AIMC Topic: Proteome
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Decoding the glycoproteome: a new frontier for biomarker discovery in cancer.
Journal of hematology & oncology
Mar 22, 2024
Cancer early detection and treatment response prediction continue to pose significant challenges. Cancer liquid biopsies focusing on detecting circulating tumor cells (CTCs) and DNA (ctDNA) have shown enormous potential due to their non-invasive natu...
An atlas of protein homo-oligomerization across domains of life.
Cell
Feb 6, 2024
Protein structures are essential to understanding cellular processes in molecular detail. While advances in artificial intelligence revealed the tertiary structure of proteins at scale, their quaternary structure remains mostly unknown. We devise a s...
Parsing 20 Years of Public Data by AI Maps Trends in Proteomics and Forecasts Technology.
Journal of proteome research
Dec 14, 2023
The trends of the last 20 years in biotechnology were revealed using artificial intelligence and natural language processing (NLP) of publicly available data. Implementing this "science-of-science" approach, we capture convergent trends in the field ...
Cross-protein transfer learning substantially improves disease variant prediction.
Genome biology
Aug 7, 2023
BACKGROUND: Genetic variation in the human genome is a major determinant of individual disease risk, but the vast majority of missense variants have unknown etiological effects. Here, we present a robust learning framework for leveraging saturation m...
Turnover number predictions for kinetically uncharacterized enzymes using machine and deep learning.
Nature communications
Jul 12, 2023
The turnover number k, a measure of enzyme efficiency, is central to understanding cellular physiology and resource allocation. As experimental k estimates are unavailable for the vast majority of enzymatic reactions, the development of accurate comp...
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Analytical chemistry
May 1, 2023
Four-dimensional (4D) data-independent acquisition (DIA)-based proteomics is a promising technology. However, its full performance is restricted by the time-consuming building and limited coverage of a project-specific experimental library. Herein, w...
DeepSTABp: A Deep Learning Approach for the Prediction of Thermal Protein Stability.
International journal of molecular sciences
Apr 18, 2023
Proteins are essential macromolecules that carry out a plethora of biological functions. The thermal stability of proteins is an important property that affects their function and determines their suitability for various applications. However, curren...
Recent advances in predicting and modeling protein-protein interactions.
Trends in biochemical sciences
Apr 14, 2023
Protein-protein interactions (PPIs) drive biological processes, and disruption of PPIs can cause disease. With recent breakthroughs in structure prediction and a deluge of genomic sequence data, computational methods to predict PPIs and model spatial...
DeepDetect: Deep Learning of Peptide Detectability Enhanced by Peptide Digestibility and Its Application to DIA Library Reduction.
Analytical chemistry
Mar 12, 2023
In tandem mass spectrometry-based proteomics, proteins are digested into peptides by specific protease(s), but generally only a fraction of peptides can be detected. To characterize detectable proteotypic peptides, we have developed a series of metho...
Learning the protein language of proteome-wide protein-protein binding sites via explainable ensemble deep learning.
Communications biology
Jan 19, 2023
Protein-protein interactions (PPIs) govern cellular pathways and processes, by significantly influencing the functional expression of proteins. Therefore, accurate identification of protein-protein interaction binding sites has become a key step in t...
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