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<html>
<title>BOSC2003 Abstracts</title>
<style type="text/css"><!--
h1 { color: #336; font-style: normal; font-weight: bolder; font-family: Arial, Helvetica }
h2 { color: #336; font-style: normal; font-weight: bolder; font-family: Arial, Helvetica }
h3 { color: #336; font-style: normal; font-weight: bolder; font-family: Arial, Helvetica }-->
</style>
<body bgcolor="white">
<table border="0" cellpadding="2" cellspacing="2">
<tr>
<td colspan="2" align="right" valign="top">
<a href="index.html"><img src="bosc-2003-logo.gif" alt="BOSC 2003" width="302" height="81" hspace="10"></a></td>
<td valign="center" hspace=20>
<img src="title.gif" alt="Bioinformatics Open Source Conference" width="394" height="53">
<p>
<font face="Arial,Helvetica,Geneva,Swiss,SunSans-Regular">
<font size=+5><B>BOSC 2003 Talk Abstracts</B></font><br>
View <a href="program.html">the program</a><P>
</font>
</td>
</tr>
</table>
<a name="biojava"/>
27 June, 9:20 - 9:50
<h2>BioJava Turns 1.3</h2>
<P><i><b>Mark Schreiber</b>, Thomas Down, David Huen, Keith James, Matthew Pocock</i></P>
<P>At the time of writing the BioJava project, now in its fifth year,
is preparing its 1.3 release. This release represents a considerable
step forward in the stability, usability and documentation of the core
APIs. The project has close to 1000 java classes contributed by 38
authors. BioJava is distributed under the LGPL license. The
improvement in usability has been brought about by the widespread
introduction of convenience methods to perform common tasks. A
cookbook style project called <i>BioJava in Anger</i> is available on
the web (<a href="http://bioconf.otago.ac.nz/biojava/">bioconf.otago.ac.nz/biojava</a>)
to provide recipes for common tasks and continued improvement of the
javadocs have helped to reduce the learning curve</P>
<P>BioJava handles many common bioinformatics tasks such as file
parsing, sequence manipulation, sequence statistics and analysis,
dynamic programming, and HMMs. BioJava also supports many "Enterprise"
level bioinformatics tasks with support for the OBDA specifications
such as BioSQL, DAS, remote data sources and Ensembl bindings. There
is also robust serialization and distributed programming support and
recent testing indicates BioJava 1.3 is compliant with J2EE
technologies which should enable the rapid development of very
scalable BioJava based bioinformatics solutions.</P>
Homepage: <a href="http://www.biojava.org/">http://www.biojava.org/</a>
<hr>
<a name="kegg"/>
27 June, 9:50 - 10:20
<h2>BioRuby project and the KEGG API</h2>
<P>
<i><b>Toshiaki Katayama</b>, Naohisa Goto, Mitsuteru C. Nakao,
Shuichi Kawashima, Yoko Sato, Minoru Kanehisa</i><br/>
Bioinformatics center, Kyoto University, Japan
</P>
<P>
<a href="http://www.bioruby.org">BioRuby</a> is a class library for bioinformatics written in an object
oriented scripting language <a href="http://www.ruby-lang.org/">Ruby</a>. The Ruby language, born in Japan,
is now getting popular over the world after its 10 years of
development. We believe Ruby is one of the easiest languages for the
object oriented programming because of its clean syntax. This makes
beginners to start using Ruby very quickly without learning the
#*$%@ing enchantments. Furthermore, Ruby is also powerful enough for
the various bioinformatics tasks by its unlimited data structures, by
its ability to manipulate strings with Perl-like regular expressions,
and by its extensibility with the external C library. Thus, BioRuby
will be suitable both for the bioinformatics begginers in the wet lab
and the hard-core developers, simultaneously.
</P>
<P>
BioRuby has been developed over the past 2 years and is compliant with
the OBDA (Open Bio Database Access) specifications to access sequence
databases by cooperating with other precedent Open Bio* projects
including BioJava, BioPerl and BioPython. As well as the OBDA,
BioRuby can handle biological sequences, parse and create index for
over 20 flat file database formats including KEGG databases, executes
local and/or remote blast/fasta/hmmer searches, accessing DAS based
genome databases for sequence annotations and PubMed database for
reference information etc.
