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ECCB 2010 Workshop:
Annotation, interpretation and management of Mutations (AIMM2010) - Call for Papers
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http://www.unbsj.ca/sase/csas/data/aimm2010/ [3]
This year's will workshop showcase the state of the art in extraction and
reuse of genotype-phenotype information. Annotation of mutations with their
impact on phenotypic expression is crucial to understanding genetic
mechanisms involved in phenotypic processes and ultimately in complex
diseases. Managing this knowledge is key to generating novel hypotheses.
Despite the existence of literature and databases describing impacts
of mutations, association studies fail to deliver linkage to
phenotypes which is the most important contemporary research interest.
Extraction of such information from scientific literature is a
promising research field and existing solutions are ready to be
deployed as services and as semantic web services.
Keynote Speakers:
Michael Schroeder - Professor BIOTEC Technical University Dresden, DE.
Joost Schymkowitz - Professor VIB Switch Laboratory, Vrije Universiteit
Brussel.
Submissions:
We invite short papers (3000 words / 8 pages) and demonstrations on the
following topics:
* Issues related to storage and representation of mutation
information, including traditional databases, RDF triple stores,
semantic knowledgebases and mutation ontologies.
* NLP tools and systems for recognition and grounding of entities
related to mutations and their annotations: including mutation impacts
and mutation grounding. Also evaluations of these NLP tools and systems.
* Systems for mutation impact prediction, reusing existing mutation
databases and text extracted data.
* Bioinformatics data integration, discoverable semantic web services
and workflows, and semantic assistants for mutation annotation
integration.
Submissions can be made through the EasyChair submission page:
https://www.easychair.org/account/signin.cgi?conf=aimm2010 [4]
Submission guidelines can be found on our website
http://www.unbsj.ca/sase/csas/data/aimm2010/ [3]
Organizers
Christopher J.O. Baker
Ph.D., Associate Professor / Innovatia Research Chair, Department of
Computer Science and Applied Statistics, University of New Brunswick,
Saint John, Canada.
Email: bakerc at unb.ca
Dietrich Rebholz-Schuhmann
MD, Ph.D., Research Group Leader, European Bioinformatics Institute,
Welcome Trust Genome Campus, Hinxton, Cambridge, United Kingdom.
Email: Rebholz at ebi.ac.uk
René Witte
Dr.-Ing., Assistant Professor, Group Leader, Semantic Software Lab,
Concordia University, Department of Computer Science and Software
Engineering, Montreal, Canada.
Email: rwitte at cse.concordia.ca
Important Deadlines:
Abstract submission: July 20
Full paper submission: July 26
Acceptance notification: August 12
Final manuscript submission: September 2
AIMM2010 workshop: September 26
Venue: ECCB2010 @ Ghent, Belgium. http://www.eccb2010.org/ [5]
Previous Events:
http://www.ebi.ac.uk/Rebholz-srv/aimm.html [6]
http://www.biomedcentral.com/content/pdf/1471-2105-10-S8-info.pdf [7]
2010 Session Topics:
http://www.unbsj.ca/sase/csas/data/aimm2010/ [3]
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Mutation Databases and Metadata: Design, Content, Accuracy
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Over 400 mutation databases have been produced in the past (determined
via ‘google’ search). Many are no longer maintained and cover very
specific data sets. In total, these repositories have been designed to
support a wide range of features including listings of SNPs, point
mutations, insertions, deletions, and observed phenotypes. Furthermore
they incorporate a wide range of modified protein features and metrics
in the accompanying annotations to the mutation descriptions. In the
main these databases are manually curated however mutation annotations
are frequently inaccurate e.g. in the PDB, inaccurate to the degree of
40 % of all PDB records. In addition to assessing content and coverage
issues this session will explore issues related to storage and
representation of mutations information showcasing a spectrum of
mutation repositories types from traditional databases to RDF triple
stores semantic knowledgebases and mutation ontologies.
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Extraction of mutations and annotations from literature
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AI techniques such as text mining and natural language processing have
been used in BioNLP to enable the extraction and grounding of named
entities (mutations, protein, organisms) and impact annotations
(protein properties, directions and scale of impact) from the mutation
literature, with high levels of precision and recall, albeit prototype
in scale. To facilitate their adoption it is necessary to measure the
accuracy, recreation and update of existing mutation databases as we
as their incorporation into semi manual annotation pipelines - the
next milestone. In addition there is continuing discussion over the
appropriate metrics for individual tasks within these systems which
requires community involvement. This emergent technology now needs
standardization. For the workshop we will solicit presentations,
posters and demos of NLP tools, evaluations of mutation pipelines,
mutation ontology population, and invite suggestions for a database
reconstruction challenge to illustrate state of the art performance.
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Impacts of Mutations: Prediction and Bootstrapping
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The ability to predict the impact of a mutation or the consequence of
a sequence variant is central to the diagnosis of genetic diseases.
Non-synonymous mutations may impact translational regulation, mRNA
stability, mRNA splicing and rates of translation. Proteins affected
by nsSNPs may have altered; catalytic sites, stability, ability to
aggregate, and or post-translational modifications. Moving from SNP to
sequence to structure and function has been addressed with varying
degrees of accuracy with sequence and structure based (molecular
mechanism, empirical energy function or machine learning) methods.
Applying such techniques at a genome scale requires that robust
approaches are identified, benchmarked with standard metrics in order
to assign valid significance to ns mutations. Reuse of existing
mutation databases and text extracted data for training prediction
algorithms and checking quality of predictions is pivotal.
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Mutation Data Integration and Reuse
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For scientists to make rapid advances in our understanding of living
systems our infrastructures and techniques for knowledge translation
are insufficient. Hypothesis generation based on the reuse of
extracted information and in-silico predictions remains a distant
capability for most scientists. Furthermore building the derived
insights of mutational studies into robust models of a specific
biological domain also seems far off. A multi level approach to
biology must be accompanied by integrated infrastructures build from a
diverse toolset. Integration with information from different systems
will require the adoption of rich metadata for semantic knowledge
integration, such as provided by existing phenotype ontologies and
ontologies specific to impacts, sequence rearrangements and in vitro
methodologies to construct mutants. For integration of bioinformatics
data, discoverable semantic web services and workflows for mutation
integration are emerging paradigms and this session will host examples
of reusable mutation extraction and data integration workflows.
Semantic assistant clients facilitating real time mutation annotation
integration to desktop applications e.g. when browsing pubmed
abstracts will be also be showcased.
