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Sequence signatures and the probabilistic identification of proteins in the

Summary: Sequence signatures and the probabilistic
identification of proteins in the
Myc-Max-Mad network
William R. Atchley*§¶
and Andrew D. Fernandes
*Department of Genetics, Graduate Program in Biomathematics, and Center for Computational Biology, North Carolina State University,
Raleigh, NC 27695-7614; and §Max Planck Institute for Mathematics in the Sciences, D-04103 Leipzig, Germany
Communicated by Walter M. Fitch, University of California, Irvine, CA, March 1, 2005 (received for review June 2, 2004)
Accurate identification of specific groups of proteins by their
amino acid sequence is an important goal in genome research. Here
we combine information theory with fuzzy logic search procedures
to identify sequence signatures or predictive motifs for members
of the Myc-Max-Mad transcription factor network. Myc is a well
known oncoprotein, and this family is involved in cell proliferation,
apoptosis, and differentiation. We describe a small set of amino
acid sites from the N-terminal portion of the basic helix­loop­helix
(bHLH) domain that provide very accurate sequence signatures for
the Myc-Max-Mad transcription factor network and three of its
member proteins. A predictive motif involving 28 contiguous bHLH
sequence elements found 337 network proteins in the GenBank NR


Source: Atchley, William R.- Department of Genetics, North Carolina State University


Collections: Biology and Medicine