Archive for category ChemConnector

Social Media Tools for Scientists and Building an Online Profile

This presentation will be given at the Janelia Farm Research Campus, a research campus of the Howard Hughes Medical Institute. The presentation abstract is below.

ABSTRACT
Despite the availability of many platforms for scientists to connect and share with their peers in the scientific community the majority do not make use of these tools, despite their promise and potential impact and influence on our careers. We are already being indexed and exposed on the internet via our publications, presentations and data and new “AltMetric scores” are being assigned to scientific publications as measures of popularity and, supposedly, of impact. We now have even more ways to contribute to science, to annotate and curate data, to “publish” in new ways, and many of these activities are as part of a growing crowdsourcing network. This presentation provides an overview of the various types of networking and collaborative sites available to scientists and ways to expose your scientific activities online. It will discuss the new world of AltMetrics that is in an explosive growth curve and will help you understand how to influence and leverage some of these new measures. Participating online, whether it be simply for career advancement or for wider exposure of your research, there are now a series of web applications that can provide a great opportunity to develop a scientific profile within the community.

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Investigating Impact Metrics for Performance for the US-EPA National Center for Computational Toxicology

This presentation was presented at the American Chemical Society in Philadelphia in August 2016

DAY & TIME OF PRESENTATION: Sunday, August, 21, 2016 from 4:10 PM – 4:30 PM
ROOM & LOCATION: Room 112B – Pennsylvania Convention Center

Title: Investigating Impact Metrics for Performance for the US-EPA National Center for Computational Toxicology

The U.S. Environmental Protection Agency (EPA) Computational Toxicology Program integrates advances in biology, chemistry, and computer science to help prioritize chemicals for further research based on potential human health risks. This work involves computational and data driven approaches that integrate chemistry, exposure and biological data. We have delivered public access to terabytes of open data, as well to a large number of publicly accessible databases and applications, to support the research efforts for a large community of scientists. Many of our contributions to science are summarily described in research papers but  to date we have not optimized our contributions to  inform altmetrics statistics associated with our work. Critically missing from altmetrics is access to our numerous software applications and web service accesses, as well as the growing importance of our experimental data and models (e.g ToxCast, ExpoCast, DSSTox and others) to the scientific and regulatory communities.  This presentation will provide an overview of our efforts to more fully understand, and quantify, our impact on the environmental sciences using a combination of our measurement approaches and available altmetrics tools. This abstract does not reflect U.S. EPA policy.

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Presentations and Posters at #ACSPhiladelphia August 2016

I will be delivering five presentations and a poster (twice) at the ACS Meeting in Philadelphia this week. These presentations will introduce the latest version of our CompTox Dashboard, renamed from the iCSS Chemistry Dashboard because now we are offering way more than just a large set of chemical structures! I look forward to introducing attendees to the latest and greatest.

DAY & TIME OF PRESENTATION: Sunday, August, 21, 2016 from 1:10 PM – 1:35 PM
ROOM & LOCATION: Room 105A – Pennsylvania Convention Center

Title: Structure Identification Using High Resolution Mass Spectrometry Data and the EPA’s Chemistry Dashboard

The iCSS Chemistry Dashboard is a publicly accessible dashboard provided by the National Center for Computation Toxicology at the US-EPA. It serves a number of purposes, including providing a chemistry database underpinning many of our public-facing projects (e.g. ToxCast and ExpoCast). The available data and searches provide a valuable path to structure identification using mass spectrometry as the source data. With an underlying database of over 720,000 chemicals, the dashboard has already been used to assist in identifying chemicals present in house dust. However, it can also be applied to many other purposes, e.g., the identification of agrochemicals in waste streams. This presentation will provide a review of the EPA’s platform and underlying algorithms used for the purpose of compound identification using high-resolution mass spectrometry data. We will also discuss progress towards a high-throughput non-targeted analysis platform for use by the mass spectrometry community.  This abstract does not reflect U.S. EPA policy.

