Call for Papers

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21 Οκτ 2013 (πριν από 3 χρόνια και 1 μήνα)

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Call for Papers

ICDM
-
201
3

Workshop
on
Biological Data Mining and its Applications in Healthcare

December
8
, 201
3
,
Dallas, Texas USA

Workshop Co
-
Chairs:

Xiao
-
Li Li
,
See
-
Kiong Ng
,

Jason T.L. Wang

http://www1.i2r.a
-
star.edu.sg/~xlli/BioDM2013/BioDM.html

1. Introduction

The biologists are stepping up their efforts to understand the biological processes that underlie
disease pathways. This has resulted in a flood of biological and clinical data from genomic
sequences, DNA microarrays, and protein interactio
ns, to biomedical images, disease pathways,
and electronic health records.
We are in a situation where our ability to generate biomedical data has
greatly surpassed our ability to mine and analyze the data
.

We can expect data mining to play an increasingl
y crucial role in furthering biological research,
since data mining is designed to handle challenging data analysis problems. In fact, it is our hope
that
data mining will be the next technical innovation employed by biologists to enable them to make
insi
ghtful observations and groundbreaking discoveries from their wide array of heterogeneous data from
molecular biology to pharmaceutical and clinical domains
.

There are still many fundamental data analysis challenges to be overcome in order to discover
new

knowledge from the biomedical data to translate into clinical applications. These include
practical issues such as handling noisy and incomplete data (e.g. protein interactions have high false
positive and false negative rates), processing compute
-
intensi
ve tasks (e.g. large scale graph
mining), and integrating heterogeneous data sources (e.g. linking genomic data, proteomics data
with clinical databases).

This is an unprecedented opportunity for data mining researchers from the computer science
domain to

contribute to the meaningful scientific pursuit together with the biologists and clinical
scientists.
This workshop’s mission is to disseminate the research results and best practices of data
mining approaches to the cross
-
disciplinary researchers and pra
ctitioners from both the data
mining disciplines and the life sciences domains.
We encourage submission of papers describing the
design and use of data mining techniques to address the various challenging issues in biological
data analysis. We particularly

welcome paper submissions that report the development of data
mining techniques in healthcare
-
related applications that integrate the use of biological data in a
clinical context for translational research.

2. The topics of interest


The topics of the
workshop include but are not limited to:



Biological
and medical
data collection
,
cleansing
, and integration



Big biomedical data management, analysis, and
prediction



Biological
and medical data

visualization



Bioimage analysis



Data pre
-
processing to handle noisy, missing
biological and medical
data



Knowledge representation and annotation of biological and medical data



Machine learning algorithms for biological and healthcare applications



Disease bioinformatics



Computational met
hods for d
rug discovery



Biological markers detection



Pharmacogenomics data mining and personalized medicine



Big data mining with high
-
throughput and next
-
generation sequencing technologies
(DNA
-
seq, RNA
-
seq, ChIP
-
seq, etc.)



Analysis of complex disorders



Integration of biological and clinical data

for translational research



Bioinformatics databases

and resources




Text

mining algorithms
for biological and healthcare applications



Biological network

analysis

(protein interaction

network
, metabolic

network
,
tr
anscription factor

network
, signalling

network
, etc.)



Pattern analysis in computational genetics, genomics and proteomics



Semantic web and knowledge acquisition in biology and healthcare



Electronic health records and biomedical repositories

3. Important D
ates

Aug
3
, 201
3
:

Due date for paper submission

Oct

1
, 201
3
:


Notification of paper acceptance

to authors

Dec

8
, 201
3
:



Workshop
date


4. Submissions

Paper submissions are limited to a maximum of 8 pages in the
IEEE 2
-
column format

(
Please refer
to

http://icdm2013.rutgers.edu/dates
). All papers will be reviewed by the Program Committee
based on tech
nical quality, relevance to data mining, originality, significance, and clarity. A double
blind reviewing process will be adopted. Authors should therefore avoid using identifying
information in the text of the paper. All papers should be submitted through

the ICDM Workshop
Submission Site.

All accepted workshop papers will be published in a separate ICDM workshop proceedings
published by the IEEE Computer Society Press. In addition, authors with accepted papers to the
workshop will have the opportunity
to be invited to publish their extended versions in the
following two venues: a) as book chapters in

an edited book which will be published by

World
Scientific

and b) as journal papers in
International Journal of Knowledge Discovery in
Bioinformatics

(IJKDB).


5. PC members

Zhang Aidong, State University of New York at Buffalo (UB), USA

Tatsuya Akutsu, Kyoto University, Japan

Zeyar Aung, Masdar Institute of Science and Technology, United Arab Emirates

Vladimir Bajic, King Abdullah University of Scienc
e and Technology, Saudi Arabia

Christopher Baker, University of New Brunswick, Canada

Jake Chen, Indiana University School of Informatics, Indianapolis, USA

Jin Chen, Michigan State University, USA

Phoebe Chen, La Trobe University, Australia

Honnian Chua,
Harvard University, USA

Juan Cui, University of Georgia, USA

Yang Dai, University of Illinois at Chicago, USA

Aryya Gangopadhyay, University of Maryland, Baltimore County, USA

Xiaoxu Han, Eastern Michigan University, USA

David Hansen, Australian e
-
Healt
h Research Centre, Australia

Wen
-
Lian Hsu, Academia Sinica, Taiwan

Jun (Luke) Huan, University of Kansas, USA

Jimmy Huang, York University, Canada

Raphael Isokpehi, Jackson State University, USA

Asif Javed, IBM Thomas J. Watson Research Center, USA

Igor
Jurisica, University of Toronto, Canada

Maricel Kann, University of Maryland, Baltimore County, USA

Daisuke Kihara, Purdue University, USA

Shonali Krishnaswamy, Monash University, Australia

Chee Keong Kwoh, Nanyang Technological University, Singapore

Dawei

Li, Yale University, USA

Haiquan Li, University of Chicago, USA

Ming Li, University of Waterloo, Canada

Yongjin Li, St Jude Children's Research Hospital, USA

Hiroshi Mamitsuka, Kyoto University, Japan

Sean Mooney, Indiana University, USA

Laxmi Parida, IBM

T. J. Watson Research Center, USA

George Perry, University of Texas at San Antonio, USA

Raul Rabadan, Columbia University, USA

Mark A. Ragan, The University of Queensland, Australia

Jianhua Ruan, University of Texas at San Antonio, USA

Saeed Salem, North
Dakota State University

Indra Neil Sarkar, University of Vermont, USA

Ambuj K Singh, University of California at Santa Barbara, USA

Narayanaswamy Srinivasan, Indian Institute of Science, India

Zeeshan Syed, University of Michigan, USA

Vincent S. Tseng, Nat
ional Cheng Kung University, Taiwan

Alfonso Valencia, Spanish National Cancer Research Centre, Spain

Hong Yan, City University of Hong Kong, China

Sungroh Yoon, Seoul National University, Korea

Philip S. Yu, University of Illinois at Chicago, USA

Xiaoling (Shirley) Zhang, Boston University, Boston, MA

Erliang Zeng, University of Notre Dame, USA

Marketa Zvelebil, Breakthrough Breast Cancer Research
-

ICR, UK