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Private fears in public places? Ethical and regulatory concerns regarding human genomic databases

Organizer(s): David Gurwitz, gurwitz@post.tau.ac.il, Tel-Aviv University and Barbara Prainsack, barbara.prainsack@univie.ac.at, University of Vienna
Sponsored by: F. Hoffmann-La Roche Ltd
URL: http://www.univie.ac.at/transformation/GwB/ISMB/
Date: Sunday, July 22, 2007
Start time: 9:30 a.m. — End time: 12:30 p.m.
Room Location: Hall F2
*Schedule subject to change

The completion of the Human Genome Project along with rapid advancement of bioinformatics tools has made possible the establishment and use of large human genomic databases both in the field of medicine and in the field of forensics. Accounts of success and problems encountered by large-scale genomic databases have raised public interest in the potential, but also the dangers, of running such large population genomics databases. Very large human genetic databases (several thousands of donors) are indispensable for improving the quality of health care through knowledge gained from pharmacogenomics (PGx); if we wish to uncover the potential of PGx for improving medical care, we must address the ethical and regulatory barriers related to the formation of large human genomic databases where large sets of DNA sequence data are linked to large sets of phenotypic medical records.

Also in the realm of forensics, the emergence of large-scale DNA profile databases has changed relevant aspects of crime prevention and investigation. What is applauded by some as an efficient tool to make crime investigation more effective has been criticized by others as being conceptually incompatible with the presumption of innocence underlying justice systems in democratic countries.

This Special Session seeks to explore in what concrete contexts public fears concerning the “civil safety” of genomic databases are justified. Instead of a mere ethical evaluation of certain aspects of large-scale genomic data-banking, the aim of this session is to work towards finding practical ways to address such legitimate concerns in an interdisciplinary manner. Rather than “having ethicists tell others what they do wrong”, we attempt to create synergetic effects between the expertise and practical experiences of professionals in the fields of bioinformatics, medical research, criminology, law, and regulatory ethics in dealing with such challenges, and to explore options for facilitating interdisciplinary collaboration on in this field in a sustainable way.

Furthermore, the bioinformatics angle enables us to bring together experts from two communities which have traditionally been regarded as separate: While we acknowledge that many of the ethical and regulatory concerns regarding medical and forensic genomic databases are indeed different, our aim is to sharpen our perception for commonalities. Recent discussions of the use of medical genomic databanks for forensic purposes (such as Disaster Victim Identification after the Tsunami in 2004) and ongoing international debates on the permissibility of retaining DNA samples (in addition to profiles) in forensic contexts prove the timeliness of this endeavour.

Dr. David Gurwitz
Director, National Laboratory for the Genetics of Israeli Populations
Department of Human Molecular Genetics and Biochemistry
Sackler Faculty of Medicine
Tel-Aviv University, Tel-Aviv 69978 Israel
E-mail: gurwitz@post.tau.ac.il

Dr. Gurwitz directs the National Laboratory for the Genetics of Israeli Populations (NLGIP) at Tel-Aviv University. The NLGIP is the national human DNA and cell-lines repository of Israel. Dr Gurwitz´ research interests include improving the safety of pharmacotherapy by using genomic information. In 2005 he co-organized an ESF-sponsored workshop entitled “Personalized Medicine Europe: Health, Genes & Society” which included discussions on ethical aspects of research on human genomic data: http://www.functionalgenomics.org.uk/sections/activitites/2005/Livshits/info.htm

Dr Gurwitz recently co-authored a call for creating comprehensive pharmacogenomics databases via collaboration of the academic and private sectors: Gurwitz D, Lunshof JE, Altman RB. A call for the creation of personalized medicine databases. Nat Rev Drug Discov. 2006;5:23-26. Dr Gurwitz advises the European Commission on pharmacogenomics and is a member of the OECD expert panel on pharmacogenetics and pharmacogenomics.

Dr. Barbara Prainsack
Life Science Governance Research Platform
Department of Political Science
University of Vienna
Universitätsstraße 7
A-1010 Wien / Vienna, Austria

Dr. Prainsack is a trained political scientist whose work focuses on biotechnology regulation; health governance; ethical, social and legal aspects of genomics research and applications, and public attitudes towards new medical technologies. She directs an international collaborative project on the governance of genomic research and applications (funded by the Austrian Federal Ministry of Education, Science and Culture´s GEN-AU – “Genomeresearch in Austria” programme) and manages interdisciplinary research collaborations with a number of academic institutions in Europe and in Israel. Current research focuses on practices of DNA profiling for criminal investigation (in close collaboration with forensic psychologists and criminalists). Recent publications include:

Barbara Prainsack, and Ursula Naue (2006) “Relocating health governance: personalized medicine in times of ‘global genes’” Personalized Medicine 3/3: 349-355.

