Homology Analysis Observations List

NOTE:

We distinguish between different types of ageing relevance evidence. Experimental studies on ageing factors result in observations with experimental ageing relevance evidence (1). According to our definition of ageing factors a comparison of two situations, with and without the action of the ageing factor, is required. Almost all data in AgeFactDB is of this type. There are however also a few lifespan data for populations or species included that are certainly relevant to ageing with a slightly different meaning of the term ageing relevance, however. But in this case there is no intervention study and therefore these data cannot be assigned to an ageing factor (2). Furthermore, there are experimental studies where no significant effect of an assumed ageing factor was found (3). And finally there are genes included that are homologous to known ageing-relevant genes for which there is no experimental evidence. They are considered as putative ageing-relevant genes with computational evidence (4).
Order of importance:

1. yes (Experimental Analysis)
2. yes, but no ageing factor assigned (Experimental Analysis)
3. no (Experimental Analysis)
4. putative (Computational Analysis)

The color indicating the ageing relevance type of an observation may differ from the corresponding color for the ageing factor related to this observation. The reason is that for ageing factors associated with more than one observation, the most important observation color is chosen as ageing factor color. This is always the color with the lowest number in the order given above.

Ageing phenotype observations are considered as experimental analysis. They confirm or reject the ageing relevance for particular ageing factor(s). For genes that are homologous to known ageing-relevant genes there is thus far no experimental evidence. They are considered as candidate genes.
Due to the different data structures of ageing phenotype observation data integrated from other databases we subdivide these observations into type 1 and 2. Observations of type 1 contain the phenotype data mostly unseparated within a single description. Observations of type 2 contain lifespan data in a more structured form (e.g.: separated into lifespan effect, lifespan change, lifespan value). Currently there might be an overlap between the observations of type 1 and 2 from the same source, namely GenAge. But we are working on a reduction of this overlap.

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