AIMC Topic: Electrophoresis

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Experimentally profiling dielectric properties of Escherichia coli and Staphylococcus aureus by movement velocity and force.

Scientific reports
The gradual research in integrating artificial intelligence in the Dielectrophoresis system is rapid since the evolution of AI in every aspect of technology since the early 2020s. The benefits of AI integration into DEP systems include improving posi...

Development and validation of a deep learning-based protein electrophoresis classification algorithm.

PloS one
BACKGROUND: Protein electrophoresis (PEP) is an important tool in supporting the analytical characterization of protein status in diseases related to monoclonal components, inflammation, and antibody deficiency. Here, we developed a deep learning-bas...

A new fuzzy rule based multi-objective optimization method for cross-scale injection molding of protein electrophoresis microfluidic chips.

Scientific reports
Injection molding is one of the most promising technologies for the large-scale production and application of polymeric microfluidic chips. The multi-objective optimization of injection molding process for substrate and cover plate on protein electro...

Deep Collocative Learning for Immunofixation Electrophoresis Image Analysis.

IEEE transactions on medical imaging
Immunofixation Electrophoresis (IFE) analysis is of great importance to the diagnosis of Multiple Myeloma, which is among the top-9 cancer killers in the United States, but has rarely been studied in the context of deep learning. Two possible reasons...

Combination of large volume sample stacking with polarity switching and cyclodextrin electrokinetic chromatography (LVSS-PS-CDEKC) for the determination of selected preservatives in pharmaceuticals.

Talanta
In this study, a large volume sample stacking (LVSS) with polarity switching (PS) and cyclodextrin electrokinetic chromatography (CDEKC) method has been developed for the simultaneous separation and determination of 8 preservatives: methylparaben (MP...

The generalisability of artificial neural networks used to classify electrophoretic data produced under different conditions.

Forensic science international. Genetics
Previous work has shown that artificial neural networks can be used to classify signal in an electropherogram into categories that have interpretational meaning (such as allele, baseline, pull-up or stutter). The previous work trained the neural netw...

An artificial neural network system to identify alleles in reference electropherograms.

Forensic science international. Genetics
Electropherograms are produced in great numbers in forensic DNA laboratories as part of everyday criminal casework. Before the results of these electropherograms can be used they must be scrutinised by analysts to determine what the identified data t...

Changing techniques in crop plant classification: molecularization at the National Institute of Agricultural Botany during the 1980s.

Annals of science
Modern methods of analysing biological materials, including protein and DNA sequencing, are increasingly the objects of historical study. Yet twentieth-century taxonomic techniques have been overlooked in one of their most important contexts: agricul...

Teaching artificial intelligence to read electropherograms.

Forensic science international. Genetics
Electropherograms are produced in great numbers in forensic DNA laboratories as part of everyday criminal casework. Before the results of these electropherograms can be used they must be scrutinised by analysts to determine what the identified data t...

Texture analysis in gel electrophoresis images using an integrative kernel-based approach.

Scientific reports
Texture information could be used in proteomics to improve the quality of the image analysis of proteins separated on a gel. In order to evaluate the best technique to identify relevant textures, we use several different kernel-based machine learning...