Barbara Prainsack (2006) “Negotiating Life: The Regulation of Embryonic Stem Cell Research and Human Cloning in Israel”, Social Studies of Science 36/2 (April): 173-205.

Speakers and topics: (20 min talk for each speaker, followed by topical discussions)

1. A Call for Legislators: Criminalizing Misuse of Genetic Information
Dr. David Gurwitz, Tel Aviv University, Israel:
Special Session organizer; for more information, please see above

2. The Personal Genome project: the challenge of comprehensive identifying genetic information & the public domain
Jeantine Lunshof, VU University Medical Center, Amsterdam, The Netherlands:

Ms. Lunshof research focuses on ethical issues in genomics, pharmacogenomics and personalized medicine. She is also an ELSI advisor to the Personal Genome Project.

3. Independent Health Record Banks – Integrating Clinical and Genomic Data into Patient-Centric Longitudinal and Cross-Institutional Health Records
Dr. Amnon Shabo, IBM Research Lab, Haifa, Israel:

Dr. Shabo is an expert in the field of electronic health records and clinical genomics. He is a co-chair of the HL7 Clinical Genomics standards group and a co-editor of the HL7 CDA (Clinical Document) standard. He is a member of the OECD expert panel on pharmacogenetics and pharmacogenomics.

4. Forensic DNA databases: Impacts on offenders’ tactics and public representations of police work and civil rights
Dr. Barbara Prainsack, University of Vienna, Austria

Special Session organizer; for more information, please see above

5. Base Assumptions? Aspects of DNA Forensics and U.S. Internal Security
Ms. Harriet Washington, De Paul University College of Law, Chicago, IL, USA

Ms. Washington is currently a Visiting Scholar at DePaul University College of Law in Chicago, USA. Her work focuses on ethical aspects of forensic DNA collections at the NYC Police Department (special focus on racial bias and discrimination issues).

6. Dr. Stefan Hanslik, Austrian Federal Ministry of Education, Science and Culture:
“Boon and bane of forensic DNA databases”

Dr. Hanslik has broad experience with the establishment and governance of forensic DNA databases in Austria and abroad.



Organizer: Matthias Rarey, rarey@zbh.uni-hamburg.de, Center for Bioinformatics, University of Hamburg
Date: Sunday, July 22, 2007
Start time: 2:30 p.m. — End time: 5:45 p.m.
Room Location: Hall F2
*Schedule subject to change

Synopsis: The application of computational methods in chemistry has a long tradition going back to the early 60ies when computer programs for calculating molecular properties and structure were first developed. Besides applications in theoretical chemistry, the computer has become an important tool for the application of informatics approaches in chemical research in general, resulting in the field of cheminformatics. Today, applications range from information retrieval from chemical databases using software tools for visualizing, manipulating and modelling molecular structures to text mining to the prediction of physico-chemical and biological properties of molecules.

In the post-genomic era, a shift in bioinformatics away from classical sequence-based analysis towards structural-based approaches can be noticed. Moreover, computational systems biology uses molecular interactions between proteins and between proteins and small molecules as its probably most important data source. Structural bioinformatics as well as systems biology clearly show the need for strengthening the link to cheminformatics. Today, the bio- and cheminformatics communities work more or less independently from each other. The aim of this special session is to help close the gap between these fields and make bioinformaticians aware of the wealth of methods and tools available in cheminformatics.