</P>
<P>
Recently, we have added a new feature called KEGG API which provides
valuable means for accessing the KEGG system at the GenomeNet in
Japan. The KEGG API is a SOAP based web service for searching and
computing biochemical pathways in cellular processes and analyzing the
universe of genes in the completely sequenced genomes. The BioRuby
interface of the KEGG API enables the users to easily write customized
procedures for automated analyses of the pathways and/or the gene
universe.
</P>
Homepage: <a href="http://www.genome.ad.jp/kegg/soap/">http://www.genome.ad.jp/kegg/soap/</a>
<hr>
<a name="bioperl"/>
27 June, 10:40 - 11:10
<h2>BioPerl in 2003: a users perspective</h2>
<P>
<i><b>Niel Saunders</b></i><br/>
School of Biotechnology and Biomolecular Sciences, The University of New South Wales
</P>
<P>
The BioPerl project, officially organised in 1995, has developed into a
mature collection of Perl modules for building solutions to
bioinformatics problems. BioPerl now contains a large number of modules
that enable researchers to perform many fundamental tasks in
bioinformatics analysis. These include: accessing sequence data from
remote or local databases, creating or converting sequence files in
various formats, parsing the output from software packages (such as
BLAST), manipulating biological data (e.g. sequence alignments,
phylogenetic trees, structure files), running external programs and even
querying bibliographic databases. The BioPerl community is an
open, active group and welcomes contributions from developers and users.
<P>
</P>
The first part of this talk is an overview of the BioPerl project and
includes a brief look at recent developments. In the second part, a
number of real examples will be discussed to illustrate how BioPerl is
being used in a microbial genomics research group.
</P>
Homepage: <a href="http://www.bioperl.org/">http://www.bioperl.org/</a>
<hr>
<a name="bioperldb"/>
27 June, 11:10 - 11:40
<h2>Persistent Bioperl</h2>
<P>
<i><b>Hilmar Lapp</b></i><br/>
Genomics Institute of the Novartis Research Foundation
</P>
<P>
Bioperl-db adds transparent database persistence to the Bioperl object
model. The package provides the client with the ability to turn a given
Bioperl object into a so-called persistent object, which speaks the same
APIs that the original Bioperl object did, but in addition also is able
to handle persistence operations, like insert, update, and delete.
</P>
<P>
This enables the programmer to manipulate objects after they have been
retrieved from or inserted into the database, and then update with a
single function call the respective rows in the database to reflect
those changes. As a practical example, one can retrieve a sequence
object by accession from the underlying database, then programmatically
or interactively manipulate the annotation for that sequence object by
adding, changing, or removing features, database cross-references, and
tag/value pairs. Subsequently one can update the database to reflect the
changed annotation by asking the sequence object to update itself, which
will cascade down to its annotation.
</P>
<P>
The actual persistence operations are presently implemented with
bindings to a Biosql schema served by either MySQL, PostgreSQL, or
Oracle. One aim of the design was to minimize the effort to write
bindings to a different schema. It is a future goal to provide bindings
to schemas that differ from Biosql in their relational model, like Chado
or Ensembl.
</P>
<P>
In summary, Bioperl-db together with Biosql adds easy-to-use,
transparent, and freely available persistence to one of the, if not the
most important Perl package in the life sciences, complete with schema
and database loading scripts. In my talk I will present an overview on
the functionality of the package, demonstrate some simple use cases, and
conclude with the current status and future directions. I will also
touch on the utility of Biosql as the underlying open source schema that
facilitates interoperability between the Bio* projects.
</P>
Homepage: <a href="http://www.bioperl.org/">http://www.bioperl.org/</a>
<hr>
<a name="biopython"/>
27 June, 11:40 - 12:10
<h2>Using Biopython for Laboratory Analysis Pipelines</h2>
<P>
<i><b>Brad Chapman</b></i><br/>
The Plant Genome Mapping Laboratory, University of Georgia
</P>
<P>
The Biopython project is distributed collaborative effort to develop Python
libraries to address the needs of researchers doing bioinformatics work.
Python is an interpreted object-oriented programming language that we feel is
well suited for both beginning and advanced computational researchers. Biopython
has been around since 1999, and has a number of active contributors and
users who continue its regular development.
</P>
<P>
One major problem in bioinformatics work is developing analysis pipelines
which combine data from a number of different sources. Advanced
scientific questions will require information from many disparate sources
such as web pages, flat text files and relational databases. Additionally,
these sources of information will often be found in different, non-compatible
formats. The challenge of many researchers and software developers is to
organize this information so that it can be readily queried and examined.
This problem is made even more difficult by the varied and rapidly changing
interests of scientists who want to ask questions with the data.
