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Digital Biology
It should come as no surprise that the infatuation is requited because some biologists are just as fascinated with the bits that live in computers. They love to wonder whether the software crosses the line and become a sentient being, whatever that may be. They want to know whether a programmer can play Dr. Frankenstein and create life or at least an indistinguishable imitation. They are entranced with the computer's ability to boil vast amounts of data into a coherent answer and they want to harness this power to solve problems about truly organic creatures.
Peter J. Bentley's new book, Digital Biology is a lively tour through some of the research that joins both of these worlds. It's a quickly paced, colorful examination of how computer scientists and biologists can share metaphors like "the immune system" or "growth." If both groups sit down and compare metaphors, computer scientists may learn something about building robust, self-healing, self-reproducing software from looking at carbon- based creatures while biologists will learn something about creatures by studying them with silicon-based software software.
The book is aimed at the same market that embraced the meme of "Chaos" through reading James Gleick's book. The book is light on equations and heavy on showmanship. In many cases, this is more than satisfying. One description of digital flocks of birds describes how three simple rules can keep the birds floating and swarming with all of the coordinated rolling and swooping. There's no need to invoke numbers or distance measurements to convey what's happening.
At other times, the examples can be so tantalizing that the lack of depth can be a bit frustrating. Bentley promises "The number of different applications that we have successfully used evolution for is immense." To explain this, he offers an example of a coffee table designed by a computer program mixing, matching and cross-breeding varieties. After each generation, the computer cuts some desks apart, creates new combinations and then uses an equation to find the most fit and desirable desks. Eventually, a reasonable candidate emerges. After explaining that genetic algorithms may find patterns of credit card fraud and help us find better jet turbine blades, there's no space to tell us the finer details. We do learn that stunning results can emerge when computer programmers mix the three principles of inheritance, variation and selection. But no book can include everything.
While the book is aimed at a broad market, it does not come with many of the traditional flourishes of journalism. Bentley is research fellow at University College in London, not a newspaper hack who churns out stories for a living. So when he introduces other researchers and colleagues, he doesn't bother with dressing them up with details about their homes, their wives, or the usual chestnuts journalists offer in the hope of humanizing the subjects. The book focuses on the ideas and metaphors themselves and doesn't bother with the window dressing. The names are just incidental markers to give credit and a pointer for further research. Scientists will love the lack of distraction, but casual readers looking for colorful anecdotes about the wacky geniuses in labcoats will need to look elsewhere.
The book, as expected, is generally enthusiastic and heavily invested in the field. Software modeled on biological systems, we are told, will, "detect crime for us, identify faults, ... design new products for us, create art, and compose music."
Despite this partisan flavor, the book shines in the few paragraphs where Bentley pauses to discuss some of the limitations of the systems. "We cannot prove that evolution will find us a good solution-- but it almost invariably does. And we certainly cannot predict that solutions that evolution generates," he notes as a caveat to everyone planning to use genetic programming to solve world peace.
At one point, he discusses one of the principle criticisms of the entire area. After describing flourishing digital forests filled with fractal ferns, problem solving viruses, and swooping swarms of evolving birds and insects, he pauses and offers this quote from another biologist: "Where's the experiment?" He notes that most of these creatures are flights of our imagination untested in the lab against real ferns, viruses or birds. Nor is there any real way to test a fern hypothesis. The digital versions look real, but there's little gritty lab work to establish them as true metaphors for sussing out the secret laws of nature. Is looking real enough? Can you measure verisimilitude? Do any traditional experiments measure anything better than the quality of a simulacrum? Is appearance enough or is it only skin deep? After a pause, though, the book is on to more talk of big payoff and grand promises.
In its heart, the book is more a document that shows evolution of problem solving techniques. If you want to get the sales pitch from the computational biology world, you can turn to this book. When there were no machines, scientists used symbols, algebra, calculus and other mathematics to describe the world. Biologists have long employed differential equations to describe the booms and bust in ecologies of predators and prey. Now that we have computers capable of billions of operations in a second, we don't need the old school of mathematics to provide a closed-form solution. The computers can just simulate the world itself. There's no need to struggle for a set of equations that is both easy-to-solve and appropriate. We can just use little worlds of sims creatures, sim fronds, sim viruses, and sim antibodies.