1. Introduction: Computational Methods in Cheminformatics
Matthias Rarey, Center for Bioinformatics, University of Hamburg

2. Tools and Methods of Proven Value in Cheminformatics and Structure-Based Design
Martin Stahl, Hoffmann -La Roche GmbH, Basel

3. QSAR: Quantitative Modelling of Molecular Properties and Activities using Chemical Descriptors
Alexander Tropsha, University of North Carolina, USA

4. Structure-based Molecular Design
Gregory Warren, OpenEye Scientific Software, Inc, USA


Genetic networks: Inferring pathways by combinatorial perturbation

Organizer: Frederick ‘Fritz’ Roth, froth@hms.harvard.edu, Department of Biological Chemistry & Molecular Pharmacology, Harvard Medical School
Sponsored by: Rosetta Inpharmatics/Merck, Pfizer, MathWorks, and Combinatorx
Date: Monday, July 23, 2007
Start time: 9:30 a.m. End time: 12:30 p.m.
Room Location: Hall F2
*Schedule subject to change

Sometimes when two (or more) genes are perturbed simultaneously, the organism behaves quite differently than might be expected given the effects of perturbations in each gene alone. This phenomenon, called genetic interaction, suggests related functions. Small-scale genetic interaction studies of have shaped our understanding of almost every known biological pathway. The use of genetic interactions to determine gene order in pathways has century-old roots that are intertwined with those of statistics and computer science. These connections have lain largely dormant, but they are reawakening in the light of modern molecular and systems biology.

The genomic era has brought the systematic study of genetic interaction. For example, 4% of all S. cerevisiae gene pairs have been systematically tested to reveal ~3000 genetic interactions. Similar genetic interaction screens have been impracticable in multicellular organisms, because targeted gene deletion and genetic crosses are more labor-intensive. However, RNAi (subject of the 2006 Nobel Prize in Medicine) has provided an essential breakthrough. Efficient ‘knockdown’ of specific genes at the transcript level is now possible. The worm C. elegans is particularly amenable to large-scale RNAi experiments, and studies of genetic interaction in C. elegans have become increasingly large scale. Large-scale RNAi experiments have become increasingly routine for cultured cells of the fruit fly Drosophila, mouse and human. A wave of genetic interaction data in these organisms is inevitable.
Ad hoc rules for determining causal gene relationships from genetic interactions have developed in classical Mendelian genetics, but these rules have only recently been formalized and automated. In the field of quantitative genetics, R.A. Fischer applied linear models to define genetic interactions and S. Wright analyzed genetic interactions using a pathway analysis technique which has had a strong influence on the modern theory of causality. Although these analytic methods have proven extremely valuable, they are relics from an age before the advent of molecular biology, reverse-genetics, and genome-scale experimentation.
Computational biologists can now use systematic genetic perturbation studies to develop models relating genetic interactions to pathway structure. Genome-wide studies can associate single-nucleotide polymorphisms (SNPs) and other polymorphisms with multigenic human disease (by definition the result of genetic interaction). A wealth of functional genomics data can now be integrated with genetic interactions to optimize pathway structure models, including protein networks, mRNA expression profiles, genetic association studies, high-throughput phenotyping and comparative genomics. Finally, algorithms for characterizing causal pathways in biological systems could prove useful for other causal inference problems (as has been demonstrated in the case of structural equation modeling).

Session Outline for Monday, July 23:

9:25 am – 9:35 am
Introduction to the Genetic Networks Session

9:35 am – 9:55 am
Fritz Roth (Dept. of Biol. Chem. & Molec. Pharm., Harvard Medical School)
Reverse-and forward-genetic networks in S. cerevisiae

Reverse-genetic networks: I will describe a quantitative genetic interaction network among DNA repair genes in S. cerevisiae , and its use in mapping gene order in pathways and predicting gene function. This work will draw on both quantitative and Mendelian definitions of genetic interaction. Forward-genetic networks: I will describe a network of genetic interactions arising from natural polymorphisms in outbred S. cerevisiae strains, drawing on the population-genetic definition of genetic interaction.

10:00 am – 10:20 am
Trey Ideker (Bioengineering, Univ. of California , San Diego)
Elucidating pathways of genotoxicity using single and double gene knockouts.

Cells respond to toxic agents through the complex interplay of a variety of different signaling and regulatory pathways. Although the complete structure of these pathways has not yet been elucidated, protein interaction mapping projects provide the raw materials for mapping them at large-scale. We describe one such mapping project, involving systematic screens for transcriptional interactions that mediate the response to DNA alkylating agents. We also describe methods for mining these networks to model the effects of single and double genetic perturbations on the system-wide genotoxic response. These methods uniformly rely on the principle of network alignment and comparisons—that is, the pathways of interest are efficiently mapped by comparing protein networks between toxic and non-toxic conditions, between genetic and physical maps, and between species.

