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MachineLearningMicroarrayAnalysis-LOPAL 2018 : Special Session on Machine Learning for Microarray Analysis at LOPAL’2018


When May 2, 2018 - May 5, 2018
Where Rabat, Morocco
Submission Deadline Jan 1, 2018
Notification Due Feb 15, 2018
Final Version Due Apr 1, 2018
Categories    machine learning   pattern recognition   bioinformatics   biomedical

Call For Papers

Call for Papers - Special Session on "Machine Learning for Microarray Analysis" at LOPAL’2018

International Conference on Learning and Optimization Algorithms: Theory and Applications (LOPAL 2018)

2-5 May 2018, Rabat, Morocco -

Microarrays have emerged as a high-throughput technology for large-scale analysis of the expression levels of genes simultaneously within a few different tissue or cell samples. A plethora of machine learning methods have been adopted for the analysis of microarrays in a much more rapid and cost-effective fashion. By using machine learning in microarray analysis, it is possible to classify the category of a tissue sample based on its gene-expression profile, to reveal mutations of single genes, to characterize distinct classes or subclasses of tumours, to predict the reaction to a specific therapeutic drug and the risk of relapse, etc.
While the power of this technology has been recognized, many open questions remain about appropriate analysis of microarray data. For instance, a challenging problem arises from the huge amount of genes and the scarce quantity of samples, which is typically known as the “Large G, small n” or “curse of dimensionality” dilemma. Some other characteristics of microarrays that make this analysis especially complicated are the imbalance in class distribution, the overlapping between classes, and the presence of irrelevant features, to mention just a few.
The aim of this special session is to bring together researchers from different fields of expertise, leading to better respond to the challenges of microarray analysis using advanced machine learning techniques. In particular, we seek original contributions or works in progress addressing a wide range of topics that show the potential and the limitations of new ideas or refinements of different machine learning algorithms. Both theoretical and practical results are welcome to our special session.

Prospective authors must submit their paper through the LOPAL portal following the instructions provided in Each paper will undergo a peer reviewing process for its acceptance. Authors should send as soon as possible an e-mail with the tentative title of their contribution to the special session organisers.

Submission of papers: 1 January 2018
Notification of acceptance: 15 February 2018
LOPAL conference: 2-5 May 2018

Prof. J. Salvador Sánchez – Universitat Jaume I (Castelló de la Plana, Spain)
Dr. Vicente García – Universidad Autónoma de Ciudad Juárez (Chihuahua, Mexico)

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