@article{KrausMathewStephenSchapranow2021,
  author    = {Kraus, Sara Milena and Mathew-Stephen, Mariet and Schapranow, Matthieu-Patrick},
  title     = {Eatomics},
  series = {Journal of proteome research},
  volume    = {20},
  journal   = {Journal of proteome research},
  number    = {1},
  publisher = {American Chemical Society},
  address   = {Washington},
  issn      = {1535-3893},
  doi       = {10.1021/acs.jproteome.0c00398},
  pages     = {1070 -- 1078},
  year      = {2021},
  abstract  = {Quantitative proteomics data are becoming increasingly more available, and as a consequence are being analyzed and interpreted by a larger group of users. However, many of these users have less programming experience. Furthermore, experimental designs and setups are getting more complicated, especially when tissue biopsies are analyzed. Luckily, the proteomics community has already established some best practices on how to conduct quality control, differential abundance analysis and enrichment analysis. However, an easy-to-use application that wraps together all steps for the exploration and flexible analysis of quantitative proteomics data is not yet available. For Eatomics, we utilize the R Shiny framework to implement carefully chosen parts of established analysis workflows to (i) make them accessible in a user-friendly way, (ii) add a multitude of interactive exploration possibilities, and (iii) develop a unique experimental design setup module, which interactively translates a given research hypothesis into a differential abundance and enrichment analysis formula. In this, we aim to fulfill the needs of a growing group of inexperienced quantitative proteomics data analysts. Eatomics may be tested with demo data directly online via https://we.analyzegenomes.com/now/eatomics/or with the user's own data by installation from the Github repository at https://github.com/Millchmaedchen/Eatomics.},
  language  = {en}
}
@misc{GieblerRuthTanneberg2018,
  author    = {Giebler, Heiko and Ruth, Saskia P. and Tanneberg, Dag},
  title     = {Why choice matters},
  series = {Politics and Governance},
  volume    = {6},
  journal   = {Politics and Governance},
  number    = {1},
  publisher = {Cogitatio Press},
  address   = {Lisbon},
  issn      = {2183-2463},
  doi       = {10.17645/pag.v6i1.1428},
  pages     = {1 -- 10},
  year      = {2018},
  abstract  = {Measures of democracy are in high demand. Scientific and public audiences use them to describe political realities and to substantiate causal claims about those realities. This introduction to the thematic issue reviews the history of democracy measurement since the 1950s. It identifies four development phases of the field, which are characterized by three recurrent topics of debate: (1) what is democracy, (2) what is a good measure of democracy, and (3) do our measurements of democracy register real-world developments? As the answers to those questions have been changing over time, the field of democracy measurement has adapted and reached higher levels of theoretical and methodological sophistication. In effect, the challenges facing contemporary social scientists are not only limited to the challenge of constructing a sound index of democracy. Today, they also need a profound understanding of the differences between various measures of democracy and their implications for empirical applications. The introduction outlines how the contributions to this thematic issue help scholars cope with the recurrent issues of conceptualization, measurement, and application, and concludes by identifying avenues for future research.},
  language  = {en}
}