Archive for category People in Science

Richard D. Cramer selected as 2013 Herman Skolnik Award recipient

Richard D. Cramer selected as 2013 Herman Skolnik Award recipient

Dr. Richard D. (Dick) Cramer will be the recipient of the 2013 Herman Skolnik Award presented by the ACS Division of Chemical Information.

The award recognizes outstanding contributions to and achievements in the theory and practice of chemical information science and related disciplines. The prize consists of a $3,000 honorarium and a plaque. Dr. Cramer will also be invited to present an award symposium at the Fall 2013 ACS National Meeting to be held in Indianapolis.

Cramer is best known as the inventor of the technique of Comparative Molecular Field Analysis (CoMFA) and its introduction to the molecular and drug design fields (JACS 1998, 110, 5959-5967).  The technique and its implementation was one of the one of the first widely available and usable 3D QSAR software methods and was developed in collaboration with David Patterson and Jeffrey Bunce.  The CoMFA process was one of the first patents in the cheminformatics and computational chemistry fields and has been used in the pharmaceutical industry as the standard method for small molecule bioactivity prediction for the last twenty-five years.

Early in his career, in the research group of E.J. Corey, he was involved with the first artificial intelligence methods to predict chemical synthesis, coining the acronym ‘LHASA’ (Logic and Heuristics Applied to Synthetic Analysis) for the project, which is known today as one of the very first attempts at computer aided design in chemistry.  While his entire later career has been in industry, Cramer has taken an academic approach to solving complex problems and this has resulted in a number of break-through developments that are synonymous with innovation in chemical information and QSAR.

Cramer has remained active in research and publishing at the forefront of his field.  His work on ‘topomeric’ descriptors, (J. Med. Chem. 2003, 46, 374-388) which allows CoMFA without tedious alignment of ligands, is proving a very successful tool in drug discovery (as recently shown in. J. Med. Chem. 2011, 54, 3982-3986) allowing the design of more selective ligands.

Admired by his colleagues, Cramer is described as personable and open to discussing science with all and any interested parties, a “gentleman” scientist.

While Cramer is known to the chemical information world as a top rate scientist, he has made major contributions to another field entirely:  baseball.   Cramer became interested in applying computers to baseball statistics and developed a program to feed detailed baseball statistics into the commentators’ box. He consulted with a number of major league teams, and is featured in the book “Moneyball” by Michael Lewis (recently made into a major motion picture).

Dr. Cramer received his A.B. degree from Harvard University in Chemistry and Physics in 1963 and his Ph.D. in Physical Organic Chemistry from the Massachusetts Institute of Technology in 1967.  Dick worked for Polaroid Corporation from 1967 through 1969 and then completed a two year fellowship under direction of Dr. E. J. Corey.  After more than a decade working with Smith Kline & French Laboratories, he moved to Tripos in 1983 as Vice President of New Products.  He currently serves as Senior Vice President, Science, and Chief Scientific Officer for Tripos, a Certara Company.

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Lee Dirks was an all around great guy…

I just read the sad news about Lee Dirks on Twitter and read Savas’ blogpost. Lee and his wife Judy were killed in an accident in Peru. It’s a sad day. My thoughts go out to his family, friends and colleagues. Lee was a great guy.

The last time I saw Lee he and I were sharing the podium for a session at the NFAIS meeting in Philadelphia. I was presenting on our experiences with curation and crowdsourcing and Lee was presenting on Microsoft Academic Search. His presentation is here.

Whenever I saw Lee it was always a strong handshake, a big smile, a “how’s it going” and just all around positive emotion. He could hold a room. His presentations were amusing, his style engaging and his larger than life presence was a joy to be around both professionally and socially. I never met him outside of professional circles but in my mind I can only imagine him to be a fun man to live with…high-spirited, good sense of humor, adventurer, open-minded, a supportive husband and fun dad. That’s how he showed up professionally! And clearly he was an adventurer.

