Bioinformatics

[Abu Naser]

Hello Everyone,

I have just installed opencog on Ubuntu. I am a biologist and wish to use opencog  for solving biological problems. I have been wondering whether there is any tutorial related to Bioinformatics. Please let me know.

With best regards,

Abu 

[Ivan V.]

Hi Mr. Naser,

I'm just a lurker here, but I was wondering, has there been any improvements in protein synthesis recently? I read there was problems in forming big chains of amino-acids. Also, how are proteins related to medicaments production, if I may ask?

Thank You for your patience, and forgive me if I ask too much,

Ivan V.

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[Abu Naser]

Hello Ivan,

Thank you for your email.  It is more of a problem of protein folding. It is OK to synthesise short peptides because of their simpler structural conformation. But, when the protein gets bigger, it may become aggregated with other fellow protein molecules. As a result,  site of adding new amino acids may be hidden due to the aggregation or misfolding . 

Answer of your second question is:yes, proteins can be used as medicine. Diabetic patients use insulin which is a protein, for controlling blood sugar level.  In future, synthetic drugs will be replaced by protein which has less or no side effect. 

Hope this answer your questions.

With best,

Abu

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[Ivan V.]

Mr. Abu Naser,

Thank You very much for the response, I'll check those keywords (aggregation and misfolding) more thoroughly between web research papers when I get more time.

As for OpenCog, I'm generally interested in used technology (though I'm far away from being an expert), but I'm not aware of a use in bioinformatics other than using OpenCog SAT solver to solve traveling salesman problem (TSP), which has something to do with optimal energy distribution in folding protein prediction. If TSP is an area of Your interest, hopefully I can help with translating TSP to SAT solving supported by OpenCog. But if Your interests reach to other fields, I sincerely hope someone more informed on this mail list can help you.

Again, I'm just a lurker here, but I'll try to do my best to learn and share available knowledge.

Ivan V.

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[Abu Naser]

Hi Ivan,

Yes, protein folding is one of my interests. I am very new to opencog and any help will be very useful. Please let me know how to go about TSP with opencog. 

With regards,

Abu

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[Linas Vepstas]

Hi,

Opencog has many parts to it.There is an agi-bio part for bioinformatics but it seems slim, and I think the main part of that system is somewhere else. I'm hoping Mike Duncan can respond in more detail.

--linas

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[Abu Naser]

Hi Linas,

Thank for the update. I will be waiting for Mike's response. 

With regards,

Abu

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[Ivan V.]

Hi, Abu

The task about travelling salesman problem used in protein folding is not such a trivial task.

These two papers I have in mind that relate to computing protein folding, regardless to OpenCog:

• A Travelling Salesman Approach to Protein Conformation - 44daca495f4b0a9d9affbe68c6926cc3a751.pdf

• A traveling salesman approach for predicting protein functions

There were some understatements to me the last time i read those, but I hope you could resolve that, as a biologist and chemistry expert. As you will see, there are some trade offs between accuracy and speed, and I have to warn you, things get very complicated if you opt to completely simulate molecular physics. I think you would need a senior programmer for implementing this part. Also, here is an eye catchy free application link if you are about to visualize proteins (a bit complicated input, but if you manage to crunch the first papers, this would be the less painful part).

Regardless to protein folding, I believe openCog has built in SAT solver among its tools (But you'll have to ask someone more expert on this matter). Once you master OpenCog SAT solving, the problem of TSP can be reduced to SAT following this paper:

• 2014ICRA_SAT-TSP(submitted).pdf

A bit of logic understanding is needed, but if OpenCog has an ability to solve SAT problems, I believe that previous paper is a way to translate TSP to SAT. Once you have a logic conglomerate representing TSP, OpenCog should be able to provide you result of the shortest path (meaning a conformation with lowest energy distribution among amino acids).

I'm sorry not to have the entire problem already programmed in just one application / OpenCog tool. I was planning to code some of it in some future point, but my research bent me over so many sides (mostly in general knowledge representation area), I didn't get chance to come near to coding it. I know all these guidelines pose a much work, but this is all I have for now.

Oh, you might be interested in these projects, if you want to check the competition that doesn't ever sleep (thankfully):

• Folding@home – Fighting disease with a world wide distributed super computer.
• Solve Puzzles for Science | Foldit
• Rosetta@home

Finally, if you decide to grapple with a task of  this scale, you might want to consult with some of OpenCog creators (in this mailing list, very friendly and openminded people, I have to attribute), is the entire OpenCog with its SAT solver an overkill, just to have the TSP part solved. But you never know, artificial intelligence is such an inspiring area, some idea may pop up that would completely boost up the protein research field.

