AIMC Topic: Proteomics

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Machine Learning of Plasma Proteomics Classifies Diagnosis of Interstitial Lung Disease.

American journal of respiratory and critical care medicine
Distinguishing connective tissue disease-associated interstitial lung disease (CTD-ILD) from idiopathic pulmonary fibrosis (IPF) can be clinically challenging. To identify proteins that separate and classify patients with CTD-ILD and those with IPF...

Integrated multi-omics with machine learning to uncover the intricacies of kidney disease.

Briefings in bioinformatics
The development of omics technologies has driven a profound expansion in the scale of biological data and the increased complexity in internal dimensions, prompting the utilization of machine learning (ML) as a powerful toolkit for extracting knowled...

Proteomic prediction of diverse incident diseases: a machine learning-guided biomarker discovery study using data from a prospective cohort study.

The Lancet. Digital health
BACKGROUND: Broad-capture proteomic technologies have the potential to improve disease prediction, enabling targeted prevention and management, but studies have so far been limited to very few selected diseases and have not evaluated predictive perfo...

The Immunopeptidomics Ontology (ImPO).

Database : the journal of biological databases and curation
The adaptive immune response plays a vital role in eliminating infected and aberrant cells from the body. This process hinges on the presentation of short peptides by major histocompatibility complex Class I molecules on the cell surface. Immunopepti...

Expanding the coverage of spatial proteomics: a machine learning approach.

Bioinformatics (Oxford, England)
MOTIVATION: Multiplexed protein imaging methods use a chosen set of markers and provide valuable information about complex tissue structure and cellular heterogeneity. However, the number of markers that can be measured in the same tissue sample is i...

AI-Assisted Processing Pipeline to Boost Protein Isoform Detection.

Methods in molecular biology (Clifton, N.J.)
Proteomics, the study of proteins within biological systems, has seen remarkable advancements in recent years, with protein isoform detection emerging as one of the next major frontiers. One of the primary challenges is achieving the necessary peptid...

Multi-omics Combined with Machine Learning Facilitating the Diagnosis of Gastric Cancer.

Current medicinal chemistry
Gastric cancer (GC) is a highly intricate gastrointestinal malignancy. Early detection of gastric cancer forms the cornerstone of precision medicine. Several studies have been conducted to investigate early biomarkers of gastric cancer using genomics...

Image-Based Subtype Classification for Glioblastoma Using Deep Learning: Prognostic Significance and Biologic Relevance.

JCO clinical cancer informatics
PURPOSE: To apply deep learning algorithms to histopathology images, construct image-based subtypes independent of known clinical and molecular classifications for glioblastoma, and produce novel insights into molecular and immune characteristics of ...

Explainable artificial intelligence for omics data: a systematic mapping study.

Briefings in bioinformatics
Researchers increasingly turn to explainable artificial intelligence (XAI) to analyze omics data and gain insights into the underlying biological processes. Yet, given the interdisciplinary nature of the field, many findings have only been shared in ...