Representation and use of chemistry in the global electronic age.

We present an overview of the current state of public semantic chemistry and propose new approaches at a strategic and a detailed level. We show by example how a model for a Chemical Semantic Web can be constructed using machine-processed data and information from journal articles.This manuscript addresses questions of robotic access to data and its automatic re-use, including the role of Open Access archival of data. This is a pre-refereed preprint allowed by the publisher's (Royal Soc. Chemistry) Green policy. The author's preferred manuscript is an HTML hyperdocument with ca. 20 links to images, some of which are JPEgs and some of which are SVG (scalable vector graphics) including animations. There are also links to molecules in CML, for which the Jmol viewer is recommended. We susgeest that readers who wish to see the full glory of the manuscript, download the Zipped version and unpack on their machine. We also supply a PDF and DOC (Word) version which obviously cannot show the animations, but which may be the best palce to start, particularly for those more interested in the text

Internet based molecular collaborative and publishing tools

The scientific electronic publishing model has hitherto been an Internet based delivery of electronic articles that are essentially replicas of their paper counterparts. They contain little in the way of added semantics that may better expose the science, assist the peer review process and facilitate follow on collaborations, even though the enabling technologies have been around for some time and are mature. This thesis will examine the evolution of chemical electronic publishing over the past 15 years. It will illustrate, which the help of two frameworks, how publishers should be exploiting technologies to improve the semantics of chemical journal articles, namely their value added features and relationships with other chemical resources on the Web. The first framework is an early exemplar of structured and scalable electronic publishing where a Web content management system and a molecular database are integrated. It employs a test bed of articles from several RSC journals and supporting molecular coordinate and connectivity information. The value of converting 3D molecular expressions in chemical file formats, such as the MOL file, into more generic 3D graphics formats, such as Web3D, is assessed. This exemplar highlights the use of metadata management for bidirectional hyperlink maintenance in electronic publishing. The second framework repurposes this metadata management concept into a Semantic Web application called SemanticEye. SemanticEye demonstrates how relationships between chemical electronic articles and other chemical resources are established. It adapts the successful semantic model used for digital music metadata management by popular applications such as iTunes. Globally unique identifiers enable relationships to be established between articles and other resources on the Web and SemanticEye implements two: the Document Object Identifier (DOI) for articles and the IUPAC International Chemical Identifier (InChI) for molecules. SemanticEye’s potential as a framework for seeding collaborations between researchers, who have hitherto never met, is explored using FOAF, the friend-of-a-friend Semantic Web standard for social networks

Chemical information matters: an e-Research perspective on information and data sharing in the chemical sciences

Recently, a number of organisations have called for open access to scientific information and especially to the data obtained from publicly funded research, among which the Royal Society report and the European Commission press release are particularly notable. It has long been accepted that building research on the foundations laid by other scientists is both effective and efficient. Regrettably, some disciplines, chemistry being one, have been slow to recognise the value of sharing and have thus been reluctant to curate their data and information in preparation for exchanging it. The very significant increases in both the volume and the complexity of the datasets produced has encouraged the expansion of e-Research, and stimulated the development of methodologies for managing, organising, and analysing "big data". We review the evolution of cheminformatics, the amalgam of chemistry, computer science, and information technology, and assess the wider e-Science and e-Research perspective. Chemical information does matter, as do matters of communicating data and collaborating with data. For chemistry, unique identifiers, structure representations, and property descriptors are essential to the activities of sharing and exchange. Open science entails the sharing of more than mere facts: for example, the publication of negative outcomes can facilitate better understanding of which synthetic routes to choose, an aspiration of the Dial-a-Molecule Grand Challenge. The protagonists of open notebook science go even further and exchange their thoughts and plans. We consider the concepts of preservation, curation, provenance, discovery, and access in the context of the research lifecycle, and then focus on the role of metadata, particularly the ontologies on which the emerging chemical Semantic Web will depend. Among our conclusions, we present our choice of the "grand challenges" for the preservation and sharing of chemical information

A metadata-driven approach to data repository design

The design and use of a metadata-driven data repository for research data management is described. Metadata is collected automatically during the submission process whenever possible and is registered with DataCite in accordance with their current metadata schema, in exchange for a persistent digital object identifier. Two examples of data preview are illustrated, including the demonstration of a method for integration with commercial software that confers rich domain-specific data analytics without introducing customisation into the repository itself

Amjambo Africa! (April 2018)

Welcome to Amjambo Africa! Welcome to Amjambo Africa! We are Maine’s free newspaper for and about New Mainers from Sub-Saharan Africa. Amjambo Africa! is here to help New Mainers thrive and to help Maine welcome and benefit from our new neighbors. Amjambo Africa! will serve as a conduit of information for newcomers as they navigate life in Maine. Amjambo Africa! will include background articles about Africa so those from Maine can understand why newcomers have arrived here. Amjambo Africa! will profile successful New Mainers from Sub-Saharan Africa in order to give hope to those newly arrived as well as make clear the benefits to our state of welcoming newcomers. Amjambo Africa! will share on the ground news updates from contributors living in Africa now. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.https://digitalcommons.usm.maine.edu/samgen_amjambo/1000/thumbnail.jp

Design and implementation of a platform for predicting pharmacological properties of molecules