 

DAY & TIME OF PRESENTATION: Sunday, August, 21, 2016 from 4:10 PM – 4:30 PM
ROOM & LOCATION: Room 112B – Pennsylvania Convention Center

Title: Investigating Impact Metrics for Performance for the US-EPA National Center for Computational Toxicology

The U.S. Environmental Protection Agency (EPA) Computational Toxicology Program integrates advances in biology, chemistry, and computer science to help prioritize chemicals for further research based on potential human health risks. This work involves computational and data driven approaches that integrate chemistry, exposure and biological data. We have delivered public access to terabytes of open data, as well to a large number of publicly accessible databases and applications, to support the research efforts for a large community of scientists. Many of our contributions to science are summarily described in research papers but  to date we have not optimized our contributions to  inform altmetrics statistics associated with our work. Critically missing from altmetrics is access to our numerous software applications and web service accesses, as well as the growing importance of our experimental data and models (e.g ToxCast, ExpoCast, DSSTox and others) to the scientific and regulatory communities.  This presentation will provide an overview of our efforts to more fully understand, and quantify, our impact on the environmental sciences using a combination of our measurement approaches and available altmetrics tools. This abstract does not reflect U.S. EPA policy.

DAY & TIME OF PRESENTATION: Wednesday, August, 24, 2016 from 9:40 AM – 10:00 AM
ROOM & LOCATION:
Juniper’s Ballroom – Philadelphia Downtown Courtyard by Marriott

Title: Delivering The Benefits of Chemical-Biological Integration in Computational Toxicology at the EPA

Abstract: Researchers at the EPA’s National Center for Computational Toxicology integrate advances in biology, chemistry, and computer science to examine the toxicity of chemicals and help prioritize chemicals for further research based on potential human health risks. The intention of this research program is to quickly evaluate thousands of chemicals for potential risk but with much reduced cost relative to historical approaches. This work involves computational and data driven approaches including high-throughput screening, modeling, text-mining and the integration of chemistry, exposure and biological data. We have developed a number of databases and applications that are delivering on the vision of developing a deeper understanding of chemicals and their effects on exposure and biological processes that are supporting a large community of scientists in their research efforts. This presentation will provide an overview of our work to bring together diverse large scale data from the chemical and biological domains, our approaches to integrate and disseminate these data, and the delivery of models supporting computational toxicology. This abstract does not reflect U.S. EPA policy.

 

DAY & TIME OF PRESENTATION: Wednesday, August, 24, 2016 from 11:10 AM – 11:40 AM
ROOM & LOCATION: Ormandy East – DoubleTree by Hilton Hotel Philadelphia Center City

Title: Data Aggregation, Curation and Modeling Approaches to Deliver Prediction Models to Support Computational Toxicology at the EPA

The U.S. Environmental Protection Agency (EPA) Computational Toxicology Program develops and utilizes QSAR modeling approaches across a broad range of applications. In terms of physical chemistry we have a particular interest in the prediction of basic physicochemical parameters such as logP, aqueous solubility, vapor pressure and other parameters to invoke in our exposure models or for the purpose of modeling environmental toxicity. We are also interested in the development of models related to environmental fate. As a result of our efforts we have assembled and curated data sets for various physicochemical properties and, utilizing modern machine-learning modeling approaches, have developed a number of high performing models that we are now delivering to the public. Our website, the iCSS Chemistry Dashboard, provides access to data predicted for over 700,000 chemical compounds. The original training data are available for review and the details of prediction for each endpoint include the domain of applicability as well as a measure of performance accuracy.  This presentation will provide an overview of the existing aggregated data, our approaches to data curation and our progress towards an interactive environment for prediction of physicochemical and environmental fate parameters. The utilization of these parameters to support read-across approaches will also be discussed. This abstract does not reflect U.S. EPA policy.

 

DAY & TIME OF PRESENTATION: Thursday, August, 25, 2016 from 3:00 PM – 3:20 PM
ROOM & LOCATION:: Room 104A – Pennsylvania Convention Center

Title: The EPA iCSS Chemistry Dashboard to Support Compound Identification Using High Resolution Mass Spectrometry Data

There is a growing need for rapid chemical screening and prioritization to inform regulatory decision-making on thousands of chemicals in the environment. We have previously used high-resolution mass spectrometry to examine household vacuum dust samples using liquid chromatography time-of-flight mass spectrometry (LC-TOF/MS). Using a combination of exact mass, isotope distribution, and isotope spacing, molecular features were matched with a list of chemical formulas from the EPA’s Distributed Structure-Searchable Toxicity (DSSTox) database. This has further developed our understanding of how openly available chemical databases, together with the appropriate searches, could be used for the purpose of compound identification. We report here on the utility of the EPA’s iCSS Chemistry Dashboard for the purpose of compound identification using searches against a database of over 720,000 chemicals. We also examine the benefits of QSAR prediction for the purpose of retention time prediction to allow for alignment of both chromatographic and mass spectral properties. This abstract does not reflect U.S. EPA policy.