Bentley's book is an ideal way to learn just how and why some biologists are absolute enraptured with the new powers discovered by these computer simulations of genetics, growth, flocking and other natural phenomenon. These models don't offer the kind of concrete certainty of mathematical models, but there's no denying that something is somehow there. Is it as much a breakthrough as Bentley believes? Well, maybe you the reader can create a genetic experiment to cross fertilize the ideas from the book with the ideas in your experience. After a few generations of thought, perhaps a few generations of beer, an answer might evolve.
Peter Wayner is the author of Free for All, a book on the open source software movement and Disappearing Cryptography , the second edition of a book on steganography expected to appear later this spring. He is also the author of several articles on simulation including studies of studies of the relationship between sex and AIDS , segregation , and the length of baseball games. (Each of these links includes a Java applet so you can run the simulator from your browser.) You can purchase Digital Biology from Fatbrain. Want to see your own review here? Just read the book review guidelines, then use Slashdot's handy submission form.
Does anybody remember when analog biology was good enough?
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DNA is the ultimate spaghetti code.
This book, like so many other supposedly balanced books on biology, assumes that evolution is true and pushes it at every possible opportunity. People with open minds may want to avoid this book, and members of the moral community will definitely not want to read this. "Analog" biology is a controversial enough subject, there is no need to read about digital biology.
the review will answer the question... ? =D
It will also take out the trash, make your bed, screen calls from your annoying ex-girlfriend, make sure your milk is still good, tell you you're looking skinnier, and reprogram your TV to get all the good channels.
At least to some programmers....
Writing a living, breathing program would be the goal of many of us, not just AI programmers
Here is Amazon's Review. Not bad, and much better than the slashdot review above.
This is one of the courses I followed at the university, during my artificial intelligence study.
Lots of examples of this book, came back in our practicums, there are nice links to sites about this subject on the page and also the complete course is online for you to download (not sure if my professor is going to be happy about this, but who cares, I passed the grade:)
To the worst extent possible.
:(
My psych professor explained our language lecture using layman's computer terminology, instead of psychology. I wanted to strangle him the entire time. "So... you've got this memory stuff... and it get accessed - that is - processed, by this other bit over here, right, this area of the brain... let's just call that the "software"."
It was enough to make any techie of any note sick. He actually used Microsoft as a language. Talk about wanting to shoot someone.
But what can we do? Everyone thinks they're a programmer or a techie these days, and everyone thinks that because kids use IM they must have some other association with the grey box.
Sorry fellers, that's wrong. Most kids today don't know jack about computing, much less are able to relate better when you babble incessantly about things in your half-tech, half-psychologist manner. Stick to the psychology or the biology, instead of using computer terms to explain simple concepts. It's just more confusing and more hellish.
> Scientists will love the lack of distraction, but casual readers looking for colorful anecdotes about the wacky geniuses in labcoats will need to look elsewhere.
4 6/ qid=1015865367/sr=8-1/ref=sr_8_67_1/103-9949968-63 91849
If you want that kind of thing, this book is amazing for presenting both sides (ie, the science & the people) of the stories:
http://www.amazon.com/exec/obidos/ASIN/06718723
It's called Complexity. It is a kind of answer to 'Chaos', and it has much info on the kind of biological software that the Santa Fe Institute crowd was working on a few years ago. A very highly recommended read.
"Old man yells at systemd"
Humans have a tendancy to cast biological, and even human, behaviors on anything that is outside their ken.
Case in point. When I was helping my mother restore her computer after she was infected with Code Red, she was infuriated at the worm. While she is a computer professional, she is not a coder and has no understanding of... say... how machine code executes a loop or a goto. She talked about Code Red as if it really was a living thing despite the fact that she knew better. One of the things she said that stuck in my head was 'Why would it do that to me?'
The next Slashdot story will be ready soon, but subscribers can beat the rush and slashdot the links early!
I get the authors point, but I don't think he makes it well..
No one speaks of subroutines that cp themselves through undocumented remote procedure calls because talk of 'computer viruses' carries all of the portent and weight of polio, anthrax, German Measles and tuberculosis.
Yeah, no-one speaks of the exact way all these illness viruses work either since it's easy to abstract it out to a simple term 'virus'/
IIRC it happened a year ago, upon the implementation of RFC 1149.
I love this comment
People with open minds may want to avoid this book
___
It's the end of my comment as I know it and I feel fine.
can anyone navigate the grammatical maze that is this sentence!?:
---No one speaks of subroutines that cp themselves through undocumented remote procedure calls because talk of 'computer viruses' carries all of the portent and weight of polio, anthrax, German Measles and tuberculosis.---
May you be touched by His Noodly Appendage. RAmen.
http://www.digitalbiology.com/
Plenty of good stuff. Anyone have other good links?
