AIMC Topic: Nucleic Acids

Clear Filters Showing 31 to 40 of 45 articles

Representability of algebraic topology for biomolecules in machine learning based scoring and virtual screening.

PLoS computational biology
This work introduces a number of algebraic topology approaches, including multi-component persistent homology, multi-level persistent homology, and electrostatic persistence for the representation, characterization, and description of small molecules...

Evaluation of error detection and treatment recommendations in nucleic acid test reports using ChatGPT models.

Clinical chemistry and laboratory medicine
OBJECTIVES: Accurate medical laboratory reports are essential for delivering high-quality healthcare. Recently, advanced artificial intelligence models, such as those in the ChatGPT series, have shown considerable promise in this domain. This study a...

DEMO-EMol: modeling protein-nucleic acid complex structures from cryo-EM maps by coupling chain assembly with map segmentation.

Nucleic acids research
Atomic structure modeling is a crucial step in determining the structures of protein complexes using cryo-electron microscopy (cryo-EM). This work introduces DEMO-EMol, an improved server that integrates deep learning-based map segmentation and chain...

Biomolecular Actuators for Soft Robots.

Chemical reviews
Biomolecules present promising stimuli-responsive mechanisms to revolutionize soft actuators. Proteins, peptides, and nucleic acids foster specific intermolecular interactions, and their boundless sequence design spaces encode precise actuation capab...

Machine-Learning Framework to Predict the Performance of Lipid Nanoparticles for Nucleic Acid Delivery.

ACS applied bio materials
Lipid nanoparticles (LNPs) are highly effective carriers for gene therapies, including mRNA and siRNA delivery, due to their ability to transport nucleic acids across biological membranes, low cytotoxicity, improved pharmacokinetics, and scalability....

[Intelligent design of nucleic acid elements in biomanufacturing].

Sheng wu gong cheng xue bao = Chinese journal of biotechnology
Nucleic acid elements are essential functional sequences that play critical roles in regulating gene expression, optimizing pathways, and enabling gene editing to enhance the production of target products in biomanufacturing. Therefore, the design an...

NucleoFind: a deep-learning network for interpreting nucleic acid electron density.

Nucleic acids research
Nucleic acid electron density interpretation after phasing by molecular replacement or other methods remains a difficult problem for computer programs to deal with. Programs tend to rely on time-consuming and computationally exhaustive searches to re...

RmsdXNA: RMSD prediction of nucleic acid-ligand docking poses using machine-learning method.

Briefings in bioinformatics
Small molecule drugs can be used to target nucleic acids (NA) to regulate biological processes. Computational modeling methods, such as molecular docking or scoring functions, are commonly employed to facilitate drug design. However, the accuracy of ...

EquiPNAS: improved protein-nucleic acid binding site prediction using protein-language-model-informed equivariant deep graph neural networks.

Nucleic acids research
Protein language models (pLMs) trained on a large corpus of protein sequences have shown unprecedented scalability and broad generalizability in a wide range of predictive modeling tasks, but their power has not yet been harnessed for predicting prot...