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Free eBook Collaborative Computational Technologies for Biomedical Research download

by Maggie A. Z. Hupcey,Alpheus Bingham,Sean Ekins

Free eBook Collaborative Computational Technologies for Biomedical Research download ISBN: 0470638036
Author: Maggie A. Z. Hupcey,Alpheus Bingham,Sean Ekins
Publisher: Wiley; 1 edition (July 20, 2011)
Language: English
Pages: 576
Category: Other
Subcategory: Medicine and Health Sciences
Size MP3: 1789 mb
Size FLAC: 1586 mb
Rating: 4.9
Format: doc lit docx lrf


Start by marking Collaborative Computational Technologies for Biomedical .

This book describes how the computational sciences have transformed into being a key knowledge broker, able to integrate and operate across divergent data types.

Sean Ekins, Maggie A. Z. Hupcey, Antony J. Williams. Tackling real problems from both human collaborative and data and informatics perspectives.

Methods, Processes, and Tools for Collaboration The time has come to fundamentally rethink how we handle the building of knowledge in biomedical sciences today

Methods, Processes, and Tools for Collaboration The time has come to fundamentally rethink how we handle the building of knowledge in biomedical sciences today. This book describes how the computational sciences have transformed into being a key knowledge broker, able to integrate and operate across divergent data types.

21. Pioneering Use of the Cloud for Development of Collaborative Drug Discovery (CDD) Database 335 Sean Ekins, Moses M. Hohman, and Barry A. Bunin. 28. Current and Future Challenges for Collaborative Computational Technologies for the Life Sciences 491 Antony J. Williams, Renée J. G. Arnold, Cameron Neylon, Robin W. Spencer, Stephan Schürer, and Sean Ekins.

SEAN EKINS, MSc, PhD, DSc, is the Principal at Collaborations in Chemistry, and Collaborations Director at Collaborative .

SEAN EKINS, MSc, PhD, DSc, is the Principal at Collaborations in Chemistry, and Collaborations Director at Collaborative Drug Discovery, In. as well as an Adjunct Associate Professor in the Department of Pharmaceutical Sciences, University of Maryland School of Pharmacy. MAGGIE A. HUPCEY, PhD, is a chemist working within the Life Sciences and Healthcare Practice of PA Consulting Group in Princeton, New Jersey.

Book · May 2011 with 3 Reads. How we measure 'reads'

Book · May 2011 with 3 Reads. How we measure 'reads'. Williams, Alpheus Bingham.

Methods, Processes, and Tools for Collaboration

"The time has come to fundamentally rethink how we handle thebuilding of knowledge in biomedical sciences today. This bookdescribes how the computational sciences have transformed intobeing a key knowledge broker, able to integrate and operate acrossdivergent data types."—Bryn Williams-Jones, Associate ResearchFellow, Pfizer

The pharmaceutical industry utilizes an extended network ofpartner organizations in order to discover and develop new drugs,however there is currently little guidance for managing informationand resources across collaborations.

Featuring contributions from the leading experts in a range ofindustries, Collaborative Computational Technologies for BiomedicalResearch provides information that will help organizations makecritical decisions about managing partnerships, including:

Serving as a user manual for collaborations

Tackling real problems from both human collaborative and dataand informatics perspectives

Providing case histories of biomedical collaborations andtechnology-specific chapters that balance technological depth withaccessibility for the non-specialist reader

A must-read for anyone working in the pharmaceuticals industryor academia, this book marks a major step towards widespreadcollaboration facilitated by computational technologies.

User reviews
Drelajurus
Full disclosure, I’ve worked with one of the authors (AJW) in the past.

This book sets the stage by discussing the need for collaborative technologies in drug discovery, and I liked the way the authors push for ‘truly open and standard data exchange mechanisms’. This really hit home, since I know from experience that a huge problem in collaboration is getting different databases, applications and software packages to ‘talk’ to one another when they use different formats. The chapter on collaborative innovation was pretty insightful, especially the observation that some creative people can’t be controlled by a working group, and would serve the project better in an advisory role as opposed to a one with specific tasks.

The second part of the book talks about collaborative processes in general. One particular gem from this section is the chapter on scientific networking and collaborations, where they state ‘…it is interesting to speculate whether this speed would come at the expense of deep critical thought undertaken at a more leisurely pace.’ That kind of observation is commonplace in the book, and those kinds of thought stimulate critical thinking on the subject. Generally, I would have liked to see more discussion on scientists with different backgrounds talking different languages. Biophysicists, chemical biologists, analytical chemists, etc. all use different terms and that is confusing in the initial stages; some more extensive solutions would be welcome.

The third section on tools has got a lot of info on how we store and access the data, and some regulatory concerns when you get to later stage development (ELN, LIMS, etc.). The sections on cloud computing were great since they tie it into informatics. This section would be beneficial to start-ups and small academic collaborators, since using a good cloud service lets you scale very easily and ensure you only pay for what you use.

In short I recommend the book, especially if you work with a lot of data like I do and have an issue with different non-exchangeable data formats that do essentially the same thing. That’s frustrating since you’re forced to choose software based on compatibility with your output, not based on whether the output and processes fit your needs. Overall the book presents everything is a complete package, as it goes from organizing collaborations, to methods/processes, specific tools, and then what they expect for the future. Considering the book was published in 2011 (and probably written in 2010) and they were already discussing the utility of things like Amazon Web services for drug discovery applications, I’d say they have pretty good predictive power.
Broadcaster
It's been a while since I read a science/technology book from back to back. And was it worth it? Definitely.

The book is about collaboration and is a collaboration. Ironically, the best-written chapters almost invariably are those by single authors. Which confirms my own theory that writing (including scientific writing) is not exactly collaborative activity. Especially worth noting are the contributions by Robert Porter Lynch (Chapter 2), Robin W. Spencer (Chapter 6), Victor J. Hruby (Chapter 7), Brian Pratt (Chapter 14) and Keith T. Taylor (Chapter 19); I wish the whole book was written at the level of these chapters. Then again, collaboration is always a compromise. The material presented here is diverse and heterogeneous -- what did you expect?

I am sure there are people who do all sorts of stuff using their smartphones, including scientific database browsing and chemical structure drawing (Chapter 28). This latter activity does not strike me as especially productive or convenient. In my view, for the purposes of computer graphics bigger is better: if I had a choice, I'd go for HIPerWall (25,600 × 8000 pixels) or, better still, HIPerSpace (35,840 × 8000 pixels) display walls (Chapter 27).

As much as I enjoy reading the real (hardcopy) book, it could be nice to see it online, preferably in open access. For instance, Chapter 25 has 196 references, all of them are URLs, and some of them are rather long ones. I'd love to be able to click on them rather than type!

Will the wikis, virtual communities and cloud computing replace the behemoth pharma companies and NCBI? A man can dream. Ekins et al. write (Chapter 13):

"As a result of the recent recession there is a lot of drug discovery and development talent available now due to company lay-offs. If the software or other tools to enable this workforce to be productive and collaborate were available and they participated in the existing scientific collaboration networks, then there may be potential for enormous breakthroughs."

I wish I could share the authors' optimism. Yes there is potential, but it is highly unlikely that unemployed researchers are in the mood to collaborate. In case you wonder why: being unemployed is a full-time occupation, which leaves preciously little spare time. I rather inclined to agree with Robin W. Spencer (Chapter 6):

"Especially for cutting-edge scientific challenges, the participants you need are probably well paid and not particularly enthused by another tee shirt, coffee cup, or $100 voucher."

And what happened to the old-fashioned copy editing? OK I get used to the lack of any such luxury in open access publications: if the paper is accepted, the publisher tends to keep all your typos intact. But when you buy a book from John Wiley & Sons for a hundred something bucks, you'd expect some editorial intervention. (To be honest, I did not buy it. I can't afford buying books at such prices anyway.) The major and minor irritations include:

* Typos: "chpater" instead of "chapter" (p. 281) -- I thought by now the text editing software should take care of these.
* Tautologies: "The institutes of the national Institutes of Health" (p. 496); "... we need to consider standards specifically for chemistry and biology. In chemistry specifically..." (p. 202).
* Impenetrable sentences, e.g. "Many aspects should be considered, such as a regulatory path for filing, potential market size, differentiability of the therapeutic and experience with and difficulty to carry out clinical trials in the disease of interest" (p. 252) or "This will only be done by drawing from the mental resources of an extended scientific community in an innovative and complex, yet "daily practice", manner that promises a profound impact on our ability to use existing data to generate new knowledge with the maximum conceivable serendipity" (p. 454). What?
* Overabundance of acronyms (have a look at p. 497 and you'll see what I mean).
* Overabundance of buzz-words of yesteryear: "crowdsourcing" (yuck!), "integration", "leveraging", "paradigm", "stakeholder" and so on. The worst offenders, however, are "clear" and "clearly". Clearly, when these words is used too often, it is clear that something is not quite clear.

Don't get me wrong: it is a good book. I wouldn't hesitate to recommend it to any decent scientific library. But it could have been a great book.