Kernel Methods in Computational Biology
Max Planck Society · Max Planck Institute for Biological Cybernetics · +1 more institution
Abstract
A detailed overview of current research in kernel methods and their application to computational biology. Modern machine learning techniques are proving to be extremely valuable for the analysis of data in computational biology problems. One branch of machine learning, kernel methods, lends itself particularly well to the difficult aspects of biological data, which include high dimensionality (as in microarray measurements), representation as discrete and structured data (as in DNA or amino acid sequences), and the need to combine heterogeneous sources of information. This book provides a detailed overview of current research in kernel methods and their applications to computational biology. Following three…
Citation impact
- FWCI
- 28.32
- Percentile
- 100%
- References
- 25
Authors
2- JVJean‐Philippe VertCorresponding
Max Planck Society, Max Planck Institute for Biological Cybernetics, École Nationale Supérieure des Mines de Paris
- 阿達阿久津, 達也
Max Planck Society, Max Planck Institute for Biological Cybernetics
Topics & keywords
- Computer science
- Kernel method
- Kernel (algebra)
- Data science
- Machine learning
- Biological data
- Artificial intelligence
- Computational model