Exploring the relationship between structural quality and journal impact factor
| Authors | |
|---|---|
| Year of publication | 2023 |
| Type | Conference abstract |
| MU Faculty or unit | |
| Citation | |
| Description | In structural bioinformatics, scientific research heavily depends on the structural data stored in the Protein Data Bank (PDB). The scientific community's widespread utilization of structural models puts pressure on the integrity of these structures. Consequently, a profound emphasis exists on structural validation, with the PDB providing detailed validation reports with various quality attributes. Our project embarks on an exploration of structural quality across different scientific journals. We investigate the interplay between structural quality metrics and the journal impact factor. Our methodology involves a selection of journals, categorizing them based on their impact factor, and the compilation of a dataset containing selected quality factors of these structures. Finally, our analysis uses statistical methods to describe the dynamic nature of the structural quality within each journal category. |
| Related projects: |