1. science
2. biology

Stephen Chavez
[email protected]
05/12/2015
Biology as an Engineering Science
There are certain processes we do not yet understand that go on in biological systems.
Biological systems can be cells or any living creature for that matter, given the current meaning of a living thing. One of the current unsolved biology problems is answering the really
big question. “Where did life come from in the first place?” Another unsolved question is,
“How does biological aging work?” There are multiple reasons why biology currently cannot
answer the above questions. One reason is the fact that there are no great modern tools for
biology to confirm any untested theory for the above questions. The second reason is biology
is lacking behind from the other sciences because it is stuck in old ways. Harder biology
problems need new problem-solving methods and information from many other sciences like
computer science or math.
There is the need of new intuitive tools like computer aided design programs that are
specific to biology. People are suggesting that adding computer science and other fields like
math to fix biology. From what I have read so far, computer science is going to be the most
helpful to biology. Tons of data from tests is being created faster than humans can manage
or organize that data. There are biology experiments that need computer simulations to see
if any hypothesis is correct or wrong, no human is capable of doing most biology simulations
by hand. Computers can fix these issues, but first it requires biology to evolve fast. It
also means that computer scientists need to understand the needs of biologists and biology.
Likewise, Biologists need to tell computer scientists what would be useful for them. This
paper will explain some of the ideas in computer science that are useful in biology, and why
it is failing as a science because of the old methodologies it has been using.
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Computer science is becoming so fundamentally important to today’s world. It has given
us credit cards, cellphones, and better healthcare. It gives everyone access to better information using the internet to help themselves and others. Biologists can share information
instantly without having to travel much. Concepts from computer hardware, like logic gates,
as well as the mathematics behind computer science, can be used to make biology better.
We will also be able to make little machines that act like cells, which will help us understand
life better. I will present an example of this, where a cell is made using ideas taken from
embedded devices. First though, let us peak into some history about biology. We will also
peak at some issues that biology has currently.
The ethical issue that lies within applying mathematics, computer science and engineering to biology is based on the controversial topic of metaphysical entities. An interesting
argument has been that we are only human therefor we shall not play or intend to play
“god’s” role. My stance is, because we are human and capable of creating life and have the
ability to manipulate biology in such ways that might be able to cure diseases is great! I has
been argued that people will care less if we are able to clone organs, but then again that is
determined by the supply and the cost. When, not if, the scientific community decides to
create nano bio computerized viruses that attack certain cells in the body for good or bad,
there will be an uprising. I say this because the measures to govern this will be extremely
difficult. It will be like trying to implement jurisdiction to the internet, a task unattainable
at the present moment. We want the greater good for the people yet we fail to yield to the
signs of our own destruction. Emerging fields of biology and computer science are becoming
more and more popular topics of study.
Biology has existed for more than 150 years. It has grown into other fields like marine
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biology, neuroscience, and the list goes on. It has explained multiple things like how natural
selection works, a human’s autonomous nerve system, and how living things produce energy.
Indeed, we came far from what we were before 150 years ago, but like all sciences, biology
has some unanswered problems and questions like how did life start? Even after tons of
research and successful lab work being done. We are only able to explain a small section of
problems. This is a huge problem for people who want to know how nature really works.
As biology improves, it must change. This change can be hard. What kind of changes
are needed? Put simply, biologists need to make sure that there are new ways of thinking
and tools available to them, like 3D-modelling software that can be customized to work with
cells’ functions. “At the core of systems biology lies the construction of models describing
biological systems.”[Fisher and Henzinger C., 2007, p. 1239] Models can be mathematical
equations that describe the system’s behavior at a generalized level, but don’t describe the
internal mechanisms that give rise to the results. For describing how a cell works, we need
a sort of blueprint that lists the parts and connections that makes the cell work. We do
not have that kind of high-level model for a cell yet. We also need models that combine a
blueprint and mathematical models, to see the whole idea of a particular biological system.
