A brilliant question. How I wish I had ResearchGate to ask this in 1970.

My first thought would be to follow my father's advice - looking after patients is the most rewarding thing and keeps you sane while the research is slow. Doing both is hard but perfectly possible and I would not have wanted to miss out on either. Moreover, looking after patients shows you what the real problems are - the ones worth spending twenty five years on.

Doing clinical work and research together successfully has always been a question of breaking the rules. If you follow the rules you will be stuck in treacle. Taking your own path can be lonely and frightening at times but you have to stick to the motto of the Royal Society 'Nullis in verba' - never believe what someone else says. So there is no way to advise on 'which department to work for' or 'which area to target'.

Which brings me to the next point which is my advice to find your very own question to ask and answer. Forget what everyone else is asking, find your own question. If you cannot think of your own question then you have to wonder if you are suited to research. (Unfortunately research is full of people who cannot think of their own question.) And be prepared to keep asking one question for thirty years. What you should not do is stick to the same answer for thirty years - that is the sign of failure. Wisdom is discovering you were wrong, and wrong again, and again.

Now for the knock-out point. Forget systems biology and emergent behaviour. Systems biology is just a meaningless fad. It is bad science. The body has no systems. Everything dovetails with everything. The protein that lubricates joints comes from the same gene as megakaryocyte stimulating factor. As my hero Leibniz pointed out there are no systems in nature. The current fashion for systems thinking is a march back into the middle ages. It imposes presuppositions that stop you thinking. And I have no idea what emergent behaviour is really supposed to be but I am fairly sure it does not exist in complex dynamic patterns with parts. The idea is used by people to bullshit mostly - to give the impression you have an explanation when you do not. Something like emergence does appear in terms of the partless units of quantum field theory but that is another story.

So in summary my advice is to find your own question - based on talking to people with illness. I found my question talking to people with rheumatoid arthritis. You might find it with Parkinsonism or multiple sclerosis - both well worth a lifetime's effort. And learn to forget fads like systems biology. They have nothing to do with productive research.

The biggest and most interesting problem of all is how we come to have thoughts. And why thoughts go wrong in schizophrenia is perhaps the most worthy question. Mental illness is worse than hell for the sufferer and their family. I am too old to solve this one but you might look at http://www.ucl.ac.uk/jonathan-edwards if you are brave enough to break some rules and think some different thoughts!!

Very helpful and wise comment from Jonathan, but I find it a bit astonishing to read "The body has no systems" from a researcher of rheumatoid arthritis ;))! Isn´t it exactly THE example of a disorder which we can grasp only via systemic point of view?

As for me, I think getting more and more of narrow-scoped completely unstructured information on clinical questions does not enhance our understanding on them. For me biological processes are nothing else as the systems and of course it is challenging but we have to try to create a holistic picture of dynamic life processes at all levels. Starting form the genome to the proteome and signaling, up to the complete cell, organ and even an entire organism. I do believe in the future of systems medicine, I think this is the only apporach to understand the complexity of physiological processes.

Dear Maria,

You may be astonished, but I see 'the body has no systems' as an important message to anyone hoping to do creative research. A completely unstructured observation on a clinical question, like the presence of pericarditis in rheumatoid disease, or of uveitis in ankylosing spondylitis only becomes narrow-scoped when you start to assume that it relates to some specific 'system'. Which system does rheumatoid arthritis fall under? It is 'systemic' only in the sense that it seems potentially to effect everywhere supplied by the circulation, so we might think we should address it through the 'circulatory system'. But it does not affect the brain, which has a rich blood supply. The link between RA and DR4 led people to assume it was a disease of the 'adaptive immune system', which according to the received model was controlled by T cell selection. But although RA does appear to involve an adaptive response it turns out that studying T cells has been more or less a complete waste of time. And if people had stuck to the 'unstructured observation' of the presence of autoantibodies they would not have wasted so much time. If they had stuck to 'unstructured observations' about complement interactions rather than imposing assumption about the 'function of the complement system' they might have got to the answer ten years earlier. My own research started to make progress once I realised that everything has a relation to everything else and that to think in terms of systems is to think narrowly.

During my biomedical science career 'systems biology' had not been invented yet huge progress was made. Just before I retired I was invited to a 'systems biology' meeting at UCL to discuss this 'exciting new approach'. I left after an hour of people talking empty drivel about grant applications without the least hint of a creative scientific idea. It is a buzz word invented by people with no imagination to cover up for their lack of ideas. It is based on the idea that if you think of events in terms of systems then magic patterns 'emerge' which you could not possibly have discovered by considering the individual interactions. The reverse is true. It is by painstakingly studying the individual interactions that you get the right answer. The fact that people think these magic patterns can be modelled on computers is proof of the fact that they depend only on the individual interactions because everything in a computer depends on individual interactions.

