On the order of hundreds of absorption, distribution, metabolism, excretion, and toxicity (ADME/Tox) models have been described in the literature in the past decade which are more often than not inaccessible to anyone but their authors. Public accessibility is also an issue with computational models for bioactivity, and the ability to share such models still remains a major challenge limiting drug discovery. We describe the creation of a reference implementation of a Bayesian model-building software module, which we have released as an open source component that is now included in the Chemistry Development Kit (CDK) project, as well as implemented in the CDD Vault and in several mobile apps. We use this implementation to build an array of Bayesian models for ADME/Tox, in vitro and in vivo bioactivity, and other physicochemical properties. We show that these models possess cross-validation receiver operator curve values comparable to those generated previously in prior publications using alternative tools. We have now described how the implementation of Bayesian models with FCFP6 descriptors generated in the CDD Vault enables the rapid production of robust machine learning models from public data or the user’s own datasets. The current study sets the stage for generating models in proprietary software (such as CDD) and exporting these models in a format that could be run in open source software using CDK components. This work also demonstrates that we can enable biocomputation across distributed private or public datasets to enhance drug discovery.

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Interfaces for creating visualizations typically embrace one of several common forms. Textual specifcation enables fne-grained control, shelf building facilitates rapid exploration, while chart choosing promotes immediacy and simplicity. Ideally these approaches could be unifed to integrate the user-and usage-dependent benefts found in each modality, yet these forms remain distinct.We propose parameterized declarative templates, a simple abstraction mechanism over JSON-based visualization grammars, as a foundation for multimodal visualization editors. We demonstrate how templates can facilitate organization and reuse by factoring the more than 160 charts that constitute Vega-Lite's example gallery into approximately 40 templates. We exemplify the pliability of abstracting over charting grammars by implementing-as a template-the functionality of the shelf builder Polestar (a simulacra of Tableau) and a set of templates that emulate the Google Sheets chart chooser. We show how templates support multimodal visualization editing by implementing a prototype and evaluating it through an approachability study. CCS CONCEPTS• Human-centered computing → Visualization systems and tools; Graphical user interfaces.

Unfamiliar or esoteric visual forms arise in many areas of visualization. While such forms can be intriguing, it can be unclear how to make effective use of them without long periods of practice or costly user studies. In this work we analyze the table cartogram—a graphic which visualizes tabular data by bringing the areas of a grid of quadrilaterals into correspondence with the input data, like a heat map that has been “area‐ed” rather than colored. Despite having existed for several years, little is known about its appropriate usage. We mend this gap by using Algebraic Visualization Design to show that they are best suited to relatively small tables with ordinal axes for some comparison and outlier identification tasks. In doing so we demonstrate a discount theory‐based analysis that can be used to cheaply determine best practices for unknown visualizations.

We study the Schrödinger-Newton system of equations with the addition of gravitational field energy sourcing -such additional nonlinearity is to be expected from a theory of gravity (like general relativity), and its appearance in this simplified scalar setting (one of Einstein's precursors to general relativity) leads to significant changes in the spectrum of the self-gravitating theory.Using an iterative technique, we compare the mass dependence of the ground state energies of both Schrödinger-Newton and the new, self-sourced system and find that they are dramatically different. The Bohr method approach from old quantization provides a qualitative description of the difference, which comes from the additional nonlinearity introduced in the self-sourced case.In addition to comparison of ground state energies, we calculate the transition energy between the ground state and first excited state to compare emission frequencies between Schrödinger-Newton and the self-coupled scalar case. * jfrankli@reed.edu 1 arXiv:1501.07537v1 [gr-qc]