AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Proteomics

Showing 311 to 320 of 389 articles

Clear Filters

APNet, an explainable sparse deep learning model to discover differentially active drivers of severe COVID-19.

Bioinformatics (Oxford, England)
MOTIVATION: Computational analyses of bulk and single-cell omics provide translational insights into complex diseases, such as COVID-19, by revealing molecules, cellular phenotypes, and signalling patterns that contribute to unfavourable clinical out...

UniProt: the Universal Protein Knowledgebase in 2025.

Nucleic acids research
The aim of the UniProt Knowledgebase (UniProtKB; https://www.uniprot.org/) is to provide users with a comprehensive, high-quality and freely accessible set of protein sequences annotated with functional information. In this publication, we describe o...

OrgXenomics: an integrated proteomic knowledge base for patient-derived organoid and xenograft.

Nucleic acids research
Patient-derived models (PDMs, particularly organoids and xenografts) are irreplaceable tools for precision medicine, from target development to lead identification, then to preclinical evaluation, and finally to clinical decision-making. So far, PDM-...

A Machine Learning Pipeline to Screen Large In Vivo Molecular Data to Curate Disease Signatures of High Translational Potential.

Methods in molecular biology (Clifton, N.J.)
A significantly low success rate of human clinical studies has long been attributed to a capability gap, namely, an ineffective translation of the animal data to the human context. To bridge this capability gap, several correcting measures have been ...

Automated Machine Learning Tools to Build Regression Models for Schizosaccharomyces pombe Omics Data.

Methods in molecular biology (Clifton, N.J.)
Machine learning is a powerful tool for analyzing biological data and making useful predictions. The surge of biological data from high-throughput omics technologies has raised the need for modeling approaches capable of tackling such amounts of data...

Artificial Intelligence-Driven Precision Medicine: Multi-Omics and Spatial Multi-Omics Approaches in Diffuse Large B-Cell Lymphoma (DLBCL).

Frontiers in bioscience (Landmark edition)
In this comprehensive review, we delve into the transformative role of artificial intelligence (AI) in refining the application of multi-omics and spatial multi-omics within the realm of diffuse large B-cell lymphoma (DLBCL) research. We scrutinized ...

Annotating publicly-available samples and studies using interpretable modeling of unstructured metadata.

Briefings in bioinformatics
Reusing massive collections of publicly available biomedical data can significantly impact knowledge discovery. However, these public samples and studies are typically described using unstructured plain text, hindering the findability and further reu...

Machine learning-based clustering identifies obesity subgroups with differential multi-omics profiles and metabolic patterns.

Obesity (Silver Spring, Md.)
OBJECTIVE: Individuals living with obesity are differentially susceptible to cardiometabolic diseases. We hypothesized that an integrative multi-omics approach might improve identification of subgroups of individuals with obesity who have distinct ca...

Sitetack: a deep learning model that improves PTM prediction by using known PTMs.

Bioinformatics (Oxford, England)
MOTIVATION: Post-translational modifications (PTMs) increase the diversity of the proteome and are vital to organismal life and therapeutic strategies. Deep learning has been used to predict PTM locations. Still, limitations in datasets and their ana...

A comprehensive review of machine learning techniques for multi-omics data integration: challenges and applications in precision oncology.

Briefings in functional genomics
Multi-omics data play a crucial role in precision medicine, mainly to understand the diverse biological interaction between different omics. Machine learning approaches have been extensively employed in this context over the years. This review aims t...