Literature DB >> 31752505

Portfolio Analysis of Research Grants in Data Science Funded by the National Heart, Lung, and Blood Institute.

Huiqing Li1, Marissa Miller1, Catherine Burke1, Narasimhan Danthi1, Marc Charette1, Weiniu Gan2, Pankaj Qasba3, Gina S Wei1, David C Goff1, Xiao-Zhong James Luo1.   

Abstract

Leveraging emerging opportunities in data science to open new frontiers in heart, lung, blood, and sleep research is one of the major strategic objectives of the National Heart, Lung, and Blood Institute (NHLBI), one of the 27 Institutes/Centers within the National Institutes of Health (NIH). To assess NHLBI's recent funding of research grants in data science and to identify its relative areas of focus within data science, a portfolio analysis from fiscal year 2008 to fiscal year 2017 was performed. In this portfolio analysis, an efficient and reliable methodology was used to identify data science research grants by utilizing several NIH databases and search technologies (iSearch, Query View Reporting system, and IN-SPIRE [Pacific Northwest National Laboratory, Richland, WA]). Six hundred thirty data science-focused extramural research grants supported by NHLBI were identified using keyword searches based primarily on NIH's working definitions of bioinformatics and computational biology. Further analysis characterized the distribution of these grants among the heart, lung, blood, and sleep disease areas as well as the subtypes of data science projects funded by NHLBI. Information was also collected for data science research grants funded by other NIH institutes/centers using the same search and analysis methodology. The funding comparison among different NIH institutes/centers highlighted relative data science areas of emphasis and further identified opportunities for potential data science areas in which NHLBI could foster research advances.

Entities:  

Keywords:  computational biology; data science; grant; portfolio analysis; research

Mesh:

Year:  2019        PMID: 31752505      PMCID: PMC7032595          DOI: 10.1161/CIRCGEN.119.002746

Source DB:  PubMed          Journal:  Circ Genom Precis Med        ISSN: 2574-8300


  2 in total

1.  Informatics, Data Science, and Artificial Intelligence.

Authors:  Lisha Zhu; W Jim Zheng
Journal:  JAMA       Date:  2018-09-18       Impact factor: 56.272

2.  Big Data: Astronomical or Genomical?

Authors:  Zachary D Stephens; Skylar Y Lee; Faraz Faghri; Roy H Campbell; Chengxiang Zhai; Miles J Efron; Ravishankar Iyer; Michael C Schatz; Saurabh Sinha; Gene E Robinson
Journal:  PLoS Biol       Date:  2015-07-07       Impact factor: 8.029

  2 in total

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