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DMLS 2009 : The 4th Workshop on Data Mining in Life Sciences


When Jul 22, 2009 - Jul 22, 2009
Where Leipzig, Germany
Submission Deadline Apr 30, 2009
Notification Due May 31, 2009
Final Version Due Jun 10, 2009
Categories    data mining

Call For Papers

Call for papers
The 4th Workshop on Data Mining in Life Sciences DMLS'2009 at the
9th Industrial Conference on Data Mining ICDM'2009 July 22,
2009, Leipzig/Germany

Data mining in biology and medicine is a core component of
biomedical informatics, and one of the first intensive
applications of computer science to this field, whether at the
clinic, the laboratory, or the research center. Following a
long tradition of data exploration stemming from biostatistical
data analysis, todays's biomedical data mining appears more
multifaceted with advances in knowledge discovery in databases
as well as machine learning approaches.

The goals of DMLS'09 workshop are to:

- provide a forum for identifying important contributions and
opportunities for research on data mining as it applies to
biological and/or medical data,
- promote the systematic study of how to apply data mining to
biology and medicine, and
- show case applications of data mining in biology and

Some of the technical issues addressed, and potential outcomes
of the workshop, are to identify preferred types of mining
methods, tools, and processes, preferred domains of
application, how to connect a data mining model with a problem
to solve, challenges specific to applying data mining to
biology and medicine, and guidelines to better develop data
mining projects in this domain. We welcome all those interested
in the problems and promise of data mining in biology or
medicine as well as in bioinformatics, Human Genome Project,
environmental sciences and agriculture.

Topics of interest include (but are not limited to):
With regard to different types of data:
- Discovery of high-level structures, including e.g. association networks
- Text mining from biomedical literature
- Medical images mining
- Biomedical signals mining
- Temporal and sequential data mining
- Mining heterogeneous data
- Mining data from molecular biology, genomics, proteomics, pylogenetic classification

With regard to different methodologies and case studies:
- Data mining project development methodology for biomedicine
- Integration of data mining in the clinic
- Ontology-driver data mining in life sciences
- Methodology for mining complex data, e.g. a combination of
laboratory test results, images, signals, genomic and proteomic samples
- Data mining for personal disease management
- Utility considerations in DMLS, including e.g. cost-sensitive
learning We particularly welcome case studies and applications
and discussions of the lessons learned from such case studies

Workshop Format
In this workshop we intend to bring scientists together and
actively identify common research threads, define open
problems, and develop collaborative contacts. We aimed at
providing an informal atmosphere where participants are
encouraged to ask clarifying questions throughout the talks and
to participate in longer discussions after each presentation.
Since we anticipate varied backgrounds of the participants, we
will encourage speakers to present their work from a
big-picture perspective and to clearly identify key issues in
their research before they dive into technical details.

A wrap-up round table discussion will summarize the lessons
learnt, issues identified, and future directions.

Important Dates
Submission Deadline: April 30th, 2009
Notification Date: May 31st, 2009
Camera-Ready Deadline: June 10th, 2009
Workshop date: July 22nd, 2009

Submission Requirements
Papers will be published in the workshop proceedings by IBaI
Publishing. PostScript or PDF paper submissions should be
formatted according to Springer LNCS format, with a maximum of
ten pages. Author's instructions along with LaTeX and Word
macro files are available on the web at Please e-mail
your submission to the DMLS'09 Worshop Chairs Mykola
Pechenizkiy and Isabelle Bichindaritz with "DMLS09 submission" in the
subject field.

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