Let me know if there are any questions I may answer.

Ivan V.

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[Ben Goertzel]

There are two pieces to what we've been doing w/ OpenCog for bioinformatics

1) supervised classification of genomics datasets (e.g. SNPs, gene
expression) using MOSES

2) integration of various ontologies into the Atomspace, import of
MOSES classification models into the Atomspace, and use of PLN
reasoning (currently on a pretty ad hoc, human guided basis) to do
inference based on this combined data

There are publications on both of these things, though I don't have
time to dig up the URL right now, and Mike can point you to the
code...

ben

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--

Ben Goertzel, PhD
http://goertzel.org

"Listen: This world is the lunatic's sphere, / Don't always agree
it's real. / Even with my feet upon it / And the postman knowing my
door / My address is somewhere else." -- Hafiz

[Abu Naser]

Hi Ivan,

Thank your for providing the details and the interesting papers. It will read the papers and try to understand why TSP is choice of the algorithm. 

Thanking you again,

Abu 

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[Abu Naser]

Hi Ben,

Thank your for responding my queries. I will try to find the papers and guessing you are one of the authors of the papers. It would be very useful for me if I could get Bioinfromatics related toy examples to play around, which will help me to get to know the opencog code. Hope Mike will point me to one of those example code. 

With kind regards,

Abu

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[Ben Goertzel]

The MOSES-for-supervised-learning stuff is a bit specialized, and
doesn't use the main OpenCog codebase, MOSES is a standalone system

However Nil wrote code for importing learned MOSES models into the
Atomspace, and once you've done that you can play with PLN inference
or other tools for combining MOSES models w/ other knowledge

A great project for a brave soul right now would be

-- run MOSES on some categorial SNP or gene expression data to get a
big diverse model ensemble

-- load these models into Atomspace

-- use Nil's new Pattern Miner to find surprising patterns among the
MOSES models

Then one could bring PLN into the story to integrate, say, Gene
Ontology into the surprisingness assessment...

ben

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[Linas Vepstas]

Abu,

And just to be clear -- when Ben says "a brave soul", what he means  is that it is very much a roll-up-your-sleeves-and-do-it-yourself project.  There are no easy-to-use push-button GUI's for this: you would have to read about and understand a lot of non-bioinformatics systems, and then figure out, with very little supervision or guidance, how to hook them together. 

(Totally off-topic -- there was an effort to have Jupyter notebooks for opencog -- what ever happened to that? The point was that a Jupyter notebook would be a way of show-casing some kind of data-flow that people could actually use ...  anyone know anything about this?)

--linas

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[Ben Goertzel]

the Jupyter notebooks exist ;)

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[Abu Naser]

Thank you Ben for your suggestions. I have installed AS-MOSES (the version works on atomspace). However, I had to make following changes during installation: 

3) In bscores.cc, I had to insert #include <set> 

2) in build_knobs.cc, at line 237, I had to change  distance(from, to)  to  std::distance(from, to)

1) In table.cc, at line 259, I had to change return distance(labels.begin(), pos) to return std::distance(labels.begin(), pos)

Hope these changes will not raise other issues down the line. 

Thank you again Ben, I have now something to play around with.

With regards,

Abu  

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[Abu Naser]

Thank Linas. I will try my best to achieve something with very little supervision. 

With best regards,

Abu

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[Linas Vepstas]

Hi Abu,

The changes you propose are completely reasonable.

If you really want to participate in the formal coding process, you should create a github pull request with these changes in them. .. or I could make them for you. Let me know.

A word of caution about as-moses: it may have some unintended performance profile. The original moses got very optimized to run fast; but the atomspace is an in RAM graph database which means it has indexes which means index insertion has a real cost.  Exactly how the two get stapled together is an open work item.

-----

BTW -- if Nil or Kasim or other as-moses people are listening -- perhaps it makes more sense to have make combo-trees be Value-trees during the computation -- Values are NOT indexed, they're meant to be fast, provide fast access.  Then after computation is done, the best trees, the results can be copied into the atomspace.

Another possibility might be to have either a tree-Value, (i.e. a new kind of Value that is a combo-tree) or something that converts LinkValues into combo trees (or vice-versa).   All of this might alleviate issues related to performance and mapping & etc. I don't know where you guys have these design discussions, but if any of this sounds appealing, let me know; I can clarify details.

