AIMC Topic: Proteomics

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Backyard Proteomics: A Case Study with the Black Widow Spider.

Journal of proteome research
Nearly all methods of mass-spectrometry-based proteomics rely on knowing the proteome of the species. In less studied organisms without annotated genomes, it can seem impossible to perform proteomic analysis. In this study, we sought to answer the qu...

Federated Deep Learning Enables Cancer Subtyping by Proteomics.

Cancer discovery
UNLABELLED: Artificial intelligence applications in biomedicine face major challenges from data privacy requirements. To address this issue for clinically annotated tissue proteomic data, we developed a federated deep learning approach (ProCanFDL), t...

Moving past multidisciplinary discussions and Gender-Age-Physiology model: precision medicine through biological phenotyping in interstitial lung disease.

Current opinion in pulmonary medicine
PURPOSE OF REVIEW: Interstitial lung disease (ILD) presents significant diagnostic and therapeutic challenges due to underlying biological heterogeneity and variable clinical course. Traditional diagnostic and prognostic tools are limited in their ab...

Searching for peripheral proteomic markers of primary aldosteronism.

Endocrine
PURPOSE: Primary aldosteronism (PA) is prevalent among hypertensive patients, and associated with worsened cardiovascular outcomes compared to essential hypertension (HT). Screening and diagnostics for PA are currently complicated and invasive, why n...

Integration of proteomics and artificial intelligence-driven OCT biomarker analysis in central retinal vein occlusion.

Experimental eye research
Retinal OCT biomarker analysis by artificial intelligence (AI) has not previously been integrated with proteomics. Here, we combined the two techniques to elucidate novel molecular mechanisms in central retinal vein occlusion (CRVO). Proteomic data o...

DeepMS: super-fast peptide identification using end-to-end deep learning method.

Journal of molecular biology
Mass spectrometry (MS) has emerged as a powerful omics analysis technique, particularly in proteomics, where the initial step involves identifying MS spectra as peptide sequences. However, this process often requires substantial computational resourc...

ResNeXt-Based Rescoring Model for Proteoform Characterization in Top-Down Mass Spectra.

Interdisciplinary sciences, computational life sciences
In top-down proteomics, the accurate identification and characterization of proteoform through mass spectrometry represents a critical objective. As a result, achieving accuracy in identification results is essential. Multiple primary structure alter...

Why Protein Modifications Matter for Digestibility: The Case of Ara h 1 Peanut Allergen and Trypsin Cleavage.

Journal of agricultural and food chemistry
Trypsin is the principal intestinal endopeptidase and proteomics digestion tool, yet the impact of protein modifications (PMs) on digestibility and allergenicity remains underexplored. We employed a proteomic approach to assess trypsin cleavage effic...

Integration of multi-omics data and machine learning to identify antioxidant biomarkers in type 1 diabetes.

Free radical biology & medicine
The identification of biomarkers for early diagnosis and monitoring the progression of Type 1 Diabetes (T1DM) is essential for improving disease management. This study integrates multi-omics data with machine learning to identify antioxidant stress p...

Emerging blood biomarkers in Alzheimer's disease: a proteomic perspective.

Clinica chimica acta; international journal of clinical chemistry
Early detection of Alzheimer's disease (AD) remains a formidable clinical challenge, but emerging blood-based assays show promise for identifying at-risk individuals long before cognitive symptoms arise. This is the first comprehensive synthesis comp...