Author Archives: tony

About tony

Antony (Tony) J. Williams received his BSc in 1985 from the University of Liverpool (UK) and PhD in 1988 from the University of London (UK). His PhD research interests were in studying the effects of high pressure on molecular motions within lubricant related systems using Nuclear Magnetic Resonance. He moved to Ottawa, Canada to work for the National Research Council performing fundamental research on the electron paramagnetic resonance of radicals trapped in single crystals. Following his postdoctoral position he became the NMR Facility Manager for Ottawa University. Tony joined the Eastman Kodak Company in Rochester, New York as their NMR Technology Leader. He led the laboratory to develop quality control across multiple spectroscopy labs and helped establish walk-up laboratories providing NMR, LC-MS and other forms of spectroscopy to hundreds of chemists across multiple sites. This included the delivery of spectroscopic data to the desktop, automated processing and his initial interests in computer-assisted structure elucidation (CASE) systems. He also worked with a team to develop the worlds’ first web-based LIMS system, WIMS, capable of allowing chemical structure searching and spectral display. With his developing cheminformatic skills and passion for data management he left corporate America to join a small start-up company working out of Toronto, Canada. He joined ACD/Labs as their NMR Product Manager and various roles, including Chief Science Officer, during his 10 years with the company. His responsibilities included managing over 50 products at one time prior to developing a product management team, managing sales, marketing, technical support and technical services. ACD/Labs was one of Canada’s Fast 50 Tech Companies, and Forbes Fast 500 companies in 2001. His primary passions during his tenure with ACD/Labs was the continued adoption of web-based technologies and developing automated structure verification and elucidation platforms. While at ACD/Labs he suggested the possibility of developing a public resource for chemists attempting to integrate internet available chemical data. He finally pursued this vision with some close friends as a hobby project in the evenings and the result was the ChemSpider database ( Even while running out of a basement on hand built servers the website developed a large community following that eventually culminated in the acquisition of the website by the Royal Society of Chemistry (RSC) based in Cambridge, United Kingdom. Tony joined the organization, together with some of the other ChemSpider team, and became their Vice President of Strategic Development. At RSC he continued to develop cheminformatics tools, specifically ChemSpider, and was the technical lead for the chemistry aspects of the Open PHACTS project (, a project focused on the delivery of open data, open source and open systems to support the pharmaceutical sciences. He was also the technical lead for the UK National Chemical Database Service ( and the RSC lead for the PharmaSea project ( attempting to identify novel natural products from the ocean. He left RSC in 2015 to become a Computational Chemist in the National Center of Computational Toxicology at the Environmental Protection Agency where he is bringing his skills to bear working with a team on the delivery of a new software architecture for the management and delivery of data, algorithms and visualization tools. The “Chemistry Dashboard” was released on April 1st, no fooling, at, and provides access to over 700,000 chemicals, experimental and predicted properties and a developing link network to support the environmental sciences. Tony remains passionate about computer-assisted structure elucidation and verification approaches and continues to publish in this area. He is also passionate about teaching scientists to benefit from the developing array of social networking tools for scientists and is known as the ChemConnector on the networks. Over the years he has had adjunct roles at a number of institutions and presently enjoys working with scientists at both UNC Chapel Hill and NC State University. He is widely published with over 200 papers and book chapters and was the recipient of the Jim Gray Award for eScience in 2012. In 2016 he was awarded the North Carolina ACS Distinguished Speaker Award.

The National Chemical Database Service Allowing Depositions

The UK National Chemical Database Service (available here) has been online a few years now, since 2012. When I worked at RSC I was intimately involved in writing the technical response to the EPSRC call for the service and, in this blog, I outlined a lot of intentions for the project. A key part of the project from my point of view was to deliver a repository to store structures, spectra, reactions, CIF files etc as I outlined in the blog post.

“Our intention is to allow the repository to host data including chemicals, syntheses, property data, analytical data and various other types of chemistry related data. The details of this will be scoped out with the user-community, prioritized and delivered to the best of our abilities during the lifetime of the tender. With storage of structured data comes the ability to generate models, to deliver reference data as the community contributes to its validation, and to integrate and disseminate the data, as allowed by both licensing and technology, to a growing internet of the chemical sciences.”

