AIMC Topic: Pore Forming Cytotoxic Proteins

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Machine learning-guided discovery and design of non-hemolytic peptides.

Scientific reports Oct 6, 2020
Reducing hurdles to clinical trials without compromising the therapeutic promises of peptide candidates becomes an essential step in peptide-based drug design. Machine-learning models are cost-effective and time-saving strategies used to predict biol...
Machine Learning Drug Design Amino Acid Sequence Cost-Benefit Analysis Hemolysis Pore Forming Cytotoxic Proteins
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IAMPE: NMR-Assisted Computational Prediction of Antimicrobial Peptides.

Journal of chemical information and modeling Sep 30, 2020
Antimicrobial peptides (AMPs) are at the focus of attention due to their therapeutic importance and developing computational tools for the identification of efficient antibiotics from the primary structure. Here, we utilized the CNMR spectral of amin...
Algorithms Computational Biology Support Vector Machine Bayes Theorem Amino Acids Pore Forming Cytotoxic Proteins
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Detecting antimicrobial peptides by exploring the mutual information of their sequences.

Journal of biomolecular structure & dynamics Dec 18, 2019
The rise of antibiotic resistance in pathogenic bacteria is a growing concern for every part of the world. The present study shows the prediction efficiency of mutual information for the classification of antimicrobial peptides. The proven role of an...
Machine Learning ROC Curve Bacteria Antimicrobial Cationic Peptides Pore Forming Cytotoxic Proteins
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Classification of Antibacterial Peptides Using Long Short-Term Memory Recurrent Neural Networks.

IEEE/ACM transactions on computational biology and bioinformatics Mar 7, 2019
Antimicrobial peptides are short amino acid sequences that may be antibacterial, antifungal, and antiviral. Most machine learning methodologies applied to identifying antibacterial peptides have developed feature vectors of identical lengths for each...
Neural Networks, Computer Algorithms Anti-Bacterial Agents Computational Biology Databases, Protein Sequence Analysis, Protein Pore Forming Cytotoxic Proteins
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Comprehensive assessment of machine learning-based methods for predicting antimicrobial peptides.

Briefings in bioinformatics Sep 2, 2021
Antimicrobial peptides (AMPs) are a unique and diverse group of molecules that play a crucial role in a myriad of biological processes and cellular functions. AMP-related studies have become increasingly popular in recent years due to antimicrobial r...
Machine Learning Algorithms Databases, Factual Biofilms Bacteria Computational Biology Support Vector Machine Fungi Viruses Pore Forming Cytotoxic Proteins
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