Graph machine learning (GML) is receiving growing interest within the pharmaceutical and biotechnology industries for its ability to model biomolecular structures, the functional relationships between them, and integrate multi-omic datasets - amongst other data types. Herein, we present a multidisciplinary academic-industrial review of the topic within the context of drug discovery and development. After introducing key terms and modelling approaches, we move chronologically through the drug development pipeline to identify and summarize work incorporating: target identification, design of small molecules and biologics, and drug repurposing. Whilst the field is still emerging, key milestones including repurposed drugs entering in vivo studies, suggest GML will become a modelling framework of choice within biomedical machine learning.

We describe an audiovisual live coding performance created using Gibber, a creative coding environment that runs in the browser. The performance takes advantage of novel affordances for rapidly creating music, shaders, and mappings that tie together audio and visual modalities.

We describe design decisions informing the development of Gibber, an audiovisual programming environment for the browser. Our design comprises a consistent notation across modalities in addition to high-level abstractions affording intuitive declarations of multimodal mappings, unified timing constructs, and rapid, iterative reinvocations of constructors while preserving the state of audio and visual graphs. We discuss the features of our environment and the abstractions that enable them. We close by describing use cases, including live audiovisual performances and computer science education.

A modeling technique has been produced by combining remote sensing with geologic history for building a paleoterrain model that enables visualization of topography prior to anthropogenic development. The model's foundation is comprised of LIDAR data and stratigraphic sequences for describing the local geologic history. The Yamato Marsh, located in Palm Beach County, Florida, is a paleowatershed that was chosen for this study. The paleoterrain model of the marsh site can be utilized further in understanding land-use impacts on the surrounding environment. In conclusion, the final model of the Yamato Marsh successfully offers insight as well as a glimpse at a geomorphic feature that no longer exists.