</P>
<P>
Rather then trying to build specific applications to address these data
manipulation problems, Biopython has focused on developing library
functionality to manipulate various data sources. This frees a researcher from
having to deal with low level details of parsing and data acquisition helping
to abstract the process of data conversion. Additionally, since the lower level
data manipulation code is shared amongst multiple researchers, data format
changes or problems with the code are more readily identified and fixed.
</P>
<P>
This talk will focus on using the Biopython libraries in developing analysis
pipelines for scientific research. In addition to demonstrating the uses of
Biopython, this will highlight some areas where Biopython offers unique
solutions to data manipulation problems. We will identify some of the common
challenges the libraries have to deal with, such as attempts to standardize
output from multiple programs that perform similar function, and describe our
attempts to deal with these difficulties. This will provide a foundation for both
understanding the Biopython libraries and the development process underlying
them.
</P>
Homepage: <a href="http://www.biopython.org/">http://www.biopython.org/</a>
<hr>
<a name="molabis"/>
27 June, 13:30 - 14:00
<h2>MoLabIS - A labs backbone for storing, managing, and evaluating molecular genetics data</h2>
<P><i><b>Eildert Groeneveld</b></i> Institute for Animal Science, Federal
Agricultural Research Center, Mariensee, Höltystr. 10, D-31535 Neustadt,
Germany, <i>Ralf Fischer</i> and <i>Špela Malovrh</i></P>
<P>With increased use of molecular genotyping, sample and data
management has become a major issue in molecular genetic labs. This
includes description of projects, management of tissues and DNA
samples and data produced by sequencers. Joint analysis of data from
disparate sources implies format conversion which often has to be done
manually. MoLabIS is an attempt to address theses issues in a generic
way by storing primary data from disparates source in one standard
format. It allows to
<ul>
<li> supports the management of samples, tissue and DNA, in storage by
<ul>
<li> defining and documenting projects</li>
<li> uniquely identifying samples within projects</li>
<li> tracking samples of various kinds in storage (e.g.
deep freezers)</li>
<li> allocating these samples to individuals (like
humans or animals) supporting any animal
identification scheme</li>
<li> storing additional information for each animal with
different structures of traits for different
projects. These may be measurements or descriptions
which can be included in further analyses.</li>
</li>
</ul>
<li> store all genotype data in one relational database
for any number of projects from disparate sources by
<ul>
<li> including original "data" (like images) together with
reconciled data from different sequencers</li>
<li> transforming proprietary data from disparate
sources to one uniform format using filters among
others from the Staden package</li>
<li> storing bi-allelic data like microsatellite and
sequences in one uniform format in a relational database</li>
</ul>
</li>
<li> represents a uniform interface for data analysis.
Currently, a number of measures of statistical
measures of biodiversity have been included. As such
it
<ul>
<li> allows script based analysis of all data in the database</li>
<li> serves as platform for implementation of other
procedures as they become available in the Open
Source community</li>
</ul>
</li>
<li> centralize data management in a molecular lab using a
client server infrastructure.</li>
</ul>
<P>
MoLabIS is based on the APIIS (adaptable platform
independent information system) framework which has
been developed for the rapid implementation of animal
recording systems in agriculture. It uses exclusively
Open Source software and is centered around an SQL-92
database, usually PostgreSQL. With Perl and TK-Perl it
creates client server applications. Furthermore, all
applications are also available in a browser version.
While project data can be added via a GUI interface,
molecular genetic data are loaded without human
intervention from predefined directories where
sequencers drop them off. All data manipulations are
done using SQL. MoLabIS and APIIS is going to be released
under the GPL.
</P>
<hr>
<a name="slims"/>
27 June, 14:00 - 14:15
<h2>An Open Source Small Laboratory Information System (SLIMS)</h2>
<P>
<i><b>Anton Bergheim</b></i><br/>
Department of Computer Science University of the Witwatersrand
South Africa tel: + 27 11 717 6178
</P>
<P>
There exists within the scientific community of the developing world a
real need for an open source small laboratory information system. As
the economic reality of the developing worlds science does not permit
the purchase of more sophisticated commercial systems, most smaller
laboratories are vanquished to lab books and at best primitive
databases. Lack of financial resources also means that these labs
tend to do less "big science", preferring instead to perform a larger
number of smaller more specialized experiments.
