..
[31] Ming-Chih Yu,et al. Nine- to Twelve-Month Anti-Tuberculosis Treatment Is Associated with a Lower Recurrence Rate than 6–9-Month Treatment in Human Immunodeficiency Virus-Infected Patients: A Retrospective Population-Based Cohort Study in Taiwan , 2015, PloS one.
[32] Minoru Kanehisa,et al. AAindex: amino acid index database, progress report 2008 , 2007, Nucleic Acids Res..
[33] Fatih Köksal,et al. Antimicrobial peptides as an alternative to anti-tuberculosis drugs. , 2017, Pharmacological research.
[34] Bernhard Kaltenboeck,et al. Datasets confound B-cell epitope prediction 1 Inadequate Reference Datasets Biased towards Short Non-epitopes Confound B-cell Epitope Prediction , 2016 .
[35] M. Brimble,et al. Synthesis and bioactivity of antitubercular peptides and peptidomimetics: an update. , 2016, Organic & biomolecular chemistry.
[36] S. Jhamb,et al. Determination of the activity of standard anti-tuberculosis drugs against intramacrophage Mycobacterium tuberculosis, in vitro: MGIT 960 as a viable alternative for BACTEC 460 , 2014, The Brazilian journal of infectious diseases : an official publication of the Brazilian Society of Infectious Diseases.
[37] Rolf Apweiler,et al. The SWISS-PROT protein sequence data bank and its supplement TrEMBL , 1997, Nucleic Acids Res..
[38] C. Nacy,et al. Rapid, Simple In Vivo Screen for New Drugs Active against Mycobacterium tuberculosis , 2004, Antimicrobial Agents and Chemotherapy.
[39] Hiroyuki Kurata,et al. Computational identification of microbial phosphorylation sites by the enhanced characteristics of sequence information , 2019, Scientific Reports.
[40] Andreas Christmann,et al. Support vector machines , 2008, Data Mining and Knowledge Discovery Handbook.
[41] F. M. Gama,et al. Antimicrobial peptides as novel anti-tuberculosis therapeutics. , 2016, Biotechnology advances.
[42] Md. Nurul Haque Mollah,et al. SuccinSite: a computational tool for the prediction of protein succinylation sites by exploiting the amino acid patterns and properties. , 2016, Molecular bioSystems.
[43] Alimuddin Zumla,et al. The WHO 2014 global tuberculosis report--further to go. , 2015, The Lancet. Global health.
[44] M. Yeaman,et al. Multidimensional signatures in antimicrobial peptides. , 2004, Proceedings of the National Academy of Sciences of the United States of America.