Lefteris Koumakis (Foundation for Research and Technology - Hellas)
Overview
Advances in deep learning created an unprecedented momentum in biomedical informatics and have given rise to new bioinformatics and computational biology research areas. It is evident that deep learning models can provide higher accuracies in specific tasks of genomics than the state of the art methodologies. Given the growing trend on the application of deep learning architectures in genomics research, in this mini review we outline the most prominent models, we highlight possible pitfalls and discuss future directions.
Contributions and Distinctions from Previous Works
Methods
Deep learning, Genomics, Computational biology, Bioinformatics, Gene expression and regulation, Precision medicine
Results
Cite
Lefteris Koumakis, Deep learning models in genomics; are we there yet?, Computational and Structural Biotechnology Journal, Volume 18, 2020, Pages 1466-1473, ISSN 2001-0370, https://doi.org/10.1016/j.csbj.2020.06.017.
TL;DR
This paper reviews deep learning architectures in genomics research (2020).
Paper Link
https://www.sciencedirect.com/science/article/pii/S2001037020303068?via%3Dihub
Author/Institution
Lefteris Koumakis (Foundation for Research and Technology - Hellas)
Overview
Advances in deep learning created an unprecedented momentum in biomedical informatics and have given rise to new bioinformatics and computational biology research areas. It is evident that deep learning models can provide higher accuracies in specific tasks of genomics than the state of the art methodologies. Given the growing trend on the application of deep learning architectures in genomics research, in this mini review we outline the most prominent models, we highlight possible pitfalls and discuss future directions.
Contributions and Distinctions from Previous Works
Methods
Deep learning, Genomics, Computational biology, Bioinformatics, Gene expression and regulation, Precision medicine
Results
Cite
Lefteris Koumakis, Deep learning models in genomics; are we there yet?, Computational and Structural Biotechnology Journal, Volume 18, 2020, Pages 1466-1473, ISSN 2001-0370, https://doi.org/10.1016/j.csbj.2020.06.017.
Comments
Review paper