What is Semantic Systems Biology?
Semantic technologies are playing an increasingly important role in capturing and modeling biological knowledge. Semantic systems biology can complement the bottom-up approach with data-driven generation of hypotheses. Therefore, Semantic Systems Biology (SSB) is a systems biology approach that uses semantic description of knowledge about biological systems to facilitate integrated data analysis.
What are the features of a Semantic Systems Biology approach?
There are some key elements in this new paradigm:
- Knowledge representation
- Data integration
- Reasoning =>hypothesis
- Querying =>hypothesis
In other words we all gave up doing biology and let computers both take the measurements and draw the conclusions. I Robot. I mere poorly programmed organism capable of performing menial tasks such as can also be performed by simple mechanoids. Redundancy beckons. For the whole human race.
Semantics is, of course, the discussion of meaning, of interpretation of particular words as used in language. Systems are mechanisms, operational relationships, interactive structures and biology is a generic description of living systems’ components or the operation of one of those components within the living world. In SSB are we thus discussing the interpretation of operational features observed within biological analyses?
Semantics implies a dynamic, with interchange between the elements of the study. It appears to be a holistic approach with, perhaps, the recognition that we mere mortals have little idea of how to pose interpretable questions or derive meaningful answers.
He sinks into conjecture mode to derive futures from this approach. It’s always medical, that’s where the money is, that’s where all the problems are, that’s where evidence is gathered. He thinks of “evidence based medicine” and the use of the lowest common multiple.
Now a doctor looks at his desktop computer on which are vast scrolls of data. He has grasped evidence based medicine. He has here data gathered from analogous cases are accumulated and from these have been derived the single best possible intervention for the patient in front of him. That is statistically the single course of action which has the best percentage of success as judged by defined criteria such as survival, recovery time, lasting damage etc. So he prescribes the right pill or the best pill for these circumstances.
Perhaps when to EBM we add SSB, we can achieve a computer analysis of massed data describing the best possible outcome, irrespective of a practitioner’s presence.
“Computer, what shall I do?” the individual may ask, realising that, in the old days he’d had to wait until he was ill before consulting a doctor. He will smile as he recalls how he had never taken to those overpaid, supercilious, pill prescribing disaster areas. He’d been told that less than 15% of doctor – patient sessions led to a positive outcome. Probably 80% had led to prescription of medicines, though.
Now there was a regular docking with the health monitor, which was really to confirm and reinforce his established personal maintenance programme. The whole process took minutes and, by the time he was ready to leave, in the reception area was a discrete report and sometimes a single, personalised, slow release supplement pill to bolster any minor inbalances which had been detected as present or forecast.
The report contained a “suggested” date for the next visit and any operational changes it was “recommended” he adopt. No-one ignored these. This time it was deemed his continued personal development would benefit from extended participation in extended muscular-skeletal operational interactions. To underscore this there were printed data covering median metabolic rates and rest state dynamics within his corporal musculature.
“Ah, Pranayama”, he would think, breathing deeply, remembering his next yoga class.