I'm a little worried that if this gets too 'faddy' that people could start looking for biological metaphors and ignore other eqeually effective, or perhaps more effective solutions.
:).
For example, from the review above:
genetic algorithms may find patterns of credit card fraud and help us find better jet turbine blades
The genetic algorithm is a great algorithm for optimization problems. However, its not significantly more effective than the simulated annealing algorithm or the less-known controlled random search algorithm.
Each has its advantages and disadvantages, but getting too caught up in the metaphors these algorithms and techniques are based on will unnecessarily shackle your thinking. Of course, the opposite is also true. Refusing to embrace metaphors at all will leave you without the insights that we use metaphors to see, so don't take me too seriously
if ($it != $onething) {$it = $another;}
I would probably not respond to the above and disregard it if it were not for a recent Sci Am article that showed ~40% of Americans believe in creationism over evolution.
I cannot understand how seemingly intelligent people can ignore overwhelming scientific evidence. Evolution is the most widely explanation for how we came to be. I do not see any inconsistencies with the Genesis *metaphor* for the creation of life. The Bible is written by humans, not God. They may have had divine inspiration, but it was not God's pen in the inkwell. Why do you think there are four "Gospel according to XXXX"?
BTW, God is omniscient. Don't you think He can understand and use a metaphor?
Of all the types of ignorance in the world. Those that perpetuated under the guise of religion are the most virulent and dangerous.
You can never equivocate too much.
Seeing all this spouting about some fucking lunatics in favor of creationism just make me so fucking sick I'm gonna stop reading /. for today and do something constructive instead in a continent where such wackos won't dwell. Thank you fucking very much.
Is this an honest request for help from a non-english speaker? Or an engligsh speaker unfamiliar with compound sentance structure? The sentance is fine. Subject="no one". Verb = "speaks of". Object = "subroutines that ... calls". Subject of subordinate clause="talk of 'computer viruses'".
Verb of and object subordinate clause="carries" and "all the weight of...".
Where is the problem?
This area has always interested me because I did my undergraduate degree in molecular biology, and my professional career has been in software engineering.
The first thing that strikes me when biology and computer science are brought together is that although we try to apply principles of the former to the latter, we really have a much firmer grasp of computer science than we do of biology. What we're really doing, I think, is taking some theories and concepts from biology -- evolution and immunology seem to be the big ones -- and adapting those theories to suit digital computers; we're not modelling life per se. It's important to remember, too, that although we can model evolutionary processes like variation and selection in a computer system and produce the anticipated results, we can't thereby prove that evolution applies to life. (I happen to believe that it does, but I have to admit that we have yet to irrefutably prove it). All we're doing is nicely illustrating the theory.
Someone mentioned earlier that everyone claims to be some sort of computer expert these days, and that biologists and psychologists routinely misapply computer concepts. From my perspective, the reverse is true. There seems to be a misconception that biology is straightforward and well-understood, and I just don't know where that comes from. I'm sure I'm not the only biologist who grimaces when "virus" is used to describe software. And the most gaping errors in science fiction always seem to be ones of biology. Computer scientists use words like "genotype" and "phenotype", but genetic algorithms seem to me to be so far removed from the actual complexities of gene expression as to be at best distant cousins. It's more a matter of biology lending ideas and inspiration to computer science than it is some direct translation of life processes to software processes.
Please donate your spare CPU cycles to help fight cancer and other diseases
Ben Franklin refused to patent his stove, lightning rod, bifocals, or anything else. Technology to the people!
Heh. It was the patent office that refused to accept Franklin's patent applications. There's some stupid old rule about "prior art" and having to be the first inventor to get something patented.
The same old rule still applies: in modern history, the Germans invented everything until 1945. After that, Germans living in the USA invented everything.
Even ardent Creationists cannot deny the 'fact' of hereditary mutation, selection, and hence, evolution. Christians have manipulated the genetic stocks of plants and animals for centuries. This is EXACTLY the same thing that Genetic or Evolutionary Programming is doing.
Creationsists only take issue with the scientific theory that Darwinian evolution can explain ALL of the biological phenomena. They cannot deny that evolution exists and works. They have only made arguments that it works too slowly to explain everything. Thus, this warning is extermely misguided.