I totally agree that everything has to be considered in terms of vast networks of complex relations and that sometimes computer modelling can help but we knew this long ago and the current fad for thinking that 'systems thinking' is a quick route to magic answers is just intellectual laziness.

Difficult to argue, Jonathan, to be honest ;). I have not published any systems biology paper yet, I am relatively unexperienced in this field and I do not have your wisdom gained over your brilliant career. And still, my perception of “systems biology” lies not in “buzz word invented by people with no imagination to cover up for their lack of ideas”. NO way! I have totally different experience in communicating with modelers and systems biologists.

For me both approaches are necessary and both are equally essential – the scale of a “smaller” dimension following individual interactions and the upper scale, which bridges the “small” parts together. I absolutely agree that by studying the individual interactions you get the right answer. I also love to dig into molecular mechanisms of transcriptional regulation and decipher the sites of post-translational modifications. But at some point you take a step backward and look at the context, you take a bit higher angle of perspective and try to comprehend the whole picture. Why not using at this step mathematics? As I see it, the purpose of describing systems using mathematics is not in uncovering new mechanisms or searching for “emerging” patterns, no, this is rather about putting our knowledge together and trying to systemize it.

Thank you both very much for these answers.

Jonathan, I'm also glad about this platform to ask my question but sadly it seems that advice on my original question doesn't come easy here either.

Concerning your remarks on "breaking the rules" and "taking my own path" I can tell you that it is an enormous relief to actually read it written down by someone else - especially if this person already succeeded in making a contribution.

I'm quite sure of what I would like to do with my life but it often seems to be “off the track” not in a negative but in a very weird way. These “special interests” of mine are something that always ran along in my studies and I’m rather positive about finding some question to ask as they always pop up anyway. Nevertheless it is clear for me that my primary goal would be patient care. I never confined myself to any specialty - except excluding the “cutting bussiness” as we call it in rough translation.

Considering your statements about the systems aspect I understand where you are coming from. I’m not competent to discuss the philosophy behind it and it is not my intention to do so. But concerning the statement that it is only an attempt to pretend knowledge I would contradict.

You said that you wouldn’t know what emergent behaviour should be. In fact there are strong hints that “fads” themselves are an emergent behaviour of human society. Also if you ever experienced a traffic jam without an accident or road block causing it you witnessed emergent phenomena that couldn’t be explained easily by the properties of the individual driver, the agent of the system in this case.

What I honestly think is that you fell for the most common misconception about systems theory. As in every field that experiences a hype you have researchers who try to “milk the cow” without caring about the whole picture or the proper theory. But if you judge by that you can discredit any topic that receives large interest e.g. also immunology.

In fact systems theory didn’t pop up in the end of your career. It was already around when you started it. Originating in works by Wiener, Üxeküll and my personal entry point Ludwig von Bertalanffy a theoretical biologist who wrote his “General Systems Theory” in the 1920’s - according to him. ;) Anyway it stuck around since the early 20th century and has never found great attention except in the social sciences thanks to Niklas Luhmann. This lack of attention in my eyes was due to a mainly mathematical approach to the field - which is necessary since most phenomena are counterintuitive and can only be depicted by sets of differential equations. Also a large contribution comes from physics where for quantum dynamics and statistical mechanics similar phenomena were described. To be clear: I’m not too eager about terminology. You might call it systems, networks, circuits or anything you like. Actually several fields e.g. ecology, chaos theory and information theory converged on a set of problems each discipline from it’s own perspective describing the puzzle that lies before us.

The basic point here is that systems theory is a mere descriptive approach to a set of phenomena that are reproducible in a manifold of networks. Even though the models are ghastly reductionist due to the lack of computing power and thus don’t contain the “basic features that are important” for the specialist - as Strogatz puts it - they can describe and even predict behaviour on a larger scale.

I could go on forever about the implication of this beautifully intricate science branch.

