The end of Bioinformatics?!

The End of Bioinformatics?!

I read with some interest the announcement of the Wolfram Alpha.  Wolfram intends to be the end all and be all data mining systems and some say, makes bioinformatics obsolete.

Wolfram’s basis is a formal Mathematica representation.  It’s inference engine is a large number of hand-written scripts that access data that has been accumulated and curated.  The developers stress that the system is not Artificial Intelligence and is not aiming to be.  For instance,  a sample query,

“List all human genes with significant evidence of positive selection since the human-chimpanzee common ancestor, where either the GO category or OMIM entry includes ‘muscle’”

could currently be executed with SQL, provided the underlying data is there. 

Wolfram won’t replace bioinformatics.  What it will do is make it easier for a neophyte to get answers to his or her questions because they can be asked in a simpler format.

 I would guess Wolfram uses one or more these scripts to address a specific data set in conjunction with a natural language parser.  These scripts would move this data to a common model that could then be modeled on a web page.

But why not AI?  Why not replace all those “hand-written” scripts, etc.  with a real inference engine.

I rode the first AI wave.  I was a member of the first of 25 engineers selected to be a part of the McAir AI Initiative at McDonnell Aircraft Company.  (”There is AI in McAir”).  In all, 100 engineers were chosen from engineering departments to attend courses leading to a Certificate in Artificial Intelligence from Washington University in St. Louis.

One of the neat things about the course was the purchase of at least 30 workstations (maybe as many as 60) for a young company called Sun that were loaned to Washington University for the duration of the course.  Afterwards, we got a few Symbolics machines for our CADD project. 

Other than Lisp and Prolog, the software we used was called KEE (Knowledge Engineering Environment).  Also, there was a DEC (Digital Equipment Company) language called OPS5.

The course was quite fast-paced but very extensive.  We had the best AI consultants available at the time lecture and give assignments in epistemology, interviewing techniques, and so on. I had a whole stack of books.

The only problem was that no money was budgeted (or so I was told) for AI development for the departments for the engineers when they returned from the course eager to AI everything.  A lot of people left.

Anyway, my group of three developed a “Battle Damage Repair” system that basically “patched up” the composite wing skins of combat aircraft.   Given the size and location of the damage, the system would certify whether the aircraft would be able to return to combat, and would output the size and substance of the patch if the damage wasn’t that bad.

One interesting tidbit:  We wanted to present our system at a conference in San Antonio and had a picture of a battle-damaged F-15 we wanted to use.  Well, we were told that the picture was classified and, as such, we couldn’t use it.  Well, about that same time, a glossy McAir brochure featuring our system and that photo were distributed at the AAAI (American Assn. of Artificial Intelligence) to thousands of people. 

Another system I developed dealt with engineering schematics.  These schematics were layered.  Some layers and circuits were classified.   Still another system scheduled aircraft for painting and yet another charted a path for aircraft through hostile territory, activating electronic counter measures as necessary.

I guess the most sophisticated system I worked on was with the B-2 program.  The B-2 skin is a composite material.  This material has to be removed from a freezer, molded into a final shape and cooked in a huge autoclave before it completely thawed. 

We had to schedule materials, and the behavior of that material under various circumstances, as well as people and equipment.  The purpose was to avoid “bottlenecks” in people and equipment.  I was exposed to the Texas Instruments Explorer and Smalltalk-80 on an Apple.  I’ve been in love with Smalltalk ever since.

The system was developed, but it was never used.  The problem was that we had to rank workers by expertise.  That’s union workers and that wasn’t allowed. 

It was a nice system that integrated a lot of systems and worked well.  Our RFP (Request for Proposals) went out to people like Carnegie-Mellon.  We had certain performance and date requirements that we wanted to see in the final system.  We were told that the benchmarks would be difficult, in not impossible, to attain.  Well, we did it, on our own without their help.

We also had a neural net solution that inspected completed composite parts. The parts were submerged in water and bombarded with sound waves.  The echoes were used by the system to determine part quality.

AI promised the world, and then it couldn’t really deliver.  So it kind of went to the back burner.

One problem with the end and be all.  It will only be as good as your model.  It will only be as good as the developers can determine the behavior of the parts and how they interact with the whole.  Currently, this is a moving target and is changing day to day.  Good luck.

Links -

Will Wolfram Make Bioinformatics Obsolete? - http://johnhawks.net/weblog/reviews/genomics/bioinformatics/wolfram-alpha-bioinformatics-2009.html