3 citations · 4 across the 2 of their papers we have counts for
4 papers
Extraction and integration of genetic networks from short-profile omic datasets
Jacopo Iacovacci, Alina Peluso, Timothy Ebbels +2
Mass-spectrometry technologies are widely used in the fields of ionomics and metabolomics to simultaneously profile at the genome scale intracellular concentrations of e.g. amino a…
Validating the Validation: Reanalyzing a large-scale comparison of Deep Learning and Machine Learning models for bioactivity prediction
Matthew C. Robinson, Robert C. Glen, Alpha A. Lee
Machine learning methods may have the potential to significantly accelerate drug discovery. However, the increasing rate of new methodological approaches being published in the lit…
Metabolomics in the Cloud: Scaling Computational Tools to Big Data
Jianliang Gao, Noureddin Sadawi, Ibrahim Karaman +8
Background: Metabolomics datasets are becoming increasingly large and complex, with multiple types of algorithms and workflows needed to process and analyse the data. A cloud infra…
Variational autoencoders for tissue heterogeneity exploration from (almost) no preprocessed mass spectrometry imaging data
Paolo Inglese, James L. Alexander, Anna Mroz +2
The paper presents the application of Variational Autoencoders (VAE) for data dimensionality reduction and explorative analysis of mass spectrometry imaging data (MSI). The results…