Browsing by Author "Corapcioglu, M. Erdem"

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    A Medical Decision Support System Proposal Supported by Genomic Analysis
    (2017) Corapcioglu, M. Erdem; Ogul, Hasan
    It is known that, existing knowledge and experience have a key role in decision making process. This statement is more than true for a physician who is responsible for identifying diseases and executing the related medical treatment for patients. It is known that, regardless of the decision maker may not be able to execute correct decision if there is one or more condition that will affect the decision-making process. Whatever the circumstances, erroneous decision-making can lead to irreparable results in the medical field. Recent advancements in computational analysis showed that gene expressions can be used to identify both similar cases and assign experiments to related classes. Lately, it has found that, MicroRNA which consist of 21 to 23 nucleotides, has an important role in the regulation of gene expressions. In addition to this, there are several experiments which have shown that MicroRNA gene expression can be related with diseases and gene regulations. Personalized medical researches and practices have become very important in the recent period. Also, it is known that genetic analysis has a key role in personalized medical research. In this study, we propose a system which is using gene expression analysis to support medical decision support process.
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    miSEA: MicroRNA Set Enrichment Analysis
    (2015) Corapcioglu, M. Erdem; Ogul, Hasan; 26093049
    We introduce a novel web-based tool, miSEA, for evaluating the enrichment of relevant microRNA sets from microarray and miRNA-Seq experiments on paired samples, e.g. control vs. treatment. In addition to a group of previously annotated microRNA sets embedded in the system, this tool enables users to import new microRNA sets obtained from their own research. miSEA allows users to select from a large variety of microRNA grouping categories, such as family classification, disease association, common regulation, and genome coordinates, based on their requirements. miSEA therefore provides a knowledge-driven representation scheme for microRNA experiments. The usability of this platform was discerned with a cancer type-classification task performed on a set of real microRNA expression profiling experiments. The miSEA web server is available at http://www.baskent.edu.tr/similar to hogul/misea (C) 2015 Elsevier Ireland Ltd. All rights reserved.