Efficient Fuzzy Logic-Based Algorithm for Microarray Network Identification and Prediction in Bioinformatics

P Carbonell

    Research output: Contribution to journalArticlepeer-review

    Abstract

    Fuzzy logic-based systems have been proposed as a tool for analyzing experimental data in microarrays in order to detect and predict gene regulation networks. The main drawback of this approach is the so-called curse of dimensionality associated with high dimension exhaustive searches. In this paper, it is shown that simple standard fuzzy systems can be transformed into additively separable systems by using an appropriate rotation of the input variables. By doing this, the algorithm for computing the output of the fuzzy system takes polynomial time and, therefore, it is computationally efficient for finding higher dimension interaction among genes. Ill. 3, bibl. 8 (in English; summaries in English, Russian and Lithuanian).
    Original languageEnglish
    Pages (from-to)37-40
    Number of pages4
    JournalElektronika ir Elektrotechnika
    Volume67
    Issue number3
    Publication statusPublished - 2006

    Keywords

    • fuzzy\_logic
    • microarray
    • prediction

    Research Beacons, Institutes and Platforms

    • Manchester Institute of Biotechnology

    Fingerprint

    Dive into the research topics of 'Efficient Fuzzy Logic-Based Algorithm for Microarray Network Identification and Prediction in Bioinformatics'. Together they form a unique fingerprint.

    Cite this