1887

Quantitative Analysis of the Trends Exhibited by the Three Interdisciplinary Biological Sciences: Biophysics, Bioinformatics, and Systems Biology

    Authors: Jonghoon Kang1,*, Seyeon Park1, Aarya Venkat1, Adarsh Gopinath1
    VIEW AFFILIATIONS HIDE AFFILIATIONS
    Affiliations: 1: Department of Biology, Valdosta State University, Valdosta, GA 31698
    AUTHOR AND ARTICLE INFORMATION AUTHOR AND ARTICLE INFORMATION
    • *Corresponding author. Mailing address: Department of Biology, Valdosta State University, 1500 N. Patterson St., Valdosta, GA 31698. Phone: 229-333-7140. Fax: 229-245-6585. E-mail: [email protected].
    • ©2015 Author(s). Published by the American Society for Microbiology.
    Source: J. Microbiol. Biol. Educ. December 2015 vol. 16 no. 2 198-202. doi:10.1128/jmbe.v16i2.949
MyBook is a cheap paperback edition of the original book and will be sold at uniform, low price.
  • XML
  • HTML
    37.46 Kb
  • PDF
    380.25 Kb

    Abstract:

    New interdisciplinary biological sciences like bioinformatics, biophysics, and systems biology have become increasingly relevant in modern science. Many papers have suggested the importance of adding these subjects, particularly bioinformatics, to an undergraduate curriculum; however, most of their assertions have relied on qualitative arguments. In this paper, we will show our metadata analysis of a scientific literature database (PubMed) that quantitatively describes the importance of the subjects of bioinformatics, systems biology, and biophysics as compared with a well-established interdisciplinary subject, biochemistry. Specifically, we found that the development of each subject assessed by its publication volume was well described by a set of simple nonlinear equations, allowing us to characterize them quantitatively. Bioinformatics, which had the highest ratio of publications produced, was predicted to grow between 77% and 93% by 2025 according to the model. Due to the large number of publications produced in bioinformatics, which nearly matches the number published in biochemistry, it can be inferred that bioinformatics is almost equal in significance to biochemistry. Based on our analysis, we suggest that bioinformatics be added to the standard biology undergraduate curriculum. Adding this course to an undergraduate curriculum will better prepare students for future research in biology.

References & Citations

1. Banta LM, et al 2012 Integrating genomics research throughout the undergraduate curriculum: a collection of inquiry-based genomics lab modules CBE Life Sci Educ 11 203 208 10.1187/cbe.11-12-0105 22949416 3433288 http://dx.doi.org/10.1187/cbe.11-12-0105
2. Bednarski AE, Elgin SC, Pakrasi HB 2005 An inquiry into protein structure and genetic disease: introducing undergraduates to bioinformatics in a large introductory course CBE Life Sci Educ 4 207 220 10.1187/cbe.04-07-0044 http://dx.doi.org/10.1187/cbe.04-07-0044
3. Bulmer MG 1979 Principles of statistics 154 161 Dover Publications New York, NY
4. Cooper S 2001 Integrating bioinformatics into undergraduate courses Biochem Mol Biol Educ 29 167 168
5. Ditty JL, et al 2010 Incorporating genomics and bioinformatics across the life sciences curriculum PLoS Biol 8 8 e1000448 [Online.] 10.1371/journal.pbio.1000448 20711478 2919421 http://dx.doi.org/10.1371/journal.pbio.1000448
6. Honts JE 2003 Evolving strategies for the incorporation of bioinformatics within the undergraduate cell biology curriculum CBE Life Sci Educ 2 233 247 10.1187/cbe.03-06-0026 http://dx.doi.org/10.1187/cbe.03-06-0026
7. Jenuwine ES, Floyd JA 2004 Comparison of Medical Subject Headings and text-word searches in MEDLINE to retrieve studies on sleep in healthy individuals J Med Lib Assoc 92 3 349 354
8. Kang J, Purnell CB 2011 Implications for undergraduate education of two interdisciplinary biological sciences: biochemistry and biophysics CBE Life Sci Educ 10 111 112 10.1187/cbe.10-09-0124 21633055 3105913 http://dx.doi.org/10.1187/cbe.10-09-0124
9. Lesk AM 2014 Introduction to bioinformatics Oxford University Press Oxford, United Kingdom
10. Magana AJ, Taleyarkhan M, Alvarado DR, Kane M, Springer J, Clase K 2014 A survey of scholarly literature describing the field of bioinformatics education and bioinformatics educational research CBE Life Sci Educ 13 607 623 25452484 4255348
11. National Research Council (US) 2003 BIO 2010: transforming undergraduate education for future research biologists [Online] The National Academies Press Washington, DC http://www.nap.edu
12. Pevzner P, Shamir R 2009 Computing has changed biology—biology education must catch up Science 325 541 542 10.1126/science.1173876 19644094 http://dx.doi.org/10.1126/science.1173876
13. Rosenfeld A 1969 Picture processing by computer ACM Computing Surveys 1 147 176 10.1145/356551.356554 http://dx.doi.org/10.1145/356551.356554
14. Singer SR, et al 2013 Keeping an eye on biology Science 339 408 409 10.1126/science.1229848 23349282 http://dx.doi.org/10.1126/science.1229848

