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On Things Not Seen

  • Marek KimmelEmail author
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 605)

Abstract

Some statistical observations are frequently dismissed as “marginal” or even “oddities” but are far from such. On the contrary, they provide insights that lead to a better understanding of mechanisms which logically should exist but for which evidence is missing. We consider three case studies of probabilistic models in evolution, genetics and cancer. First, ascertainment bias in evolutionary genetics, arising when comparison between two or more species is based on genetic markers discovered in one of these species. Second, quasistationarity, i.e., probabilistic equilibria arising conditionally on non-absorption. Since evolution is also the history of extinctions (which are absorptions), this is a valid field of study. Third, inference concerning unobservable events in cancer, such as the appearance of the first malignant cell, or the first micrometastasis. The topic is vital for public health of aging societies. We try to adhere to mathematical rigor, but avoid professional jargon, with emphasis on the wider context.

Keywords

Microsatellite Locus Ascertainment Bias Stepwise Mutation Model Primary Tumor Size Double Minute 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Department of StatisticsRice UniversityHoustonUSA
  2. 2.Systems Engineering GroupSilesian University of TechnologyGliwicePoland

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