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Data Handling in Collaborations

Significant efforts are also made on defining specific and meaningful productivity metrics for drug development processes [3]. However, the collaborative work does not translate directly into efficient or productive research, as it encounters data format incompatibility and results diffusion between collaborating departments or institutions. That is why the current advances in collaborative computational technologies invigorate and transform biomedical research by acting as a key knowledge broker with the ability to integrate and operate across divergent data types [4].


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Reduced cost and increased throughput of genomic technology have created an unprecedented ability to generate an excessive amount of meaningful data for clinical research and drug development. In addition to exponential data generation, numerous tools have been developed to interpret that data, to share insights, ideas and expert opinions within research community [5].

There are over web-based tools offered to academic researchers for literature exploration, data sharing, collaboration, writing and publishing, research evaluation and other activities [6]. Moreover, the productivity of scientific research is getting a serious setback from Internet browsing and mobile devices. Researches browse multiple websites, logon to multiple web-based tools to perform regular online research projects with no tracking or saving of the search results, no study continuation, and certainly - no confidence in research thoroughness.

Recently, it was shown that average user spends 23 hours a week emailing, texting and using social media and other forms of online communication [7].

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Clearly, the IT industry is facing an admirable task to develop tools and services that will not only allow for cross-talk between diverse type of data, but will support existing and evolving genomic technologies, will stimulate collaborative multi-institutional research projects, and will help users to stay focused on their primary mission — becoming experts in their specific area of scientific interest.

Recognizing the trends in biomedical research and healthcare, the mammoths of IT industry, Google and IBM, both launched special programs.

Acs collaborative computational technologies for biomedical research …

Google Scholar addresses the need in optimization of the online research, specifically — search for publications, while Discovery Advisor by IBM Watson Health group focuses on research and development projects in pharmaceutical industry, publishing and biotechnology [8]. Despite significant progress made on many fronts, much has to be done yet to advance research productivity both on bench and on-line, and to resolve mounting issues with data deluge and data silos. Share This Post.


  • Bringing Collaborations to Chemistry.
  • Computer Algebra and Symbolic Computation: Elementary Algorithms.
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  • Editor on Collaborative Computational Technologies for Biomedical Research Book!
  • Strange Days Indeed: The Golden Age of Paranoia.
  • Innovations in Biomedical Computational Science and Technology Initiative.
  • References Sarli, Cathy C. Paper Paul, Daniel S. Collaboration is essential! If we can encourage others in the government chemistry databases to adopt active collaborative approaches wonderful things could happen. Collaborative Computational Technologies for Biomedical Research. All of the authors either have extensive backgrounds in computational software for biomedical research or have done wet lab research for drug discovery.

    Collaborative Computational Technologies for Biomedical Research

    Many have worked in software companies, pharmaceutical companies or consulting companies and have the appropriate skills to produce an excellent overview of present activities in the area of Collaborative Computational Technologies for Biomedical Research. This book represents a point in time.

    Biomedical Research: Ideas to Innovation

    We are working at a time when technologies are moving so quickly that in a couple of years parts of the future vision of the book will likely already be in place. SOme of the concepts about what could be will certainly have grown in scope and the world of open data, open science and open source will have made even more significant impacts on the Life Sciences.

    Search Ames

    This was an exciting project. It represents the exciting shifts in collaboration happening every day. The outline of the book, its chapters and its authors are listed below. Waller, Ramesh V. Durvasula and Nick Lynch.


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