Journal of Data Mining in Genomics & Proteomics

Ahmad Maleki

Publications

• Research Article
  Promoter Prediction in Bacterial DNA Sequences Using Expectation Maximization and Support Vector Machine Learning Approach
  Author(s): Ahmad Maleki, Vahid Vaezinia and Ayda FekriAhmad Maleki, Vahid Vaezinia and Ayda Fekri
  
  Promoter is a part of the DNA sequence that comes before the gene and is key as a regulator of genes. Promoter prediction helps determine gene position and analyze gene expression. Hence, it is of great importance in the field of bioinformatics. In bioinformatics research, a number of machine learning approaches are applied to discover new meaningful knowledge from biological databases. In this study, two learning approaches, expectation maximization clustering and support vector machine classifier (EMSVM) are used to perform promoter detection. Expectation maximization (EM) algorithm is used to identify groups of samples that behave similarly and dissimilarly, such as the activity of promoters and non-promoters in the first stage, while the support vector machine (SVM) is used in the second stage to classify all the data into the correct class category. We have applied this method to.. View More»
  DOI: 10.4172/2153-0602.1000171

  Abstract PDF