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    • Debarka Sengupta

      Articles written in Journal of Biosciences

    • Volume 40 Issue 4 October 2015 pp 721-730 Articles

      Feature selection using feature dissimilarity measure and density-based clustering: Application to biological data

      Debarka Sengupta Indranil Aich Sanghamitra Bandyopadhyay

      More Details Abstract Fulltext PDF

      Reduction of dimensionality has emerged as a routine process in modelling complex biological systems. A large number of feature selection techniques have been reported in the literature to improve model performance in terms of accuracy and speed. In the present article an unsupervised feature selection technique is proposed, using maximum information compression index as the dissimilarity measure and the well-known density-based cluster identification technique DBSCAN for identifying the largest natural group of dissimilar features. The algorithm is fast and less sensitive to the user-supplied parameters. Moreover, the method automatically determines the required number of features and identifies them. We used the proposed method for reducing dimensionality of a number of benchmark data sets of varying sizes. Its performance was also extensively compared with some other well-known feature selection methods.

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      Forthcoming Special issue.


    • To trigger further research on plant mitochondria, the Journal of Biosciences is bringing out a special issue titled "Plant Mitochondria: Properties and Interactions with Other Organelles".


      Plant mitochondria are quite distinct and have unique features, such as a cyanide-insensitive alternate pathway. They also interact with chloroplasts to optimize photosynthetic carbon assimilation.


      Submissions are welcome until 30 July 2023. The contributions can be original articles, short communications, reviews, or mini-reviews on any topic related to plant mitochondria.


      Authors can submit their articles online at https://www.editorialmanager.com/jbsc/default2.aspx

      Posted on April 12, 2023
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