We have 3 visitors from Chris Hogue's group from Toronto (at the Samuel
Lunenfeld Research Institute). Katerina Michalickova, Gary Bader, and
Howard Feldman. They are students with him and will be presenting their
projects (see below). Each will speak for about 20 minutes. If you would
like to speak to any of these individuals, please let me kow.
David

SeqHound, an ASN.1 based in-house database system.
Katerina Michalickova

Our bioinformatics research requires a fast, reliable and up-to-date
in-house database system with public biological sequence and structure
databases.  Starting with the NCBI ftp site and the relevant databases
in ASN.1 binary form and the NCBI toolkit we have designed a
lightweight, portable integrated database system that can support our
bioinformatics research.  Database index information is stored together
with the original ASN.1 binary data in a database built using the
CodeBase Database system, (Sequiter Software Inc., Alberta) which is
like the NCBI toolkit in design, and allows us to distribute
excecutables royalty-free.  SeqHound maintains all nucleotide, protein
and 3-D data in-house in a few individual binary databases in ASN.1
format, and it can be updated daily from NCBI ftp site.  Database
searches are supported for the most common queries, including unique
geninfo identifiers (GI), GenBank accession numbers, original sequence
names, NCBI taxonomy identifiers, medline identifiers, molecular
modeling database (MMDB) identifiers and protein databank (PDB)
identifiers.  All sequences and 3-D structures can be retrieved in
several formats such as definition line, FastA format, ASN.1 print
format, GenBank flat file, PDB flat file, thanks to routines from the
NCBI toolkit.  In addition, link information is extracted and indexed,
including nucleotide-protein, structure-sequence, Taxonomy and Medline. 
Nonredundant information is also indexed by parsing the NR BLAST
database flatfiles, and the system supports nonredundant queries.  We
developed our own application programming interface (API) which utilizes
the in-house databases to retrieve data both from a local disk and
remotely through an http interface.  


BIND - A Database for Storing Biomolecular Interactions and Their
Properties
Gary D. Bader

We present a new database called BIND (Biomolecular Interaction Network
Database). This database can span the complexity of interaction
information gathered through experimental studies of biomolecular
interactions.  The ASN.1 data specification for BIND contains
interaction, molecular complex and pathway records and inherits
sequence, structure, taxonomy and other types from the NCBI ASN.1 data
model.  An interaction record is based on the interaction between two
objects.  An object can be a protein, DNA, RNA, ligand or molecular
complex.  Description of an interaction encompasses cellular location,
experimental conditions used to observe the interaction, conserved
sequence, molecular location of interaction, chemical action, kinetics,
thermodynamics, and chemical state. Molecular complexes are defined as
collections of more than two interactions that form a complex, with
extra descriptive information such as complex topology.  Pathways are
defined as collections of more than two interactions that form a
pathway, with extra descriptive information such as cell cycle stage.



A Fast Method to Sample Real Protein Conformational Space
Howard J Feldman 

A method to generate protein conformers of arbitrary amino acid
composition in O(NlogN) time has been developed, taking only the primary
sequence as input. These conformers possess physically and chirally
valid backbones with all bond lengths, angles and dihedrals within the
allowable tolerances.  The method is based upon a 2-D probability
distribution function for Ca placement called a 'trajectory graph'. 
The algorithm has been shown to be useful for both reconstructing
backbones of real proteins, and generating random proteins.  These modes
may be mixed, making it possible to sample unknown domain structures and
linker regions while reconstructing domains with known structure
simultaneously.  Experimental distance restraints such as NOEs or
hydrogen bonds can be added to bias the random walk, if known.
We have further developed a system that allows us to compute protein
dynamic trajectories, based on a physical model of protein backbone
motion.  We show protein unfolding movies, and the energies calculated
for these at each step, using an atom based potential.  Through analogy
to a 2-D gas, a relation has been drawn between this energy score and
the motion of a given residue.