Prop3D: A flexible, Python-based platform for machine learning with protein structural properties and biophysical data.

Background: Machine learning (ML) has a rich history in structural bioinformatics, and modern approaches, such as deep learning, are revolutionizing our knowledge of the subtle relationships between biomolecular sequence, structure, function, dynamics and evolution. As with any advance that rests upon statistical learning approaches, the recent progress in biomolecular sciences is enabled by the availability of vast volumes of sufficiently-variable data. To be useful, such data must be well-structured, machine-readable, intelligible and manipulable.

restfulSE: A semantically rich interface for cloud-scale genomics with Bioconductor.

Bioconductor's SummarizedExperiment class unites numerical assay quantifications with sample- and experiment-level metadata.  SummarizedExperiment is the standard Bioconductor class for assays that produce matrix-like data, used by over 200 packages.  We describe the restfulSE package, a deployment of  this data model that supports remote storage.