From my point of view systems theory is a quite powerful theory to tackle accessible phenomenology in living organisms as well as in other so called systems. Systems in a sense are - from a reductionist’s point of view - artificially localized environments that are viewed from a scale-level lacking the resolution for the constituent continuum. In this environment certain pseudo-discrete components interact. For these components usually termed agents or nodes certain properties of interaction exist. How reduced your view is depends on the aspect you want to resolve but only because of the vast complexity of the system which couldn’t be computed as a whole for now. But with the theory you can also describe the mentioned pseudo-discrete phenomenon at a lower scale level or one that emerges from the viewed level which could be essential for a larger scale. To make it accessible: In a cell a system of transcription factors is modelled with it’s key components and is probed for certain conditions in the classical input-output style. Assume we learn that for a certain variable of the output behaviour it acts as a “switch” - which is commonly termed a network motive. A competent description of those phenomena is given by Nick I Markevich (Journal of Cell Biology, 2004). In Biology such a switch is found e.g. in the bistable equilibrium of Bcl-6 and Blimp-1 that governs B-lymphocyte differentiation.

All of this can be described by a set of differential equations that depict the non-linear dynamics. Sadly maths can’t solve those complex sets of differential equations yet as I understand. But from the field of statistical mechanics we learned to model those reduced systems. Even though there are many excluded aspects these calculations need incredibly vast computing power.

This is the explanation why you only see subsets and localized approaches that fall short of your holistic pretence. Eventually and especially facilitated by the modularity of the models they may be forged into a global model - which would require computing power beyond imagination. ;)

Anyway systems theory probably won’t solve the dispute about an “atomistic” principle of our local environment. Also it can not explain what the driving force behind these phenomena is - even though Haken made a very nice point about phase transition in disequilibrium states. But what it actually can do and already does is point to the principles that demand further explanation.

All science is reductionist and has to be to the point where the hypothesis still describes all the documented phenomenology but doesn’t include non-essential aspects that blur the view on an underlying principle.

Regards,

Chris

I will reply to Chris in a while, meanwhile to Maria,

I think Chris has something specific in mind in terms of 'systems biology' relating to von Bertalanffy and his crowd. What I think you are arguing for is recognising that complex dynamics need to be described at different levels, using appropriate approximations and assumptions. That we all agree on.

What I am arguing for is the WHOLE picture, which a Bertalanffy-style systems approach does not do because it arbitrarily separates a 'system' from the whole. Even an 'organism' is an arbitrary system. And of course one wants to use mathematics, but we have been doing that for decades. Nothing new there. The problem comes with 'rubbish in - rubbish out'. And what worries me most about the systems label is that it does tend to imply just what you and I think it should not - that it will reveal some hidden magic ingredient. It may well reveal something unexpected, but not a magic ingredient - you have to programme that in!

Dear Chris,

That was a spirited response, so I will continue with a little more good advice that you will not like.

I am familiar with von Uexküll and Bertalanffy. What was new when I retired was the sudden interest in systems theory in biomedical research. Certainly, systems theory had been around for a long time but I think there was a reason for it not making an impact in the hard biomedical field until it became a buzzword. The valid parts of 'systems thinking' are not new. The other parts are, I think, either empty or just wrong. There are some serious conflations that need sifting out.

As I see it there are two uses of the term emergence that should not be confused. Chaos theory and the like describes how the dynamics of complex aggregates can show very unexpected patterns (such as fads), that as you say may be very difficult to ‘explain easily’ from individual causal relations. But that is quite different from saying that they cannot be reduced to those relations. Anything modeled on a computer is by definition reducible to individual steps. There is often a confusion here.

In contrast, in statistical thermodynamics (as you mention) and quantum field theory, aggregates are associated with new dynamic modes that **cannot** be reduced to the dynamic behaviour of the parts of the aggregate. They belong to new dynamic units, which claim their own share of energy. To model the latent heat of ice correctly you cannot just put in the rules for the molecules into the computer and hope to see strange patterns (like attractors) pop up, you have to put in extra rules for order-related modes. In my own view these modes have fascinating biological implications (i.e. I have been puzzling over emergence for ten years now and am fully aware of a range of common and uncommon misconceptions!) but for reasons that have absolutely nothing to do with Bertalanffy’s ‘systems with parts’.

Where I think there has been a confusion is in talking of ‘entropy’ in the context of information as if it were mathematically equivalent to thermodynamic entropy. The way energy is shared out in the universe really does seem to involve an odd top down component but this is not reflected in the way a computer computes, since all the events in logic gates are based on thermodynamically sanitized downhill processes.

So it is important not to conflate chaos theory issues with what happens in fundamental physics, I think. My guide in all this is Leibniz, who understood very clearly the difference between the dynamics of aggregates with parts and the dynamics of individual units. Von Uexküll I think made the mistake of confusing the aggregate system with parts with the dynamic subject relating to its ‘umwelt’. Leibniz also makes mistakes but, being a much better mathematician, I think he is on much more solid ground. Von Uexküll had gone backwards from 1714.

