The replicant

This is a molecular machine designed as a patch which would upgrade biological ribosomes. Once it attaches to a ribosome, it behaves in an almost similar ways as the synthetic ribosome Ribo-T, recently announced in  Nature 524,119–124(06 August 2015) doi:10.1038/nature14862  [1].  It thus enables an orthogonal genetic system, (i.e., citing from the mentioned Nature letter “genetic systems that could be evolved for novel functions without interfering with native translation”).

The novel function is designed for is more ambitious than specialized new proteins synthesis. It is, instead, a  two-ways translation device, between real chemistry and programmable artificial chemistry.

It behaves like a bootstrapper in computing. It is itself simulated in chemlambda, an artificial chemistry which was recently proposed as a means towards molecular computers [2].  The animation shows one of the first successful simulations.

 

spiral_boole_construct2_orig_in

 

With this molecular device in place, we can program living matter by using living cells themselves, instead of using, for example, complex, big 3D DNA printers like the ones developed by Craig Venter.

The only missing step, until recently, was the discovery of the basic translation of the building blocks of chemlambda into real chemistry.

I am very happy to make public a breakthrough result by Dr. Eldon Tyrell/Rosen, a genius who went out of academia some years ago and pursued a private career. It appears that he got interested early in this mix of lambda calculus, geometry and chemistry and he arrived to reproduce with real chemical ingredients two of the chemlambda graph rewrites: the beta rewrite and one of the DIST rewrites.

He tells me in a message  that he is working on prototypes of replicants already.

He suggested the name “replicant” instead of a synthetic ribosome because a replicant, according to him, is a device which replicates a computer program (in chemlambda molecular form) into a form compatible with the cellular DNA machine, and conversely, it may convert certain (RNA) strands into chemlambda molecules, i.e. back into  synthetic form corresponding to a computer program.

[1] Protein synthesis by ribosomes with tethered subunits,  C. Orelle, E. D. Carlson, T. Szal,  T. Florin,  M. C. Jewett, A. S. Mankin
http://www.nature.com/nature/journal/v524/n7563/full/nature14862.html

[2] Molecular computers, M Buliga
http://chorasimilarity.github.io/chemlambda-gui/dynamic/molecular.html

[This post is a reply to +Yonatan Zunger  post

where he shows that the INCEPT DATE of the Blade Runner replicant Roy Batty appears to be 8 Jan, 2016.
So here is a replicant, in the inception phase :) ]

PS: The post appeared as well in the chemlambda collection:

Mind tricks

One of my goals is to uncover the geometry in the computations. Most people see visualizations as cute, but unnecessary  additions.  Maybe with some very limited pedagogical value. Not the real thing.

The really funny thing is that, on average, people tend to take too seriously a visualization. Some animations trigger all sorts of reflexes which mislead the viewers into seeing too much.

The animal is there, skin deep. Eye deep.

 

A recent example of using visualizations for research  is how I arrived to build a kinesin like molecule by looking at the Y combinator and permutations.

This is a phenomenon which appeared previously in the artificial chemistry chemlambda. Recall how the analysis of the predecessor lambda term,  led to the introduction of chemlambda quines?

Same here.

Chemical computation is a sort of combinatorial movement, if this makes any sense. Lambda calculus or other means towards rigorous notions of computation clash with the reality: chemical computations, in living organisms, say, are horrendously complex movements of atoms and rearrangements of bonds. There is no input, nor output written with numbers. That’s all there is: movements and rearrangements.

Chemlambda marks some points by showing how to take lambda calculus as inspiration, then how we can see some interesting, movements and rearrangements related thing in the behaviour of the lambda term, then how we can exploit this for designing some pure (artificial) chemistry tour de force of unsupervised cascades of reactions which achieve some goal. Unsupervised, random!

OK, so here is a kinesin built in chemlambda. I see it works and I want to play a bit with it and also to show it.

The following animation has stirred some attention on 4chan, and less attention on google+, of course compared with others from the amazing chemlambda collection :)

kinesinX2

It makes sense, you can relate with the two kinesins which meet together, they salute each other, then they go their way. One of them detaches from the microtubule (a particularly designed one, which allows kinesins to go in both directions, hm, because I can). The other roams a bit, quick, concerned.

It’s the result of randomness, but it conveys the right info, without introducing too much unrelated stuff.

The next one is about 4 kinesins on a circular microtubule.

kinesin_round

This is a bit to much. They look like suspiciously quick moving spiders… Not something to relate to.

But still, there is no false suggestion in it.

People love more the following one, where there are 8 kinesins.

kinesin_round_2

It looks like a creature which tries to feel the boundary of the frame. Cool, but misleading, because:

  • the coordinates of nodes of the graph in this representation are irrelevant
  • the boundary of the frame is not part of the model, it means nothing for the molecule.

