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Guangshun Wang
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Changes in Carbapenemase-Producing Carbapenem-Resistant Enterobacterales. 2019 to 2023
10.7326/annals-25-02404 · 2025
Antibacterial peptides: basic facts and emerging concepts
10.1046/j.1365-2796.2003.01228.x · 2003
Antimicrobial peptides of multicellular organisms
10.1038/415389a · 2002
Antibiofilm activity of host defence peptides: complexity provides opportunities
10.1038/s41579-021-00585-w · 2021
Immune modulation by multifaceted cationic host defense (antimicrobial) peptides
10.1038/nchembio.1393 · 2013
Two distinct amphipathic peptide antibiotics with systemic efficacy
10.1073/pnas.2005540117 · 2020
Machine Learning Prediction of Antimicrobial Peptides
10.1007/978-1-0716-1855-4_1 · 2022
AI-Driven Antimicrobial Peptide Discovery: Mining and Generation
10.1021/acs.accounts.0c00594 · 2025
Research Advance in the Development of Antimicrobial Peptides Using Deep Learning
10.1002/jcc.70203 · 2025
Harnessing AI for enhanced screening of antimicrobial bioactive compounds in food safety and preservation
10.1016/j.tifs.2025.104887 · 2025
Harnessing AI for Antimicrobial Peptide Innovation against Multidrug Resistance
10.1021/jacsau.5c01520 · 2026
Unresolved referenced work
Kept as external metadata until matched
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10.1016/j.cbpa.2026.102685 · 2026
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10.1093/nar/gkh025 · 2004
APD3: the antimicrobial peptide database as a tool for research and education
10.1093/nar/gkv1278 · 2016
APD6: the antimicrobial peptide database is expanded to promote research and development by deploying an unprecedented information pipeline
10.1093/nar/gkaf860 · 2026
Analysis and prediction of antibacterial peptides
10.1186/1471-2105-8-263 · 2007
Use of artificial intelligence in the design of small peptide antibiotics effective against a broad spectrum of highly antibiotic-resistant superbugs
10.1021/cb800240j · 2009
CS-AMPPred: an updated SVM model for antimicrobial activity prediction in cysteine-stabilized peptides
10.1371/journal.pone.0051444 · 2012
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10.1093/nar/gkh032 · 2004
CAMP: a useful resource for research on antimicrobial peptides
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LAMP: A Database Linking Antimicrobial Peptides
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DBAASP: database of antimicrobial activity and structure of peptides
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DRAMP: a comprehensive data repository of antimicrobial peptides
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dbAMP: an integrated resource for exploring antimicrobial peptides with functional activities and physicochemical properties on transcriptome and proteome data
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UniProt: the Universal Protein Knowledgebase in 2025
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The antimicrobial peptide database provides a platform for decoding the design principles of naturally occurring antimicrobial peptides
10.1002/pro.3702 · 2020
APD2: the updated antimicrobial peptide database and its application in peptide design
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The antimicrobial peptide database is 20 years old: Recent developments and future directions
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Associating Biological Activity and Predicted Structure of Antimicrobial Peptides from Amphibians and Insects
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Mining Amphibian and Insect Transcriptomes for Antimicrobial Peptide Sequences with rAMPage
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Identification of antimicrobial peptides from the human gut microbiome using deep learning
10.1038/s41587-022-01226-0 · 2022
Tutorial: guidelines for the use of machine learning methods to mine genomes and proteomes for antibiotic discovery
10.1038/s41596-025-01144-w · 2025
Discovery of antimicrobial peptides in the global microbiome with machine learning
10.1016/j.cell.2024.05.013 · 2024
One-Step Design of Potent and Nonhemolytic Antimicrobial Peptides by Using a Database-Guided, Nonmachine Learning Approach
10.1021/acsinfecdis.5c01022 · 2026
Unifying the classification of antimicrobial peptides in the antimicrobial peptide database
10.1016/bs.mie.2021.09.006 · 2022
The expanding scope of antimicrobial peptide structures and their modes of action
10.1016/j.tibtech.2011.05.001 · 2011
BAGEL4: a user-friendly web server to thoroughly mine RiPPs and bacteriocins
10.1093/nar/gky383 · 2018
Discovery and classification of new reptile cathelicidins by genome mining: study of their structure and genomic organization in Testudines and Squamata
10.1016/j.dci.2026.105560 · 2026
