@article{HeidrichPinkertBrandletal.2021,
  author    = {Heidrich, Lea and Pinkert, Stefan and Brandl, Roland and B{\"a}ssler, Claus and Hacker, Hermann and Roth, Nicolas and Busse, Annika and M{\"u}ller, J{\"o}rg and Friess, Nicolas},
  title     = {Noctuid and geometrid moth assemblages show divergent elevational gradients in body size and color lightness},
  series = {Ecography},
  volume    = {44},
  journal   = {Ecography},
  number    = {8},
  doi       = {10.1111/ecog.05558},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-256694},
  pages     = {1169-1179},
  year      = {2021},
  abstract  = {Previous macroecological studies have suggested that larger and darker insects are favored in cold environments and that the importance of body size and color for the absorption of solar radiation is not limited to diurnal insects. However, whether these effects hold true for local communities and are consistent across taxonomic groups and sampling years remains unexplored. This study examined the variations in body size and color lightness of the two major families of nocturnal moths, Geometridae and Noctuidae, along an elevational gradient of 700 m in Southern Germany. An assemblage-based analysis was performed using community-weighted means and a fourth-corner analysis to test for variations in color and body size among communities as a function of elevation. This was followed by a species-level analysis to test whether species occurrence and abundance along an elevation gradient were related to these traits, after controlling for host plant availability. In both 2007 and 2016, noctuid moth assemblages became larger and darker with increasing elevation, whereas geometrids showed an opposite trend in terms of color lightness and no clear trend in body size. In single species models, the abundance of geometrids, but not of noctuids, was driven by habitat availability. In turn, the abundance of dark-colored noctuids, but not geometrids increased with elevation. While body size and color lightness affect insect physiology and the ability to cope with harsh conditions, divergent trait-environment relationships between both families underline that findings of coarse-scale studies are not necessarily transferable to finer scales. Local abundance and occurrence of noctuids are shaped by morphological traits, whereas that of geometrids are rather shaped by local habitat availability, which can modify their trait-environment-relationship. We discuss potential explanations such as taxon-specific flight characteristics and the effect of microclimatic conditions.},
  language  = {en}
}
@article{PinkertSchultzReichardt2010,
  author    = {Pinkert, Stefan and Schultz, Joerg and Reichardt, Joerg},
  title     = {Protein Interaction Networks-More Than Mere Modules},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-68426},
  year      = {2010},
  abstract  = {It is widely believed that the modular organization of cellular function is reflected in a modular structure of molecular networks. A common view is that a ''module'' in a network is a cohesively linked group of nodes, densely connected internally and sparsely interacting with the rest of the network. Many algorithms try to identify functional modules in protein-interaction networks (PIN) by searching for such cohesive groups of proteins. Here, we present an alternative approach independent of any prior definition of what actually constitutes a ''module''. In a self-consistent manner, proteins are grouped into ''functional roles'' if they interact in similar ways with other proteins according to their functional roles. Such grouping may well result in cohesive modules again, but only if the network structure actually supports this. We applied our method to the PIN from the Human Protein Reference Database (HPRD) and found that a representation of the network in terms of cohesive modules, at least on a global scale, does not optimally represent the network's structure because it focuses on finding independent groups of proteins. In contrast, a decomposition into functional roles is able to depict the structure much better as it also takes into account the interdependencies between roles and even allows groupings based on the absence of interactions between proteins in the same functional role. This, for example, is the case for transmembrane proteins, which could never be recognized as a cohesive group of nodes in a PIN. When mapping experimental methods onto the groups, we identified profound differences in the coverage suggesting that our method is able to capture experimental bias in the data, too. For example yeast-two-hybrid data were highly overrepresented in one particular group. Thus, there is more structure in protein-interaction networks than cohesive modules alone and we believe this finding can significantly improve automated function prediction algorithms.},
  subject      = {Netzwerk},
  language  = {en}
}