PT  - JOURNAL ARTICLE
AU  - Auste Kanapeckaite
TI  - Fiscore Package: Effective Protein Structural Data Visualisation and Exploration
AID  - 10.1101/2021.08.25.457640
DP  - 2021 Jan 01
TA  - bioRxiv
PG  - 2021.08.25.457640
4099  - http://biorxiv.org/content/early/2021/09/06/2021.08.25.457640.short
4100  - http://biorxiv.org/content/early/2021/09/06/2021.08.25.457640.full
AB  - The lack of bioinformatics tools to quickly assess protein conformational and topological features motivated to create an integrative and user-friendly R package. Moreover, the Fiscore package implements a pipeline for Gaussian mixture modelling making such machine learning methods readily accessible to non-experts. This is especially important since probabilistic machine learning techniques can help with a better interpretation of complex biological phenomena when it is necessary to elucidate various structural features that might play a role in protein function. Thus, Fiscore builds on the mathematical formulation of protein physicochemical properties that can aid in drug discovery, target evaluation, or relational database building. In addition, the package provides interactive environments to explore various features of interest. Finally, one of the goals of this package was to engage structural bioinformaticians and develop more robust R tools that could help researchers not necessarily specialising in this field. Package Fiscore (v.0.1.3) is distributed via CRAN and Github.Competing Interest StatementThe authors have declared no competing interest.