Why is accident and random happening a better explanation than purposeful action by an active intelligence? Belief in Evolution requires as much faith as belief in Creation.
It's not about elitism, it's about morality. Evolution precludes morality because evolution precludes God and molars come from God. Morality is about humbleness before God, not about holding the door at the store open for a little old lady (which evolutionists often claim to do, as proof that they are moral.)
This does not impress me.
I know that God understands metaphors and even has used them from time to time. However you must understand that creation is not a metaphor. If the six day creation is not true, then neither is the story of Adam and Eve and the fall from grace. If that is not true, then mankind is not in need of a Savior, then Christianity falls apart, which is a logical impossibility. There are metaphors in the Bible, like where Joshua makes the "sun stand still", clearly this is a metaphor for stopping the spinning of the earth. But creation as a metaphor, let's not go down that road, okay.
By the way you should not so smugly say that evolution has overwheling evidence, I have seen tracks of man and dinosaur side by side. Isn't that sort of hard when science says that they lived millions of years apart. Or maybe those "millions of years" are millions of lies.
Oh man, Klerck, he got the widening AND lengthening goatse.cx post!! How are you going to top that??
I cannot understand how seemingly intelligent people can ignore overwhelming scientific evidence.
Because to most people Science is just as mysterious and magical as Religion.
Millions of children are enrolled in Sunday-School or fulltime religious school learning "You are not supposed to understand this". Truth has nothing to with logic or understanding. "Proof" of truth is not merely meaningless, but rejected as missleading.
Another goal of religious traning is rejecting competing religions. Science seems like just another religion to fight off - a bunch of ideas and beliefs that they don't expect to understand.
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- - You can't take something off the Internet! That's like trying to take pee out of a swimming pool.
Even ardent Creationists cannot deny the 'fact' of hereditary mutation, selection, and hence, evolution... They cannot deny that evolution exists and works.
Sure they can. They do it all the time, hehe.
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- - You can't take something off the Internet! That's like trying to take pee out of a swimming pool.
Anybody ever notice that the kernel is the core part of a UNIX system, similar to the kernel of an atom, and that the shell is the outer part of each? In each instance the shell is changable, and also the 'interface', as it were, to the whole unit. Seems like this might be a good example of somebody getting cross-field terminology right.
Love justice; desire mercy.
This guy needs to get a life. Reading books like these are for the computer illiterate.
Saying that the frog jumps out immediately from the boiling water assumes: a) the water is suffeciently shallow for the frog to push against the bottom of the pot (I don't know if the pressure exherted against water would be enough to propel a frog out of a pot); b) that the difference in height between the water level and top of the pot is small enough for said amphibious hopper to get out; c) that being submerged in boiling water does not immediately disable the frog's jumping capacities.
I've fried crickets before (yes, I eat strange things), and when you toss them onto a hot pan with some oil (mmm.... butter), they simply don't have time to react before the proteins in their muscles are hydrolized. Not to be morbid about it, but I really don't think our frog has a chance in the boiling water.
Conversely, how dumb do we really think frogs are?? I mean, come on-- if you feel your legs scalding, don't you generally get out of the tub? Admittedly, when the temperature is raised gradually your heat tolerance increases. Indeed, people get so comfortable in saunas that they post warnings about brain damage from being in there too long. But come on. Is the frog really going to sit there and pass on blissfully to oblivion? A fish, I can understand. As the water gets hotter, fewer gasses can be dissolved in it. Since the fish breathes the dissolved gasses, it gradually suffocates. Which is beside the point, since the fish can't jump out of the pot in the first place, but you get the idea.
Somebody, please! Clear up this confusion! In the name of all that is analgous! In the meantime, I'm going to get back to my cricket stir-fry.
p.s. True science and true religion never conflict. To have a complete understanding of science is to understand the universe as it is. True religion is the same. Religion covers the why, science coveres the how. Since our understanding of both is imperfect at best, it's pointless to argue about frivolous details that don't pertain to our salvation. One way or another when we're all dead and sitting around in the waiting room, maybe there will be a documentary video playing in the VCR (DVD? What format do celestial beings use?). Then we can all nod our heads and say, "Oh, duh! Of course." Until then, deal with the fact that currently neither science nor religion has a monopoly on the full truth of "how" things came into being. Let science debate the how of the universe, let religion inspire us with the why, and what our purpose in it is.
Darned tropical millipede! What's it doing in our apartment?
