AIMC Topic: Cross-Linking Reagents

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Modelling protein complexes with crosslinking mass spectrometry and deep learning.

Nature communications Sep 9, 2024
Scarcity of structural and evolutionary information on protein complexes poses a challenge to deep learning-based structure modelling. We integrate experimental distance restraints obtained by crosslinking mass spectrometry (MS) into AlphaFold-Multim...
Deep Learning Models, Molecular Iron Bacillus subtilis Mass Spectrometry Protein Conformation Cross-Linking Reagents Bacterial Proteins
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Effects of various cross-linked collagen scaffolds on wound healing in rats model by deep-learning CNN.

Computer methods in biomechanics and biomedical engineering Feb 15, 2024
Scar tissue is connective tissue formed on the wound during the wound-healing process. The most significant distinction between scar tissue and normal tissue is the appearance of covalent cross-linking and the amount of collagen fibers in the tissue....
Rats, Sprague-Dawley Wound Healing Rats Tissue Scaffolds Neural Networks, Computer Cross-Linking Reagents Female Disease Models, Animal Animals Collagen Deep Learning
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A deep learning model for predicting optimal distance range in crosslinking mass spectrometry data.

Proteomics May 3, 2023
Macromolecular assemblies play an important role in all cellular processes. While there has recently been significant progress in protein structure prediction based on deep learning, large protein complexes cannot be predicted with these approaches. ...
Cross-Linking Reagents Models, Molecular Deep Learning Mass Spectrometry Proteins
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Generation of Interconnected Neural Clusters in Multiscale Scaffolds from Human-Induced Pluripotent Stem Cells.

ACS applied materials & interfaces Nov 17, 2021
The development of in vitro neural networks depends to a large extent on the scaffold properties, including the scaffold stiffness, porosity, and dimensionality. Herein, we developed a method to generate interconnected neural clusters in a multiscale...
Cross-Linking Reagents Induced Pluripotent Stem Cells Neural Stem Cells Nanofibers Particle Size Gels Humans Cell Differentiation Surface Properties Neural Networks, Computer
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Retention time prediction using neural networks increases identifications in crosslinking mass spectrometry.

Nature communications May 28, 2021
Crosslinking mass spectrometry has developed into a robust technique that is increasingly used to investigate the interactomes of organelles and cells. However, the incomplete and noisy information in the mass spectra of crosslinked peptides limits t...
Escherichia coli Proteins Time Factors Chromatography, Reverse-Phase Cross-Linking Reagents Proteomics Chromatography, High Pressure Liquid Protein Interaction Mapping Neural Networks, Computer Tandem Mass Spectrometry Multiprotein Complexes Escherichia coli Peptides
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Predicting degradation rate of genipin cross-linked gelatin scaffolds with machine learning.

Materials science & engineering. C, Materials for biological applications Oct 24, 2019
Genipin can improve weak mechanical properties and control high degradation rate of gelatin, as a cross-linker of gelatin which is widely used in tissue engineering. In this study, genipin cross-linked gelatin biodegradable porous scaffolds with diff...
Gelatin Regression Analysis Cross-Linking Reagents Machine Learning Iridoids Neural Networks, Computer Materials Testing Models, Theoretical Microscopy, Electron, Scanning Tissue Scaffolds
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