</P>
<P>
Although a large amount of work has been done to address this issue,
most of it seems to cater for the larger laboratories performing more
high throughput tasks (LIMaS for microarrays, a system from the
Weizmann Institute of Science which caters for DNA sequencing, and
SNPSnapper for SNP genotypes, amongst others). While these systems
are applicable, they seem better suited for laboratories which
emphasize more throughput processes with less variation in the
techniques performed.
</P>
<P>
The need for a small laboratory LIMS system is one that has been
recognized previously (the Open LIMS Project, the BioJava LIMS system
and Gnosis being prime examples). Rather than reinvent the wheel,
SLIMS will be designed to take advantage of the experiences and code
(when available) of all these previous projects.
</P>
<P>
The challenge is to design a LIMS system that is both powerful and
flexible while working on sparse resources with a minimal amount of
training. Any LIMS system used in this environment has to be designed
such that it allows the user to easily add many different types of
experimental procedures rapidly. To do this a type of workflow system
has to be devised or an existing one used. In this sense, the SLIMS
project most closely resembles the bioJava LIMS system (SLIMS plans to
utilize much of the bioJava LIMS system as well as extending it).
</P>
<P>
Preliminary studies have begun assessing user requirements. These
requirements dictate a system which allows for ease of use, ease of
installation, maximum data security, and extensive data, project and
people tracking. The system will have to automatically integrate with
existing machinery (a gel documentation system or a automated
sequencer for example). Beyond storing data, and generating
workflows, the SLIMS system has to allow for extensive data querying.
Typical user queries can be of the sort "show me all information about
sample x?" or "show me all experiments done by person y?". Some data
types mentioned include sequencing gel pictures, DNA sequences,
agarose gel pictures and attached annotation, autoradiographs (SSCP
analysis, Southern, Western and Northern blots and DNA library
probing), as well as project and people information.
</P>
<P>
One possible architecture that seems to cater for most user
requirements uses a Java based GUI front end with a relational
database behind it. The system will have to be designed such that it
can work on a stand alone PC as well a computer network. The first
version of the SLIMS will effectively be a data store and show
application controlled through workflows. Later versions will have
functionality allowing for automated integration with other laboratory
machinery, as well as more sophisticated data and project tracking,
and tight integration with bioinformatic analysis tools.
</P>
<P>
As any LIMS system is a large undertaking, it is the hope of this
author that a collaboration can be formed to develop this emerging
system such that it can become an invaluable tool for smaller labs
throughout the developing world.
</P>
<hr>
<a name="flymine"/>
27 June, 14:15 - 14:45
<h2>FlyMine</h2>
<P>
<i><b>Andrew Varley</b></i>, FlyMine project, Cambridge University, UK
</P>
<P>
The FlyMine project is an open-source project to build an integrated
database of genomic, expression and protein data for Drosophila and
Anopheles. We aim to provide a powerful and flexible query system,
with the data available for arbitrary queries via a web interface and
a programming API.
</P>
<P>
The database itself is an object database built on top of PostgreSQL
using the Apache OJB object/relational mapping tool, modified heavily
in order to allow proper object-based queries, either using OQL or the
FlyMine Query API (Java). At the underlying SQL level, the data in the
tables are redundantly stored in a collection of "Precomputed
tables" -- tables that are materialised views of one or more master
tables. All incoming queries are automatically analysed to see if
any combinations of these precomputed tables can be used to shorten
the response time. This approach results in a substantial speed
increase for many queries. This SQL re-writing module can be used
independently of the FlyMine project to improve access to read-only
SQL databases.
</P>
<P>
Remote bioinformatics users will be able to access the data using the
same query API over SOAP/HTTPS to the main FlyMine servers. The data
model is specified as a UML diagram, which is used to automatically
generate all model-specific parts of the system: therefore the FlyMine
project can easily be applied to other domains. We will also provide a
graphical object query tool to make it easy for non-programmers to
formulate complex arbitrary queries against the data model.
</P>
<P>
The source code will be made available under a LGPL licence around the
time of BOSC and will be available on a public CVS server.
</P>
Homepage: <a href="http://www.flymine.org/">http://www.flymine.org/</a>
<hr>
<a name="pysystemsbio"/>
27 June, 14:45 - 15:15
<h2>Python and the Systems Biology extension module for inferring gene regulatory networks from time-course gene expression data</h2>
<P>
<i><b>Michiel de Hoon</b>, Seiya Imoto, Satoru Miyano</i><br/>
Laboratory of DNA Information Analysis, Human Genome Center Institute of
Medical Science, University of Tokyo 4-6-1 Shirokanedai, Minato-ku,
Tokyo 108-8639, Japan
</P>
<P>
Scripting languages such as Perl and Python are commonly used in
bioinformatics for database access, file parsing, and sequence
manipulation. Python together with Numerical Python is also very
suitable for analyzing numerical data, such as gene expression data
produced in cDNA microarray experiments.
