Fuzzy systems and unsupervised computing: exploration of applications in biology

Leiden Repository

Fuzzy systems and unsupervised computing: exploration of applications in biology

Type: Doctoral Thesis
Title: Fuzzy systems and unsupervised computing: exploration of applications in biology
Author: Cai, F.
Issue Date: 2017-12-12
Keywords: Fuzzy systems
Unsupervised computing
Bioinformatics
Data analysis pipeline
Background correction
Feature selection
Information clustering
Genomic study
Abstract: In this thesis we will explore the use of fuzzy systems theory for applications in bioinformatics. The theory of fuzzy systems is concerned with formulating decision problems in data sets that are ill-defined. It supports the transfer from a subjective human classification to a numerical scale. In this manner it affords the testing of hypothesis and separation of the classes in the data. We first formulate problems in terms of a fuzzy system and then develop and test algorithms in terms of their performance with data from the domain of the life-sciences. From the results and the performance, we will learn about the usefulness of fuzzy systems for the field, as well as the applicability to the kind of problems and practicality for the computation itself.
Promotor: Supervisor: Verbeek F.J.
Faculty: Science
University: Leiden
Uri: urn:isbn:9789461828606
Handle: http://hdl.handle.net/1887/57983
 

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