 

SESSION: Sci-Mix
SESSION TIME:
August 22, 2016 from 8:00 PM to 10:00 PM

and

SESSION TIME: Wednesday, August, 24, 2016, 6:00 PM – 8:00 PM
ROOM & LOCATION:
Hall D – Pennsylvania Convention Center

Poster Title: The EPA Online Prediction Physicochemical Prediction Platform to Support Environmental Scientists

As part of our efforts to develop a public platform to provide access to predictive models we have attempted to disentangle the influence of the quality versus quantity of data available to develop and validate QSAR models.  Using a thorough manual review of the data underlying the well-known EPI Suite software, we developed automated processes for the validation of the data using a KNIME workflow. This includes: approaches to validate different chemical structure representations (e.g. molfile and SMILES), identifiers (chemical names and registry numbers), and methods to standardize the data into QSAR-consumable formats for modeling. Our efforts to quantify and segregate data into various quality categories has allowed us to thoroughly investigate the resulting models developed from these data slices, as well as allowing us to examine whether or not efforts into the development of large high-quality datasets has the expected pay-off in terms of prediction performance. Machine-learning approaches have been applied to create a series of models that have been used to generate predicted physicochemical and environmental parameters for over 700,000 chemicals. These data are available online via the EPA’s iCSS Chemistry Dashboard. This abstract does not reflect U.S. EPA policy.

 

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NCSU Presentation: Data integration and building a profile for yourself as an online scientist

This is a presentation I gave at North Carolina State University hosted by Denis Fourches.

Data integration and building a profile for yourself as an online scientist

Many of us nowadays invest significant amounts of time in sharing our activities and opinions with friends and family via social networking tools. However, despite the availability of many platforms for scientists to connect and share with their peers in the scientific community the majority do not make use of these tools, despite their promise and potential impact and influence on our future careers. We are being indexed and exposed on the internet via our publications, presentations and data. We also have many more ways to contribute to science, to annotate and curate data, to “publish” in new ways, and many of these activities are as part of a growing crowdsourcing network. This presentation will provide an overview of the various types of networking and collaborative sites available to scientists and ways to expose your scientific activities online. Many of these can ultimately contribute to the developing measures of you as a scientist as identified in the new world of alternative metrics. Participating offers a great opportunity to develop a scientific profile within the community and may ultimately be very beneficial, especially to scientists early in their career.

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A chemistry data repository to serve them all

A presentation that I am giving around UK universities in September/October 2014

A chemistry data repository to serve them all

Over the past five years the Royal Society of Chemistry has become world renowned for its public domain compound database that integrates chemical structures with online resources and available data. ChemSpider regularly serves over 50,000 users per day who are seeking chemistry related data. In parallel we have used ChemSpider and available software services to underpin a number of grant-based projects that we have been involved with: Open PHACTS – a semantic web project integrating chemistry and biology data, PharmaSea – seeking out new natural products from the ocean and the National Chemical Database Service for the United Kingdom. We are presently developing a new architecture that will offer broader scope in terms of the types of chemistry data that can be hosted. This presentation will provide an overview of our Cheminformatics activities at RSC, the development of a new architecture for a data repository that will underpin a global chemistry network, and the challenges ahead, as well as our activities in releasing software and data to the chemistry community.

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Using an online database of chemical compounds for the purpose of structure identification #ACSsanfran

Using an online database of chemical compounds for the purpose of structure identification

Online databases can be used for the purposes of structure identification. The Royal Society of Chemistry provides access to an online database containing tens of millions of compounds and this has been shown to be a very effective platform for the development of tools for structure identification. Since in many cases an unknown to an investigator is known in the chemical literature or reference database, these “known unknowns” are commonly available now on aggregated internet resources. The identification of these types of compounds in commercial, environmental, forensic, and natural product samples can be identified by searching against these large aggregated databases querying by either elemental composition or monoisotopic mass. Searching by elemental composition is the preferred approach as it is often difficult to determine a unique elemental composition for compounds with molecular weights greater than 600 Da. In these cases, searching by the monoisotopic mass is advantageous. In either case, the search results can be refined by appropriate filtering to identify the compounds. We will report on integrated filtering and search approaches on our aggregated compound database for the purpose of structure identification and review our progress in using the platform for natural product dereplication purposes.

