Prediction of the synergistic effect of antimicrobial peptides and antimicrobial agents via supervised machine learning

[1]  Mehmet Akif Özdemir,et al.  Plasma medicine: The era of artificial intelligence , 2023, Plasma Processes and Polymers.

[2]  Mehmet Akif Ozdemir,et al.  Hand gesture classification using time-frequency images and transfer learning based on CNN , 2022, Biomed. Signal Process. Control..

[3]  Mehmet Akif Ozdemir,et al.  Machine learning to predict the antimicrobial activity of cold atmospheric plasma-activated liquids , 2022, Mach. Learn. Sci. Technol..

[4]  Bara' Al-Mistarehi,et al.  Using Machine Learning Models to Forecast Severity Level of Traffic Crashes by R Studio and ArcGIS , 2022, Frontiers in Built Environment.

[5]  M. Totsika,et al.  Combination Therapies for Biofilm Inhibition and Eradication: A Comparative Review of Laboratory and Preclinical Studies , 2022, Frontiers in Cellular and Infection Microbiology.

[6]  V. R. Joseph.  Optimal ratio for data splitting , 2022, Stat. Anal. Data Min..

[7]  Taqwa F. Shaban,et al.  Prediction of qualitative antibiofilm activity of antibiotics using supervised machine learning techniques , 2021, Comput. Biol. Medicine.

[8]  Andrés J. García,et al.  Biomaterial-based antimicrobial therapies for the treatment of bacterial infections , 2021, Nature Reviews Materials.

[9]  Hao Li,et al.  Toward insights on antimicrobial selectivity of host defense peptides via machine learning model interpretation. , 2021, Genomics.

[10]  Zahed Siddique,et al.  Effect of Data Scaling Methods on Machine Learning Algorithms and Model Performance , 2021, Technologies.

[11]  Finbarr Murphy,et al.  A Machine Learning Tool to Predict the Antibacterial Capacity of Nanoparticles , 2021, Nanomaterials.

[12]  Aydin Akan,et al.  Epileptic EEG Classification by Using Time-Frequency Images for Deep Learning , 2021, Int. J. Neural Syst..

[13]  Mehmet Akif Ozdemir,et al.  Classification of COVID-19 electrocardiograms by using hexaxial feature mapping and deep learning , 2021, BMC Medical Informatics and Decision Making.

[14]  Xingyong Yang,et al.  Plant antimicrobial peptides: structures, functions, and applications , 2021, Botanical studies.

[15]  Jiangning Song,et al.  Comprehensive assessment of machine learning-based methods for predicting antimicrobial peptides , 2021, Briefings Bioinform..

[16]  M. Dawson,et al.  Influence of Lipophilicity on the Antibacterial Activity of Polymyxin Derivatives and on Their Ability to Act as Potentiators of Rifampicin. , 2021, ACS infectious diseases.

[17]  Obed Ramírez-Sánchez,et al.  Machine learning-guided discovery and design of non-hemolytic peptides , 2020, Scientific Reports.

[18]  Irini Furxhi,et al.  Predicting In Vitro Neurotoxicity Induced by Nanoparticles Using Machine Learning , 2020, International journal of molecular sciences.

[19]  Geoffrey I. Webb.  Naïve Bayes , 2020, Encyclopedia of Machine Learning.

[20]  K. Kavousi,et al.  BIPEP: Sequence-based Prediction of Biofilm Inhibitory Peptides Using a Combination of NMR and Physicochemical Descriptors , 2020, ACS omega.

[21]  Hui Ding,et al.  Escherichia Coli DNA N-4-Methycytosine Site Prediction Accuracy Improved by Light Gradient Boosting Machine Feature Selection Technology , 2020, IEEE Access.

[22]  D. George,et al.  Logistic Regression , 2019, IBM SPSS Statistics 26 Step by Step.

[23]  Lydia P. Howell,et al.  Artificial Intelligence and Machine Learning in Pathology: The Present Landscape of Supervised Methods , 2019, Academic pathology.

