Upcoming Special Issues
Call for papers: Novel applications of machine learning in cheminformatics
There has been a renewed interest in novel machine learning techniques in cheminformatics during the last years. This has been driven both by new methods, access to larger and imbalanced datasets as well as progress in high-performance and cloud computing. For example, methods such as conformal prediction, deep learning and matrix factorization have already made a significant impact and are part of making the drug discovery process more data-driven and efficient.
The Journal of Cheminformatics announces a special article collection titled “Novel applications of machine learning in cheminformatics”. We welcome submissions on all types of cheminformatics-related research involving applications or methods of machine learning with a novel direction. Note that we will not consider publications that simply apply traditional machine learning models to a new dataset or reanalyzing an old dataset with a different method. Novel directions might include (but are not limited to):
- New ways of applying machine learning methods
- Applications to new areas not traditionally covered by machine learning
- Confidence/probabilistic predictors
- Large-scale applications using modern e-infrastructure
- Novel ways of modeling particularly complex or problematic datasets
The 6th Symposium on Conformal and Probabilistic Prediction with Applications (COPA 2017) was held at Karolinska Institutet, Stockholm, Sweden on June 14-16, 2017. We invite authors whose papers were accepted to this conference (see Proceedings of Machine Learning Research, Volume 60) in the special section on cheminformatics to submit an extended version to this special article collection.
Papers will be continuously peer-reviewed according to Journal of Cheminformatics author guidelines and published in the collection, but the deadline for submission is March 20th, 2018. Please submit manuscripts using the online system, and select the special article collection “Novel applications of machine learning in cheminformatics”. Please note that review papers will not be considered for this article collection. This special article collection for Journal of Cheminformatics is Guest Edited by Ola Spjuth, Uppsala University, Sweden.
Journal of Cheminformatics levies an article-processing charge (APC) for each article accepted for publication. For assistance with the APC for authors who do not have access to APC finding, please visit our OA Funding Support Service page, or get in touch with Editorial at the email below.
For further information or queries contact the in-house Editor at firstname.lastname@example.org