Coffee Break

10:45 am – 11:05 am
Blaz Zupan (Computer & Information Science, Univ. of Ljubljana , Slovenia ; Molecular & Human Genetics, Baylor College of Medicine)
Inference of gene regulatory relations from mutant-based phenotypes.

In classical genetics, mutant-based morphological phenotypes provided ground to reason about gene regulatory relations. Relations can report on the effect of a single gene, or could relate two genes with respect to the process under observation. Typically, relations between two genes that could be inferred from the data included parallelism and epistasis. Traditionally, results of double-mutant experiments were costly and time consuming, so that the data was scarce and manual analysis feasible. Yet, with recent advent of high throughput experimental techniques analysis of mutant data requires dedicated computational tools. Pathway reconstruction algorithms can in this endeavor mimic the domain experts, but require formalization of the reasoning logic. In the talk we will show how this was done for GenePath, our web-based pathway reconstruction tool. We will also argue that once the reasoning logic is formalized, it also enables us to use computational tools for experiment planning, possibly closing a circle of data gathering, analysis, and experimentation, leaving open door for genome-wide automatization of knowledge discovery. Phenotypes, however, do not need to be limited to morphology, and for genome-wide studies should be complemented with surrogates that can encode the state of the entire organism. We will show how global gene expression profiles can be used in place of morphology-based phenotypes, but also emphasize that principal formalization of reasoning logic can remain the same and can be equally applied to any phenotypes experimentalists are able to gather.

11:10 am – 11:30 am
Joseph Lehar (Combinatorx, Inc.)
Synergy and connectivity in E. coli metabolism.

Efforts to construct models of biological systems require large and diverse sets of data on functional connections between their components. The responses to paired mutations in yeast have proven to be productive indicators of functional connections between genes. Chemical combinations can provide complementary information as they probe different cellular components and can be applied to disease models that are not amenable to mutagenesis. Chemical probes also offer increased flexibility, as they can be continuously dosed, temporally controlled, and readily combined. We have shown (Lehar et al. 2007, Nature MSB in press) that the type of synergy produced by combined chemicals is directly related to how their targets are functionally connected. Here we present simulated proliferation responses to paired enzymatic inhibitors in a flux-balance model of the E.coli metabolic network. The resulting synergies will be classified using novel connectivity measures to determine synergy-connectivity associations that cover the range of connectivities within the network. We will also explore the generality of these association rules when applied to other networks.

11:35 am – 11:55 am
Eytan Ruppin (Computer Science & Medicine, Tel Aviv Univ.)
Using game-theoretical tools to infer functional pathways from combinatorial perturbations.

This talk will present a high-level overview of methods for rigorously analyzing multi-perturbation experiments, aiming to provide a functional description of how a given function is carried out by the system studied. The methods described rely on the rich results obtained within the axiomatic Shapley Value framework developed in Game Theory. Their application to the analysis of a DNA repair system will be shown and open challenges will be discussed, as time will permit.

12:00 pm – 12:20 pm
Eric Schadt (Rosetta Inpharmatics/Merck Inc.)
Building predictive gene networks to identify the key drivers of complex physiological phenotypes.

The ability to monitor transcript levels in a comprehensive fashion allows for a more general characterization of transcriptional networks and their relationship to disease and other complex physiological processes. I present an analysis of the patterns of correlations among thousands of gene expression traits in multiple tissues collected from more than 1000 animals in a number of segregating mouse populations. Networks reconstructed from each of the tissues and sexes profiled are observed to be scale free and hierarchical, with highly interconnected gene modules enriched for different functional pathways and common expression quantitative trait loci easily identified, reflecting common genetic control and functional properties among genes in a given network module. Co-expression networks combined with genotypic data are used to dissect complex genetic loci driving disease traits associated with obesity, diabetes, and atherosclerosis, leading to the identification of core network modules that are supported as strongly causal for these disease associated traits. I demonstrate how to dissect the connectivity structure of these network modules using perturbation experiments focused on genes in the modules that have been validated as causal for disease by matching patterns of expression manifested by this module with patterns induced by the perturbation experiments. The connection these modules have to a number of disease-associated traits is further validated by identifying and validating novel susceptibility genes for the traits of interest in vivo. The analyses I present provide direct experimental support that complex diseases like obesity are emergent properties of molecular networks, driven by complex genetic loci that require the integration of multiple data sources in order to elucidate the effects these loci have on networks that cause disease.