In chemlambda there is a choice made: chemistry is separated from physics. The chemistry (so to say) part, i.e. the graph rewrites and the algorithm of application, is independent from the d3.js rendering of the evolution of the graph.

But people love to see graphs in space, they love to see boundaries and they relate with things which have an appearance of life (or some meaning).

That’s how we are made, no problem, but it plays mind tricks on us.

A clever influencer would play these tricks in favor of the model…

The viewers, if asked to support the research, would be less willing to do it after seeing the fast moving spiders…

I find this very entertaining!

For the record, here is another direction of thinking, inspired by the same permutations which led me to kinesins.

Symmetries of conflicts

Can you find hidden symmetries in the conflict diagrams of chemlambda? There are now two pages to play with, if you want to help (and have some fun maybe): [1] and [2].

What’s that? Each rewrite/chemical reaction in the artificial chemistry chemlambda has a pattern which triggers the reaction, and then the pattern is replaced by another one by an invisible “enzyme”. Now, the pattern which triggers the reaction is called LP (left pattern).

[3] is the list of rewrites, to be clear!

In chemlambda all LP consist of a pair of nodes, with some ports connected by an external bond (the internal bonds being those which connect the node with its ports). It happens that there exist two pairs of nodes, say LP1 and LP2, which overlap: they have a node in common.

In such a case it means that there are two possible reaction which may happen, but which one will happen? They can’t both happen at the same time, because the patterns overlap and so the results would be incompatible. That’s a conflict.

 

conflict_wo_T
In a conflict diagram, as the one which is represented here, you see the nodes of chemlambda which enter in he composition of possible LPs, here you see the FI and L (red, but with different colors and radii of ports) FO and A (green, with different ports etc) and FOE (yellow). For each possible LP (i.e. for each rewrite which is triggered by an LP) there is a bond (thin white line) which connects the relevant ports of the pair of nodes of the LP.

What we get is not a chemlambda molecule, because there may be many bonds which connect a port with others. Here for example you see the FOE port middle_in which is connected with 4 other ports, indeed, this is because we find FOE in all DIST rewrites L-FOE, A-FOE, FO-FOE and in the rewrite FI-FOE.

But such a diagram allows to quickly read the possible conflicts.

Now, to symmetries: the conflict diagram shows the role of the nodes not absolutely, but as they enter in relative configurations. Therefore any symmetry of the nodes, ports and bonds (i.e. of rewrites) tells us something about chemlambda which is not obvious in isolation.

For example, I used the conflicts diagram [2] to group the nodes and bonds in order to show that in a sense the rewrites which involve L (the lambda abstraction) and the FI (the fanin node) are “the same”. THere are hints towards an overall symmetry of ports and rewrites in the diagram.

You can find others, in [2] or [3] which has also the node T (here the color of the node is red) and the PRUNING rewrites added.

For this you can move the nodes and fix their position by click and drag, or release them by double click.

Tell me if something seems weird, hidden there.

[1] http://chorasimilarity.github.io/chemlambda-gui/dynamic/conflicts_wo_T.html

[2] http://chorasimilarity.github.io/chemlambda-gui/dynamic/conflicts.html

[3] http://chorasimilarity.github.io/chemlambda-gui/dynamic/moves.html

Do triangulations of oriented surfaces compute?

In a precise sense, which I shall explain, they do. But the way they do it is hidden behind the fact that the rewrites seem non local.

  1. They compute, because ribbon graphs with colored, trivalent nodes and directed edges do compute, via the encoding of untyped lambda terms into this family of graphs, provided by chemlambda. Indeed, a chemlambda molecule is a ribbon graph with these properties. If you want to encode a lambda term into chemlambda then there is a simple procedure: start from the lambda term on a form which eliminates the need of any alpha conversion. Then build the syntactic tree and replace the nodes by A nodes for application and L nodes for lambda abstraction (don’t forget that L nodes have one in and 2 out ports, differently from the syntactic tree node for lambda abstraction). Then eliminate the variables which are at the leaves by grafting trees of FO (green fanout) nodes from the lambda abstraction node to the places where the variables occur, or by grafting T (terminal) nodes to the lambda node which issues a variable which does not occur later, or simply by just erasing the variable label for those variables which are not issued from an abstraction. That’s it, you get a ribbon graph which is open (it has at least the root half-edge and maybe the half-edges for the variables which don’t come from an abstraction), but then you may add FRIN (free in) and FROUT (free out) nodes and think about them as tadpoles and you get a trivalent ribbon graph. The dual of this graph is (equivalent to) a triangulated, oriented surface, which has faces colored (corresponding to the nodes of the graph), directed edges, such that there are no faces with the 3 edges directed in a cyclic way.
  2. How they compute? Chemlambda uses a set of graph rewrites which has some classic ones, like the Wadsworth-Lamping graphical version of the beta move, but it has two types of fanouts (FO and FOE), one FANIN, and different than usual rules for distributivity. Look at the moves page to see them. All these rewrites are local, in the sense that there is a small number, fixed a priori, which is an upper bound for the number of nodes and edges which enter (in any way) into the graph rewrite (as a condition or as the left pattern, or as the right pattern). The algorithm of application of the rewrites is a very important piece which is needed to make a model of computation. The algorithm is very simple, it can be deterministic or random, and consists, in the deterministic case, into the application of as many rewrites as possible, with a priority for the distributivity moves in case of conflict, and in the random case, it’s just random application of rewrites.

