The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Research in systems biology integrates experimental, theoretical, and modeling techniques to study and understand biological processes such as gene regulation. The genomic sequences for human and other model organisms such as yeast and bacteria are already established. The next major step is to discover functional roles of genes whose functions are not yet discovered and to investigate how genes interact...
Visualization techniques provide attractive tools to explore and analyze huge and high dimensional gene expression sets. Several visualization techniques have been developed that enabled users to visually analyze high dimensional data. However, these techniques should be integrated with efficient exploration techniques, as efficient clustering, outlier analysis, ensembles and cluster validation to...
Mining techniques are needed to extract important information from huge high dimensional gene expression sets. Targeting unique expression behavior as over/under-expression is specific to gene expression data and is needed to explore another direction in the relation of genes to tumor conditions. This research proposes criteria for filtering over-expression genes, identifying over-expression related...
MicroRNAs (miRNAs) are small Ribonucleic Acid (RNA) molecules ~18-22 nucleotides (nt) in length that regulates gene expression in animals, plants and viruses. Due to its small size and occurrence in different development stages of organisms, the experimental identification of miRNAs becomes difficult, and computational approaches are being developed in order to precede and guide biological experiments...
Feature selection is a very important preprocessing step in data classification. By applying it we are able to reduce the dimensionality of the problem by removing redundant or irrelevant data. High dimensional data sets are becoming usual nowadays specially in bio-informatics, biology, signal processing or text classification, increasing the need for efficient feature selection methods. In this paper...
Advances in DNA microarray technology has motivated the research community to introduce sophisticated techniques for analyzing the resulted large-scale datasets. Biclustering techniques have been widely adapted for analyzing microarray gene expression data due to its ability to extract local patterns with a subset of genes that are similarly expressed over a subset of samples. Mostly, biclustering...
The biclustering problem consists in simultaneously clustering rows and columns of a data matrix. The aim of this paper is to empirically assess the performance of cooperative coevolution as an alternative approach for coping with the task of discovering good and sizeable biclusters. For this purpose, two cooperative coevolutionary algorithms, one configured with genetic algorithms (GAs) and another...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.