In March 2014 at the ACS Meeting in Dallas I presented on our progress towards providing the repository (see this Slidedeck). ChemSpider has been online for over ten years and we were accepting structure depositions in the first 3 months and spectra a few weeks later (see blogpost). The ability to deposit structures as molfiles or SDF files has been available on ChemSpider for a long time and we delivered the ability to validate and standardize using the CVSP platform ( that we submitted for publication three years ago (October 28th, 2014) and is published here: With structure and spectra deposition in place for over a decade, a validation and standardization platform made public three years ago, and a lot of experience with depositing data onto ChemSpider, all building blocks have been in place for the repository.

Today I received an email into my inbox announcing “Compound and Spectra Deposition into ChemSpider“. I read it with interest as I guess it meant it was “going mainstream” in some way as it’s been around for a decade as capability. Refactoring for any mature platform should be a constant so my expectation was that this would show a more seamless process of depositing various types of data, a more beautiful interface, new whizz-bang visualization widgets building on a decade of legacy development and taking the best of what we built as data registration, structure validation and standardization (and all of its lessons!) and rebuilds of some of the spectral display components that we had. It’s not quite what I found when I tested it.

Here’s my review.

My expectations would be to go to and deposit data to ChemSpider. The website is simply a blue button with “Log in with your ORCID”. There is language recognizing that the OpenPHACTS project funded the validation and standardization platform work which is definitely appropriate but some MORE GUIDANCE as to what the site is would be good!

“Validation and standardisation of the chemical structures was developed as part of the Open PHACTS project and received support from the Innovative Medicines Initiative Joint Undertaking under grant agreement no. 115191, resources of which are composed of financial contribution from the European Union’s Seventh Framework Programme (FP7/2007-2013) and EFPIA companies’ in-kind contribution.”

This means that it should be possible to deposit a molfile, have it checked (validated) and standardized then deposited into ChemSpider, having passed through CVSP. So what happened?

I downloaded the structure of Chlorothalonil from our dashboard and loaded it. The result is shown below. The structure was standardized and correctly recognized as a V3000 molfile. The original structure was not visible, there were no errors or warnings and the structure DID standardize.

Deposition into ChemSpider failed with an Oops

Next I tried a structure from ChemSpider, because if the structures are going INTO ChemSpider then I should be able to load one that comes FROM ChemSpider. I wanted to get something fun so grabbed one of the many Taxol-related structures. There are 61 Taxol-related structures in total. I downloaded the version with multiple C13-labels. It looked like this:

When I uploaded this, a V2000 molfile, the result is as shown below.

The original isotope labels were removed, the layout was recognized as congested and partially defined stereo recognized. But it wouldn’t deposit. I tried many others and they would not deposit and was going to give up but tried Benzene, V2000, downloaded from ChemSpider. And….YAY….it went in. The result is below.

A unique DOI is issued to the record, associated with my name. It is NOT deposited into ChemSpider as far as I can tell because the structure is already in ChemSpider. There is also no link from ChemSPider back to my deposition, that I can find. My next try was to find a chemical NOT in ChemSpider and to deposit that. That failed. I tried Benzene again and it worked a second time. I judged that maybe a simple alkyl chain would work for deposition. The result is below.

The warning “Contains completely undefined stereo: mixtures” does not make sense at all for this chemical. PLUS it wouldn’t deposit.

I then tried to register a sugar as a projection with the result shown below. I consider this one to have some real errors and do not AT ALL like the standardized version.

I tried a simple inorganic. I think KCl should be recognized as an ionic compound as K+Cl-, at least SOME warning!?

The testing I did took about an hour overall. I identified a LOT of issues. I think this release, while it may be a beta release for feedback, is way premature and needs a lot more testing. I am hopeful that more people will fully test the platform as the ABILITY to deposit data, get a DOI, and associate it with your ORCID account, but it’s not obvious that anything is linked back to ORCID and it is nothing more than being used for login.

I did NOT test spectral deposition but am concerned that the request seems to be for original data. In binary vendor file format? Uh-oh. That’s not a good idea!

I hope this blog motivates the community to test, give feedback and push the deposition system to deal with complex chemistries so at least the boundary conditions of performance for Deposit.ChemSpider.Com, which appears to be more of writing a chemical to some other repository as there is no real connection to ChemSpider I can find (?), can be defined, the system can be improved and a community can be built around the functionality.

Building public domain chemistry databases is hard work. User feedback and guidance is essential. Please give your feedback and test the system.


