Article

NeTOIF: A Network-based Approach for Time-Series Omics Data Imputation and Forecasting

2021-06-07

Abstract excerpt

<h4>Motivation</h4> High-throughput studies of biological systems are rapidly generating a wealth of ‘omics’-scale data. Many of these studies are time-series collecting proteomics and genomics data capturing dynamic observations. While time-series omics data are essential to unravel the mechanisms of various diseases, they often include missing (or incomplete) values resulting in data shortage. Data missing and...

Topics

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

Identifiers and source

Literature Corpus work: 5c69f510-830d-572b-9fba-170e94b44ae0
DOI: 10.1101/2021.06.05.447209

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

NeTOIF: A Network-based Approach for Time-Series Omics Data Imputation and ForecastingDOI 10.1101/2021.06.05.447209Read

LEOPARD: missing view completion for multi-timepoint omics data via representation disentanglement and temporal knowledge transferSemantic proximity Read

Multi-Omics Regulatory Network Inference in the Presence of Missing DataSemantic proximity Read

Incomplete time-series gene expression in integrative study for islet autoimmunity prediction.Semantic proximity Read

DANSE: a pipeline for dynamic modelling of time-series multi-omics dataSemantic proximity Read

omicsMIC: a Comprehensive Benchmarking Platform for Robust Comparison of Imputation Methods in Mass Spectrometry-based Omics DataSemantic proximity Read

Comparative Assessment and Outlook on Methods for Imputing Proteomics DataSemantic proximity Read

DreamAI: algorithm for the imputation of proteomics dataSemantic proximity Read

NPmatch: Latent Batch Effects Correction of Omics data by Nearest-Pair MatchingSemantic proximity Read

Optimizing Network Propagation for Multi-Omics Data IntegrationSemantic proximity Read

ProteoForge: An Imputation-Aware Framework for Differential Proteoform Discovery in Bottom-Up ProteomicsSemantic proximity Read

Multi-scale variational autoencoder for imputation of missing values in untargeted metabolomics using whole-genome sequencing data.Semantic proximity Read

cpiVAE: Robust and Interpretable Cross-Platform Proteomics ImputationSemantic proximity Read