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Peptide Fragments

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Prediction of Incident Atrial Fibrillation in Chronic Kidney Disease: The Chronic Renal Insufficiency Cohort Study.

Clinical journal of the American Society of Nephrology : CJASN
BACKGROUND AND OBJECTIVES: Atrial fibrillation (AF) is common in CKD and associated with poor kidney and cardiovascular outcomes. Prediction models developed using novel methods may be useful to identify patients with CKD at highest risk of incident ...

DeepLC can predict retention times for peptides that carry as-yet unseen modifications.

Nature methods
The inclusion of peptide retention time prediction promises to remove peptide identification ambiguity in complex liquid chromatography-mass spectrometry identification workflows. However, due to the way peptides are encoded in current prediction mod...

Single-molecule fluorescence imaging and deep learning reveal highly heterogeneous aggregation of amyloid-β 42.

Proceedings of the National Academy of Sciences of the United States of America
Polymorphism in the structure of amyloid fibrils suggests the existence of many different assembly pathways. Characterization of this heterogeneity is the key to understanding the aggregation mechanism and toxicity, but in practice it is extremely di...

Deep-Learning-Assisted Stratification of Amyloid Beta Mutants Using Drying Droplet Patterns.

Advanced materials (Deerfield Beach, Fla.)
The development of simple and accurate methods to predict mutations in proteins remains an unsolved challenge in modern biochemistry. It is discovered that critical information about primary and secondary peptide structures can be inferred from the s...

Pulmonary transit time of cardiovascular magnetic resonance perfusion scans for quantification of cardiopulmonary haemodynamics.

European heart journal. Cardiovascular Imaging
AIMS: Pulmonary transit time (PTT) is the time blood takes to pass from the right ventricle to the left ventricle via pulmonary circulation. We aimed to quantify PTT in routine cardiovascular magnetic resonance imaging perfusion sequences. PTT may he...

Interpretable Machine Learning of Amino Acid Patterns in Proteins: A Statistical Ensemble Approach.

Journal of chemical theory and computation
Explainable and interpretable unsupervised machine learning helps one to understand the underlying structure of data. We introduce an ensemble analysis of machine learning models to consolidate their interpretation. Its application shows that restric...

Deep learning-based NT-proBNP prediction from the ECG for risk assessment in the community.

Clinical chemistry and laboratory medicine
OBJECTIVES: The biomarker N-terminal pro B-type natriuretic peptide (NT-proBNP) has predictive value for identifying individuals at risk for cardiovascular disease (CVD). However, it is not widely used for screening in the general population, potenti...

Artificial intelligence universal biomarker prediction tool.

Journal of thrombosis and thrombolysis
Through experiencing cardiopulmonary arrest, an artificial intelligence universal biomarker prediction tool was developed to help patients understand improvement in the trends of their disease. PyPI tool handles two biomarkers, hbA1c for diabetes and...