12:15 pm – 12:20 pm
Wrap up


Computational epigenetics and chromatin regulation

Organizer: Michael Q. Zhang, mzhang@cshl.edu, Cold Spring Harbor Laboratory, NY, USA
URL: http://rulai.cshl.org/courses/ISMB07SpecialSession.htm
Date: Monday, July 23, 2007
Start time: 2:30 p.m. — End time: 5:40 p.m.
Room Location: Hall F2
*Schedule subject to change

Epigenetic mechanisms make gene expression patterns stable by maintaining gene regulatory information through the cell cycle. In some cases, this is thought to occur through heritable modification of chromatin structure. It has been shown to play important roles in development and differentiation, its lesion can cause many human diseases ranging from developmental abnormality to cancer. Epigenomics, large-scale study of epigenetic regulation, is becoming an emerging field, genome-wide data on DNA methylation, Histone modifications and variations, higher-order chromatin structures demand novel computational approaches and its connection to ncRNAs and intergetic transcription are creating profound impact in our current view of gene regulation networks. This special session would be timely because some of the pioneers will be able to provide expert perspective on this exciting new field of research and to give the initial account of what and how more and younger computational biologists may be getting involved and making valuable contributions.

Session Outline:

Human insulators and CTCF localization — M. Q. Zhang
Allelic expression and genomic imprinting — A. Hartemink
DNase I hypersensitive mapping and chromatin states — W.S. Noble
Histone variation and nucleosome positioning — E. Segal
CpG Island and DNA Methylation — T. Lengauer/C. Bock


Computational Approaches to the Modern RNA World

Organizer: Ivo Hofacker, ivo@tbi.univie.ac.at, University of Vienna
URL: http://www.tbi.univie.ac.at/ISMB-RNA/
Date: Tuesday, July 24, 2007
Start time: 9:30 a.m. — End time: 2:55 p.m.
Room Location: Hall F2
*Schedule subject to change

Molecular biology has long regarded RNA as a molecule of minor importance. The few known non-coding RNAs, such as tRNAs and ribosomal RNAs and ribozymes were generally regarded as exotic remnants of an RNA world that preceded the evolution of the biochemically more versatile proteins. This view has been challenged in recent years due to several key developments.

An unexpected variety of non-coding RNAs (ncRNAs) has been identified in recent years using a variety of experimental and computational approaches, especially in the higher organisms such as mammals.

These ncRNAs perform a variety of regulatory functions. In particular microRNAs (the best studied class of ncRNAs) have been shown to play a central role in gene regulation.
Recent studies of the mammalian transcriptome show that most of the transcriptional output of a human cell is non-coding, indicating that the known ncRNAs represent only the tip of the iceberg.

As a result of these developments, the demand for RNA related bioinformatics tools has risen sharply over the past years. RNA related bioinformatical tasks, such as secondary structure prediction, RNA alignment and RNA homology searches, or the prediction of microRNA targets, are nowadays common in many molecular biology labs. Yet even for such basic tasks, available tools are not nearly as elaborate and efficient as their protein counterparts, and in many cases there is no consensus which approach is most suitable.

Our special session at the ISMB will therefore present the state of the art in RNA bioinformatics and highlight many of the still open problems that present opportunities for future research. In particular we will focus on a list of key topics, each represented roughly by one talk of the session:

  • RNA alignment and homology search:
    To date high quality structural alignments of RNAs are usually the result of much manual work. A fundamental problem in RNA bioinformatics is therefore how to compute high quality structural alignments for a set of RNA sequences. A related problem is how to use this information in homology searches in order to find new homologs of known RNA families.
  • RNA gene-finding, classification and annotation:
    Annotation of ncRNAs in most genomes is poor to non-existent. There is thus a need for RNA gene-finders that can locate potential ncRNA genes and other functional RNA structures in genomic sequences. Of particular interest are methods that can detect novel ncRNAs without significant homology to known RNA families. Beyond the mere prediction of the genomic location of ncRNAs, there is a need for tools that can annotate ncRNAs, be they obtained from prediction methods or experimental screens, by assigning them to known classes of ncRNAs, such as snoRNAs or miRNAs.
  • Folding Dynamics of RNA:
    Most common approaches to RNA structure prediction try to predict a single thermodynamically optimal secondary structure. In many cases, however, RNA function depends on the dynamics of structural changes.
  • Modeling tertiary

Most of RNA bioinformatics treats RNA on the level of secondary structure only. Prediction of the full tertiary structure, however, remains the ultimate, and often elusive, goal. The availability of X-ray structures of the ribosome, has opened new opportunities to study frequent tertiary structure motifs and their underlying sequence patterns. Tertiary structure motifs can thus be identified on the basis of sequence alignments and the known substitution patterns of common tertiary structure motifs.