Lee’s work on Microsoft Academic Search was taking the platform to a new place as the presentation at NFAIS explained. I’ve inserted it below.

While a man’s work is not THE measure of who he is it is A measure. I think Lee, measured by his work, was a wonderful man. Measured by my interactions with him he was a great man. And measured by the small number of times he spoke of his family, he loved them very much.

I will miss meeting him, receiving his smile and having a good strong handshake. It’s a sad day and a wake up call to all of us to embrace the moments we have, hug our kids, love our partner and go big or go home in life. Life is frail

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Social networking tools as public representations of a scientist

This is one of my presentations at the ACS meeting today in San Diego regarding how to use social networking tools to expose yourself as a scientist

Social networking tools as public representations of a scientist

The web has revolutionized the manner by which we can represent ourselves online by providing us the ability to exposure our data, experiences and skills online via blogs, wikis and other crowdsourcing venues. As a result it is possible to contribute to the community while developing a social profile as a scientist. At present many scientists are still measured by their contributions using the classical method of citation statistics and a number of freely available online tools are now available for scientists to manage their profile. This presentation will provide an overview of tools including Google Scholar Citations and Microsoft Academic Search and will discuss how these are and other tools, when integrated with the ORCID identifier, may more fully recognize the collective contributions to science. I will also discuss how an increasingly public view of us as scientists online will likely contribute to our reputation above and beyond citations.

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Why are pornstars more notable than scientists on Wikipedia?

I’m a BIG Wikipedia fan. It is one of my favorite sites, our 9 year old twins have spent many hours on the site with me, and I have personally spent a lot of time, including Christmas, curating chemistry on Wikipedia. I like what Wikipedia has achieved, have willingly contributed articles, but also enjoy a good laugh at Wikipedia’s expense when appropriate. In the past 24 hours I’ve giggled at the latest XKCD cartoon as well as this blog post about Jimmy Wales.

Despite my affection for Wikipedia this week I am annoyed about what’s going on for me on Wikipedia. I’ve read The Wikipedia Revolution and understand the editorial activities and I’ve had many discussions about how authors of Wikipedia articles have been “beaten up” in a friendly way. I’ve been warned about Conflict of Interest policies and yet, because I think it’s important, have tried to navigate the complexities of contributing articles. At present however my contributions on Wikipedia regarding scientists and projects I know about have all been flagged, either for deletion or for “notability”.

I’ve  written the bulk of these articles: Gerhard Ecker, Sean Ekins and Gary Martin. Some of the flags on the articles include “It may have been edited by a contributor who has a close connection with its subject. Tagged since November 2011.

Gary Martin and Sean Ekins are personal friends so YES, I have close connections with the subject. And I believe I can objectively write a good article about them. Just like I wrote about the village I grew up in…Afonwen. I only spent 12 years of my life there….so have a close connection with that too. I have known Gerhard Ecker for about three years, and know about his work from reading his articles and hearing him speak, and feel its valid to contribute an article as I JUDGE he’s a notable scientist. Gary Martin has almost 300 publications, and an h-index of 27. In the domain of NMR anyone who is doing small molecule structure elucidation is almost certainly using technology he has contributed too. He is notable. Sean Ekins is also notable, in my opinion. And surely Wikipedia is about collective opinions.

I have tried to follow notability guidelines for academics but have clearly failed so encourage anyone reading this post to help clean up the articles. If any of you out there happen to know Gerhard, Gary or Sean DON’T contribute though…you might get flagged as being a contributor who has a close connection. It’s much better to write about people you don’t know. Clearly I understand the possible bias …

If I look at the number of chemists on Wikipedia I find the following list of about 480 chemists. That article is a list of world-famous chemists. There is also a smaller list of Russian Chemists. The end of the list looks like this:

See also

These are likely all NOTABLE chemists as I couldn’t find a single article in the list with a challenge on it…but I confess to not looking at each one one at a time. But that’s what we have for chemists….a list of world-famous chemists, biochemists and Russian chemists.

