Literature DB >> 20944088

Network dynamics to evaluate performance of an academic institution.

Michael E Hughes1, John Peeler, John B Hogenesch.   

Abstract

Statistical assessments of performance are common in industry and for individual scientists, but the use of such measures to assess productivity in scientific organizations has lagged behind. The need for defined performance measures has grown as team science has begun to play a larger role in biomedical research, such as in the area of translational medicine. We used a metric, node degree over time, to measure the change in the rate of collaboration over the past five years within an organization, the University of Pennsylvania's Institute for Translational Medicine and Therapeutics (ITMAT). The number of collaborative papers and grants roughly doubled over the past five years among investigators within but not outside of ITMAT. Also, collaborations within institutions and departments were more frequent than those between them--an actionable area of improvement.

Mesh:

Year:  2010        PMID: 20944088     DOI: 10.1126/scitranslmed.3001580

Source DB:  PubMed          Journal:  Sci Transl Med        ISSN: 1946-6234            Impact factor:   17.956


  12 in total

1.  Evolution in translational science: Whither the CTSAs?

Authors:  Garret A FitzGerald
Journal:  Sci Transl Med       Date:  2015-04-22       Impact factor: 17.956

2.  Social network analysis of biomedical research collaboration networks in a CTSA institution.

Authors:  Jiang Bian; Mengjun Xie; Umit Topaloglu; Teresa Hudson; Hari Eswaran; William Hogan
Journal:  J Biomed Inform       Date:  2014-02-18       Impact factor: 6.317

3.  Evidence of community structure in biomedical research grant collaborations.

Authors:  Radhakrishnan Nagarajan; Alex T Kalinka; William R Hogan
Journal:  J Biomed Inform       Date:  2012-09-07       Impact factor: 6.317

4.  Charting the Publication and Citation Impact of the NIH Clinical and Translational Science Awards (CTSA) Program From 2006 Through 2016.

Authors:  Nicole Llewellyn; Dorothy R Carter; Latrice Rollins; Eric J Nehl
Journal:  Acad Med       Date:  2018-08       Impact factor: 6.893

5.  Social network analysis to assess the impact of the CTSA on biomedical research grant collaboration.

Authors:  Radhakrishnan Nagarajan; Charlotte A Peterson; Jane S Lowe; Stephen W Wyatt; Timothy S Tracy; Philip A Kern
Journal:  Clin Transl Sci       Date:  2014-11-30       Impact factor: 4.689

6.  Breaking down silos: mapping growth of cross-disciplinary collaboration in a translational science initiative.

Authors:  Douglas A Luke; Bobbi J Carothers; Amar Dhand; Ryan A Bell; Sarah Moreland-Russell; Cathy C Sarli; Bradley A Evanoff
Journal:  Clin Transl Sci       Date:  2014-12-04       Impact factor: 4.689

7.  The growth and impact of Alzheimer disease centers as measured by social network analysis.

Authors:  Michael E Hughes; John Peeler; John B Hogenesch; John Q Trojanowski
Journal:  JAMA Neurol       Date:  2014-04       Impact factor: 18.302

8.  An NIH intramural percubator as a model of academic-industry partnerships: from the beginning of life through the valley of death.

Authors:  Michael R Emmert-Buck
Journal:  J Transl Med       Date:  2011-05-08       Impact factor: 5.531

9.  Nine criteria for a measure of scientific output.

Authors:  Gabriel Kreiman; John H R Maunsell
Journal:  Front Comput Neurosci       Date:  2011-11-10       Impact factor: 2.380

10.  Academic Cross-Pollination: The Role of Disciplinary Affiliation in Research Collaboration.

Authors:  Amar Dhand; Douglas A Luke; Bobbi J Carothers; Bradley A Evanoff
Journal:  PLoS One       Date:  2016-01-13       Impact factor: 3.240

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