[Ieee_vis] CFP: BIOKDD 2020 International Workshop on Data Mining in Bioinformatics

[Hsiang-Yun WU]

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  Call for Paper: 19th International Workshop on Data Mining in Bioinformatics
                            AUGUST 24, 2020
                           San Diego, CA, USA
                   http://home.biokdd.org/biokdd20/
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# Introduction
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Bioinformatics is the science of managing, mining, and interpreting
information from biological data, and data mining plays an essential
role in addressing the fundamental problems in Biomedical Informatics.
The annual BIOKDD workshop is an established forum for researchers and
practitioners of Biomedical Informatics and Data Mining to explore
cutting-edge techniques and to exchange ideas and experiences. BIOKDD
has been successfully held in conjunction with SIGKDD for 18 years.

The goal of the 19th International Workshop on Data Mining in
Bioinformatics (BIOKDD'20) is to encourage KDD researchers to tackle
the numerous challenges of mining and learning in Bioinformatics,
Biomedical and Health Informatics. We are soliciting papers and
abstracts that presenting research that utilizes Big Data technology,
data visualization, and effective data mining and machine learning
approaches to analyze large amounts of heterogeneous complex
biological and medical data, together with those that describe
innovative applications in Bioinformatics and Health Informatics. The
key goal is to accelerate the convergence between Data Mining and
Biomedical Informatics communities to expedite discoveries in basic
biology, medicine and healthcare. Research that battles the COVID-19
pandemic is especially encouraged.

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# Topics
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We invite the submission of original research contributions in (but
not limited to) the areas listed below. Quality papers accepted will
be invited to publish in IEEE/ACM Transactions on Computational
Biology and Bioinformatics (TCBB).

Research that battles COVID-19
Bioimage analysis, single-cell analysis
Biological network visualization
Information visualization and visual analytics for biomedical data
Development of deep learning methods for biological and clinical data
Novel methods and frameworks for mining and integrating big biological data
Discovering biological networks and pathways underlying biological
processes and diseases
Analysis, discovery of biomarkers and mutations, and disease risk assessment
Comparative genomics
Metagenome analysis using sequencing data
RNA-seq and microarray-based gene expression analysis
Genome-wide analysis of non-coding RNAs
Genome-wide regulatory motif discovery
Structural bioinformatics
Automated annotation of genes and proteins
Discovery of structural variations from next-generation sequencing (NGS) data
Correlating NGS with proteomics data analysis
Discovery of genotype-phenotype associations
Building predictive models for complex phenotypes
Functional annotation of genes and proteins
Cheminformatics
Special biological data management techniques
Privacy and security issues in mining genomic databases
Predictive modeling for personalized treatment
Semantic web and ontology-driven data integration methods
Text mining for biomedical literature and clinical notes
Information retrieval for healthcare and Biomedical applications
Biomedical signal analysis and processing
Intelligent medical data management
Collaboration technologies for biomedicine
Social networks for biomedicine

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# Important Dates
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SUBMISSION DUE: MAY 20, 2020
NOTIFICATION DATE: JUNE 15, 2020
WORKSHOP DATE: AUGUST 24, 2020

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# Submission Guidelines
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Papers should be at most 10 pages in length, single-spaced, in font
size 10 or larger with one-inch margins on all sides. Using the ACM
Proceedings Format is highly recommended. A paper should be submitted
in PDF format through EasyChair at the following link:
https://easychair.org/conferences/?conf=biokdd20200. The submissions
will be judged for quality and relevance through single-blind
reviewing.

Best regards,
Hsiang-Yun (on behalf of the organization team)

-- 
Hsiang-Yun WU

e-mail: wu (at) cg.tuwien.ac.at
phone: +43-1-58801-18602 ext. 186206
fax: +43-1-58801-18698
URL: https://www.cg.tuwien.ac.at/staff/HsiangYunWu.html
URL2: http://yun-vis.net/