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What follows is a rant about what I see as a dichotomy between the stunning success and an epic failure of modern Biology. While this may seem like an indictment or judgement, specifically of disciplines such as Systems Biology, it’s supposed to be a start of a conversation. 1/16
I don't know if this is a biocentric view of science or if this extends across other disciplines, but I am absolutely bewildered by the divergence between ever increasing capabilities and what feels like ever decreasing fundamental understanding. 2/16
Techniques and experimental approaches are improving at a dizzying speed. Automation enables vast experimental throughput in virtually every area. And integration of computational approaches enables digestion and interpretation of ever larger datasets. 3/16
Yet, I never get the feeling that any of these improvements (and sometimes astounding leaps) lead to true understanding. Every bit of understanding is (if present at all) only incremental and as soon as you think it is established, it has to be questioned again. 4/16
Any conclusion will get refined, counterexamples are found, there are edge-cases where rules don’t apply, and what is the most frequent issue: As experiments get more and more refined, the findings are less and less likely to be broadly generalizable. 5/16
And worse, as we gain better understanding and ever more refined insight, even the 'truths' from the past get overthrown. We learn that what we thought of as discrete, quantifiable processes are virtually always the emerging phenomena. 6/16
Underlying, there are a myriad of heterogeneous subprocesses, all with their own variations in space and time. So, with more and deeper understanding, things oddly enough get harder and more complex, and not easier. 7/16
But even as we drill down into molecular mechanisms, ultimately, what we truly want is to understand ‘the whole'. This goal of understanding functions at the level of an organism rather than molecules, gets ever-more unreachable, it seems. 8/16
Maybe there needs to be a shift in the emphasis, from drilling down in to every more detail, to the focus of synthesizing what we are learning. 9/16
This, as I see it at least, was the promise of Systems Biology. But of course, that check never got cashed. In fact, you can argue that Systems Biology is the main driver on this downhill ramp to measuring things in ever more detail and at an ever-larger scope. 10/16
Maybe it's time for a new sub-discipline in biology to emerge. One that disavows collecting more detailed information and bends all its focus on synthesizing knowledge out of what we learned already. 11/16
However, I do not feel in any way confident that there is any chance this will happen. For one, human nature is to try to peek behind the curtain, and this means for any process we are curious to find out what lies underneath. 12/16
And very rarely are people content with working exclusively with the data others create. We see this in Computational Biology, where folks often start mining data, but then realize that the data collection could (and should be improved), thus the circle continues. 13/16
How do we fix this? Will we at some point reach ‘the bottom’ and suddenly with that we put everything together and ‘understand’ how a disease are caused and can be treated at a molecular level? 14/16
Don’t get me wrong, though. I do know the countless success stories, where molecular understand has broad organismal implications (e.g. BCR-ABL translocation, HER2 amplification, BRAF), but I’d argue such examples are rare. 15/16
I guess my hope would be that we could at the least shift priorities somewhat. If we were to only focus 10% of our effort from drilling down into molecular details to working back ‘upward’ to the organism, we could make impactful progress in both directions. 16/16
Please accept my apologies for the seemingly random tagging, but I'm curious what others think about this. If you are interested, feel free to answer or retweet the first tweet of the rant and tag others.
