Article

Structured decomposition improves systems serology prediction and interpretation

2021-01-04

Abstract excerpt

Systems serology measurements provide a comprehensive view of humoral immunity by profiling both the antigen-binding and Fc properties of antibodies. Identifying patterns in these measurements will help to guide vaccine and therapeutic antibody development, and improve our understanding of disorders. Furthermore, consistent patterns across diseases may reflect conserved regulatory mechanisms; recognizing these may...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 886c97d0-07c7-503b-82c3-c4104afdf3a8
DOI: 10.1101/2021.01.03.425138

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 8 closest

Structured decomposition improves systems serology prediction and interpretationDOI 10.1101/2021.01.03.425138Read

Tensor factorization toward precision medicine.Semantic proximity Read

Tensor Factorization for Precision Medicine in Heart Failure with Preserved Ejection Fraction.Semantic proximity Read

Dimensionality reduction of longitudinal 'omics data using modern tensor factorizations.Semantic proximity Read

Multi-view learning to unravel the different levels underlying hepatitis B vaccine responseSemantic proximity Read

Four-Dimensional Sparse Bayesian Tensor Decomposition for Gene Expression DataSemantic proximity Read

Matrix completion with side information and its applications in predicting the antigenicity of influenza viruses.Semantic proximity Read

Interpretable single-cell factor decomposition using sciREDSemantic proximity Read