1. Welcome and introduction
Ivo Hofacker, University of Vienna

2. Advances in RNA secondary structure prediction
Robert Giegerich, University of Bielefeld, Germany

3. RNA alignment and homology search
Rolf Backofen, University of Freiburg, Germany

4. Detection and Annotation of non-coding RNAs
Peter Stadler, University of Leipzig, Germany

5. RNA folding kinetics and pathways
Hervé Isambert, Institut Curie, Paris

6. Modelling RNA tertiary structure
Eric Westhof, CNRS, Strasbourg


Dry work in a wet world: Improving methodology and access of computational methods in Systems Biology

Organizer: Ewan Birney
URL: http://www.enfin.org/page.php?page=ISMBECCB2007

Date: Wednesday, July 25, 2007
Start time: 9:45 a.m. — End time: 12:45 p.m.
Room Location: Hall F2
*Schedule subject to change

Although bioinformatics tools are often developed in conjunction with high-throughput large-scale experimental projects in biology, there is still the need for both software development and the necessary social changes (by both computational and experimental researchers) to make the computer as useful as the PCR machine in the standard wet laboratory. This is particularly true in the era of mid- to high-throughput experimental techniques, often requiring systems-biology modelling techniques to understanding how the interacting components work. With the aim of bridging the gap existing between standard wet laboratories and bioinformatics, the European Network of Excellence ENFIN develops integrative technologies to bring the latest computational techniques to bear directly on questions dedicated to Systems Biology in the wet laboratory.

At this Special Session, we will make these computational approaches accessible to a broader range of experimentalists and bioinformaticians without a modelling background, therefore progressively growing the area of computational systems biology beyond its traditionally theoretical level on one hand, and on the other hand introducing more “wet” experimentalists to power of these “dry” computational tools.

Selected biologists will expose their areas of research and their use and needs in terms of computational analysis tools. Besides, some areas of the activity of the ENFIN Network will also be illustrated by examples driven by both specific method development and an extensive integration across computational tools. A discussion will be constructed upon the different experiences that will be presented.

Reference: Kahlem P. and Birney E. (2006) Dry work in a wet world: computation in systems biology. Molecular Systems Biology 2 doi:10.1038/msb4100080.

Session Outline:

Dr. Ewan Birney / Dr. Pascal Kahlem (EMBL-EBI, UK)
European Molecular Biology Laboratory-European Bioinformatics Institute, Hinxton, UK

Systems biology and complex systems theory.
Prof. Erik Mosekilde, Department of Physics, The Technical University of Denmark)

Gene Network Modelling.
Dr. Martin Kuiper, University of Gent, Belgium

Studies of the transforming growth factor-beta pathway.
Dr. Lukasz Huminiecki, Ludwig Institute for Cancer Research, Uppsala University, Sweden

Boolean modelling techniques.
Dr. Ioannis Xenarios, Serono Pharmaceutical Research Institute, Geneva, Switzerland)

Maintenance of self-renewal and pluripotency in embryonic stem cells.
Dr. James Adjaye, Max-Planck Institute for Molecular Genetics, Berlin, Germany

Modelling of diabetes-related pathways.
Prof. John Hancock, MRC Mammalian Genetics Unit, Harwell, UK)

Metabolic modelling and genetic experiments.
Dr. Vincent Schachter, Genoscope, Evry, France

Mitotic spindle protein prediction.
Dr. Roman Koerner, Max-Planck Institute of Biochemistry, Martinsried, Germany

Optimised use of literature mining in biology.
Prof. Alfonso Valencia, Spanish National Cancer Research Centre, Madrid, Spain

Domain interaction networks.
Prof. Gianni Cesareni, University of Rome Tor Vergata, Rome, Italy

Bioinformatics access for databases
Dr. Antony Quinn, European Molecular Biology Laboratory-European Bioinformatics Institute, Hinxton, UK

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