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BMC Bioinformatics
BioMed Central
Open Access
Introduction
Highlights from the 5th International Society for Computational
Biology Student Council Symposium at the 17th Annual
International Conference on Intelligent Systems for Molecular
Biology and the 8th European Conference on Computational
Biology
Thomas Abeel*1,2, Jeroen de Ridder3,4 and Lucia Peixoto5
Address: 1Department of Plant Systems Biology, VIB, Ghent University, Gent, Belgium, 2Broad Institute of MIT and Harvard, Cambridge, MA, USA,
3Delft Bioinformatics Lab, Delft University of Technology, Delft, The Netherlands, 4Bioinformatics and Statistics, Dept. of Molecular Biology,
Netherlands Cancer Institute, Amsterdam, The Netherlands and 5Department of Biology and PENN Genome Frontiers Institute, University of
Pennsylvania, Philadelphia, PA, USA
Email: Thomas Abeel* - thomas@abeel.be
* Corresponding author
from Fifth International Society for Computational Biology (ISCB) Student Council Symposium
Stockholm, Sweden. 27 June 2009
Published: 19 October 2009
BMC Bioinformatics 2009, 10(Suppl 13):I1
doi:10.1186/1471-2105-10-S13-I1
<supplement> <title> <p>Highlights from the Fifth International Society for Computational Biology (ISCB) Student Council Symposium</p> </title> <editor>Thomas Abeel</editor> <note>Meeting abstracts – A single PDF containing all abstracts in this Supplement is available <a href="http://www.biomedcentral.com/content/files/pdf/1471-2105-10-S13-full.pdf">here</a>.</note> <url>http://www.biomedcentral.com/content/pdf/1471-2105-10-S13-info.pdf</url> </supplement>
This article is available from: http://www.biomedcentral.com/1471-2105/10/S13/I1
© 2009 Abeel et al; licensee BioMed Central Ltd.
Abstract
This meeting report gives an overview of the keynote lectures and a selection of the student presentations at the 5th
International Society for Computational Biology Student
Council Symposium at the 17th Annual International
Conference on Intelligent Systems for Molecular Biology
(ISMB) and the 8th European Conference on Computational Biology (ECCB). The symposium was held in Stockholm, Sweden from June 27 to July 2, 2009. We also
report on other Student Council events that were organized at ISMB/ECCB 2009.
Introduction
The Student Council (SC) of the International Society for
Computational Biology (ISCB) is a world-spanning
organization for students in the broad field of computational biology and bioinformatics.
The major aims of the Student Council are to organize
events and facilitate networking opportunities for students. The main contribution of the SC is to nurture soft
skills, such as working in a team, organizational and net-
working skills, to complement the normal academic program. Since its inception, the Student Council has
organized an annual student symposium for the benefit of
the student community. This year the fifth Student Council Symposium was held in conjunction with the joint
ISMB and ECCB conferences on June 27th. Over 120 delegates took part in this first anniversary edition of the Student Council Symposium. The symposium featured three
keynote lectures, a research partner session with two
speakers, a tutorial, a panel discussion, nine student presentations and a poster session.
This year's keynotes were delivered by three very wellestablished and acclaimed scientists. The symposium
started with a keynote lecture by Peer Bork (EMBL Heidelberg, Germany) on the topic of "Integration of heterogeneous data in Biology: from chemicals to ecosystems".
The afternoon session was initiated by Michal Linial (The
Hebrew University of Jerusalem, Jerusalem, Israel) with a
presentation titled "In search of overlooked functions:
hidden connections among proteins, toxins and viruses".
The day was concluded by Overton Prize winner Trey
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BMC Bioinformatics 2009, 10(Suppl 13):I1
Ideker (UC San Diego School of Medicine, USA) with his
presentation "Biological Networks: Facebook for Proteins".
In the research partner session we were fortunate to have
two presenters that delivered highly interesting scientific
lectures. First, Barend Mons (Netherlands Bioinformatics
Centre) gave an overview of the initiatives and tools developed at NBIC to optimize the value added to bioinformatics research. Next was Jong Bhak (Korea Bioinformation
Centre), who gave an account of the first sequenced
genome of a Korean individual, and showed that this provides unique insights in this socio-ethnic group.
