Klingler, T. M. and Brutlag, D. L. (1993). ISMB-93 , 225-33.
Department of
Biochemistry and Section
on Medical Informatics Stanford
University School of Medicine, Stanford
California 94305-5307.
Using an flexible representation of biological sequences, we have
performed a comparative analysis of 1208 known tRNA sequences. We
believe we our technique is a more sensitive method for detecting
structural and functional relationships in sets of aligned sequences
because we use a flexible representation (for sequences), as well as
a general statistical method that can detect a wide range of
relationships between positions in a sequence. Our method utilizes
functional classifications of the sequence building-blocks
(nucleotide bases and amino acids) based on physical or chemical
properties. This flexibility in sequence representation improves the
significance of finding sequence relationships mediated by the
defining property. For example, using a purine/pyrimidine
classification, we can detect base-stacking interactions in sets of
nucleotide sequences that form base-paired helices. We use several
statistical measures, including chi 2-tests, Monte Carlo simulations
and an information measure to detect significant correlations in
sequences. In this paper we illustrate our method by analyzing a set
of tRNA sequences and showing that the correlations our program
discovers, in each case, correspond to the known base-pairing and
higher order interactions observed in tRNA crystal structures.
Furthermore, we show that novel and interesting features of tRNAs are
detected when sequence correlations with the charged amino acid (and
anticodon) are evaluated. This technique is a powerful method for
predicting the structure of RNAs and for analyzing specific
functional characteristics.
To
get Acrobat: 
[Back to Doug] [Address] [Academics] [Honors] [Publications] [Presentations] [Public Service]