This paper is in the following e-collection/theme issue:

Bioinformatics, genomics, tools and databases (24) Tools, Programs and Algorithms (323) Genome Analysis and Visualization (15)

Published on in Vol 3, No 1 (2022): Jan-Dec

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/30890, first published .
An Analysis of Different Distance-Linkage Methods for Clustering Gene Expression Data and Observing Pleiotropy: Empirical Study

An Analysis of Different Distance-Linkage Methods for Clustering Gene Expression Data and Observing Pleiotropy: Empirical Study

An Analysis of Different Distance-Linkage Methods for Clustering Gene Expression Data and Observing Pleiotropy: Empirical Study

Authors of this article:

Joydhriti Choudhury1 Author Orcid Image ;   Faisal Bin Ashraf1 Author Orcid Image
Article Authors Cited by (3) Tweetations Metrics

Journals

  1. Xu Y, Chan C, Chan E, Chen J, Cheung F, Xu Z, Liu J, Yip P. Tracking and Profiling Repeated Users Over Time in Text-Based Counseling: Longitudinal Observational Study With Hierarchical Clustering. Journal of Medical Internet Research 2024;26:e50976 View
  2. Mahmoudian-Hamedani S, Lotfi-Shahreza M, Nikpour P. Investigating combined hypoxia and stemness indices for prognostic transcripts in gastric cancer: Machine learning and network analysis approaches. Biochemistry and Biophysics Reports 2025;41:101897 View

Conference Proceedings

  1. Rahman I, Soumma S, Ashraf F. 2022 25th International Conference on Computer and Information Technology (ICCIT). Machine Learning Approaches to Metastasis Bladder and Secondary Pulmonary Cancer Classification Using Gene Expression Data View