The Open Spectral Database: an open platform for sharing and searching spectral data

BACKGROUND: A number of websites make available spectral data for download (typically as JCAMP-DX text files) and one (ChemSpider) that also allows users to contribute spectral files. As a result, searching and retrieving such spectral data can be time consuming, and difficult to reuse if the data is compressed in the JCAMP-DX file. What is needed is a single resource that allows submission of JCAMP-DX files, export of the raw data in multiple formats, searching based on multiple chemical identifiers, and is open in terms of license and access. To address these issues a new online resource called the Open Spectral Database (OSDB) http://osdb.info/ has been developed and is now available. Built using open source tools, using open code (hosted on GitHub), providing open data, and open to community input about design and functionality, the OSDB is available for anyone to submit spectral data, making it searchable and available to the scientific community. This paper details the concept and coding, internal architecture, export formats, Representational State Transfer (REST) Application Programming Interface and options for submission of data. RESULTS: The OSDB website went live in November 2015. Concurrently, the GitHub repository was made available at https://github.com/stuchalk/OSDB/, and is open for collaborators to join the project, submit issues, and contribute code. CONCLUSION: The combination of a scripting environment (PHPStorm), a PHP Framework (CakePHP), a relational database (MySQL) and a code repository (GitHub) provides all the capabilities to easily develop REST based websites for ingestion, curation and exposure of open chemical data to the community at all levels. It is hoped this software stack (or equivalent ones in other scripting languages) will be leveraged to make more chemical data available for both humans and computers

The IUPAC Gold Book website

In the past 100 years IUPAC has become well known for the development of nomenclature standards for chemicals and terminology for communication of chemically related concepts. Initially published in IUPAC\u27s Pure and Applied Chemistry (PAC), terminology recommendations have been incorporated into the IUPAC Color Books published by the divisions. Subsequently, many terms from the color books have been incorporated into the Gold Book - the Compendium of Chemical Terminology. While the work to date as been focused on the standardization of concept (term) definitions for human use, the aggregated set of all PAC recommendations on terminology constitutes a corpus of high quality definitions for entries into an ontology for use in computer representation of chemical concepts. This is sorely needed at a time when there is a significant move toward machine learning approaches to understand science both within and outside chemistry. With it chemical data scientists can envision and apply this \u27common language\u27 into their cheminformatics work, promoting interoperability in chemical data. This paper will review the history of the PAC recommendations, the color books, and highlight how the existing guidelines for the development of terms supports the renovation of the terms for computer use. The current update to the Gold Book website will be discussed (including machine processability) as well as future ontological representation of the terms. Finally, this development will be highlighted as one of the most important in the next 100 years of IUPAC

Flow Injection Reagent Introduction by Supported Liquid and Nafion Membranes: Determination of Phosphate

The use of membrane tubing for the introduction of reagents for the determination of phosphate in waters by flow injection analysis was studied. The use of membranes eliminates the need for confluence points in the design of flow injection manifolds. This increases the sensitivity of the manifold by providing a sufficient reagent excess for the reaction without diluting the sample. Methods for the introduction of acid, molybdate and hydrazine were devised for the determination of phosphate by the Molybdenum Blue method. Several membranes were examined and Nafion and Accurel (microporous polypropylene) were found to be most useful. Molybdate introduction was achieved using a supported liquid membrane (SLM). Calibration was linear and a detection limit of 12 ppb phosphate (4 ppb phosphorus) was obtained

Development of the Continuously Variable Volume Reactor for Flow Injection AnalysisDesign, Capabilities and Testing

A new apparatus for mixing sample and reagent in flow injection analysis is described. The continuously variable volume reactor (CVVR) replaces the conventional mixing coil in a flow injection manifold to provide mixing and dilution. A linear actuator motor allows control of the chamber volume via Lab VIEW software. The chamber volume can be incremented in steps of 1 uL over the range 68-1704 uL. In addition, the chamber has an integral variable-speed stirring unit that is also under computer control. Experiments were performed to evaluate the dispersion characteristics of this new device, evaluate the volume reproducibility, and understand the mixing characteristics. Use of the chamber is shown in the determination of iron (II) in pond water, and in NIST SRM 1643d with excellent results and a detection limit of 3.7 ug/L iron(II). Advantages of the CVVR and future research activities using the device are discussed

Swift: A modern highly-parallel gravity and smoothed particle hydrodynamics solver for astrophysical and cosmological applications

Numerical simulations have become one of the key tools used by theorists in all the fields of astrophysics and cosmology. The development of modern tools that target the largest existing computing systems and exploit state-of-the-art numerical methods and algorithms is thus crucial. In this paper, we introduce the fully open-source highly-parallel, versatile, and modular coupled hydrodynamics, gravity, cosmology, and galaxy-formation code Swift. The software package exploits hybrid task-based parallelism, asynchronous communications, and domain-decomposition algorithms based on balancing the workload, rather than the data, to efficiently exploit modern high-performance computing cluster architectures. Gravity is solved for using a fast-multipole-method, optionally coupled to a particle mesh solver in Fourier space to handle periodic volumes. For gas evolution, multiple modern flavours of Smoothed Particle Hydrodynamics are implemented. Swift also evolves neutrinos using a state-of-the-art particle-based method. Two complementary networks of sub-grid models for galaxy formation as well as extensions to simulate planetary physics are also released as part of the code. An extensive set of output options, including snapshots, light-cones, power spectra, and a coupling to structure finders are also included. We describe the overall code architecture, summarize the consistency and accuracy tests that were performed, and demonstrate the excellent weak-scaling performance of the code using a representative cosmological hydrodynamical problem with $\approx$$300$ billion particles. The code is released to the community alongside extensive documentation for both users and developers, a large selection of example test problems, and a suite of tools to aid in the analysis of large simulations run with Swift.Comment: 39 pages, 18 figures, submitted to MNRAS. Code, documentation, and examples available at www.swiftsim.co

Catalytic residues in hydrolases: analysis of methods designed for ligand-binding site prediction

The comparison of eight tools applicable to ligand-binding site prediction is presented. The methods examined cover three types of approaches: the geometrical (CASTp, PASS, Pocket-Finder), the physicochemical (Q-SiteFinder, FOD) and the knowledge-based (ConSurf, SuMo, WebFEATURE). The accuracy of predictions was measured in reference to the catalytic residues documented in the Catalytic Site Atlas. The test was performed on a set comprising selected chains of hydrolases. The results were analysed with regard to size, polarity, secondary structure, accessible solvent area of predicted sites as well as parameters commonly used in machine learning (F-measure, MCC). The relative accuracies of predictions are presented in the ROC space, allowing determination of the optimal methods by means of the ROC convex hull. Additionally the minimum expected cost analysis was performed. Both advantages and disadvantages of the eight methods are presented. Characterization of protein chains in respect to the level of difficulty in the active site prediction is introduced. The main reasons for failures are discussed. Overall, the best performance offers SuMo followed by FOD, while Pocket-Finder is the best method among the geometrical approaches