If we are just talking about creating mathematical models on computers that cope with complex aggregate dynamics than that is fine, but I see the tag of ‘systems theory’ as a dangerous promise for more than can be delivered. I have not yet ever come across something predicted by systems theory that is not just mathematical common sense. I don’t need extra jargon terms to understand a bistable equilibrium. And it seems in the end you admit that often the number crunching cannot be done. In my experience the interesting bits of science are working out the critical dynamic patterns based on fairly simple perturbation observations and then finding some acid test with another perturbation/intervention. You ‘clamp’ as many variables as you can and get a dose-response curve or some pharmacodynamics or whatever. If that is what you call systems biology then fine but I cannot see what it has to do with old Bertalanffy.

I would dispute the bald statement that all science is reductionist. That to me is a misconception spread about by philosophers. The purpose of science is not to reduce but to find the dynamic regularities in the changes in our experiences. Reduction is simply one of the tools for getting the grain right.

If you want to test biodynamics with differential equations I guess that can be fun. If you want to call it systems biology you will almost certainly get more papers published, so I am not telling you not to do that. What I might recommend though, is to find a research group that is interested in the biodynamic problem itself, rather than in ‘doing systems biology’. Such groups used to be the norm but biomedical science has been taken over by Vogue these days.

Perhaps the point I would come back to was that rather nicely described by Michael Neuberger, who worked out how antibody diversity works and sadly died recently in his prime. He said you need to keep gnawing at one bone. You may have to change your technology completely half way through (I certainly did) and forget differential equations if the problem you choose has to be solved with a clinical trial. Find a real disease-related problem to solve and use systemflapdoodlery when it is useful and non-systemflapdoodlery when its not!!

And finally, if all this stuff interests you, read the Monadology of 1714. It is still 100 years ahead of us now. That is where to find inspiration, with the man who invented the calculus.

Dear Jonathan,

This answer will take me some time to think about it and to find an answer myself.

But be sure that I don't dislike it. I'm rather very delighted and certainly didn't expect such good conversation when I asked my question. :)

Thank you

Dear Jonathan,

now that I have read your response properly I think we agree one quite many terms.

I never thought of the “systems” tag as a magical explanation of how things fall into place. In fact I feel comfortable with any approach from classical physiology like Claude Bernard practiced it, traditional Immunology as it was done from beginning to the late 20th century to modern model-supported bio-dynamics, quantitative physiology or any other approach to similar questions. As I said I’m not too eager about terminology. This has nothing to do with lazy thinking but with the very same way of thinking about scientific method as you suggest it. I will not try to squeeze my hypotheses into one “school of thought” – does this work in English?

To the notion of “gnawing” I would think that it can be a good and a very bad advice. If you take it literally you would try to tackle the same problem with certain persistence from different angles and when “it’s done” - definitely - you leave it. But you could also read into it that you try to strip the problem of every last bit of flesh not widening your scope for other more feasible pieces. In my eyes it can also be a very rewarding and practical approach to use a new tool on different problems that where left abandoned due to lack of a certain angle – I would also feel ok being a scavenger. To put it shortly: I’m not a big fan of allegory in written form. ;)

Anyway I’m not quite following on the differentiation between environmental interaction of the single unit and the dynamics of aggregates. For me this discrimination is as artificial as any other reduction in science and is just a question of which variables - as you put it - you “clamp”. But I’m neither a philosopher with background in natural philosophy nor do I have the mathematical endowment to formalize this problem. What I always saw as a shortcoming is my lack of classical philosophical education. I tried to learn a bit in parallel to my studies but this only reached as far as dilettantism for me. Nevertheless I will start looking into Leibniz’ work since reading the proceedings of great minds gives me quite a lot of pleasure.

To what extend the quantum scale interactions lye beyond the approach of classical thermodynamics I cannot grasp. Also in the share of energy you lost me. Could you explain to me what you think of when you differentiate “top-down” and “down-hill”?

Finally to stand up for my end of this conversation I would like to propose non-triviality for the implications of the two-sided approach of formalized mathematical modeling and “hard” biomedical research.

