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Bacterial Proteins

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Predicting bacterial transcription factor binding sites through machine learning and structural characterization based on DNA duplex stability.

Briefings in bioinformatics
Transcriptional factors (TFs) in bacteria play a crucial role in gene regulation by binding to specific DNA sequences, thereby assisting in the activation or repression of genes. Despite their central role, deciphering shape recognition of bacterial ...

Deciphering Cas9 specificity: Role of domain dynamics and RNA:DNA hybrid interactions revealed through machine learning and accelerated molecular simulations.

International journal of biological macromolecules
CRISPR/Cas9 technology is widely used for gene editing, but off-targeting still remains a major concern in therapeutic applications. Although Cas9 variants with better mismatch discrimination have been developed, they have significantly lower rates o...

A novel machine-learning aided platform for rapid detection of urine ESBLs and carbapenemases: URECA-LAMP.

Journal of clinical microbiology
Pathogenic gram-negative bacteria frequently carry genes encoding extended-spectrum beta-lactamases (ESBL) and/or carbapenemases. Of great concern are carbapenem resistant , , and . Despite the need for rapid AMR diagnostics globally, current molecu...

AI-based automated construction of high-precision Geobacillus thermoglucosidasius enzyme constraint model.

Metabolic engineering
Geobacillus thermoglucosidasius NCIMB 11955 possesses advantages, such as high-temperature tolerance, rapid growth rate, and low contamination risk. Additionally, it features efficient gene editing tools, making it one of the most promising next-gene...

[AcidBasePred: a protein acid-base tolerance prediction platform based on deep learning].

Sheng wu gong cheng xue bao = Chinese journal of biotechnology
The structures and activities of enzymes are influenced by pH of the environment. Understanding and distinguishing the adaptation mechanisms of enzymes to extreme pH values is of great significance for elucidating the molecular mechanisms and promoti...

Analysis of high-molecular-weight proteins using MALDI-TOF MS and machine learning for the differentiation of clinically relevant Clostridioides difficile ribotypes.

European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology
PURPOSE: Clostridioides difficile is the main cause of antibiotic related diarrhea and some ribotypes (RT), such as RT027, RT181 or RT078, are considered high risk clones. A fast and reliable approach for C. difficile ribotyping is needed for a corre...

Lipid discovery enabled by sequence statistics and machine learning.

eLife
Bacterial membranes are complex and dynamic, arising from an array of evolutionary pressures. One enzyme that alters membrane compositions through covalent lipid modification is MprF. We recently identified that MprF synthesizes lysyl-phosphatidylgl...

Extending visual range of bacteria with upconversion nanoparticles and constructing NIR-responsive bio-microrobots.

Journal of colloid and interface science
The motility of bacteria is crucial for navigating competitive environments and is closely linked to physiological activities essential for their survival, such as biofilm development. Precise regulation of bacterial motility enhances our understandi...

Machine Learning-Assisted, Dual-Channel CRISPR/Cas12a Biosensor-In-Microdroplet for Amplification-Free Nucleic Acid Detection for Food Authenticity Testing.

ACS nano
The development of novel detection technology for meat species authenticity is imperative. Here, we developed a machine learning-supported, dual-channel biosensor-in-microdroplet platform for meat species authenticity detection named CC-drop (RISPR/C...

Predicting photosynthetic bacteria-derived protein synthesis from wastewater using machine learning and causal inference.

Bioresource technology
Causal inference-assisted machine learning was used to predict photosynthetic bacterial (PSB) protein production capacity and identify key factors. The extreme gradient boosting algorithm effectively predicted protein content, while the gradient boos...