Pfeiffer T, Hoffmann R "Temporal patterns of genes in scientific publications " Proceedings of the National Academy of Sciences of the United States of America 104(29): 12052-12056, July 17, 2007

Eugene Garfield garfield at CODEX.CIS.UPENN.EDU
Wed Nov 28 16:11:47 EST 2007


E-mail Addresses: pfeiffer at fas.harvard.edu 

Title: Temporal patterns of genes in scientific publications 

Author(s): Pfeiffer T (Pfeiffer, Thomas), Hoffmann R (Hoffmann, Robert) 

Source: PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED 
STATES OF AMERICA 104 (29): 12052-12056 JUL 17 2007 

Document Type: Article 

Language: English 

Cited References: 30      Times Cited: 0        

Abstract: Publications in scientific journals contain a considerable 
fraction of our scientific knowledge. Analyzing data from publication 
databases helps us understand how this knowledge is obtained and how it 
changes over time. In this study, we present a mathematical model for the 
temporal dynamics of data on the scientific content of publications. Our 
data set consists of references to thousands of genes in the >15 million 
publications listed in PublMed. We show that the observed dynamics may 
result from a simple process: Researchers predominantly publish on genes 
that already appear in many publications. This might be a rewarding 
strategy for researchers, because there is a positive correlation between 
the frequency of a gene in scientific publications and the journal impact 
of the publications. By comparing the empirical data with model 
predictions, we are able to detect unusual publication patterns that often 
correspond to major achievements in the field. We identify interactions 
between yeast genes from PubMed and show that the frequency differences of 
genes in publications lead to a biased picture of the resulting interaction 
network. 

Addresses: Pfeiffer T (reprint author), Harvard Univ, Program Evolut Dynam, 
One Brattle Square, Cambridge, MA 02138 USA
Harvard Univ, Program Evolut Dynam, Cambridge, MA 02138 USA
MIT, Comp Sci & Artificial Intelligence Lab, Cambridge, MA 02139 USA

E-mail Addresses: pfeiffer at fas.harvard.edu 

Publisher: NATL ACAD SCIENCES, 2101 CONSTITUTION AVE NW, WASHINGTON, DC 
20418 USA 

Subject Category: Multidisciplinary Sciences 

IDS Number: 192KA 

ISSN: 0027-8424 



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