Was my proposal to "grab the cow by its horns" to try something in a the context of a pilot to naive in your opinion?
Not at all. It's exactly what I'm exploring. I am looking for frameworks from which to work in where we can start building out the model and layers even if it's what seems hopelessly simplistic at first :
.
.
.
With the leg bone connected to the knee bone,
and the knee bone connected to the thigh bone,
and the thigh bone connected to the hip bone.
.
.
.
With the systems approach we enumerate everything and simply start looking for the association points between each element in each list. The more associations we can make, the stronger the model becomes over time. It becomes hideously complex over time but that's where we bring in the big guns of machine learning, genetic algorithms, puzzle building algorithms, etc.
Would it be possible to select only certain aspects of the behaviour of cells in its environment by selecting only the interfaces that matter for the aging process to test / model these?
Absolutely. After enumerating the basic data elements across the various layers we focus on building outwards from the data elements implicated in the aging process and start linking them up. The causes of aging, the aging related metabolic changes, the genes involved, the damage that accumulates (e.g. amyloids, cancers, diseased tissues, inflammation types, etc). We stick all the data together and assign numerical values to them in various ways. We rank them, we put biological ages to them as to when they occur, etc.
While we build on all of this data we continuously look for ways to visualize it from different perspectives in order to find new and unique patterns that might give us some theoretical interventions or even predict what the missing pieces of the puzzle are.
Do we even have sufficient knowledge to make such a selection?
We have sufficient knowledge to start building the prototypes but the data is scattered all over the place and biologists have historically had a bad habit of describing data with much verbosity. We need it to be machine readable to extract any value out of it. I'd love to find ways to pull all of the known aging data together into a relational database and curate it for the next generation of upcoming gerontologists.
Would it be possible to start somewhere in the middle of the structural hierarchy?
It's probably the only place we can start. I propose that a good starting place is to enumerate all of the aging diseases, age related changes, causes of aging and damage that accumulates whether they be confirmed or theoretical. We could start mapping them all together as best we can and inch our way into more complex realms as time, data and our ability permits. Hopefully more experts might get involved from various fields to help overcome hurdles as they arise. There's always bribery and blackmail if they refuse
Like taking a simple generally representative organ, virtually remove it from its real environment and test / model all its (functional) interfaces? Thereby using a high level of abstraction as a reduction of complexity?
Or use both approaches combined?
Academic efforts have been trying this for quite awhile. The projects usually end when the grant money runs out or they hit the complexity wall. Rounding these up and compiling the data they gathered into a central systems model would be one of the goals of such an endeavor.
Edited by maestro949, 10 August 2007 - 06:13 PM.