</P>
<P>
Inferring gene regulatory networks from gene expression data is an
important topic in bioinformatics. Since recently, dynamic Bayesian
network models have been used to infer gene regulatory relations from
time-course gene expression data. Software tools for dynamic Bayesian
network calculations are in most cases proprietary.
</P>
<P>
We have developed the Systems Biology extension module for Python,
consisting of fast-running C routines to fit noisy dynamical system
models (a generalization of dynamic Bayesian networks) to time-course
gene expression data. The routines allow for missing data values and
can handle different time intervals between measurements; several
statistical criteria are available to determine the number of
transcription factors for each gene. For visualization, we made use of
the Pygist scientific plotting package, which was recently ported to
Windows and Mac OS X
</P>
<P>
Using this extension module, we were able to generate a highly
significant validation of gene regulation by transcription factors in
Bacillus subtilis from time-course gene expression data. We also
predicted which sigma factors regulate the transcription of the sigY
and sigV genes in Bacillus subtilis, whose regulation is currently not
well understood.
</P>
<P>
The Systems Biology extension module makes use of the GNU Scientific
Library, and was itself released under the GNU General Public
License. It is available at
<a href="http://bonsai.ims.u-tokyo.ac.jp/~mdehoon/software/python/">http://bonsai.ims.u-tokyo.ac.jp/~mdehoon/software/python</a>.
</P>
Homepage: <a href="http://bonsai.ims.u-tokyo.ac.jp/~mdehoon/software/python/systems.html">http://bonsai.ims.u-tokyo.ac.jp/~mdehoon/software/python/systems.html</a>
<hr>
<a name="elm"/>
28 June, 9:00 - 9:15
<h2>The Eukaryotic Linear Motif Resource</h2>
<P>
<i><b>Rune Linding</b></i>, EMBL
</P>
<P>
ELM is a resource for predicting functional sites (described by linear
motifs) in eukarytic proteins. Putative functional sites are
identified by conventional methods, such as patterns (regular
expressions) or HMM models. To improve the predictive power,
context-based rules and logical filters will be developed and applied
to reduce the amount of false positives.
</P>
<P>
The current version of the ELM server provides basic functionality
including filtering by cell compartment and globular domain clash
(using the SMART/Pfam databases). The current set of motifs is not
exhaustive. The ELM resource will be regularly enhanced through 2003.
</P>
Homepage: <a href="http://ELM.eu.org/">http://ELM.eu.org/</a>
<hr>
<a name="globplot"/>
28 June, 9:15 - 9:30
<h2>Exploring protein sequences for globularity and disorder</h2>
<P>
<i><b>Rune Linding</b></i>, EMBL
</P>
<P>
A major challenge in the proteomics and structural genomics era is to
predict protein structure and function, including identification of
those proteins that are partially or wholly unstructured. Non-globular
sequence segments often contain short linear peptide motifs
(e.g. SH3-binding sites) which are important for protein function. We
present here a new tool for discovery of such unstructured, or
disordered regions within proteins. GlobPlot (<a href="http://globplot.embl.de/">http://globplot.embl.de</a>) is a web
service that allows the user to plot the tendency within the query
protein for order/globularity and disorder.
</P>
Homepage: <a href="http://globplot.embl.de/">http://globplot.embl.de/</a>
<hr>
<a name="lectin"/>
28 June, 9:30 - 9:45
<h2>An online database of C-type Lectin Like Domain-containing sequences</h2>
<P>
<b>Alex Zelensky</b>, Jill Gready<br/>
Computational Proteomics and Therapy Design Group, Division of Molecular Bioscience, John Curtin School of Medical Research, Australian National University
</P>
<P>
While analyzing a family of C-type Lectin-like Domain (CTLD) containing
proteins (CTLD-cp), we have realized that the huge volume of existing
sequences and literature information (>1500 GenPept entries, thousands
Medline-indexed publications) require more robust data management tools
than office software commonly used by biologists. To suit our needs we
have developed of a relational database, and a web interface to it,
which allow storage, integration, classification and expert annotation
of various kinds of biological information related to the protein
family we are interested in. The product can be broadly classified as a
biological content-management system, and focuses on providing
high-quality biological information and a collaborative environment for
its annotation.
