Deep learning-based clustering approaches for bioinformatics

• Published in: Briefings in bioinformatics Vol. 22; no. 1; pp. 393 - 415
• Main Authors: Karim, Md Rezaul, Beyan, Oya, Zappa, Achille, Costa, Ivan G, Rebholz-Schuhmann, Dietrich, Cochez, Michael, Decker, Stefan
• Format: Journal Article
• Language: English
• Published: England Oxford University Press 18.01.2021; Oxford Publishing Limited (England)
• Subjects: Algorithms; Artificial neural networks; Bioinformatics; Biological activity; Cellular structure; Centroids; Cluster analysis; Clustering; Computer applications; Data mining; Data points; Deep learning; Gene mapping; Genomics; Learning algorithms; Machine learning; Medical imaging; Neural networks; Representations; Self organizing maps; State-of-the-art reviews; Unstructured data

Abstract Clustering is central to many data-driven bioinformatics research and serves a powerful computational method. In particular, clustering helps at analyzing unstructured and high-dimensional data in the form of sequences, expressions, texts and images. Further, clustering is used to gain insi...