Tree Graph Subproject Description
Home RNA Tree Graph Subproject Home How to Represent RNA Trees as Planar Graphs Database of RNA Trees
Ribonucleic acid (RNA) molecules are important in the performance of
biological processes in the cell. Some of their known roles include
protein synthesis and transport, catalysis, and chromosome replication
and regulation. Studies have shown that there are different types
of RNA that perform the different biological functions. These RNA
molecules have a vast number of structures. Using graph theory, we
aim to describe and analyze these structures and apply the fingings to
many important problems such as RNA design. Our graphical representations
are limited to RNA secondary elements. Still, graph representation
allows enumeration of RNA's repertoire. Since we find that only few
RNAs have been found compared to the number of possible topologies, these
graphs will help the search of missing RNA structures and stimulate the
production of RNAs in the laboratory.
Our purpose is to classify and analyze existing RNA's according to their
topological characteristics and to discovery structure/function relationships
between RNAs. We will further apply the findings to RNA search, design,
and structure prediction.
Our tree database utilizes graph theory by transforming secondary RNA
structures into tree graphs.
These tree graphs provide a simplified image of what the actual secondary
structures look like and so allow us to apply the tools of graph theory
to study these graphs in more depth. By using computational methods
we calculate the corresponding Laplacian
matrices and their eigenvalues for each graph. The next step
is to analyze the various eigenvalues and to search for clusters and relationships
between the eigenvalues of an RNA found in nature and those for the RNA
that have not been found yet. Finally, these data and information
will be applied to the design of RNA as well as to the search of RNA.
The trees for the existing and non-existing RNAs are distinguished by
color in the database. In addition, the tree graphs have been
organized according to two different methods. In one method, the
graphs are ordered by the number of vertices (in ascending order).
In the other classification method, graphs are ordered according to the
RNA type. You may look at all of the graphs with a particular number
of vertices or of certain type at any one time. In each classification,
graphs are ordered by the second eigenvalue of their corresponding Laplacian
matrix (i.e., in order of increasing compactness). More information
about a particular structure may be obtained by clicking on the graph.
Links to different parts of the rest of this database have been provided
as well as links to other useful databases and programs.