Posted by on October 20, 2017 in Uncategorized


Call for Abstracts for ACS Spring 2018 Symposium ” Applications of Cheminformatics to Environmental Chemistry”

Grace Patlewicz and I have the pleasure of hosting a symposium at the Spring 2018 ACS National Meeting in New Orleans as outlined below. We believe that a presentation from you would enhance the line-up for the gathering and encourage you to consider our invitation. Our expectations are that we will have a full day of stimulating presentations and discussions regarding the application of cheminformatics to Environmental Chemistry. We sincerely hope you will consider our invitation and  submit an abstract to the CINF division listed at  Please confirm your intention to participate via email. Thank you in advance.

 Applications of Cheminformatics to Environmental Chemistry

Cheminformatics and computational chemistry have had an enormous impact in regards to providing environmental chemists access to data, information and software tools and algorithms. There is an increasing number of online resources and software tools and the ability to source data, perform real time QSAR prediction and even read-across analyses online is now available. Environmental scientists generally seek chemical data in the form of chemical properties, environmental fate and transport or toxicity-based endpoints. They also search for data regarding chemical function and use, information regarding their exposure potential, and their transformation in environmental and biological systems. The increasing rate of production and release of new chemicals into commerce requires improved access to historical data and information to assist in hazard and risk assessment. High-throughput in vitro and in silico analyses increasingly are being brought to bear to rapidly screen chemicals for their potential impacts and interweaving this information with more traditional in vivo toxicity data and exposure estimation to provide integrated insight into chemical risk is a burgeoning frontier on the cusp of cheminformatics and environmental sciences.

This symposium will bring together a series of talks to provide an overview of the present state of data, tools, databases and approaches available to environmental chemists. The session will include the various modeling approaches and platforms, will examine the issues of data quality and curation, and intends to provide the attendees with details regarding availability, utility and applications of these systems. We will focus especially on the availability of Open systems, data and code to ensure no limitations to access and reuse.

The topics that would be covered in this session are, but are not limited to:


  • Environmental chemistry databases
  • Data: Quality, Modeling and Delivery
  • Computational hazard and risk assessment
  • Prioritizing environmental chemicals using screening and predictive computational tools
  • Standards for data exchange and integration in environmental chemistry
  • Implementations of Read-across prediction
  • Adverse Outcome Pathway data and delivery


Please submit your abstracts using the ACS Meeting Abstracts Programming System (MAPS) at  General information about the conference can be found at  Any other inquiries should be directed to the symposium organizers:

Antony J. Williams and Grace Patlewicz, National Center for Computational Toxicology, Environmental Protection Agency, Research Triangle Park, Durham, NC

Emails: and

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Posted by on September 20, 2017 in Uncategorized


Call for Abstracts for ACS Spring 2018 Symposium: “Open Resources for automated structure verification and elucidation”

I have the pleasure of hosting a symposium with Emma Schymanski at the Spring 2018 ACS National Meeting in New Orleans as outlined below. Our expectations are that we will have a full day of stimulating presentations and discussions regarding how Open Resources, specifically data and software, can support automated structure verification and elucidation. If this is an area of research for you please submit an abstract to the ANYL division listed at

Open Resources for automated structure verification and elucidation

Antony J. Williams1 and Emma L. Schymanski2
1National Center for Computational Toxicology, US EPA, Research Triangle Park, Durham, NC, USA.
2Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Campus Belval, Luxembourg.
Cheminformatics methods form an essential basis for providing analytical scientists with access to data, algorithms and workflows. There are an increasing number of free online databases (compound databases, spectral libraries, data repositories) and a rich collection of software approaches that can be used to support automated structure verification and elucidation, specifically for Nuclear Magnetic Resonance (NMR) and Mass Spectrometry (MS). This symposium will bring together a series of speakers to overview the state of data, tools, databases and approaches available to support chemical structure verification and elucidation. The session will cover the different databases and libraries available and examine the issues of data quality and curation. We intend to provide attendees with details regarding availability (both online and offline), utility and application of various tools and algorithms to support their identification and interpretation efforts. We will focus especially on the availability of Open systems, data and code with no limitations to access and reuse, yet reflect critically on the potential limitations and future needs of Open approaches. Case studies will demonstrate the potential for cheminformatics to enable single-structure elucidation through to high throughput, untargeted data discovery approaches. This work does not necessarily reflect U.S. EPA policy.