--linas

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[Abu Naser]

Hi Linas,

It is probably easier for your to change for me. 

Thanks for letting me know the performance limitation of as-moses. 

With regards.

Abu

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[Linas Vepstas]

On Sat, Mar 2, 2019 at 2:21 PM Abu Naser <nase...@gmail.com> wrote:

Hi Linas,

It is probably easier for your to change for me. 

OK.
 

Thanks for letting me know the performance limitation of as-moses. 

There might not be one. I'm just not sure. OpenCog is all about "how do you represent knowledge?" and "how do you move it around frictionlessly between different processing systems?" A meta-goal is to avoid brittle stove-pipe constructions, AKA spaghetti-code of data moving from here to there.

Moses does a very specific kind of machine learning. The way it represents data is "almost like" how the atomspace does. The AtomSpace provides a foundation for reasoning and inference and other kinds of knowledge processing; (e.g. adding appropriate neural-net support is a work-in-progress).  So far, we don't have seamless, friction-free access between different algorithms, and the different kinds of data people use. But we're making small steps.  In the meanwhile, you are welcome to create stove-pipe constructions that are just good enough for what you need to do...

-- Linas

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[Ben Goertzel]

AS-MOSES is a work in progress, and should only be used at this point
by folks who want to help develop it...

Development is being led by Kasim in our Addis Ababa office, guided by
Nil in Bulgaria (one of our long time OpenCog code and theory
gurus...)

For practical bio-AI work right now, you should use the good old
standalone MOSES code...

ben

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[Nil Geisweiller]

Hi,

On 3/2/19 8:32 PM, Linas Vepstas wrote:
> A word of caution about as-moses: it may have some unintended
> performance profile. The original moses got very optimized to run fast;
> but the atomspace is an in RAM graph database which means it has indexes
> which means index insertion has a real cost. Exactly how the two get
> stapled together is an open work item.

For now as-moses is fully backward compatible with moses. That is it
should behave identically as long as you don't use new options like
--atomspace-port, etc.

However if stability is a primary concern it's better to use moses,
just to be cautious.

> -----
> BTW -- if Nil or Kasim or other as-moses people are listening -- perhaps
> it makes more sense to have make combo-trees be Value-trees during the
> computation -- Values are NOT indexed, they're meant to be fast, provide
> fast access. Then after computation is done, the best trees, the
> results can be copied into the atomspace.

as-combo actually has its own interpreter, that indeed outputs
values. It is planned to eventually merge this interpreter to
atomspace's but for now we feel it's easier if they are separated,
especially since it is still highly experimental at this stage.

Nil

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> >> --
> >> Ben Goertzel, PhD
> >> http://goertzel.org
> >>
> >> "Listen: This world is the lunatic's sphere, / Don't
> always agree
> >> it's real. / Even with my feet upon it / And the postman
> knowing my
> >> door / My address is somewhere else." -- Hafiz
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>
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[Linas Vepstas]

On Tue, Mar 5, 2019 at 2:14 AM Nil Geisweiller <ngei...@googlemail.com> wrote:

> -----
> BTW -- if Nil or Kasim or other as-moses people are listening -- perhaps
> it makes more sense to have make combo-trees be Value-trees during the
> computation -- Values are NOT indexed, they're meant to be fast, provide
> fast access.  Then after computation is done, the best trees, the
> results can be copied into the atomspace.

as-combo actually has its own interpreter, that indeed outputs
values. It is planned to eventually merge this interpreter to
atomspace's but for now we feel it's easier if they are separated,
especially since it is still highly experimental at this stage.

OK, yes.

[Michael Duncan]

hi abu, sorry for the delay in responding.  most current work on opencog based bioinformatics is happening in the context of singularitynet services (see here).  much of the current agi-bio repo is outdated but i'm slowly getting it up to speed.  the biosciences module does need to be built and installed with the opencog stack to provide the custom atomtypes "GeneNode" and "MoleculeNode".  knowledge-import/SNET has the scripts that generate the atomspace used by the service (GO, reactome, and bioGRID) plus the small molecule pathway database which has a non-commercial license.  this repo has the scheme code used by the service for you to experiment with, while the service (which can be built to run in a local docker container) includes a browser based network visualization that is importable into cytoscape.

please post specific code questions as issues in the appropriate github repo or more general questions here in the google groups so we can most effectively respond to your questions and suggestions.

looking forward to your feedback!

mike

[Abu Naser]

Hi Mike,

Thank you very much the relevant link. I will have a look and let you know if I have any questions.

With best regards,

Abu

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