I think the reviewer's points about differential equations are good ones. If you check out the link in the bio, one article on AIDS points to the mistakes you can make with choosing the wrong rules for your "metaphors." Differential equations, for instance, require you to be able to take derivatives of the functions and fit the derivatives to some equation. That's great if the functions have derivatives, but it can be misleading if they don't. In one example, an economist hell-bent on using differential equations decides that AIDS can be curtailed if we all have more sex. (I kid you not!).
So are biological metaphors just as suspect? Perhaps. Digital evolution is cool, but I don't see why it is better than any of the other optimization techniques. If anything, the digital bio metaphor forces you to mimic creatures and all of their semi-monogamous, one-on-one reproduction. Equations don't have to conform to such a binary vision.
By the way you should not so smugly say that evolution has overwheling evidence, I have seen tracks of man and dinosaur side by side.
I thought even the creationists were abandoning this piece of "evidence". See this site for details.
Besides, even if you proved dinosaurs and man did have some overlap in the chronology of life on Earth, it certainly doesn't prove a six-day creation, or a 6000-year-old Earth. Once again, Creationists show their lack of comprehension not only of the scientific process, but also of simple logic.
Hey kids, there's only 5 days left 'til Yak Shaving Day!
The fundamental reason why we cannot model biology with computers is that biological systems are chaotic. They respond to extremely small fluctuations no floating point processor can handle. In fact the human eye can respond to a single photon. See: http://math.ucr.edu/home/baez/physics/ParticleAndN uclear/see_a_photon.html
Biological systems are sensitive on quantum level and computers certainly cannot be.
The above comment, despite apparently looking interesting/insightful to a few moderators already, is absolutely moronic and meaningless. I would be surprised if a human wrote this. It looks like the output from some kind of a science-babble generator.
Please move on.
What's wrong with the liberal use of a metaphor here and there? The people we're talking about here (biologists and technologists) aren't idiots...they're highly trained and intelligent individuals. As such, most of them can tell when a metaphor is being taken too far.
Let's say I'm trying to explain a concept in molecular biology to a computer scientist. Is it really so bad if I make an analogy connecting something the computer scientist already knows (programming, for example) and something he or she does not know (MAPK pathways, for example)? As long as the analogy holds up on the level that I explain it at, things should work fine.
But because neither the computer scientist nor the biologist are stupid, they won't take the analogy too far. The computer scientist won't immediately think, "I bet obscure programming fact XXXX holds for this biological system he's explaining to me, because he just used programming language YYYY in his metaphor." This won't happen because the computer scientist is a rational person, who knows what a metaphor is and its probable limits.
Yes, it's true that if everyone takes metaphors literally, then we'll run into problems. But the entire reason we can use metaphors for something useful, is that we can also also understand that a metaphor can break down at some point.
I'll admit, I get pissed when popular culture misquotes some arcane (or even general) biological principle. However, that's a totally different thing than using some other subject as a metaphor. Without metaphors, those involved would have to learn these things from scratch, without drawing upon what one already understands. I think it's totally valid to dispense snippets of information through metaphor, since the alternative is working one's way up from ground zero without using metaphor. And that's way too much to ask, considering in biology it takes a PhD for anyone to consider you above zero level.
4-star general in a one-man army.
Never say never. When you really get down to it, the only thing that allows organisms to register a single photon is that photon tripping some chromophore into a different conformation. So it's just one particle making an atom switch, thereby making an amino acid twist, thereby making an entire protein move. The subsequent amplification all rely on principles of signal transduction.
So computers must be able to measure single photons, otherwise how did the physicists know that they were emitting a single photon? And to go from single-photon-detection to whole-organism-response only requires a long series of amplification cascades. Why is such a setup so hard to envision in a computer system?
4-star general in a one-man army.
Yes, and no. One could design a computer system (electro-optical system) to measure a single photon. and we (not me pesonally) have. The single photon example was simply an example of how sensitive biological systems are to just about everything. To reproduce them, the computer system would have to be as sensitive, and thus would have to be analog for a start. Secondly, any, repeat, any rounding off error would result in different behaviour. I am not saying that we cannot produce a system as complicated as a biological one in a computer, I'm saying we cannot replicate the biological one to any degree of accuracy.
Folks interested in the book might also be interested in a letter to the editor published in the latest issue of the Centers for Disease Control and Prevention (CDC) journal Emerging Infectious Diseases. The journal is a scholarly source about biological diseases. The letter, Contagion on the Internet, compares the biology and evolution of biological viruses to computer viruses.
