Downloads provided by UsageCounts
This document describes the best practice guides developed by BioExcel for our core codes and workflow engines. With regards to the core codes the guides cover best practices for using CP2K to perform QM/MM simulation of biomolecular systems, general usage of GROMACS and obtaining good performance on specific HPC machines available to EU researchers through PRACE, and best practices for molecular docking with HADDOCK. Additional guides cover several aspects of computational workflows; development process using Common Workflow Language, choice of workflow engines, and how to package workflow results combining multiple FAIR standards. The BioExcel guides have been planned based on our experience developing and using the codes and workflow engines, our engagement with users at training events and workshops, through provision of in-depth support, and through community surveys, all of which have allowed us to identify and prioritise user needs. We have begun and will continue to promote, revise and expand the guides based on our engagement with the computational biomolecular research community through our support mechanisms and through BioExcel-organised events in 2021, such as the EMBO conference and various training events. The guides have been made available as structured web pages editable through open source processes, inviting further contributions from the respective user communities. We consider how we can make the guides follow FAIR guidelines and increase their outreach using traditional publication and integration with existing software documentation portals.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 6 | |
| downloads | 7 |

Views provided by UsageCounts
Downloads provided by UsageCounts