[24]  R. Darouiche,et al.  Does antimicrobial coating and impregnation of urinary catheters prevent catheter-associated urinary tract infection? A review of clinical and preclinical studies , 2019, Expert review of medical devices.

[25]  J. Lu,et al.  Hydrophobic Control of the Bioactivity and Cytotoxicity of de Novo Designed Antimicrobial Peptides. , 2019, ACS applied materials & interfaces.

[26]  Sadaf Gull,et al.  AMAP: Hierarchical multi-label prediction of biologically active and antimicrobial peptides , 2019, Comput. Biol. Medicine.

[27]  Siheng Li,et al.  Antimicrobial strategies for urinary catheters. , 2018, Journal of biomedical materials research. Part A.

[28]  R. Hancock,et al.  Design and Assessment of Anti-Biofilm Peptides: Steps Toward Clinical Application , 2018, Journal of Innate Immunity.

[29]  Andrei Gabrielian,et al.  Predictive Model of Linear Antimicrobial Peptides Active against Gram-Negative Bacteria , 2018, J. Chem. Inf. Model..

[30]  Alexander Brenning,et al.  Performance evaluation and hyperparameter tuning of statistical and machine-learning models using spatial data , 2018, Ecological Modelling.

[31]  Simon Fong,et al.  AmPEP: Sequence-based prediction of antimicrobial peptides using distribution patterns of amino acid properties and random forest , 2018, Scientific Reports.

[32]  Andy Liaw,et al.  Extreme Gradient Boosting as a Method for Quantitative Structure-Activity Relationships , 2016, J. Chem. Inf. Model..

[33]  Randal S. Olson,et al.  Automating Biomedical Data Science Through Tree-Based Pipeline Optimization , 2016, EvoApplications.

[34]  Ping Zhong,et al.  Active Learning With Gaussian Process Classifier for Hyperspectral Image Classification , 2015, IEEE Transactions on Geoscience and Remote Sensing.

[35]  Shiqing Zhang,et al.  Facial Expression Recognition via Deep Learning , 2015 .

[36]  T. Sondergaard,et al.  Rational Design of Alpha‐Helical Antimicrobial Peptides: Do's and Don'ts , 2015, Chembiochem : a European journal of chemical biology.

[37]  A. Daley,et al.  Reducing hospital-acquired infections and improving the rational use of antibiotics in a developing country: an effectiveness study , 2014, Archives of Disease in Childhood.

[38]  L. M. Carrasco,et al.  Novel Formulations for Antimicrobial Peptides , 2014, International journal of molecular sciences.

[39]  D. Lebeaux,et al.  Biofilm-Related Infections: Bridging the Gap between Clinical Management and Fundamental Aspects of Recalcitrance toward Antibiotics , 2014, Microbiology and Molecular Reviews.

[40]  William Stafford Noble,et al.  Support vector machine , 2013 .

[41]  Ying Cao,et al.  Advance and Prospects of AdaBoost Algorithm , 2013, Acta Automatica Sinica.

[42]  Shreyas Karnik,et al.  ClassAMP: A Prediction Tool for Classification of Antimicrobial Peptides , 2012, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[43]  Manoj Kumar,et al.  AVPpred: collection and prediction of highly effective antiviral peptides , 2012, Nucleic Acids Res..

[44]  Marc Torrent,et al.  Connecting Peptide Physicochemical and Antimicrobial Properties by a Rational Prediction Model , 2011, PloS one.

[45]  S. Gorman,et al.  The use of lytic bacteriophages in the prevention and eradication of biofilms of Proteus mirabilis and Escherichia coli. , 2010, FEMS immunology and medical microbiology.

[46]  Thomas Lengauer,et al.  Permutation importance: a corrected feature importance measure , 2010, Bioinform..

