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* School of Informatics, Indiana University, Bloomington, Indiana; Laboratory of Statistical Genetics, The Rockefeller University, New York, New York; Center for Information Science and Technology, Temple University, Philadelphia, Pennsylvania; Center for Computational Biology and Bioinformatics, Department of Biochemistry and Molecular Biology, School of Medicine, Indiana University, Indianapolis, Indiana; and ¶ Institute for Biological Instrumentation, Russian Academy of Sciences, Pushchino, Moscow Region, Russia
Correspondence: Address reprint requests to Prof. A. Keith Dunker, Tel.: 317-278-9650; E-mail: kedunker{at}iupui.edu; or Dr. Vladimir N. Uversky, Tel.: 317-278-9194; E-mail: vuversky{at}iupui.edu.
The recent advances in the prediction of intrinsically disordered proteins and the use of protein disorder prediction in the fields of molecular biology and bioinformatics are reviewed here, especially with regard to protein function. First, a close look is taken at intrinsically disordered proteins and then at the methods used for their experimental characterization. Next, the major statistical properties of disordered regions are summarized, and prediction models developed thus far are described, including their numerous applications in functional proteomics. The future of the prediction of protein disorder and the future uses of such predictions in functional proteomics comprise the last section of this article.
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