New this year was a tutorial session. Keeping in mind the
increasing need of statistical analysis and data mining in
bioinformatics, we selected a topic of broad interest: R/
Bioconductor. The tutorial was given by Wolfgang Huber
(EMBL Heidlberg, Germany), one of the core members of
the Bioconductor project, who gave valuable insights into
this very important topic.
The theme of our panel discussion this year was "Bioinformatics in the era of personal genomics". We invited three
panelists from academia and industry to talk about their
experiences and discuss questions from the audience. The
discussion was moderated by Jeroen de Ridder. This year's
panelists were Michael Brudno (University of Toronto,
Canada), Subhajyoti De (University of Cambridge,
United Kingdom) and Dirk Evers (Illumina, United Kingdom). The discussion was highly interactive and many of
the delegates participated actively.
Proceedings
Eight students had the opportunity to present their work
orally, while 64 students accepted the opportunity to
show their accomplishments during the poster session.
For the meeting report we selected the best abstracts from
the 101 submissions. This comprises seven abstracts from
the oral presentations and seven abstracts from the bestranked poster presentations. The review procedure, supervised by the Program Chair Thomas Abeel, was conducted
by an international group of more than 40 students and
young researchers.
The fourteen abstracts can be grouped in four very broad
categories: (i) functional genomics and gene expression,
(ii) protein structure and function, (iii) evolution and
population biology and (iv) next-generation sequencing
analysis and applications.
1. Functional genomics and gene expression
Genome-wide sequencing has undoubtedly revolutionized the way we do biology. Nowadays, thousands of
complete genomes are available, and many more will be
http://www.biomedcentral.com/1471-2105/10/S13/I1
available within the next decade. The challenges of
genome assembly and annotation have largely been conquered. However, the functional output of those genomes
is not yet completely understood, and is currently the
focus of research. One of those functional outputs is gene
expression, which is the first step towards the generation
of a phenotype. During the symposium several studies
have taken advantage of the capabilities of genome-wide
expression technologies and the availability of such data
that has been accumulated in the past decade to answer
relevant biological questions. For example, Szczepińska et
al. [1] use gene expression data to explore relations
between gene expression and genomic context. They identify and functionally annotate distant genomic clusters
within co-expression clusters. The number of annotated
clusters was significantly higher than random. Koeva et al.
[2] combine shared differential expression with homology to define "core stemness mechanisms" in mouse stem
cell types. Co-expression analysis has become an essential
part of the data exploration phase when dealing with
genome-wide expression data. Although several algorithms are available for this purpose, new and more efficient ones are constantly being developed. One new
algorithm, designed by Schulteiss et al. [3], uses a newly
developed SVN-kernel to identify regulatory modules.
Exploring functional aspects of the genome does not need
to involve generating new data, since a vast amount of
data is publicly available. This allows us to search for sets
of related experiments with biological relevance. Caldas et
al. [4] describe an algorithm to query the data based on
the actual measurements instead of the textual annotations. Such a huge amount of data requires specialized visualization to be interpretable. Standard heat maps and
profile plots cannot handle hundreds of thousands of
samples. This is where Space Maps come in, a visualization technique developed by Gehlenborg et al. [5].
Expressed genes are by no means the only functional output of genomes. The role of non-coding RNAs in the regulation of cell processes cannot be ignored. Moreover,
their function can actually be used to uncover the functions of genes, by using high-throughput siRNA screens.
These screens can identify genes that underlie similar phenotypes by the clustering of their screen profiles. Samusik
et al. [6] describe how genes that show the same phenotypes are more likely to interact with each other and they
developed a method of cross-validation of siRNA screening data using protein-protein interactions.
2. Protein structure and function
Proteins are the building blocks of life. Ultimately, the
expression of genes leads to the expression of proteins.
However, computationally speaking, proteins are much
more complex than DNA, since their function is extremely
dependent on its tridimensional structure, which varies
from protein to protein.
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BMC Bioinformatics 2009, 10(Suppl 13):I1
http://www.biomedcentral.com/1471-2105/10/S13/I1
Predicting how a protein will fold from its linear sequence
of amino acids is in itself a complex problem and it is even
more challenging for transmembrane proteins. Tran et al.
