A framework for neighbourhood configuration to improve the KNN based imputation algorithms on microarray gene expression data
by Shilpi Bose; Chandra Das; Kuntal Ghosh; Matangini Chattopadhyay; Samiran Chattopadhyay
International Journal of Bioinformatics Research and Applications (IJBRA), Vol. 18, No. 3, 2022

Abstract: Due to technical problems in DNA microarray experiments, a large number of entries are found missing in microarray datasets. As a consequence, the effectiveness of the analysis algorithms deteriorates. Among different imputation techniques, the weighted average based methods always generate consistent results, are algorithmically simple and very popular but they also suffer from some drawbacks. These deficiencies have been pointed out in this work, and a new framework has been suggested to overcome those. The proposed framework is embedded in the K-nearest neighbour imputation method (KNNimpute), as well as its different versions. It is based on a hybrid distance and gene transformation procedure which utilises simultaneously the advantages of Euclidean distance, mean squared residue score, and Pearson correlation coefficient to select the best possible neighbours, using pattern-based similarity. The framework is tested on well-known microarray datasets. From the experimental results, the superiority of the proposed work has been found.

Online publication date: Mon, 22-Aug-2022

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Bioinformatics Research and Applications (IJBRA):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com