Christopher Bystroff

Department of Biology, Rennselaer Polytechnic Institute, Troy, NY 12180

Lab Members:

Yu Shao

Xin Yuan

I-sites is a method for predicting the local structure of a protein from its amino acid sequence. The I-sites Library is a set of sequence patterns that strongly correlate with protein structure at the local level.

 

References :

Bystroff, C. & Baker, D. (1997). Blind predictions of local protein
structure in CASP2 targets using the I-sites library. Proteins Suppl 1, 167-71.

Bystroff, C. & Baker, D. (1998). Prediction of local structure in proteins
using a library of sequence-structure motifs. J Mol Biol 281, 565-77.

Bystroff, C. & Shao, Y. (2002). Fully automated ab initio protein
structureprediction using I-SITES, HMMSTR and ROSETTA. Bioinformatics in press.

Bystroff, C., Thorsson, V. & Baker, D. (2000). HMMSTR: A hidden markov
modelfor local sequence-structure correlations in proteins. Journal of Molecular
Biology 301, 173-90.

Han, K. F., Bystroff, C. & Baker, D. (1997). Three-dimensional structures
and contexts associated with recurrent amino acid sequence patterns. Protein
Sci 6, 1587-90.

Simons, K. T., Ruczinski, I., Kooperberg, C., Fox, B. A., Bystroff, C. &
Baker, D. (1999). Improved recognition of native-like protein structures
using a combination of sequence-dependent and sequence-independent features of
proteins. Proteins 34, 82-95.

Yi, Q., Bystroff, C., Rajagopal, P., Klevit, R. E. & Baker, D. (1998).
Prediction and structural characterization of an independently folding
substructure in the src SH3 domain. J Mol Biol 283, 293-300.

Zaki, M. J. & Bystroff, C. (2001). Mining Residue Contacts in Proteins. In
Data Mining for Scientific and Engineering Applications (R. Grossman, C.
Kamath, P. Kegelmeyer, Kumar, V. & Namburu, R., eds.), pp. 141-164. Kluwer
Academic Publishers,, Boston, MA.