Category: Mathematical Modelling

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Mathematics and Biology II – Practical considerations

Last month I wrote about the historical world-views of mathematicians and biologists. These articles are part of a planned four part series, in an attempt to first understand and then improve the working relationship between these two key scientific disciplines. This is all a work in progress, so at the end, I will try to take the key learnings from each of the articles and distill them into a single composed article.

This month, I want to discuss the practical considerations why mathematics and biology still don’t work so well together.

Continue reading “Mathematics and Biology II – Practical considerations”

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Preprint Announcement – Roving and Unsupervised Bias

This week has been a really big week for me. I finally uploaded the first paper from my time as a postdoc to a pre-print server, called the bioRxiv. I did three major pieces of work, during my time as a postdoc, this is the first and potentially the only, of these, to see the light of day.

I am not usually so tardy in getting work out. I published two papers from my PhD – a record for working with my PhD supervisor – the work for both of which was finished before I ever defended the thesis. My postdoc work was a bit special, I ended up directly proving that the previous work of my collaborators was mistaken. Continue reading “Preprint Announcement – Roving and Unsupervised Bias”

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AI in Healthcare II

Continued from Part I

Part I of this article appeared last week. In it I introduced the topic of statistical vs biophysical approaches to biological applications. I discussed the huge power of statistical approaches in image analysis and providing decision support services to doctors. I then discussed the 5 major limitations of data-driven approaches when they are applied to biological problems.

I will now continue by looking at biophysical approaches, their pros and cons, and finishing up with a brief introduction to hybrids which attempt to combine these two methods. Continue reading “AI in Healthcare II”

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AI in Healthcare I

Motivation

I live in Berlin, which is fast becoming the tech hub of Europe. Over the past two years we have seen a massive up-tick in the number of healthcare oriented startups, which are receiving funding on the basis of their use of Artificial Intelligence (AI). As somebody who knows a bit about the underlying technical and application problems of AI, what I see has made me very uneasy.

As a result of some personal conversations I was invited to give a Keynote address to the Digital Health Forum of the Berlin Institute of Health in March. This is a big deal because the BIH is a joint venture between Europe’s biggest teaching hospital, Charité Berlin, and one of Germany’s foremost centres for biological research, the Max-Delbrueck-Center, Berlin. The talk was extremely well received, so I have now given a public version at PyData Berlin 2018 which will be published on their YouTube channel in the coming weeks. (Update: the video is available here). In the meantime, I have written the discussion up as an article in two parts: part I is below and part II is available here. Continue reading “AI in Healthcare I”

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Influences: Steve Grand

One of my favourite games from my childhood was Creatures. I still remember buying it in a large cardboard box and finding the small 3.5″ floppy disk which nestled inside. This was my first experience of two new technologies: virtual worlds and alife.

The game featured little furry creatures (they reminded me of Ewoks, from Star Wars) called Norns. These creatures hatch from eggs. The installation disk, as far as I recall, hosts the simulation environment and the encoding for your first Norn egg. The basic idea was that your Norn would hatch and was supposed to have certain behavioural traits which would make it unique compared to those of your friends. The baby Norn would then wander around the virtual world (a side-on platform type world, with very rich background graphics) and try to interact with a number of the items littering the environment. Continue reading “Influences: Steve Grand”

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Mathematics and Biology

Having worked in two traditionally distinct fields, both separately and combining the methods of both, I have more than a few thoughts on what separates these disciplines and how this can be quite detrimental.

As I see it there are two core differences between a mathematical world-view and a biological one: the first is in how knowledge is acquired; and the other is the difference between a dynamical world-view and a static one. What may surprise you is which one is static and which one is dynamic!

Knowledge acquisition

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Simmunology is….

my first real startup. That is, the first time that I’ve actually incorporated a company. Simmunology Limited exists since last week.

The path to incorporation has been an interesting and sometimes terrifying ride. (Aside: understatement will typically be an element of my style, this should be borne in mind when reading my prose.)  I finished up a postdoc in computational neuroscience at TU Berlin last December (2017). Since then I have been trying to establish a place for myself in the world in which I get to use my, not inconsiderable, experience to choose my own directions.

I left academia with a strong feeling that not-all is right in the academic world. In fact it is very, very wrong. But more importantly, I don’t think that the kind of cross-disciplinary talents which I bring to the table will ever be fully utilised in that sector, at least not as it exists today.

I came up with two pet projects which I thought I could work on to bring an impact to the world. The first,  Continue reading “Simmunology is….”