Special Session
Special Session on
Advances in Machine Learning Applied to Gene Expression Data -
MLGED
2019
22 - 24 February, 2019 - Prague, Czech Republic
Within the 12th International Joint Conference on Biomedical Engineering Systems and Technologies - BIOSTEC 2019
* CANCELLED *
CHAIR
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Paulo E Ambrosio
Universidade Estadual de Santa Cruz
Brazil
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Brief Bio
Paulo Eduardo Ambrosio is a Doctor in Medical Sciences. His research interests are Computational Biology and Pattern Recognition.
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SCOPE
Gene expression is a measurement of expression levels of various genes at once, with the intent to discover his function. One way to analyze this expression data is through clustering techniques, which aim to group genes of similar expression tendencies together. The current big problem in this research area is the huge amount of data that needs to be processed simultaneously, which require the development of new techniques and algorithms, principally on machine learning advances. This special session aims to show recent advances in the area, presenting new techniques of processing, automated analysis and pattern classification. It also intends to be a forum for sharing experiences between specialists, researchers and beginners in the area, presenting and discussing relevant ideas.
IMPORTANT DATES
Paper Submission:
December 20, 2018 (expired)
Authors Notification:
January 7, 2019 (expired)
Camera Ready and Registration:
January 15, 2019 (expired)
SPECIAL SESSION PROGRAM COMMITTEE
Available soon.
PAPER SUBMISSION
Prospective authors are invited to submit papers in any of the topics listed above.
Instructions for preparing the manuscript (in Word and Latex formats) are available at: Paper Templates
Please also check the Guidelines.
Papers must be submitted electronically via the web-based submission system using the appropriated button on this page.
PUBLICATIONS
After thorough reviewing by the special session program committee, all accepted papers will be published in a special section of the conference proceedings book - under an ISBN reference and on digital support - and submitted for indexation by DBLP, Web of Science / Conference Proceedings Citation Index, EI, Microsoft Academic, SCOPUS, Semantic Scholar and Google Scholar.
SCITEPRESS is a member of CrossRef (http://www.crossref.org/) and every paper is given a DOI (Digital Object Identifier).
All papers presented at the conference venue will be available at the SCITEPRESS Digital Library