I learned somuch about OO programming through models already present in bio of populations. If you want to emulate complex systems, I recommend that you study the human body's transport mechanisms or ant chemical communication.
There is so much there in teh bio world that is damn cool that we can TRY to use to inspire us to create great subsystems and communicaton mechanisms.
- Zav
One of the great difficulties in this area -- especially when dealing with the question of Xenobiology -- is the issue of how to define whether something is "alive" or not. No one has yet come up with an acceptable definition that includes everything that humans think of as "life," and that excludes everything that we don't. In addition, we have a human tendency to anthropomorphize "inanimate" objects. Referring to cars, boats, computers, etc "as if" they were alive and had a will of their own.
So the standard way of dealing with it has been a kind of "I know it when I see it" approach to the question of whether or not something is alive. For the most part, this works pretty well. There's almost nothing on Earth that isn't clearly "alive" or "not-alive" and so it's easy to believe that a clear demarcation exists, but that we simply haven't identified the proper criteria yet.
There are some ambiguities, however, which can be controversial. Tom Ray considered his "Tierra" creatures to be alive. Some have claimed that computer viruses are a kind of life form. (Both of these meet the self-replication criteria.) More controversial are the Gaia hypothesis, and the question of whether or not a fetus/embryo/blastocyst qualifies as "human life."
However, it may well be the case that there can be no well-defined demarcation between "life" and "non-life." At one time it was believed that racial distinctions could be biologically defined, yet this turned out not to be true. There is no clear definition that would unambiguously put every single individual into one clear racial category or the other. Some people simply defy such categorization. Even though in most cases, I suspect that most of us feel that we "know it when we see it" what racial category a person belongs to. Also well known to many biologists is that among humans there are certain individuals who do not fall easily into either the category of "male" or "female."
What I suspect is that the concept of whether or not something is "alive" is, in fact, not definable. But that the existence of these categories is merely an artifact of the wiring of human brain. That as humans, our brains evolved to search for patterns and to classify things in categories. These categories often served us well in the environment that we evolved in, where the ambiguous cases may have simply been absent -- or so exceedingly rare as to be unimportant. However, in the larger world of "objective reality", the categories of "alive" and "not-alive" may lose their meaning. We may some day find "things" on Mars or Europa or elsewhere that we simply cannot agree as to whether or not they qualify as "alive."
Something I heard pointed out once with regard to the infamous "Face on Mars" is that humans are genetically programmed/predisposed to "see" faces. It's a part of what has enabled us to survive as social creatures. It allows us to distinguish "human" from "non-human." This can be important for species survival. And so, like many optical illusions, our tendency to recognize a "face" in the rocky patterns of the Martian surface says more about how our brains are wired than it says about life on Mars.
The same may be true of the definition of "life" itself.
Two of the four diseases the author mentions, ie anthrax and tuberculosis, are caused by bacteria and not viruses.
viruses named:
polio
common cold
German Measles
bacteria passed off as viruses:
anthrax
tuberculosis
black plague
*sigh*.
Well, I'd personally say that point is arguable. Let's say we're making a system that is capable of responses as complicated as those exhibited as a cell, for example. It's really just a matter of adding in billions of responses. So we'd model a receptor-ligand system by saying "if stimulus X in Y amount then trigger Z." Things get really complicated when you stipulate that stimulus X in Y amount will ONLY trigger Z if your "receptor" is present in the right amount.
When you really get down to it, most biological processes aren't analog. Instead, they're regulated by molecules that can take on a finite number of states. Given, the number of molecules involved is fantastically large, and the number of states they can take is almost always more than 2 (especially since you have to take the effect of things like protein misfolding due to mutation into account).
So yes, it's relatively simple (heh) to produce a computer-based system that's as complicated as a biological one. But to replicate a biological system we'd have to know every X molecule, and all of the resultant Z triggers that can result from Y concentration of X. Then, we'd have to already know how all of the different X molecules connect to eachother (in ways as subtle as "you can't make any more X1 because all of the zinc was used to make X2").
However, while we can't replicate biological systems (and probably never will be able to), we certainly can model them. This is much easier, since we interweave a bunch of different functions in an attempt to arrive at something that generally makes sense. Then try to model some situations where the result is already known. If your model matches reality in almost every case, then you've probably got a winner. Otherwise, Do Not Pass Go.
4-star general in a one-man army.