Emma Schymanski and Antony Williams,
Chairs of the Open Resources for automated structure verification and elucidation symposium,
ANYL Division, ACS Spring Meeting 2018, New Orleans


Online networking, data sharing and research activity distribution tools for scientists

This is just a short post, and I need to write more when I have time, about the result of a writing collaboration with Lou Peck and Sean Ekins on an article entitled “The new alchemy: Online networking, data sharing and research activity distribution tools for scientists” ( This took a LONG time to get published, and morphed from the original concept, but there appears to be a lot of interest judging by the views and downloads stats in the first few days (775 views and 20% of this number as downloads). That’s a good conversion rate. It’s open for PUBLIC COMMENTS and we welcome your feedback.

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Posted by on August 8, 2017 in AltMetrics, ImpactStory


Predicting organ toxicity using in vitro bioactivity data and chemical structure

I get to work with some great scientists in my job. I am getting to work on projects that a couple of years ago were way out of my depth. Let’s be honest, I have no formal training as a toxicologist and my training is formally as an analytical scientist, then cheminformatician, then into publishing and informatics and now in the National Center for Computational Toxicology. I didn’t realize that the trial by fire would be so stimulating and fun but working at EPA is great. So many people make flippant comments about working for the government, leaving early, etc. We work HARD and are productive and, for me at least, I feel we are doing important work and making real contributions. The latest paper I am involved with is “Predicting organ toxicity using in vitro bioactivity data and chemical structure” ( The abstract is listed below…

“Animal testing alone cannot practically evaluate the health hazard posed by tens of thousands of environmental chemicals. Computational approaches making use of high-throughput experimental data may provide more efficient means to predict chemical toxicity. Here, we use a supervised machine learning strategy to systematically investigate the relative importance of study type, machine learning algorithm, and type of descriptor on predicting in vivo repeat-dose toxicity at the organ-level. A total of 985 compounds were represented using chemical structural descriptors, ToxPrint chemotype descriptors, and bioactivity descriptors from ToxCast in vitro high-throughput screening assays. Using ToxRefDB, a total of 35 target organ outcomes were identified that contained at least 100 chemicals (50 positive and 50 negative). Supervised machine learning was performed using Naïve Bayes, k-nearest neighbor, random forest, classification and regression trees, and support vector classification approaches. Model performance was assessed based on F1 scores using five-fold cross-validation with balanced bootstrap replicates. Fixed effects modeling showed the variance in F1 scores was explained mostly by target organ outcome, followed by descriptor type, machine learning algorithm, and interactions between these three factors. A combination of bioactivity and chemical structure or chemotype descriptors were the most predictive. Model performance improved with more chemicals (up to a maximum of 24%) and these gains were correlated (ρ= 0.92) with the number of chemicals. Overall, the results demonstrate that a combination of bioactivity and chemical descriptors can accurately predict a range of target organ toxicity outcomes in repeat-dose studies, but specific experimental and methodologic improvements may increase predictivity.”

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Posted by on August 6, 2017 in EPA Presentations


Open Science for Identifying “Known Unknown” Chemicals

I am happy to announce the publishing of an article regarding “Open Science for Identifying “Known Unknown” Chemicals” at I have been involved with two other articles about the identification of “Known Unknowns”.

The first one was a ChemSpider article: “”Identification of “known unknowns” utilizing accurate mass data and ChemSpider”. Journal of The American Society for Mass Spectrometry. 23: 179–185. doi:10.1007/s13361-011-0265-y.”

The second one was a recent article from the EPA: “”Identifying known unknowns using the US EPA’s CompTox Chemistry Dashboard”. Analytical and Bioanalytical Chemistry. 409: 1729–1735. doi:10.1007/s00216-016-0139-z.”

The most recent publication was a collaboration with Emma Schymanski from Eawag and it was a real pleasure to write this together. If you are interested in how Open Science can contribute to the challenges associated with the identification of known unknowns check out our latest publication!