</P>
<P>
A web interface was developed to manage MySQL-based sequence and
annotation databases. Bioperl objects are used to handle rich sequence
information, which is stored in a BioSQL schema based DB, while
homology relationships, custom annotations and classifications, as well
as web user information, are stored in a second database. DB accessor
and controller Perl modules were developed for objects that are not
available through BioPerl. The structure of the annotation database is
phylogeny-focused and contains three principal tiers: product
(translated gene product or its part, whose sequence was deposited in a
protein sequence database), gene locus and GOG (group of orthologous
genes from different species). Sequence collection was developed from
the ground up, starting with a selection of GenPept entries containing
CTLDs. After clustering redundant entries, homologous protein sequence
DB entries were classified as paralogues, orthologues or alternative
splicing products based on sequence similarity, genomic references and
literature data. This simple bookkeeping phase allowed us to update and
extend the existing CTLD-cp classifications (Drickamer 1996; Drickamer
2002), and provide a basis for further analyses, e.g. for studying
alternative splicing events that are common in the CTLD family. Next,
we started comparing the created catalogue of CTLD-cps to sequenced
genomes (human and Fugu at the moment), which allowed us to see how
well the family was studied and to find new members of established
CTLD-cp groups as well as previously unknown classes of CTLD-cp.
</P>
<P>
After finishing the initial content creation and QA checks of both
contents and interface, the database will be made public and the CTLD
community will be invited to use and extend it. Also, though at the
moment the database and software are tailored to a particular set of
proteins, they can be developed into a more universal biological
content-management system, which could be used by other laboratories
for managing and sharing their expertise in other protein families.
Source codes and schema will be readily provided to anyone interested.
</P>
<P>
Drickamer K, Fadden AJ. Genomic analysis of C-type lectins. Biochem
Soc Symp. 2002;(69):59-72. PMID: 12655774<br/>
Drickamer K. Evolution of Ca(2+)-dependent animal lectins. Prog
Nucleic Acid Res Mol Biol. 1993;45:207-32. PMID: 8341801
</P>
<hr>
<a name="webservices"/>
28 June, 9:45 - 10:15
<h2>Transition to Web Services in bioinformatics (driven by use cases)</h2>
<P>
<i><b>Martin Senger</b></i>, EBI
<P>
Web Services is a technology applicable for computationally
distributed problems, which includes access to large databases. The
technology is capable to deal with heterogeneous environments - but it
is not too different from its predecessors, such as CORBA. The article
presents the main differences between these middleware approaches
(firewall-friendliness, user sessions, market forces, object views)
and shows two concrete use cases of the Web Services deployed at
EMBL-EBI.
</P>
<h3>Web Services</h3>
<P>
The Web Services are ubiquitously connected to XML. The universality
of XML makes almost anything connected to XML a very attractive way
to communicate information between programs. And that is where the Web
Services are focused at - it is a technology used for distributed
computing, connecting many resources available on the Internet and
making them work together.
</P>
<P>
The role of XML is clearly dominant. The other parts - even though
they are not mandatory they are used in most cases - are SOAP and
HTTP. The SOAP specifies how to encode various data types into XML
documents and how to exchange such documents in a decentralised,
distributed environment. Then the HTTP carries the encoded messages
between internet sites and its presence is reflected in the
firewall-friendliness of the Web Services.
</P>
<P>
The important, if not the most important feature of Web Services is
the language defining and describing their interfaces - the WSDL.
WSDL enables to separate the description of the abstract functionality
offered by a service from concrete details such as the service
location and its access protocol.
</P>
<h3>Web Services versus CORBA</h3>
<P>
In previous years, many investments, both in money and human resources
and skills, were made into CORBA, COM, RMI, and other technologies for
distributed computing. Therefore, there is a very legitimate question
what could be gained by using a new middleware in the current and new
projects in bioinformatics. An executive summary answer would be that
CORBA proved itself to be efficient, robust and strong inter-operable
solution ideally fit in the intranets. On the other hand, the Web
Services, by their design, are very suitable for using over the
Internet. Last but not least, the both technologies can co-exist
together in the layered architecture so one can use the strength of
both.
</P>
<P>
In more detailed answer one would say that both CORBA and Web Services
are software components designed to be used by programmers in the
first place, and both provide connectivity in a distributed
architecture. The both technologies can provide very similar features
and they both can do it with reasonably same effort from the
programmer's point of view. The more visible differences are:
<ul>
<li>Web Services (at least today) are easier to deploy because they
regularly use the firewall-friendly port 80 (used by the HTTP
carrying Web Services messages).