Many of us have heard about how “open” Wikipedia is including many of the exchanges regarding pornography on Wikipedia. In many cases I have to simply caution “welcome to the internet”. We all know its out there…how could we not. There is material on Wikipedia that is shocking, but at the same time educational. But where I take issue, just for comparison purposes, is that top-notch scientists, in my opinion (and I judge that of many others) can be flagged as not notable, yet pages like those listed below for pornstars can exist without question, without flagging but,  I have to assume, are both encyclopedic and notable.

Similar to the list of chemists a search on pornstars gives a full article here but then these incredibly long lists!

The last one is quite a list! I guess its appropriate to list pornstars by decade but scientists tend to perform better over the longer term and can have 40-50 year careers whereas I don’t even want to imagine that for the other career! I struggle to see why the list of references for Ron Jeremy is any more notable/appropriate than the list of references for Gary Martin.

What’s ridiculous is that there is even an article about pornstar pets. What??? This has more of a place on Wikipedia than some of our worlds most published scientists? Is there something wrong with this picture?

While I may not fully understand what is deemed to be appropriate in terms of notability for a scientist, and I do understand the judgment that I might be too close to the scientists to be objective (but I challenge that!) I definitely challenge the status that ponstars deserve more exposure, pardon the pun, than the worlds chemists.

Despite my rants I understand the challenges that will likely show up as comments on this blogpost. I understand that I will be pointed to WP:COI and WP:Notability. I do not get to set the rules, I need to follow them as I am a small part of a very important community of crowdsourced improvement. But, overall, I remain surprised at how there appears to be so much diligence looking at the articles of scientists rather than those of pornstars. I think scientists are generally involved in very notable activities that generally distinguish them from the bulk of the population. I think pornstars are involved in activities that are not particularly notable as the bulk of the population will do them at some point in their life….well, not ALL activities that pornstars do I’m sure…..

I believe we need a change in policy. I believe that scientists deserve more notability than pornstars and that diligence, while appropriate, should be used in a more tempered manner.

There is an alternative solution…

 

 

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Google’s Brilliance Shows Again with Google Scholar Citations

My colleague David Sharpe pointed me to an interesting blog today concerning Google Scholar Citations. I’d always imagined it would come but didn’t know when. So what a happy lunchtime it was when I sat down to read the blog and register for a citations account here. When I registered on Microsoft Academic Search I was initially impressed.

ONE of my personas on Microsoft Academic Search

Since then I have been collapsing a number of different “authors called Antony Williams”. I’ve been working on it for a few weeks and despite numerous attempts to collapse them, including email requests…I still exist as

http://academic.research.microsoft.com/Author/18547547/antony-j-williams

http://academic.research.microsoft.com/Author/12789419/antony-j-williams

http://academic.research.microsoft.com/Author/22810554/antony-j-williams

http://academic.research.microsoft.com/Author/24519715/antony-j-williams

If anyone from Microsoft can possibly help me get these collapsed I’d appreciate it! I’ve tried using the approach below and failed.

 

It’s a shame…I really want to take advantage of a lot of the wonderful tools that Microsoft Academic Search offers. An example is below.

Again…if anyone can help me collapse the various forms of me I’d appreciate it!
Now to  Google Scholar Citations. I registered, I searched on my name and accepted it. Done. The result was, as far as I can tell, a complete capture of my papers. Caveat..I have NOT yet sat and compared with my CV . What impressed me is that I am one person under Google Scholar Citations…no complex “collapsing process”. It also took me 10 mins….it was done with a few button clicks and it looks like this.
Google…impressed again. NICELY DONE!

 

 

 

 

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How are NMR Prediction Algorithms and AFM Related?