[7] implemented a new algorithm that can successfully
deal with super-secondary structures in beta-barrel transmembrane proteins. Once folds and structures have been
determined, structural alignment allows extending them
to closely related homologs. Although several methods
exist today to achieve such a task, they are mostly heuristic. Wohlers et al. [8] developed PAUL, a non-heuristic
approach that can outperform existing methods. There are
several factors that influence variability in structural alignments. Pirovano et al. [9] determined that certain types of
folds (helices and coils) are usually observed in inconsistent alignment regions. Since this observation is at odds
with currently used alignment strategies, more care
should be taken in the development of new algorithms.
Protein structures, more than the sequences themselves,
capture the function of a protein. Hence, they are better
suited to identify functional homologs. Combining structure searches with advanced HMMs is a much more reliable way to search for conserved functions than simple
sequence similarity searches. Petrossian et al. [10] uses
this strategy to predict novel methyltransferases that are
also shown to bind the appropriate substrate.
Biosystems SOLiD, Helicos HeliScope) are currently able
to produce "ultra-short" paired reads of lengths starting at
25 nt. It is still an open question whether genome resequencing is feasible with ultra-short paired reads.
Chikhi et al. [13] show that re-sequencing requires significantly (48.3%) shorter paired reads to produce results
comparable to unpaired reads. High-throughput sequencing technologies open exciting new approaches to transcriptome profiling (RNA-Seq). Bohnert et al. [14]
developed a new technique to accurately infer the underlying transcript abundances based on linear programming, which is also a powerful tool to reveal and quantify
novel (alternative) transcripts.
3. Evolution and population biology
If proteins determine phenotype, evolution determines
which of those phenotypes we are likely to see by natural
selection. Selection itself depends on diversity. Functional
divergence or selection for new function is the hallmark of
successful adaptation. Hence, the identification of proteins under functional divergence is of broad interest. Williams et al. [11] present a fast new method for detecting
these changes on the whole-genome level across a complex phylogenetic tree. They also apply the method successfully to the evolution of pathogenicity in divergent
bacterial lineages. The diversity that selection operates on
can also be the source of disease susceptibility among
individuals. Genome-wide association studies aim to find
the association between genetic markers, usually SNPs,
and disease. Lee et al. [12] address the challenge of selecting representative SNPs for supporting a disease-gene
association. They demonstrate superior performance
when using a Pareto optimality based approach.
Thanks to our generous sponsors, we were able to hand
out nine travel fellowships to help cover expenses for students to attend ISMB/ECCB and the Student Council Symposium. Two of the travel fellowships were given to
excellent students from developing nations to give them
the opportunity to present their work and to meet potential collaborators.
4. Next-generation sequencing analysis and applications
Next-generation sequencing technology is enabling massive production of high-quality data with a variety of
applications. It will undoubtedly revolutionize the limits
of what is possible and affordable in experimental biology. Applications of next-generation sequencing include
de novo sequencing, re-sequencing and sequencing of
RNAs for applications formerly limited to microarrays.
Many platforms (Illumina Genome Analyzer, Applied
Conclusion
In total we received 101 abstract submissions. Each
abstract was rigorously reviewed by at least 3 reviewers.
From the 101 abstracts, we could only select 8 for oral
presentation, due to time limitations on the program.
One abstract was rejected and the authors of the remaining 92 abstracts were invited to present their poster, which
64 of them accepted. The presented research covers a
broad range of topics including microarrays, proteomics,
genetics and genomics. Fourteen outstanding abstracts
have been selected to compile this supplement.
A new initiative introduced this year was the Student
Council Career Central (SCCC) in form of a lounge in the
exhibit area and seminars. This initiative is an endeavor by
the Student Council to address the needs of recruiters and
job seekers in the field of computational biology. SCCC
provides a platform for research institutes and companies
to attract some of the best talents in computational biology from the Student Council community and attendees
at ISCB conferences all over the world. During the ISMB/
ECCB 2009 conference SCCC offered one-on-one resume
critique sessions sponsored by FASEB with Dr. Clifford S.
Mintz, who helped students to improve their CVs and
resumes. Seminars about various career options available
at the European Bioinformatics Institute and non-academic career paths were also offered as a part of SCCC this
year.
The future
The 6th Student Council Symposium will be held in Boston, MA, USA in conjunction with ISMB 2010 in July
2010. Further information about the Student Council and
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BMC Bioinformatics 2009, 10(Suppl 13):I1
the events we organize is available on our website: http://
www.iscbsc.org.
http://www.biomedcentral.com/1471-2105/10/S13/I1
7.