Here is an example, where I play with the reduction of false omega id in chemlambda

  1. Now let’s pass to the duals, the triangulated surfaces. The nodes of the triangulated surface correspond to the faces of the ribbon graph. Or the faces of the ribbon graph are global notions, because they are the orbits of a permutation. After one of the rewrites, the faces (of the ribbon graph) change in a way which has to be non local, because one has to compute again the orbits of the permutation for the new graph, and there is no upper bound on the number of half-edges which have to be visited for doing that.
  2. So triangulated, oriented surfaces do compute, but the rewrites and the algorithm of application are hidden behind this duality. They are non-local for triangulated surfaces, but local for ribbon graphs.
  3. Finally, a word of attention: these surfaces do compute not by being arrows in a category. They don’t compute in this usual, say Turaev kind of way. They compute by (the duals of) the rewrites, there is nothing else than triangulated surfaces, colored by 3 colors (red, green, yellow), there is no decoration which actually does the computation by substitution and evaluation. I don’t know why, but this seems very hard to understand by many. Really, these surfaces compute by rewrites on the triangulations, not by anything else.

ADDED: If you look at the tadpoles as pinches, then make the easy effort to see what  the SKI formalism looks like, you’ll see funny things. The I combinator is the sphere with one pinch (the plane), the K combinator is the sphere with two pinches (cylinder) and the S combinator is the torus with one pinch. But what is SKK=I? What is KAB=A? What you see in the dual (i.e in the triangulation) It depends globally on the whole term, so these reductions do not appear to be the same topological manipulations in different contexts.

Res vs objectus

Objects are evidence. If reality is the territory, then objects are on the map.  Objective reality is to be compared with bureaucracy.
If reality is not objective, then how is it? Real, of course. Evidence is a map  of the real. Passive, done already, laid further in the court, ready to be used in the argumentation.
Who makes the map has the power over reality, in the same way as bureaucrats have the power over the people.
The confusion  between res and objectus has very concrete effects in our society.
We communicate on the net via evidence. The technical solutions are these, issued from historical reasons, like wars and analytic philosophy.
We are discontent about the lack of privacy of evidence.
Objects as evidence of happiness are not the same as happiness. We are discontent because objects are not enough, when we are told that they should be.
In this setting, who controls the map making mechanism, who controls the data processing, has the power.
Ultimate bureaucracy presented as the unique way. As the only real way. A lie.

After the IoT comes Gaia

They say that sneakernet does not scale. If you think about the last product of Amazon, the AWS Import/Export Snowball, this clumsy suitcase contains less than a grain of pollen.

Reason from these arguments:

  • the Internet of Things is an extension of the internet, where lots of objects in the real world will start to talk and to produce heaps of data
  • so there is a need for a sneakernet solution in order to move these data around,  because the data are only passive evidence and they need to be processed,
  • compared though with biology, this quantity of data is tiny
  • and moreover biology does not function via signal transmission, it functions via signal transduction, a form of sneakernet,

you’ll get to the unavoidable conclusion that the IoT is only a small step towards a global network which works with chemical like interactions, transports data (which are active themselves) via signal transduction and it extends the real world biology.

After the IoT comes Gaia. A technological version, to be clear.

Some time in the future, but not yet when we could say that the Gaia extension appeared, there will still be a mixture of old ways IoT and new ways biological like. Maybe there will be updates, say of the informational/immunity  OS, delivered via anycasts issued from  tree like antennas, which produce pollen particle. The “user” (what an ugly reductionistic name) breaths them and the update start to work.

The next scene may be one which describes what happens if somebody find out that some antennas produce faulty grains. Maybe some users have been alerted by their (future versions of) smartwatches that they inhaled a possible terminal vector.

The faulty updates have to be identified, tracked (chemically, in real world) and anihilated.

The users send a notification via the old internet that something is wrong and somewhere, perhaps on the other side of the planet, a mechanical turk identifies the problem, runs some simulations of the real chemistry with his artificial chemistry based system.

His screen may show something like this:

mask_of_anarchy_new_short

Once a solution is identified, the artificial chemistry solution is sent to a Venter printer close to the location of the faulty antenna and turned real. In a matter of hours the problem is solved, before the affected users metabolisms go crazy.

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