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Immunoinformatics Comes of Age

Overview of attention for article published in PLoS Computational Biology, June 2006
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Title
Immunoinformatics Comes of Age
Published in
PLoS Computational Biology, June 2006
DOI 10.1371/journal.pcbi.0020071
Pubmed ID
Authors

Bette Korber, Montiago LaBute, Karina Yusim

Abstract

With the burgeoning immunological data in the scientific literature, scientists must increasingly rely on Internet resources to inform and enhance their work. Here we provide a brief overview of the adaptive immune response and summaries of immunoinformatics resources, emphasizing those with Web interfaces. These resources include searchable databases of epitopes and immune-related molecules, and analysis tools for T cell and B cell epitope prediction, vaccine design, and protein structure comparisons. There is an agreeable synergy between the growing collections in immune-related databases and the growing sophistication of analysis software; the databases provide the foundation for developing predictive computational tools, which in turn enable more rapid identification of immune responses to populate the databases. Collectively, these resources contribute to improved understanding of immune responses and escape, and evolution of pathogens under immune pressure. The public health implications are vast, including designing vaccines, understanding autoimmune diseases, and defining the correlates of immune protection.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 227 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 1%
India 3 1%
Spain 2 <1%
Germany 2 <1%
United Kingdom 2 <1%
Brazil 2 <1%
Chile 1 <1%
Italy 1 <1%
Colombia 1 <1%
Other 4 2%
Unknown 206 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 52 23%
Student > Ph. D. Student 49 22%
Student > Master 31 14%
Student > Bachelor 19 8%
Student > Postgraduate 12 5%
Other 33 15%
Unknown 31 14%
Readers by discipline Count As %
Agricultural and Biological Sciences 86 38%
Biochemistry, Genetics and Molecular Biology 30 13%
Medicine and Dentistry 20 9%
Computer Science 15 7%
Immunology and Microbiology 14 6%
Other 25 11%
Unknown 37 16%