<li>Web Services are quite well marketed and they have visible support
from the big IT companies (Microsoft, IBM, Oracle, Sun, HP...) and
from the Open Source projects as well (Apache, Perl,...).
<li>The integration of the Web Services into workflows seems to have
more choices and keeps momentum (comparing to the rival CORBA
Components effort).
<li>On the other hand, the peer-to-peer communication in Web Services
is problematic. The Web Services clients use much more lightweight
software and they have less privileges to go through firewalls on
their sites. It requires to use different approaches for server's
callbacks and other asynchronous notification services. For
example, to use the SMTP protocol, or to extend the interface of a
Web Service to include a negotiation of available protocols.
<li>Also, in CORBA it is easier (at least today) to handle user
sessions (because of its object references). The CORBA
state-fullness is far more standardised which makes the user
sessions quite inter-operable and language independent.
<li>The CORBA is ubiquitously presented as objects where Web Services
are rather oriented on messages. Therefore, a project designer must
usually find a suitable technique to mimic CORBA's object
references in the Web Services world. One solution is to use the
string-based handlers representing the state-full objects on the
server side.
</ul>
<h3>The use cases implemented at EMBL-EBI</h3>
<P>
The EMBL-EBI is participating in a number of projects contributing
towards the development of an e-Science and grid infrastructure for
biology, many of them are based or partly based on Web Services. The
use cases presented below show the symbiosis between CORBA and Web
Services ("Soaplab" use case) and between CORBA adopted specification
and Web Services ("BQS" use case). Both described use cases are also
used in the myGrid, a multi-organisational project developing the
infrastructural middleware for an "e-Biologist's" workbench, funded by
EPSRC.
</P>
<h3>OpenBQS</h3>
<P>
OpenBQS provides a freely available implementation of the
Bibliographic Query Service specification that was standardised and
approved by the Object Management Group. The implementation
includes a Web Service providing access to the MEDLINE database
with more than 11 millions bibliographic citations.
</P>
<P>
This use case and its open-source implementation was reported
during the BOSC 2002.
</P>
<P>
<A HREF="http://industry.ebi.ac.uk/openBQS">http://industry.ebi.ac.uk/openBQS</A>
</P>
<h3>Soaplab</h3>
<P>
Soaplab is a set of Web Services providing a programatic access to
some applications on remote computers. Because such applications,
especially in the scientific environment usually analyze data,
Soaplab is often referred to as an Analysis Web Service.
</P>
<P>
Soaplab is both a specification for an Analysis Service (based on
an OMG approved specifications for sequence analyses) and its
implementation. The EMBL-EBI has Soaplab service running on top of
several tens of EMBOSS analyses.
</P>
<P>
Soaplab does not access individual analysis programs directly but
it uses a general-purpose package AppLab that hides all details
about finding, starting, controlling, and using applications
programs. The AppLab uses CORBA - but it is hidden from the Soaplab
users as an implementation detail. It documents how several
distributed techniques can be successfully combined in a layered
architecture design.
</P>
<P>
<A HREF="http://industry.ebi.ac.uk/soaplab">http://industry.ebi.ac.uk/soaplab</A>
</P>
Homepage: <a href="http://industry.ebi.ac.uk/soaplab/">http://industry.ebi.ac.uk/soaplab/</a>
<hr>
<a name="pal"/>
28 June, 10:35 - 10:50
<h2>The Phylogenetic Analysis Library project</h2>
<P>
<b>Matthew Goode</b>, University of Auckland) /
Korbinian Strimmer, University of Munich / Alexei Drummond, University of Oxford
</P>
<P>
The Phylogenetic Analysis Library project (PAL) is a collaborative
effort dedicated to provide a high quality Java library for use in
molecular evolution and phylogenetics. It provides a growing Object
Orientated resource for phylogenetic tree inference and analysis,
including Maximum Likelihood methods. Support is included for
coalescent and alignment simulation, alignment manipulation (data-type
translation, bootstrapping), and statistical analysis. Future
development will add, amongst other things, sequence alignment and
tree searching.
</P>
<P>
Pal is released under the lGPL licence, and is available from
<a href="http://www.cebl.auckland.ac.nz/pal-project/">http://www.cebl.auckland.ac.nz/pal-project/</a>.
