AIMC Topic: Plasmids

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Quantifying complexity in DNA structures with high resolution Atomic Force Microscopy.

Nature communications Jul 1, 2025
DNA topology is essential for regulating cellular processes and maintaining genome stability, yet it is challenging to quantify due to the size and complexity of topologically constrained DNA molecules. By combining high-resolution Atomic Force Micro...
Animals Escherichia coli Nucleic Acid Conformation Xenopus laevis DNA Replication DNA Microscopy, Atomic Force Plasmids
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Surface enhanced Raman spectroscopy and machine learning for identification of beta-lactam antibiotics resistance gene fragment in bacterial plasmid.

Analytica chimica acta Aug 16, 2024
BACKGROUND: Antibiotic resistance stands as a critical medical concern, notably evident in commonly prescribed beta-lactam antibiotics. The imperative need for expeditious and precise early detection methods underscores their role in facilitating tim...
Machine Learning Anti-Bacterial Agents Spectrum Analysis, Raman Escherichia coli beta Lactam Antibiotics Plasmids Surface Properties beta-Lactam Resistance beta-Lactams
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Identification of key drivers of antimicrobial resistance in using machine learning.

Canadian journal of microbiology Jul 30, 2024
With antimicrobial resistance (AMR) rapidly evolving in pathogens, quick and accurate identification of genetic determinants of phenotypic resistance is essential for improving surveillance, stewardship, and clinical mitigation. Machine learning (ML)...
Anti-Bacterial Agents Drug Resistance, Bacterial Microbial Sensitivity Tests Humans Machine Learning Enterococcus faecium Plasmids Bacterial Proteins Gram-Positive Bacterial Infections Enterococcus faecalis Genome, Bacterial
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Synergistic Polymer Blending Informs Efficient Terpolymer Design and Machine Learning Discerns Performance Trends for pDNA Delivery.

Bioconjugate chemistry Jun 26, 2024
Cationic polymers offer an alternative to viral vectors in nucleic acid delivery. However, the development of polymer vehicles capable of high transfection efficiency and minimal toxicity has remained elusive, and continued exploration of the vast de...
Gene Transfer Techniques Transfection HEK293 Cells Plasmids DNA Polymers Humans Machine Learning Cell Survival
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Data-driven learning of structure augments quantitative prediction of biological responses.

PLoS computational biology Jun 3, 2024
Multi-factor screenings are commonly used in diverse applications in medicine and bioengineering, including optimizing combination drug treatments and microbiome engineering. Despite the advances in high-throughput technologies, large-scale experimen...
Bacterial Infections Models, Biological Plasmids Escherichia coli Regression Analysis Bioengineering Humans Machine Learning Drug Resistance, Bacterial Computer Simulation Bacteria
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Neural-Like P Systems With Plasmids and Multiple Channels.

IEEE transactions on nanobioscience Mar 31, 2023
Neural-like P systems with plasmids (NP P systems, in short) are a kind of distributed and parallel computing systems inspired by the activity that bacteria process DNA such as plasmids. An important biological fact is that one or more pili have exis...
Bacteria Neurons Plasmids Neural Networks, Computer
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Aglow: A Fluorescence Assay and Machine Learning Model to Identify Inhibitors of Intracellular Infection.

ACS infectious diseases Jun 24, 2022
is a genus of Gram-negative bacteria that has for centuries caused large-scale morbidity and mortality. In recent years, the resurgence of rickettsial diseases as a major cause of pyrexias of unknown origin, bioterrorism concerns, vector movement, a...
Bayes Theorem Machine Learning Plasmids
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Computing within bacteria: Programming of bacterial behavior by means of a plasmid encoding a perceptron neural network.

Bio Systems Jan 19, 2022
In nature, bacteria exhibit a limited repertoire of behaviors in response to environmental changes. Synthetic biology has now opened up the possibility of programming cells or unicellular organisms in order to enable them to perform certain tasks, wh...
Humans Neural Networks, Computer Bacteria Synthetic Biology Plasmids Biotechnology
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Enhancement of protein thermostability by three consecutive mutations using loop-walking method and machine learning.

Scientific reports Jun 4, 2021
We developed a method to improve protein thermostability, "loop-walking method". Three consecutive positions in 12 loops of Burkholderia cepacia lipase were subjected to random mutagenesis to make 12 libraries. Screening allowed us to identify L7 as ...
Protein Engineering Burkholderia cepacia Mutagenesis Escherichia coli Hydrolases Molecular Conformation Proteins Plasmids Mutagenesis, Site-Directed Hot Temperature Kinetics Mutation Lipase Machine Learning Molecular Dynamics Simulation Polymerase Chain Reaction Computational Biology Enzyme Stability
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Enhancing CRISPR-Cas9 gRNA efficiency prediction by data integration and deep learning.

Nature communications May 28, 2021
The design of CRISPR gRNAs requires accurate on-target efficiency predictions, which demand high-quality gRNA activity data and efficient modeling. To advance, we here report on the generation of on-target gRNA activity data for 10,592 SpCas9 gRNAs. ...
Deep Learning Humans Lentivirus HEK293 Cells Software Computational Biology Genetic Vectors Plasmids CRISPR-Cas Systems RNA, Guide, CRISPR-Cas Systems Gene Editing
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