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New Years Resolution, DNA, GA and more

For the past day or so a little diagram for the transcription of DNA/RNA -> Amino acid bases has been going around my head. I think it’s a project to be done 🙂

So this is a personal challenge that currently is months/years outside of my current experience level, which is the point.

To do it, I’ve got to understand sufficient of several fields at once to make the thing meaningful.

The broad outlines start with the DNA transcriber. Using the simplest elements of F#, the first stage will be construct a tree data structure suitable for hunting down triplets of bases.

So we have cytosine, guanine, adenine and thymine that are used to code for 20 or so amino acids and stop/start points. This is a great candidate for a computation expression as the project will need to be fully parallel.

The full project will require both parallel and agent based models, make use of online data sources and will have the ultimate aim of translating arbitrary lengths of DNA into proteins.

As it stands, the basic components lend themselves well to being very parallel.

Following this project will be two further exploratory F# pieces. The first will be basic neural networking, the second will be about gene expression programming. The latter will be a deeper experiment to see how plausible generating neural networks by GEA/GA techniques will be.

Code generation has always been a minor interest to me, so this project will stretch this notion to the limit. Generate neural networks efficiently from evolved GEA code? I may find this is a naïve view of the field, after all I’m very much a novice at coding.

That just makes it more interesting.

Eventually the projects may join up but that’s a whole other thing.

That’s the New Year’s Resolution – dig into some serious AI work as described. This will ensure that the languages I need to use will be pushed to their limits.

A fuller description may be added to this post later!