adenine is a machine learning framework designed for biological data exploration and visualization. Its goal is to help bioinformaticians achieving a first and quick overview of the main structures underlying their data. This software tool encompasses state-of-the-art techniques for missing values imputing, data preprocessing, dimensionality reduction and clustering. adenine has a scalable architecture which seamlessly work on single workstations as well as on high-performance computing facilities. adenine is capable of generating publication-ready plots along with quantitative descriptions of the results. In this paper we provide an example of exploratory analysis on a publicly available gene expression data set of colorectal cancer samples. The software and its documentation are available at https://github.com/slipguru/adenine under FreeBSD license.
CITATION STYLE
Fiorini, S., Tomasi, F., Squillario, M., & Barla, A. (2019). Adenine: A HPC-oriented tool for biological data exploration. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10834 LNBI, pp. 51–59). Springer Verlag. https://doi.org/10.1007/978-3-030-14160-8_6
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