Tese de mestrado, Bioinformática e Biologia Computacional, Universidade de Lisboa, Faculdade de Ciências, 2019O processo de descoberta e desenvolvimento de novos medicamentos prolonga-se por vários anos e implica o gasto de imensos recursos monetários. Como tal, vários métodos in silico são aplicados com o intuito de dimiuir os custos e tornar o processo mais eficiente. Estes métodos incluem triagem virtual, um processo pelo qual vastas coleções de compostos são examinadas para encontrar potencial terapêutico. QSAR (Quantitative Structure Activity Relationship) é uma das tecnologias utilizada em triagem virtual e em optimização de potencial farmacológico, em que a informação estrutural de ligandos conhecidos do alvo terapêutico é utilizada para prever a actividade biológica de um novo composto para com o alvo. Vários investigadores desenvolvem modelos de aprendizagem automática de QSAR para múltiplos alvos terapêuticos. Mas o seu uso está dependente do acesso aos mesmos e da facilidade em ter os modelos funcionais, o que pode ser complexo quando existem várias dependências ou quando o ambiente de desenvolvimento difere bastante do ambiente em que é usado. A aplicação ao qual este documento se refere foi desenvolvida para lidar com esta questão. Esta é uma plataforma centralizada onde investigadores podem aceder a vários modelos de QSAR, podendo testar os seus datasets para uma multitude de alvos terapêuticos. A aplicação permite usar identificadores moleculares como SMILES e InChI, e gere a sua integração em descritores moleculares para usar como input nos modelos. A plataforma pode ser acedida através de uma aplicação web com interface gráfica desenvolvida com o pacote Shiny para R e directamente através de uma REST API desenvolvida com o pacote flask-restful para Python. Toda a aplicação está modularizada através de teconologia de “contentores”, especificamente o Docker. O objectivo desta plataforma é divulgar o acesso aos modelos criados pela comunidade, condensando-os num só local e removendo a necessidade do utilizador de instalar ou parametrizar qualquer tipo de software. Fomentando assim o desenvolvimento de conhecimento e facilitando o processo de investigação.The drug discovery and design process is expensive, time-consuming and resource-intensive. Various in silico methods are used to make the process more efficient and productive. Methods such as Virtual Screening often take advantage of QSAR machine learning models to more easily pinpoint the most promising drug candidates, from large pools of compounds. QSAR, which means Quantitative Structure Activity Relationship, is a ligand-based method where structural information of known ligands of a specific target is used to predict the biological activity of another molecule against that target. They are also used to improve upon an existing molecule’s pharmacologic potential by elucidating the structural composition with desirable properties. Several researchers create and develop QSAR machine learning models for a variety of different therapeutic targets. However, their use is limited by lack of access to said models. Beyond access, there are often difficulties in using published software given the need to manage dependencies and replicating the development environment. To address this issue, the application documented here was designed and developed. In this centralized platform, researchers can access several QSAR machine learning models and test their own datasets for interaction with various therapeutic targets. The platform allows the use of widespread molecule identifiers as input, such as SMILES and InChI, handling the necessary integration into the appropriate molecular descriptors to be used in the model. The platform can be accessed through a Web Application with a full graphical user interface developed with the R package Shiny and through a REST API developed with the Flask Restful package for Python. The complete application is packaged up in container technology, specifically Docker. The main goal of this platform is to grant widespread access to the QSAR models developed by the scientific community, by concentrating them in a single location and removing the user’s need to install or set up software unfamiliar to them. This intends to incite knowledge creation and facilitate the research process

An open source chemical structure curation pipeline using RDKit.

Funder: European Molecular Biology Laboratory; doi: http://dx.doi.org/10.13039/100013060BACKGROUND: The ChEMBL database is one of a number of public databases that contain bioactivity data on small molecule compounds curated from diverse sources. Incoming compounds are typically not standardised according to consistent rules. In order to maintain the quality of the final database and to easily compare and integrate data on the same compound from different sources it is necessary for the chemical structures in the database to be appropriately standardised. RESULTS: A chemical curation pipeline has been developed using the open source toolkit RDKit. It comprises three components: a Checker to test the validity of chemical structures and flag any serious errors; a Standardizer which formats compounds according to defined rules and conventions and a GetParent component that removes any salts and solvents from the compound to create its parent. This pipeline has been applied to the latest version of the ChEMBL database as well as uncurated datasets from other sources to test the robustness of the process and to identify common issues in database molecular structures. CONCLUSION: All the components of the structure pipeline have been made freely available for other researchers to use and adapt for their own use. The code is available in a GitHub repository and it can also be accessed via the ChEMBL Beaker webservices. It has been used successfully to standardise the nearly 2 million compounds in the ChEMBL database and the compound validity checker has been used to identify compounds with the most serious issues so that they can be prioritised for manual curation

The Value of New Scientific Communication Models for Chemistry

This paper is intended as a starting point for discussion on the possible future of scientific communication in chemistry, the value of new models of scientific communication enabled by web based technologies, and the necessary future steps to achieve the benefits of those new models. It is informed by a NSF sponsored workshop that was held on October 23-24, 2008 in Washington D.C. It provides an overview on the chemical communication system in chemistry and describes efforts to enhance scientific communication by introducing new web-based models of scientific communication. It observes that such innovations are still embryonic and have not yet found broad adoption and acceptance by the chemical community. The paper proceeds to analyze the reasons for this by identifying specific characteristics of the chemistry domain that relate to its research practices and socio-economic organization. It hypothesizes how these may influence communication practices, and produce resistance to changes of the current system similar to those that have been successfully deployed in other sciences and which have been proposed by pioneers within chemistry.National Science Foundation, Microsof