[47]  Ayyalusamy Ramamoorthy,et al.  Multifunctional host defense peptides: functional and mechanistic insights from NMR structures of potent antimicrobial peptides , 2009, The FEBS journal.

[48]  M. Fischbach,et al.  Antibiotics for Emerging Pathogens , 2009, Science.

[49]  W. Florio,et al.  Evaluation of the inhibitory effects of human serum components on bactericidal activity of human beta defensin 3 , 2008, Peptides.

[50]  I. Mellman,et al.  Plasmacytoid dendritic cells sense self-DNA coupled with antimicrobial peptide , 2007, Nature.

[51]  Dianhong Wang,et al.  Survey of Improving K-Nearest-Neighbor for Classification , 2007, Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007).

[52]  D. Wishart,et al.  DrugBank: a comprehensive resource for in silico drug discovery and exploration , 2005, Nucleic Acids Res..

[53]  Yang Liu,et al.  An introduction to decision tree modeling , 2004 .

[54]  Michael R Hamblin,et al.  Photodynamic therapy: a new antimicrobial approach to infectious disease? , 2004, Photochemical & photobiological sciences : Official journal of the European Photochemistry Association and the European Society for Photobiology.

[55]  D. Pittet,et al.  Prevention of Bloodstream Infections With Central Venous Catheters Treated With Anti-Infective Agents Depends on Catheter Type and Insertion Time: Evidence From a Meta-Analysis , 2002, Infection Control & Hospital Epidemiology.

[56]  J. Andrews,et al.  Determination of minimum inhibitory concentrations. , 2001, The Journal of antimicrobial chemotherapy.

[57]  K. Lewis,et al.  Riddle of Biofilm Resistance , 2001, Antimicrobial Agents and Chemotherapy.

[58]  M. Botelho.  Fractional inhibitory concentration index of combinations of antibacterial agents against cariogenic organisms. , 2000, Journal of dentistry.

[59]  Donna L. Hudson,et al.  Neural networks and artificial intelligence for biomedical engineering , 1999 .

[60]  J. Costerton,et al.  Bacterial biofilms: a common cause of persistent infections. , 1999, Science.

[61]  Robert P. W. Duin,et al.  Bagging for linear classifiers , 1998, Pattern Recognit..

[62]  D. Nicolau,et al.  Synergistic Activity of Trovafloxacin and Ceftriaxone or Vancomycin against Streptococcus pneumoniae with Various Penicillin Susceptibilities , 1998, Antimicrobial Agents and Chemotherapy.

[63]  Andrew P. Bradley,et al.  The use of the area under the ROC curve in the evaluation of machine learning algorithms , 1997, Pattern Recognit..

[64]  J. Ross Quinlan,et al.  Learning decision tree classifiers , 1996, CSUR.

[65]  J. H. Steiger.  Tests for comparing elements of a correlation matrix. , 1980 .

[66]  M. Berenbaum,et al.  A method for testing for synergy with any number of agents. , 1978, The Journal of infectious diseases.

[67]  G. Hitchings,et al.  Antagonists of nucleic acid derivatives. VIII. Synergism in combinations of biochemically related antimetabolites. , 1954, The Journal of biological chemistry.

[68]  Kenji Hatano,et al.  A Resampling Method for Imbalanced Datasets Considering Noise and Overlap , 2020, KES.

[69]  Kartik Krishna Bhardwaj,et al.  Artificial Intelligence Based Diagnostics, Therapeutics and Applications in Biomedical Engineering and Bioinformatics , 2019, Internet of Things in Biomedical Engineering.

[70]  R. Hancock,et al.  Host defense (antimicrobial) peptides , 2018 .

[71]  A. Hassanien,et al.  Linear discriminant analysis: A detailed tutorial , 2017, AI Commun..

[72]  Robert E W Hancock,et al.  Antimicrobial Peptides: An Introduction. , 2017, Methods in molecular biology.

[73]  Pavel Pudil,et al.  Introduction to Statistical Pattern Recognition , 2006 .