Most puzzling to us is the null hypothesis testing approach described by Burstyn et al. in their letter, in which associations were dichotomized to conclude a "link" when confidence limits excluded the null value, or "no link" otherwise.
We conclude that link and network radius-based attributes of street formations have significant effects on the spatial variations of walking within multi-scale walkable neighborhoods.
We conclude that linking a stakeholder analysis, comprising rarely asked questions, with a rigorous social network analysis is very fruitful and generates complementary results.
We conclude that linking CAT to a GIS data-base supports simulations at the city scale that reflect the local intra-urban variability.
Based on the above observations, we conclude that link-based community detection algorithms have the ability to partially recover functional communities, but such ability is inherently limited by the essential differences between functional communities and link-based communities.
We conclude that linking patterns of species diversity with the temporal dynamics of habitats substantially improves the understanding of the variation in species diversity, and thus helps to identify species of conservation concern.
High-protein proponents have conducted multiple literature reviews and conclude no links exist between kidney damage and excessive protein intake.
However, we also conclude that linking EDs to the outcomes observed in mammalian species, or other testing protocols, is necessary to buttress epidemiological results, both at the ultimate end point level and at intermediate end points leading to it.
Since we find the driving force behind fusion events not to be a high frequency of interactions between a given protein domain pair but a large number of individual interaction partners, we conclude that links appearing in the innermost cores of the co-occurring networks are the result of underlying important domain interactions.
Protein domains mentioned in the description link to their entries in the Pfam database (http://pfam.sanger.ac.uk/); the description concludes with links to the pathway ontology report page and as applicable, to related GO term or DO term ontology report page(s), KEGG map, PharmGKB report and/or Reactome entry.