Supplemental Material

No supplementary material available for this content.

Loading

Article metrics loading...

/content/journal/jmbe/10.1128/jmbe.v16i2.949
2015-12-01
2019-05-25

Abstract:

New interdisciplinary biological sciences like bioinformatics, biophysics, and systems biology have become increasingly relevant in modern science. Many papers have suggested the importance of adding these subjects, particularly bioinformatics, to an undergraduate curriculum; however, most of their assertions have relied on qualitative arguments. In this paper, we will show our metadata analysis of a scientific literature database (PubMed) that quantitatively describes the importance of the subjects of bioinformatics, systems biology, and biophysics as compared with a well-established interdisciplinary subject, biochemistry. Specifically, we found that the development of each subject assessed by its publication volume was well described by a set of simple nonlinear equations, allowing us to characterize them quantitatively. Bioinformatics, which had the highest ratio of publications produced, was predicted to grow between 77% and 93% by 2025 according to the model. Due to the large number of publications produced in bioinformatics, which nearly matches the number published in biochemistry, it can be inferred that bioinformatics is almost equal in significance to biochemistry. Based on our analysis, we suggest that bioinformatics be added to the standard biology undergraduate curriculum. Adding this course to an undergraduate curriculum will better prepare students for future research in biology.

Highlighted Text: Show | Hide
Loading full text...

Full text loading...

/deliver/fulltext/jmbe/16/2/jmbe-16-198.xml.a.html?itemId=/content/journal/jmbe/10.1128/jmbe.v16i2.949&mimeType=html&fmt=ahah

Figures

Image of FIGURE 1

Click to view

FIGURE 1

Comparison of observed and predicted values of biophysics publication numbers normalized to that of biochemistry. The observed values were obtained from PubMed database searches of biochemistry and biophysics publications. The predicted values were obtained from an equation ( Eq. 1 ) derived from a previous study ( 8 ). (A) This validation was conducted over five years from 2010 to 2014. A chi-square analysis demonstrates that the two sets of values are highly similar. (B) Fitting a sigmoid equation ( Eq. 2 ) to the data of biophysics papers from 1985 to 2014. The sigmoid function (solid line) obtained from the nonlinear regression is = 22.9/(1 + [-( – 2009.6)/13.2]) with = 0.9931. Eq. 1 (dotted line) is overlaid for comparison. A divergence between the two functions is clearly noticeable in 2009.

Source: J. Microbiol. Biol. Educ. December 2015 vol. 16 no. 2 198-202. doi:10.1128/jmbe.v16i2.949
Download as Powerpoint
Image of FIGURE 2

Click to view

FIGURE 2

Normalized publication data for bioinformatics (A) and systems biology (B) in PubMed. Publication numbers of bioinformatics and systems biology normalized to that of biochemistry are shown as a function of year. (A) The curve is generated by fitting both sigmoidal and Gompertz functions to the data, creating a divergence between the two trend lines past the year 2014. By 2025, the range of this gap is between 77% and 93%. (B) The curve is generated by fitting only a Gompertz equation to the data because the Gompertz equation has the highest coefficient of determination and the lowest sum of squares.

Source: J. Microbiol. Biol. Educ. December 2015 vol. 16 no. 2 198-202. doi:10.1128/jmbe.v16i2.949
Download as Powerpoint

This is a required field
Please enter a valid email address
Please check the format of the address you have entered.
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error