In Silico Prediction of Physicochemical Properties of Environmental Chemicals Using Molecular Fingerprints and Machine Learning

Recently we published on the curation of physicochemical data sets that were then made available as Open Data. The work was reported in:

“An automated curation procedure for addressing chemical errors and inconsistencies in public datasets used in QSAR modeling, SAR and QSAR in Environmental Research, K. Mansouri, C.Grulke, R. Judson and A.J. Williams, SAR and QSAR in Environmental Research,Volume 27 2016 – Issue 11, Pages 911-937

The data has since been modeled using an alternative approach to that we used and is now reported in


“In Silico Prediction of Physicochemical Properties of Environmental Chemicals Using Molecular Fingerprints and Machine Learning, Q. Zang, K. Mansouri, A.J. Williams, R.S. Judson, D.G. Allen, W.M. Casey, and N.C. Kleinstreuer, J. Chem. Inf. Model., 2017, 57 (1), pp 36–49″

The abstract for the article is below


There are little available toxicity data on the vast majority of chemicals in commerce. High-throughput screening (HTS) studies, such as those being carried out by the U.S. Environmental Protection Agency (EPA) ToxCast program in partnership with the federal Tox21 research program, can generate biological data to inform models for predicting potential toxicity. However, physicochemical properties are also needed to model environmental fate and transport, as well as exposure potential. The purpose of the present study was to generate an open-source quantitative structure–property relationship (QSPR) workflow to predict a variety of physicochemical properties that would have cross-platform compatibility to integrate into existing cheminformatics workflows. In this effort, decades-old experimental property data sets available within the EPA EPI Suite were reanalyzed using modern cheminformatics workflows to develop updated QSPR models capable of supplying computationally efficient, open, and transparent HTS property predictions in support of environmental modeling efforts. Models were built using updated EPI Suite data sets for the prediction of six physicochemical properties: octanol–water partition coefficient (logP), water solubility (logS), boiling point (BP), melting point (MP), vapor pressure (logVP), and bioconcentration factor (logBCF). The coefficient of determination (R2) between the estimated values and experimental data for the six predicted properties ranged from 0.826 (MP) to 0.965 (BP), with model performance for five of the six properties exceeding those from the original EPI Suite models. The newly derived models can be employed for rapid estimation of physicochemical properties within an open-source HTS workflow to inform fate and toxicity prediction models of environmental chemicals.

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Posted by on February 19, 2017 in Publications and Presentations



How Poor Altmetrics are for my old articles…

In preparation for a talk later this week I have been investigating adding Altmetric and Plum analytics scores into my online CV as we as Kudos Resources. I would expect that Altmetric scores would be VERY low for old articles as they were published way before the social networking tools existed. However, the Plum Widget should be useful in terms of showing citations, views and downloads etc. The Kudos resources will be meaningful since I have been working SLOWLY through my articles with the latest first.

I think the Altmetric scores shown below bears out my opinion since MOST don’t have any score whatsoever. However, this blog post should lift a number of them over the next few days.


1. F.L. Lee, K.F. Preston, A.J. Williams, L.H. Sutcliffe, A.J. Banister, S.T. Wait, A single-crystal electron paramagnetic resonance study of the 4-phenyl-1,2,3,5-dithiadiazolyl radical   Magn. Reson. Chem. 27, 1161-1165 (1989). Link
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2. D.G. Gillies, S.J. Matthews, L.H. Sutcliffe and A.J. Williams, The Evaluation of Two Correlation Times for Methyl Groups from Carbon-13 Spin-lattice Relaxation Times and nOe Data  J. Magn. Reson., 86, 371 (1990) Link
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3. P.J. Bratt, D.G. Gillies, L.H. Sutcliffe and A.J. Williams, NMR Relaxation Studies of Internal Motions – A Comparison between Micelles and Related Systems, J. Phys. Chem., 94(7), 2727 (1990) Link
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4. R.C. Hynes, J.R. Morton, J.A. Hriljac, Y. LePage, K.F. Preston, A.J. Williams, F. Evans, M.C. Grossel and L.H. Sutcliffe,  Isolated Free Radical Pairs in Rb+TCNQ- 18-crown-6 Single Crystals, J.Chem. Soc.,Chem. Commun., 5, 439 (1990) Link
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5. P.J. Krusic, J.R. Morton, K.F. Preston, A.J. Williams and F. Lee, EPR Spectrum of the Fe2(CO)8- Radical Trapped in Single Crystals of PPN+HFe2(CO)8- , Organometallics 9, 697 (1990). Link
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6. R. Hynes, K.F. Preston, J.J. Springs, and A.J. Williams, Single-crystal EPR Study of Radical Pairs in [Fe(mesitylene)22+] {C3[C(CN)2]3-}2, J. Chem. Phys. 93(4), 2222, 1990 Link
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7. R. Hynes, K.F. Preston, J.J. Springs, and A.J. Williams, EPR Studies of Radical Pairs [M(CO)5]2 (M = Cr, Mo, W) Trapped in Single Crystals of PPN+ HM(CO)5-, Organometallics, 9, 2298 (1990) Link
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8. R. Hynes, K.F. Preston, J.J. Springs, and A.J. Williams, Electron paramagnetic resonance study of the tetracarbonyl(trimethylphosphite)tungstate(1-) radical anion trapped in a single crystal of [N(PPh3)2][W(CO)4H{P(OMe)3}], Journal of the Chemical Society, Dalton Transactions:  Inorganic Chemistry (1972-1999)  12, 3655-61(1990) Link
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9. R. Hynes, K.F. Preston, J.J. Springs, J. Tse and A.J. Williams, EPR Studies of M(CO)5-  Radicals (M = Cr, Mo, W) Trapped in Single Crystals of PPh4+ HM(CO)5- , J. Chem. Soc. Faraday Trans., 87(19), 3121 (1991) Link
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10. R.C. Hynes, J.R. Morton, K.F. Preston, A.J. Williams, F. Evans, M.C. Grossel, L.H. Sutcliffe, and S.C. Weston, An EPR Study of Isolated Free Radical Pairs in M+ 18-Crown-6 TCNQ-  salts (TCNQ:7,7,8,8-tetracyanoquinodimethane; M=K, Rb), J. Chem. Soc. Faraday Trans., 87(14), 2229 (1991) Link
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To show what it looked like when I posted this blog entry the attached image shows a small number of the articles with zero scores.