I understand that in the past the study of phenomenology brought substantial insight. From the mere capacity of computing power that is accessible now - and wasn’t back then when the reasoning about biomedical questions in dynamic terms was common - we are able to simulate larger aggregates with more complex dynamics. From this point of view biomedically unknown functionalities (often called network motives or regulatory loops in the new jargon) appear which are undoubtedly inherent to the system but not intuitive just by looking at the equations. It might be that something as simple as meta-stability or bi-stability is trivial but its effect on the organisms behavior is not. Those functionalities sometimes explain complex behavior better than the classical one-on-one approach that was “vogue” in the past years. Thus they may guide further investigation to a better understanding and help chose the right perturbation and the right acid test - especially for people like me that can’t look at the equations and automatically see the implicit behavior. ;)

In this context I would like to address your criticism on the statement that science HAS to be reductionist. I’m quite careful with such statements but from how I see it this holds true if not for a philosophical point of view then for a practical one. Even if one assumes that science tries to grasp the whole “nature” and dynamics of our localized environment the scope on it is limited – perhaps for now – by our capacity to perceive temporal and special resolution and to simultaneously scale complexity on different levels. This means that we cannot depict the objects of our studies in every dimension and against a control for all states. To be clear we have to dumb it down for us - not for the sake of the whole. As I understand this might be something we both agree on since I read this into your “get the grain right”.

If we do agree the next step for me is to take in account what I think we also agree on already. This is that a problem might require different approaches to approximate a “natural state” or our common denominator of experience that we try to encase for it.

Where I would disagree now is to just terming it “mathematical common sense” since this would imply that it is not worth looking into it. The mere application of newly developed tools for scientific probation to a new field has shown to be beneficial. Also from a scientific point of view I have a hard time to trivialize phenomena that are developing on a larger scale from the dynamics of the aggregates parts. This is for me the principal cause for differentiation into science branches in contrast to practicing one unifying science (e.g. physics).

For biomedical sciences the mechanics that seem dull to other science branches could bear a different angle on old problems. Terming it “systems biology” in particular is surely a nice trick to get attention – but to be honest I haven’t seen more spiritualists that try to see the “soul” of things in emergent behavior than in mirror neurons or cellular quantum effects.

Regarding your advice to look for a biodynamics group, this is exactly what I’m interested in but finding them is quite hard. Do you have any good advice where to find one if “such groups used to be the norm”? :)

Sorry that it took me so long to answer but putting this right in English is not too easy for me.

It’s a very delightful conversation.

Regards,

Chris

PS: Bertalanffy has huge flaws in his reasoning, no doubt. He was my first encounter not my hero.

Dear Chris,

I think it was worth thinking a bit more about the distinction between the dynamics of single units and aggregates. It is the basis of the solution to the black body radiation problem that tripped the whole of quantised physics. Single dynamic units may not be relevant to that many complex biological dynamic patterns but Goldstone theorem has raised the possibility that they may be much more relevant than expected. There is nothing arbitrary to this distinction - that is the whole point, it changes that maths of the dynamics. I would recommend reading something like Aitchison and Hey on gauge theories and a bit about Lie groups and field theories in general.

I guess that one reason for being underimpressed by systems biology is that in my home town everyone and his or her dog is doing it. It is not a lone unbeaten track but a motorway on bank holiday Monday. At University College London you more or less have to be doing systems biology to get spoken to. There is certainly masses going on here, particularly in neuroscience. And the best people, like Michael Hausser for instance, probably don't care whether their computer modelling is systems biology or not - they are just carrying on the tradition of Andrew Huxley, who wrote a paper on computer modelling of calcium dependent membrane potential oscillations in 1953! I have a reprint. It is very humbling. Good science is just good science.

I completely agree with Jonathan Edwards. We are not doing too well on medical research.

I will seize this opportunity to say: I read your post a while ago, Jonathan and I see what you are telling me. Sadly I always missed out to study the math that I would require to get a rudimentary understanding of the theories you hinted to me.

This set me off to actually catch up on the math - a thing I planned on doing for a long time since it always interested me. So I will eventually get back to this discussion when I feel comfortable with the basics. :)

The good news is that if you are really keen to get something done in science it is a pushover. Shooting fish in a barrel. If you believe you can do something different you can. And maths is underestimated - it has both beauty and usefulness. I wish I knew more.

see Prokop & Csukás Systems Biology volume by Springer

Cool! Thanks!

Educate yourself with Ayurveda and Yoga concepts, you will better appreciate the systems biology...This new term is covered well in there, ~5000 years ago... Particularly, read Charak Samhita text...

You might be interested in the work of Dr Branko Furst and the book he just published: The Heart and Circulation: An Integrative Model

http://www.amazon.com/The-Heart-Circulation-Integrative-Model/dp/144715276X