It is a commonplace observation that the more you learn about a subject, the more you come to realise how little you know. On that basis at least, this past year must be counted a resounding success: the extent of my ignorance has been greatly increased.

A main strength of the CoMPLEX MRes lies in exposing students to an inevitably tiny but suggestive fraction of both the breadth and depth of the biological sciences. There are so many disciplines, so many specialisations within those, such terrifying levels of detail in each that it would be sheer dullardry to remain undaunted.

The depths and breadths can, by their very nature, only be hinted at by experience of a few specific cases; which is why the twelve presentations and three corresponding projectlets form the essential core and highlight of the course. More is taught by them than all the rest put together, I think: a little of the research process; the slippery nature of 'the literature'; the crippling constraints of time; above all, just how much you don't know you don't know -- an important lesson, never easy to learn. I'd take issue with the free market competition for limited resources aspect of these projects, and even more with the specious and unrealistic insistence on novelty as their goal, but otherwise they are an admirable way to embrace and reveal some of the extraordinary range that biology encompasses.

The summer project is longer and somewhat more extensive, and there's perhaps more scope for actually achieving something beyond the mere short-term immersion in an unfamiliar topic, but it's a matter of degree only. While I learned a fair amount from mine, I don't think it was proportionate to the case studies.

Other aspects of the course are a bit of a mixed bag.

The early ITPL strand is dense and intellectually taxing, and all the better for it, like being beaten about the head with a stack of physics and biology textbooks. Its followup practical sessions are not always really practical, but they serve to locate the abstruse theory in the context of answering actual biological questions. This is important and valuable material, revealing many problems and potential solutions that I, at least, had never really considered before, and the case made for interdisciplinary science is very strong.

ITPL's mathematical counterpart ABMB seemed rather weaker, caught in an uneasy position of premature necessity, roughing out crucial concepts in a vacuum. I'm pretty sure I would have been lost if I hadn't already read the bulk of the Britton text, and pity any biologists who find themselves going through that unprepared.

Undergraduate lectures are, well, what you'd expect, albeit with a lot more mobile phones than in my day. Somewhat valuable, also rather infuriating.

The generic skills elements of the course are the least coherent. I found those covered by Graduate School courses mostly superfluous, with particular depths of fatuity being plumbed by the core statistics offerings. The main exception for me was the course on LaTeX and BibTeX, which was very useful indeed.

Given my background, computational tasks such as the programming exercise and website proved trivial; I would have been alarmed if it were otherwise.

Most potentially interesting of the generics are those most specific to academic practice: poster creation and referee reports. Both suffer from inevitable artificiality, given the lack of personal research expertise on which to base them. The poster creation was less impacted -- there was still something to write about and some incentive to try to do so interestingly, although in the absence of a substantive common background or any actual results it was difficult to focus on the matter in hand or determine what was worth including. The referee reports, on the other hand, were pretty much a travesty. To take on, as an outsider, papers that have already been reviewed by teams of experts and deemed publishable, and then lob a few ineffectual brickbats at them, seems a ludicrous and frustrating exercise.

And then, of course, there's this, its value hard to gauge. It is supposed to be reflective, so let's reflect. What have I learned here? Where are my strengths and weaknesses? How have I developed? What aims were achieved, what objectives missed?

As I said at the beginning, one of the main things I've learned is just how much remains to learn. This is unsurprising in biology, with its all-engulfing tide of details and contingencies. I expected that, though I never quite appreciated the scale of it; probably I still don't. But I hadn't quite accounted for the additional vast quantities of chemistry, physics, engineering and mathematics that would be required along the way and will be increasingly in future. Not that I was completely ignorant of any of these fields, but much more so than I recognised. Weaving the different fragments together into something useful is an ongoing process. It is dismaying how quickly knowledge that is not in regular use atrophies.

I am usually pretty good at grasping the essentials of a problem quickly, but often such an overview omits many important details that will return to complicate matters later. I tend to be very impatient when faced with new subjects, leaping in without proper preparation and then having to backtrack furiously. In an interdisciplinary context, where there are many aspects of a problem to attack, I prioritise those methods I am most familiar with or which are most palatable, rather than necessarily the ones that are really needed. As an obvious example, I will almost always go for simulation rather than analysis in modelling the workings of a system -- the former is easier and more intuitive and my mathematical analysis is weak. We might charitably call this pragmatism or just admit it's laziness; either way, it can be an issue -- depending on the question to be answered.

What that question will be remains to be seen. I seem to have a greater affinity for the experimental and empirical than I expected -- after 15 years in various virtual realities it is rewarding to do something concrete. I find myself drawn to PhD topics that are much more based in biology than modelling. Is that contrary to the spirit of CoMPLEX? Will it make good use of my existing skills or just waste everyone's time? Can a computer programmer survive in the laboratory environment?

As with so much else, I simply don't know -- but I can suggest an experiment to find out.