Machine learning for computational and systems biology
Section Editor: Professor Jean-Philippe Vert
As part of the launch of the journal section "Machine Learning and Artificial Intelligence in Bioinformatics", BMC Bioinformatics is excited to announce that we are now accepting manuscripts for the thematic series Machine learning for computational and systems biology.
The purpose of this thematic series is to bring together latest advances in machine learning and artificial intelligence methods in computational and systems biology, including their applications to problems in bioinformatics.
We welcome manuscripts describing novel computational techniques to analyse high throughput data such as sequences and gene/protein expressions, as well as machine learning techniques such as graphical models, neural networks or kernel methods. This includes, but is not limited to:
- Data integration/fusion/multi-view learning
- Deep learning
- Kernel methods
- Multitask/structured output prediction
- Genome-wide association studies
- Metabolomic modelling
- Synthetic biology
Please submit directly to BMC Bioinformatics stating in your cover letter that it is for the “Machine learning for computational and systems biology” collection. Alternatively you can email your pre-submission queries to the Editor of BMC Bioinformatics at firstname.lastname@example.org
All manuscripts submitted for inclusion in the series by May 6th 2019 will be considered.
There are currently no articles in this collection.