Useful links:
BioScience is an advanced Python library designed to satisfy the growing data analysis needs in the field of bioinformatics by leveraging High-Performance Computing (HPC). This library encompasses a vast multitude of functionalities, from loading specialised gene expression datasets (microarrays, RNA-Seq, etc.) to pre-processing techniques and data mining algorithms suitable for this type of datasets. BioScience is distinguished by its capacity to manage large amounts of biological data, providing users with efficient and scalable tools for the analysis of genomic and transcriptomic data through the use of parallel architectures for clusters composed of CPUs and GPUs.
BioScience is featured for:
- Unified APIs, detailed documentation, and interactive examples available to the community.
- Complete coverage for generate biological results from gene co-expression datasets.
- Optimized models to generate results in the shortest possible time.
- Optimization of a High-Performance Computing (HPC) and Big Data ecosystem.
gettingStarted/whatis gettingStarted/install gettingStarted/quickstart
userGuide/load userGuide/preprocess userGuide/dataMining userGuide/results
useCases/singleCell useCases/rnaSeq useCases/microarray
api/api
contributors/contributing contributors/developmentProcess contributors/about contributors/release
Citing bioScience:
bioScience is published in SoftwareX. If you use bioScience in a scientific publication, we would appreciate citations to the following paper:
López-Fernández, A., Gómez-Vela, F. A., Gonzalez-Dominguez, J., & Bidare-Divakarachari, P. (2024). bioScience: A new python science library for high-performance computing bioinformatics analytics. SoftwareX, 26, 101666.Key Links and Resources: