Journal metrics and structures: A dynamic interplay
| Authors | |
|---|---|
| Year of publication | 2023 |
| Type | Conference abstract |
| MU Faculty or unit | |
| Citation | |
| Description | The basis of scientific research in structural bioinformatics depends on the amount of structural data stored in the Protein Data Bank (PDB). Maintaining structural integrity becomes more critical as the scientific community continually relies on structural models. This underlines the focus on structural validation, where PDB consistently documents the quality of individual structures through various quality metrics. Our research project examines the course of structural quality within various scientific journals. We discuss the relationships between structural quality metrics and journal impact factors. Our approach begins with selecting journals with a significant volume of published structures. Journals are subsequently categorized based on their respective impact factors. In the next phase, we compile a data set containing selected quality factors of these structures. Finally, through rigorous statistical analysis, we provide a detailed description of the nature of structural quality within each journal category. |
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