Discovery and classification of new reptile cathelicidins by genome mining: study of their structure and genomic organization in Testudines and Squamata
10.1016/j.dci.2026.105560 · doi-reference
BAGEL4: a user-friendly web server to thoroughly mine RiPPs and bacteriocins
10.1093/nar/gky383 · doi-reference
The expanding scope of antimicrobial peptide structures and their modes of action
10.1016/j.tibtech.2011.05.001 · doi-reference
Unifying the classification of antimicrobial peptides in the antimicrobial peptide database
10.1016/bs.mie.2021.09.006 · doi-reference
One-Step Design of Potent and Nonhemolytic Antimicrobial Peptides by Using a Database-Guided, Nonmachine Learning Approach
10.1021/acsinfecdis.5c01022 · doi-reference
Discovery of antimicrobial peptides in the global microbiome with machine learning
10.1016/j.cell.2024.05.013 · doi-reference
Tutorial: guidelines for the use of machine learning methods to mine genomes and proteomes for antibiotic discovery
10.1038/s41596-025-01144-w · doi-reference
Identification of antimicrobial peptides from the human gut microbiome using deep learning
10.1038/s41587-022-01226-0 · doi-reference
10.1101/2024.12.17.628923
10.1101/2024.12.17.628923 · doi-reference
Mining Amphibian and Insect Transcriptomes for Antimicrobial Peptide Sequences with rAMPage
10.3390/antibiotics11070952 · doi-reference
Associating Biological Activity and Predicted Structure of Antimicrobial Peptides from Amphibians and Insects
10.3390/antibiotics11121710 · doi-reference
The antimicrobial peptide database is 20 years old: Recent developments and future directions
10.1002/pro.4778 · doi-reference
APD2: the updated antimicrobial peptide database and its application in peptide design
10.1093/nar/gkn823 · doi-reference
The antimicrobial peptide database provides a platform for decoding the design principles of naturally occurring antimicrobial peptides
10.1002/pro.3702 · doi-reference
UniProt: the Universal Protein Knowledgebase in 2025
10.1093/nar/gkae1010 · doi-reference
dbAMP: an integrated resource for exploring antimicrobial peptides with functional activities and physicochemical properties on transcriptome and proteome data
10.1093/nar/gky1030 · doi-reference
DRAMP: a comprehensive data repository of antimicrobial peptides
10.1038/srep24482 · doi-reference
DBAASP: database of antimicrobial activity and structure of peptides
10.1111/1574-6968.12489 · doi-reference
LAMP: A Database Linking Antimicrobial Peptides
10.1371/journal.pone.0066557 · doi-reference
CAMP: a useful resource for research on antimicrobial peptides
10.1093/nar/gkp1021 · doi-reference
ANTIMIC: a database of antimicrobial sequences
10.1093/nar/gkh032 · doi-reference
CS-AMPPred: an updated SVM model for antimicrobial activity prediction in cysteine-stabilized peptides
10.1371/journal.pone.0051444 · doi-reference
Use of artificial intelligence in the design of small peptide antibiotics effective against a broad spectrum of highly antibiotic-resistant superbugs
10.1021/cb800240j · doi-reference
Analysis and prediction of antibacterial peptides
10.1186/1471-2105-8-263 · doi-reference
APD6: the antimicrobial peptide database is expanded to promote research and development by deploying an unprecedented information pipeline
10.1093/nar/gkaf860 · doi-reference
APD3: the antimicrobial peptide database as a tool for research and education
10.1093/nar/gkv1278 · doi-reference
APD: the Antimicrobial Peptide Database
10.1093/nar/gkh025 · doi-reference
From generation to validation: Deep generative models for antimicrobial peptide discovery
10.1016/j.cbpa.2026.102685 · doi-reference
Harnessing AI for Antimicrobial Peptide Innovation against Multidrug Resistance
10.1021/jacsau.5c01520 · doi-reference
Harnessing AI for enhanced screening of antimicrobial bioactive compounds in food safety and preservation
10.1016/j.tifs.2025.104887 · doi-reference
Research Advance in the Development of Antimicrobial Peptides Using Deep Learning
10.1002/jcc.70203 · doi-reference
AI-Driven Antimicrobial Peptide Discovery: Mining and Generation
10.1021/acs.accounts.0c00594 · doi-reference
Machine Learning Prediction of Antimicrobial Peptides
10.1007/978-1-0716-1855-4_1 · doi-reference
Two distinct amphipathic peptide antibiotics with systemic efficacy
10.1073/pnas.2005540117 · doi-reference
Immune modulation by multifaceted cationic host defense (antimicrobial) peptides
10.1038/nchembio.1393 · doi-reference
Antibiofilm activity of host defence peptides: complexity provides opportunities
10.1038/s41579-021-00585-w · doi-reference
Antimicrobial peptides of multicellular organisms
10.1038/415389a · doi-reference
Antibacterial peptides: basic facts and emerging concepts
10.1046/j.1365-2796.2003.01228.x · doi-reference
Changes in Carbapenemase-Producing Carbapenem-Resistant Enterobacterales. 2019 to 2023
10.7326/annals-25-02404 · doi-reference