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Dealing with the Complex Challenge of Managing Diverse Chemistry Data Online to Enable Chemistry Across the World #ACSsanfran

This is my third presentation today at the ACS meeting in San Francisco on 11th August 2014

Dealing with the Complex Challenge of Managing Diverse Chemistry Data Online to Enable Chemistry Across the World

The Royal Society of Chemistry has provided access to data associated with millions of chemical compounds via our ChemSpider database for over 5 years. During this period the richness and complexity of the data has continued to expand dramatically and the original vision for providing an integrated hub for structure-centric data has been delivered across the world to hundreds of thousands of users. With an intention of expanding the reach to cover more diverse aspects of chemistry-related data including compounds, reactions and analytical data, to name just a few data-types, we are in the process of implementing a new architecture to build a Chemistry Data Repository. The data repository will manage the challenges of associated metadata, the various levels of required security (private, shared and public) and exposing the data as appropriate using semantic web technologies. Ultimately this platform will become the host for all chemicals, reactions and analytical data contained within RSC publications and specifically supplementary information. This presentation will report on how our efforts to manage chemistry related data has impacted chemists and projects across the world and will review specifically our contributions to projects involving natural products for collaborators in Brazil and China, for the Open Source Drug Discovery project in India, and our collaborations with scientists in Russia.

 

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Teaching analytical spectroscopy using online spectroscopic data #ACSsanfran

My first talk of three on August 11th 2014 at the ACS San Francisco meeting

Teaching analytical spectroscopy using online spectroscopic data

The teaching of spectroscopy can be a complex and challenging task. The Royal Society of Chemistry has been developing online resources for a number of years that provide access to analytical data as well as interactive quizzes and challenge sets. The RSC data repository houses over 250,000 spectra at this time including mass spectrometry, NMR and IR data and these are utilized to provide online games to test students capabilities, to underpin the SpectraSchool  training website and to produce source data for students and teachers alike to use in their teaching and self-training efforts. This presentation will provide an overview of RSC resources that can be used to teach spectroscopy using our online data and tools.

 

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How the InChI identifier is used to underpin our online chemistry databases at the Royal Society of Chemistry #ACSsanfran

This is my presentation at the ACS San Francisco Fall Meeting on August 10th 2014

How the InChI identifier is used to underpin our online chemistry databases at the Royal Society of Chemistry

The Royal Society of Chemistry hosts a growing collection of online chemistry content. For much of our work the InChI identifier is an important component underpinning our projects. This enables the integration of chemical compounds with our archive of scientific publications, the delivery of a reaction database containing millions of reactions as well as a chemical validation and standardization platform developed to help improve the quality of structural representations on the internet. The InChI has been a fundamental part of each of our projects and has been pivotal in our support of international projects such as the Open PHACTS semantic web project integrating chemistry and biology data and the PharmaSea project focused on identifying novel chemical components from the ocean with the intention of identifying new antibiotics. This presentation will provide an overview of the importance of InChI in the development of many of our eScience platforms and how we have used it to provide integration across hundreds of websites and chemistry databases across the web. We will discuss how we are now expanding our efforts to develop a platform encompassing efforts in Open Source Drug Discovery and the support of data management for neglected diseases.

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Presentation at the 2014 Allen Press Emerging Trends in Scholarly Publishin Seminar

Today I gave a presentation at the 2014 Allen Press Emerging Trends in Scholarly Publishing™ Seminar here in Washington DC. Over coffee I had very positive feedback about what we are doing at RSC and various comments about “real science exposed by a publisher”. The abstract and Slideshare presentation are below.

The Application of Text and Data Mining to Enhance the Royal Society of Chemistry Publication Archive

The Royal Society of Chemistry (RSC) is one of the world’s most prominent scientific societies and STM publishers. Our contributions to the scientific community include the delivery of a myriad of resources to support the chemistry community to access chemistry-related data, information and knowledge. This includes ChemSpider, a compound centric platform linking together over 30 million chemical compounds with internet-based resources. Using this compound database and its associated chemical identifiers as a basis the RSC is utilizing text and data mining approaches to data enable our published archive of scientific publications. This presentation will provide an overview of our technical approaches to text and data enable our archive of scientific articles, how we are developing an integrated database of chemical compounds, reactions, physical and analytical data and how it will be used to facilitate scientific discovery.

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