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Proteomics

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[Recent progress in capillary electrophoresis-based high-sensitivity proteomics].

Se pu = Chinese journal of chromatography
In recent years, proteomic techniques have undergone rapid progress in terms of sample pretreatment, separation, and mass spectrometry (MS) detection. The current MS-based proteomic techniques can be used to identify up to 10000 proteins both qualita...

Artificial intelligence and machine learning for protein toxicity prediction using proteomics data.

Chemical biology & drug design
Instead of only focusing on the targeted drug delivery system, researchers have a great interest in developing peptide-based therapies for the procurement of numerous class of diseases. The main idea behind this is to anchor the properties of the rec...

Artificial neural network and bioavailability of the immunosuppression drug.

Current opinion in organ transplantation
PURPOSE OF REVIEW: The success of organ transplant is determined by number of demographic, clinical, immunological and genetic variables. Artificial intelligence tools, such as artificial neural networks (ANNs) or classification and regression trees ...

DeepMSPeptide: peptide detectability prediction using deep learning.

Bioinformatics (Oxford, England)
SUMMARY: The protein detection and quantification using high-throughput proteomic technologies is still challenging due to the stochastic nature of the peptide selection in the mass spectrometer, the difficulties in the statistical analysis of the re...

Automated sample preparation with SP3 for low-input clinical proteomics.

Molecular systems biology
High-throughput and streamlined workflows are essential in clinical proteomics for standardized processing of samples from a variety of sources, including fresh-frozen tissue, FFPE tissue, or blood. To reach this goal, we have implemented single-pot ...

Methods of Computational Interactomics for Investigating Interactions of Human Proteoforms.

Biochemistry. Biokhimiia
Human genome contains ca. 20,000 protein-coding genes that could be translated into millions of unique protein species (proteoforms). Proteoforms coded by a single gene often have different functions, which implies different protein partners. By inte...

[Research progress of feature selection and machine learning methods for mass spectrometry-based protein biomarker discovery].

Sheng wu gong cheng xue bao = Chinese journal of biotechnology
With the development of mass spectrometry technologies and bioinformatics analysis algorithms, disease research-driven human proteome project (HPP) is advancing rapidly. Protein biomarkers play critical roles in clinical applications and the biomarke...

Multi-omics integration-a comparison of unsupervised clustering methodologies.

Briefings in bioinformatics
With the recent developments in the field of multi-omics integration, the interest in factors such as data preprocessing, choice of the integration method and the number of different omics considered had increased. In this work, the impact of these f...

Artificial intelligence and amniotic fluid multiomics: prediction of perinatal outcome in asymptomatic women with short cervix.

Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology
OBJECTIVE: To evaluate the application of artificial intelligence (AI), i.e. deep learning and other machine-learning techniques, to amniotic fluid (AF) metabolomics and proteomics, alone and in combination with sonographic, clinical and demographic ...