There’s a really nice News piece over on Nature News regarding “Feeling the Shapes of Molecules“. The work reports on how Atomic Force Microscopy is being used to deduce chemical structure directly, one molecule at a time. It is, quite simply, stunning. This work is an extension of the original work reported on pentacene that many scientists thought was spectacular. This work is even one step closer to the dream of single molecule structure identification. The work is entitled “Organic structure determination using atomic-resolution scanning probe microscopy” and as well as the IBM group responsible for the AFM work involves Marcel Jaspars, someone who’s work I have watched for many years as I am trained as an NMR spectroscopist and have spent a lot of time working on computer-assisted structure elucidation (CASE) approaches to examine natural product structures (see references in here…).

The molecule that they studied was cephalandole A  that had previously been mis-assigned. Interestingly my old colleagues from ACD/Labs, where I worked for over a decade, and myself had published an article in RSC’s Natural Product Reviews where we studied “Structural revisions of natural products by Computer-Assisted Structure Elucidation (CASE) systems“. The basic premise of the article is that there are incorrect structures making it into the literature because of the misinterpretation of the analytical data and that computer algorithms, specifically NMR prediction and CASE algorithms, can be used to rule out structures elucidated by the scientists.It is hard to do justice to the entire review article as we detail the approaches to CASE and NMR prediction and doing it in a blog post is tough. So, I do recommend reading the NPR article. However, I am extracting the part that applies to the elucidation of the structure of cephalandole A and how algorithms would be of value in negating the incorrect structure.

“In 2006 Wu et al isolated a new series of alkaloids, particularly cephalandole A, 16. Using 2D NMR data (not tabulated in the article) they performed a full 13C NMR chemical shift assignment as shown on structure 16.

Mason et al synthesized compound 16 and after inspection of the associated 1H and 13C NMR data concluded that the original structure assigned to cephalandol A was incorrect. The synthetic compound displayed significantly different data from those given by Wu et al. The 13C chemical shifts of the synthetic compound are shown on structure 16A.

Cephalandole A was clearly a closely related structure with the same elemental composition as 16, and structure 17was hypothesized as the most likely candidate. Compound 17 was described in the mid 1960s and this structure was synthesized by Mason et al.The spectral data of the reaction product fully coincided with those reported by Wu et al. The true chemical shift assignment is shown in structure 17. For clarity the differences between the original and revised structures are shown in Figure 17.

We expect that 13C chemical shift prediction, if originally performed for structure 16, would encourage caution by the researchers (we found dA=3.02 ppm).Figure 18 presents the correlation plots of the 13C chemical shift values predicted for structure 16 by both the HOSE and NN methods versus experimental shift values obtained by Wu et al. The large point scattering, the regression equation, the low R2 =0.932 value (an acceptable value is usually R2 ≥ 0.995) and the significant magnitude of the g-angle between the correlation plot and the 45-grade line (a visual indication for disagreement between the experiment and model) could indicate inconsistencies with the proposed structure and should encourage close consideration of the structure.Our experience has demonstrated that a combination of warning attributes can serve to detect questionable structures even in those cases when the StrucEluc system is not used for structure elucidation.

Figure 18. Correlation plots of the 13C chemical shift values predicted for structure 16 by HOSE and NN methods versus experimental shift values obtained by Wu et al. Extracted statistical parameters: R2(HOSE)=0.932, dHOSE=1.20dexp-25.6.

So, for those NMR jocks who don’t have access to the genius of IBM scientists performing AFM, and yet want to have tools to help in the elucidation process you’d be doing well to use NMR prediction algorithms and CASE systems to help….it’s rather embarrassing to have to issue a retraction on a paper with your name on.

Meanwhile I am in awe of the work reported by Marcel and his colleagues at IBM. Clearly there’s a long way to go before such approaches are mainstream but the flag is in the sand…this is where things will speed up and we are surely destined, I hope (!) to see many more reports of this type of work and how it is progressing. Let’s hope. Feedback on the NPR article welcomed!!!

Organic structure determination using atomic-resolution scanning probe microscopy

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