Title |
No-boundary thinking in bioinformatics research
|
---|---|
Published in |
BioData Mining, November 2013
|
DOI | 10.1186/1756-0381-6-19 |
Pubmed ID | |
Authors |
Xiuzhen Huang, Barry Bruce, Alison Buchan, Clare Bates Congdon, Carole L Cramer, Steven F Jennings, Hongmei Jiang, Zenglu Li, Gail McClure, Rick McMullen, Jason H Moore, Bindu Nanduri, Joan Peckham, Andy Perkins, Shawn W Polson, Bhanu Rekepalli, Saeed Salem, Jennifer Specker, Donald Wunsch, Donghai Xiong, Shuzhong Zhang, Zhongming Zhao |
Abstract |
Currently there are definitions from many agencies and research societies defining "bioinformatics" as deriving knowledge from computational analysis of large volumes of biological and biomedical data. Should this be the bioinformatics research focus? We will discuss this issue in this review article. We would like to promote the idea of supporting human-infrastructure (HI) with no-boundary thinking (NT) in bioinformatics (HINT). |
X Demographics
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 4 | 20% |
Brazil | 1 | 5% |
France | 1 | 5% |
Canada | 1 | 5% |
Sweden | 1 | 5% |
Bosnia and Herzegovina | 1 | 5% |
Comoros | 1 | 5% |
Unknown | 10 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 11 | 55% |
Scientists | 9 | 45% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 5 | 8% |
United Kingdom | 1 | 2% |
Indonesia | 1 | 2% |
Unknown | 56 | 89% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 13 | 21% |
Researcher | 13 | 21% |
Other | 6 | 10% |
Professor > Associate Professor | 6 | 10% |
Professor | 5 | 8% |
Other | 17 | 27% |
Unknown | 3 | 5% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 15 | 24% |
Biochemistry, Genetics and Molecular Biology | 9 | 14% |
Computer Science | 9 | 14% |
Medicine and Dentistry | 7 | 11% |
Engineering | 4 | 6% |
Other | 13 | 21% |
Unknown | 6 | 10% |