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Reasonable findings (such as ) are treated as true-positive cases and, albeit indirectly, are perceived to yield some validity to the methods that were used to detect them.Here, we argue that the approach of perceiving an increased validity of results, simply because they make sense, may be misleading in many cases.We particularly value the capabilities of the software in the area of scenario definitions, the easy interface to our existing vehicle dynamics models, the broad database of different sensing technologies and the professional support that we receive from the local TASS team.As a result we recently planned to extend our Pre Scan usage to our autonomous driving development and research.

Even for genes with obscure roles, it may not represent a grand challenge to unravel some connections with key genes using literature mining tools such as i HOP (information Hyperlinked Over Proteins, Hoffmann and Valencia 2004, 2005) or pathway knowledge bases such as Reactome (Vastrik et al. To this end, we assess whether scanning a genome for positive selection can result in the detection of “meaningful” genes, even if we know a priori that the genome is neutral.

By simulating neutral evolutionary histories, we demonstrate that it is possible not only to obtain an extremely high false-positive rate but also to make biological sense out of the false-positives and construct a sensible biological narrative. Analyzing X-linked quantitative trait loci (QTL) affecting cold tolerance, Svetec et al.

Results are compared with a recent polymorphism data set from lineage for instance, the search for positively selected genes has generated a rapidly growing list of candidates. (2011) found evidence for a selective sweep in the gene (Ayroles et al. In general, after conducting a genomic scan for positive selection, researchers focus on the functions and biological properties of the identified gene regions.

In other words, if a well described, reasonable scenario/narrative can be constructed from the identified genes, the credibility of the positive selection hypothesis is assumed to increase.

Often, the computational and statistical approaches that were deployed for detecting positive selection are considered to be valid and/or correctly implemented because results are biologically sensible.

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