An Evolutionary Approach for Sample-Based Clustering on Microarray Data.
ABSTRACT Sample-based clustering is one of the most common methods for discovering disease subtypes as well as unknown taxonomies.
By revealing hidden structures in microarray data, cluster analysis can potentially lead to more tailored therapies for patients
as well as better diagnostic procedures. In this work, we present a novel method for automatically discovering clusters of
samples which are coherent from a genetic point of view. Each possible cluster is characterized by a fuzzy pattern which maintains
a fuzzy discretization of relevant gene expression values. Noise genes are identified and removed from the fuzzy pattern based
on their probability of appearance. Possible clusters are randomly constructed and iteratively refined by following a probabilistic
search and an optimization schema. Experimental results over publicly available microarray data show the effectiveness of
the proposed method.
Full-textDOI: · Available from: Fernando Díaz, Jun 30, 2015
Conference Paper: Toward Virtual Machine Packing Optimization Based on Genetic Algorithm.[Show abstract] [Hide abstract]
ABSTRACT: To enable efficient resource provisioning in HaaS (Hardware as a Service) cloud systems, virtual machine packing, which migrate virtual machines to minimize running real node, is essential. The virtual machine packing problem is a multi-objective optimization problem with several parameters and weights on parameters change dynamically subject to cloud provider preference. We propose to employ Genetic Algorithm (GA) method, that is one of the meta-heuristics. We implemented a prototype Virtual Machine packing optimization mechanism on Grivon, which is a virtual cluster management system we have been developing. The preliminary evaluation implied the GA method is promising for the problem.Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living, 10th International Work-Conference on Artificial Neural Networks, IWANN 2009 Workshops, Salamanca, Spain, June 10-12, 2009. Proceedings, Part II; 01/2009