</P>
<P>
Reference: Drummond, A., and K. Strimmer. 2001. PAL: An object-oriented
programming library for molecular evolution and phylogenetics.
Bioinformatics 17: 662-663.
</P>
Homepage: <a href="http://www.cebl.auckland.ac.nz/pal-project">http://www.cebl.auckland.ac.nz/pal-project</a>
<hr>
<a name="gmod"/>
28 June, 10:50 - 11:20
<h2>GMOD</h2>
<P>To be written</P>
Homepage: <a href="http://www.gmod.org/">http://www.gmod.org/</a>
<hr>
<a name="nmds"/>
28 June, 11:20 - 11:35
<h2>A new algorithm for nonmetric multidimensional scaling method</h2>
<P>
<i><b>Y-h. Taguchi</b></i>, Dept. Phys. Chuo University, Japan<br/>
<i>Y. Oono</i>, Dept. Phys., UIUC, USA
</P>
<P>
We have developed a new algorithm for the nonmetric multidimensional
scaling method (nMDS). It is at present implemented in Fortran
77. The following features of our algorithm may be worth emphasizing.
<ol>
<li>Conceptually transparent: In contrast to the conventional nMDS
requiring a rather artificial disparity to compute the stress to be
minimized, our algorithm directly minimizes the difference between
the rank order of dissimilarities and that of distances in the
embedding space.
<li> Computationally efficient: Our algorithm avoids time-consuming
isotonic regression, so it is much faster than the conventional
ones. The computational time is of order N<sup>2</sup>log N, where N
is the number of the objects under study, because the number of
iterations is usually less than 100. 3,000 objects can be handled
easily by using low speed PCs (e.g., 1GHz Celeron PC with 526 MB
memory).
</ol>
</P>
<P>
As an application of our algorithm to bioinformatics, we present the
analysis of microarray data of <i>Caenorhabditis elegans</i> gene
expressions. The relationship among genes is visualized in a 3D space.
</P>
Homepage: <a href="http://www.granular.com/MDS/">http://www.granular.com/MDS/</a>
<hr>
<a name="microarray_data"/>
28 June, 11:35 - 11:50
<h2>Object model and C++ modules for handling multi-platform microarray data</h2>
<P>
<b>Andrey Ptitsyn</b>, Pennington Biomedical Research Center, Baton Rouge, LA, USA
</P>
<P>
Microarray expression analysis is one of the most rapidly developing
areas of computational biology. However, open source software for
microarray analysis is still one of the least represented parts in the
projects of the Open Software Foundation. One of the major challenges
for the computational biologist is multiplicity of competing
microarray technologies and high costs of microarray equipment. Only a
handful of the world's biggest research centers can afford to support
all major microarray platforms. Current state of the microarray
technology vividly reminds the state of computer industry of 60s and
70s, with rapid development, revolutionary ideas, great variety of
hardware and operating systems, fierce competition and little effort
from the rival developers to provide platform-independence for the end
users. Object-oriented programming is one of the developments of that
era that helped to build platform-independent software. In our
opinion, the same good old (already) designing style can mitigate the
problem of incompatibility of microarray analysis software. At PBRC
we have developed an object model that can handle most of the data
acquired in microarray experiments and re-use the code for data
analysis algorithms in multiple applications for diverse microarray
platforms. The first implementation of this model is done in C++ for a
number of reasons: C++ is computationally effective, highly portable,
widely available, highly standardized and has a complete set of
object-oriented features. Once developed, C++ modules can be
re-implemented in Perl, Java or Python relatively easily, while the
opposite conversion can be more problematic. One of the goals of this
presentation is to establish cooperation with the OBF project
developers and get some help porting this object model to other
languages. The object our microarray object model has two layers. The
first layer provides interface to a particular microarray
platform. Currently we have implemented modules for spotted arrays,
Affymetrix Genechip and Clontech Plastic Arrays. The second layer
provides abstract data classes and implements various conditioning,
scaling, normalization and clustering algorithms. A few applications
have been developed with a help of these C++ modules, representing
some of the extremely incompatible ends of microarray analysis: a) a
command-line PC program for local and global linear and LOWESS
normalization of spotted arrays; b) a program for LOWESS normalization
of Atlas Rat Plastic Arrays with local background correction and c) a
parallel multi-processor application for expression profile
clustering.
</P>
<hr>
<a name="biogopher"/>
28 June, 13:30 - 13:35
<h2>BIOgopher: Integrating spreadsheets with large bioinformatics databases</h2>