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Cross-Linking Reagents

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Predicting degradation rate of genipin cross-linked gelatin scaffolds with machine learning.

Materials science & engineering. C, Materials for biological applications
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...

Retention time prediction using neural networks increases identifications in crosslinking mass spectrometry.

Nature communications
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...

Generation of Interconnected Neural Clusters in Multiscale Scaffolds from Human-Induced Pluripotent Stem Cells.

ACS applied materials & interfaces
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...

A deep learning model for predicting optimal distance range in crosslinking mass spectrometry data.

Proteomics
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. ...

Modelling protein complexes with crosslinking mass spectrometry and deep learning.

Nature communications
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...