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Muramidase

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Quantitative design rules for protein-resistant surface coatings using machine learning.

Scientific reports
Preventing biological contamination (biofouling) is key to successful development of novel surface and nanoparticle-based technologies in the manufacturing industry and biomedicine. Protein adsorption is a crucial mediator of the interactions at the ...

Large-scale network analysis reveals the sequence space architecture of antibody repertoires.

Nature communications
The architecture of mouse and human antibody repertoires is defined by the sequence similarity networks of the clones that compose them. The major principles that define the architecture of antibody repertoires have remained largely unknown. Here, we...

Inexpensive robotic system for standard and fluorescent imaging of protein crystals.

Acta crystallographica. Section F, Structural biology communications
Protein-crystallization imaging and classification is a labor-intensive process typically performed either by humans or by instruments that currently cost well over $100 000. This cost puts the use of crystallization-trial imaging outside the reach o...

Design a fluorometric aptasensor based on CoOOH nanosheets and carbon dots for simultaneous detection of lysozyme and adenosine triphosphate.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Simultaneous detection of biomarkers and biomolecules with great analytical performance still is challenging. A simple fluorometric dual-functional aptasensor was designed to detect Lysozyme (LYS) and adenosine triphosphate (ATP) as models of a prote...

An apta-aggregation based machine learning assay for rapid quantification of lysozyme through texture parameters.

PloS one
A novel assay technique that involves quantification of lysozyme (Lys) through machine learning is put forward here. This article reports the tendency of the well- documented Ellington group anti-Lys aptamer, to produce aggregates when exposed to Lys...

FID-Net: A versatile deep neural network architecture for NMR spectral reconstruction and virtual decoupling.

Journal of biomolecular NMR
In recent years, the transformative potential of deep neural networks (DNNs) for analysing and interpreting NMR data has clearly been recognised. However, most applications of DNNs in NMR to date either struggle to outperform existing methodologies o...

Machine Learning Assisted Simultaneous Structural Profiling of Differently Charged Proteins in a Porin A (MspA) Electroosmotic Trap.

Journal of the American Chemical Society
The nanopore is emerging as a means of single-molecule protein sensing. However, proteins demonstrate different charge properties, which complicates the design of a sensor that can achieve simultaneous sensing of differently charged proteins. In this...

Machine Learning for Quantitative Prediction of Protein Adsorption on Well-Defined Polymer Brush Surfaces with Diverse Chemical Properties.

Langmuir : the ACS journal of surfaces and colloids
Polymer informatics has attracted increasing attention because machine learning can establish quantitative structure-property relationships in polymer materials. Understanding and controlling protein adsorption on polymer surfaces are crucial for var...