altmetric scores

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Posted by on January 10, 2017 in AltMetrics


Add Altmetric and PlumX scores and Kudos Resources to your online CV

Over the weekend I spent a little time working to integrate Altmetric and PlumX scores to my online CV here on my blog. I also integrated my Kudos resources associated with an article directly into the’s a breeze and requires only that you have DOIs for your article. See below for how ONE article in my CV is represented.

154. Programmatic Conversion of Crystal Structures into 3D Printable Files, V.F. Scalfani, <strong>A.J. Williams</strong>, V. Tkachenko, K. Karapetyan, A. Pshenichnov, R.M. Hanson, J.M. Liddie and J.E. Bara, Journal of Cheminformatics, 2016, 8:66 Article Type: Methodology <a href=””><strong>Link</strong> </a>
<strong>AltMetrics Analytics</strong>
<div class=”altmetric-embed” data-badge-type=”medium-donut” data-badge-details=”right” data-doi=”10.1186/s13321-016-0181-z“></div>
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<a href=’‘ class=’plumx-plum-print-popup’></a>
<strong>Kudos Resources</strong>
<script src=”//“></script>

Literally all you have to do is copy these few lines and swap out the DOI and the scores and Kudos resources will show up in your CV. Simple.

Altmetric, PlumX and Kudos Embedded widgets

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Posted by on January 9, 2017 in AltMetrics, Kudos, ORCID


Comparing the EPA CompTox Dashboard with ChemSpider for MS-based Structure Identification

It’s almost ten years, this April, since ChemSpider was released to the public at the 233rd ACS meeting in Chicago. For two years, prior to being acquired by RSC in May 2009, we worked very closely with a number of mass spectrometry vendors including Waters (Micromass), Thermo and Agilent. I always considered that the work that we did with ChemSpider could be highly valued by the mass spectrometry community. This was especially true after we published the work for the identification of known unknowns with James Little (  Certainly ChemSpider has become highly recognized, and used, by an increasing number of mass spectrometry vendors (through the ChemSpider Web Services).

A few months ago Andrew McEachran joined our team as a postdoc. Combining my experience with bringing ChemSpider to bear for the purpose of structure identification, his mass spectrometry skills and experience, and our tremendous development team to the development of the CompTox Chemistry Dashboard, we were able to make some further advances in the “identification known unknowns”. Our efforts were recently reported in this publication “Identifying known unknowns using the US EPA’s CompTox Chemistry Dashboard” ( Readers are pointed to the summary tables in the article (results) demonstrating the improved performance of the CompTox Chemistry Dashboard based on high quality data sources and new approaches to rank ordering results based on formula and mass searching.

We recently rolled out new functionality and “MS-Ready structure batch-based searching” to offer even greater support for MS-structure identification . We will report on further extensions to this work at the Spring ACS Meeting.

The AltMetrics for the Article are shown below