Despite the numerous studies on large-scale relationships within Sylvioidea, the relationships among the families are still largely unresolved.
Spatial analysis of remotely-sensed land cover data in conjunction with species distribution atlases can reveal large-scale relationships between animal taxa and their habitats.
The establishment of Macroben allowed one of the first attempts to search for consistent, large-scale relationships between abundance and distribution of soft-sediment benthic organisms on a pan-European scale.
The reconstruction of several large-scale relationships among eukaryotes (the so-called supergroups) has been partially based on the documentation of shared, rare characteristics such as gene fusions or indels in two or more lineages [ 26- 28].
Assessing large-scale relationships of populations should elucidate the importance of range expansions and contractions in producing the current distribution patterns of species, as well as generate hypotheses regarding the genetic structure and diversity of temperate tree lineages affected by glaciation in the latter part of the Cenozoic.
In a study of large-scale relationships within the avian superfamily Sylvioidea, Alström et al. [ 1] found, based on mitochondrial cytochrome b and nuclear myoglobin intron 2 sequence data, that two species of Cettia and one species each of Urosphena, Tesia, Abroscopus and Tickellia, and Orthotomus cucullatus formed a clade, well separated from a broad selection of other passerines.
Finally, using sequence data from hundreds of microorganisms, we constructed a large-scale relationship tree.
The limited spatial scales of many bird habitat studies restrict inference regarding large scale bird habitat relationships.
A key driver in phylogenomics is the improvement of existing phylogenetic algorithms so that we can infer, at large scale, phylogenetic relationships with minimal technical biases and greater computational efficiency.
Large scale analysis of structure activity relationships and screening data is enabling the emergence of chemogenomics approaches to understanding the relationships between chemical space and biological target space.
In this work we perform the first large scale analysis of the relationship between three experimental proxies of mRNA local translation efficiency and the local features of the corresponding encoded proteins.