8.
Competing Interests
The authors declare that they have no competing interests.
Authors contribution
9.
TA, JdR and LP drafted the manuscript.
10.
Acknowledgements
We would like to thank ISCB Executive Officer BJ Morrison McKay, ISCB Administrative Support Suzi Smith and
ISMB conference organizer Steven Leard for logistic support and invaluable advice in organizing the symposium.
We are indebted to all speakers for their time and effort.
In particular we should mention Peer Bork, Michal Linial
and Trey Ideker, our keynote speakers. We would also like
to thank the ISCB board of directors for their enthusiastic
commitment to our mission. We are grateful to the referees for their dedication and effort in reviewing the submitted abstracts. We also thank the BMC Bioinformatics
Editorial Office for their help in preparing this supplement.
11.
12.
13.
14.
Tran , Van Du , Chassignet , Philippe , Steyaert , Jean-Marc : Prediction of super-secondary structure in alfa-helical and betabarrel transmembrane proteins. BMC Bioinformatics 2009:O3.
Wohlers , Inken , et al.: PAUL: Protein structural alignment
using integer linear programming and Lagrangian relaxation. BMC Bioinformatics 2009, 10(Suppl 13):P2.
Pirovano , Walter , et al.: Structure and function analysis of flexible alignment regions in proteins. BMC Bioinformatics 2009,
10(Suppl 13):P6.
Petrossian , Tanya C, Clarke , Steven G: Computational methods
to identify novel methyltransferases. BMC Bioinformatics 2009,
10(Suppl 13):P7.
Williams , Tom A, et al.: Phylogenomic inference of functional
divergence. BMC Bioinformatics 2009, 10(Suppl 13):P4.
Lee , Phil Hyoun, Jung , Jae-Yoon , Shatkay , Hagit : Functionally
Informative Tag SNP Selection using a Pareto-Optimal
Approach: Playing the Game of Life. BMC Bioinformatics 2009,
10(Suppl 13):O5.
Chikhi , Rayan , Lavenier , Dominique : Paired-end read length
lower bounds for genome re-sequencing. BMC Bioinformatics
2009, 10(Suppl 13):O2.
Bohnert , Regina , Behr , Jonas , Rätsch , Gunnar : Transcript quantification with RNA-Seq data.
BMC Bioinformatics 2009,
10(Suppl 13):P5.
The 5th ISCB Student Council Symposium was made possible through generous financial support from the Netherlands Bioinformatics Centre, Korean Bioinformation
Center, European Bioinformatics Institute, Institute for
Systems Biology, New England BioLabs, Iowa State University and BMC Bioinformatics. The organizers are also
grateful to Oxford University Press for sponsoring the best
poster and best presentation awards.
This article has been published as part of BMC Bioinformatics Volume 10 Supplement 14, 2009: Highlights from
the Fifth International Society for Computational Biology
(ISCB) Student Council Symposium. The full contents of
the supplement are available online at http://
www.biomedcentral.com/1471-2105/10?issue=S13.
References
1.
2.
3.
4.
5.
6.
Szczepińska , Teresa , Pawłowski , Krzysztof : Looking for chromosome spatial organization rules in microarray gene expression data. BMC Bioinformatics 2009, 10(Suppl 13):O6.
Koeva , Martina , Forsberg , Camilla , Stuart , Josh : Core Stemness
Mechanisms Revealed Through Homology. BMC Bioinformatics
2009, 10(Suppl 13):O4.
Schultheiss , Sebastian J, et al.: KIRMES: Kernel-based Identification of Regulatory Modules in Euchromatic Sequences. BMC
Bioinformatics 2009, 10(Suppl 13):O1.
Caldas , José , et al.: Probabilistic retrieval and visualization of
biologically relevant microarray experiments. BMC Bioinformatics 2009, 10(Suppl 13):P1.
Gehlenborg , Nils , Brazma , Alvis : Visualization of Large Microarray Experiments with Space Maps. BMC Bioinformatics 2009,
10(Suppl 13):O7.
Samusik , Nikolay , Kalaidzidis , Yannis , Zerial , Marino : A method
for validation for clustering of phenotypic gene knockdown
profiles using protein-protein interactions information. BMC
Bioinformatics 2009, 10(Suppl 13):P3.
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