The applications above integrate computer science into biology in a practical mode. It is
clear that understanding how life works is extremely important to many. The integration of
computer science into biology can ease this process. There are many ways we could use this
for the greater good. A friend of mine talked about war being one of the positive applications
in integration of cs and biology. I thought to myself how is war good? Then it came to me,
what if we were to integrate software into biology which made it possible to target certain
individuals and not need to fire a single weapon.
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There is also the problem that humans cannot use the large sets of data from experiments
efficiently without help. The large sets of data are too much for humans to handle without
having to automate it. We have to create computer databases to search such information
to get better results more quickly. Some experiments need to repeat a lot of times and this
is tedious for humans to do. We could make a computer script or program using various
computer languages. We could tune some computer language to be more biology friendly by
automatically implementing physics laws or any law biologists might need in their program.
Having languages suited to the study of biology could save biologists a lot of time.
Sciences are generally all about proving theories and concepts with hard concrete examples and facts. The many theories one may test must be reproducible too, or else they
are not true if they do not have these things pointed out. This is hard for biology because
the small biological systems are too small to be studied normally. Why does this matter?
Put simply, biology cannot take a cell apart and put it back to experiment. We can use
non-invasive ways studying life like microscopes, but they have some issues.
Visible-light microscope don’t work anymore. This is because there are biological systems
smaller than the wavelength of visible-light. We have to use more powerful microscopes.
These more powerful microscopes work out of the wavelength of visible light. This lets us
to see smaller things by such using shorter wavelengths of light, or things other than light
like electrons. One example will be an electron microscope.
These newer devices except for optical ones, are more limited in image quality because
the images only use 1 or 2 shades of a color only a lot of times. This is where computer
science can be utilized to improve these images by enhancing it with algorithms that can
predict color, depth or other things. We can also ignore using these devices altogether and
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just use computer simulations which can show more things than static images will show.
Biology also needs to use other subjects like physics and chemistry to help explain biological life. Biology must explain things with some very high level conceptual ideas and use
qualitative measuring to become super successful. However, there isn’t any much of physics
being used in biology, but you will see a lot of chemistry.
The funny thing is that seems physics is very useful for us when we are working at smaller
scales. We don’t really use it daily in biology. As it appears to be that way anyway. Physics
will let us understand biology better. Having biologists to learn physics and programming
will let them use physics daily.
Coming from a computer science background and having interests in biology. I wanted
to know what CS was doing for biology. The first article I found was called “Executable
Biology”, it talked about some computational models and mathematical models in addition
to ideas on how to support biology from a computer scientist’s point of view. I have already
explained some of these things in this paper.
The article “Executable Cell Biology” [Fisher and Henzinger C., 2007]. This article is
good to read and study, once you are familiar with the subjects, but it is not a good starting
point if you are new to the subjects. It requires you to be proficient in computer science and
biology. I think this article “Taking the example of computer systems engineering for the
analysis of biological cell systems” [Pronk. et al., 2007] is a much better start for studying
executable biology. This is because it uses easy to understand examples that anyone can
understand.
The paper “Executable Cell Biology”[Fisher and Henzinger C., 2007] is an attempt to
bridge the gap between the high-level and mathematical views of biological systems. The
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article’s authors are Jasmin Fisher and Thomas A. Henzinger. This paper was published
under Nature Publishing Group in 2007. The paper is in the journal “Nature Biotechnology”,
in the volume 25 and issue NO. 11. The publisher has no apparent affiliations.
In Biology, there are two different ways of viewing a system. There is a high-level view,
which describes the system using building blocks. A system is made of smaller systems called
organs, tissues, cells and even the periodic elements. A system can be a part of a building
block. The building blocks has to be generalized enough to let you work at a larger scale.
You do not need to know the internal function of the building block. The building block must
be simple enough to work with other blocks. An example would be a cell. The high-level
view does not tell you how everything works. There is also a mathematical view described
very nicely in [Fisher and Henzinger C., 2007]. The model uses equations to describe a
relationship between quantities and how they change over time. Biologists have been unable
to link these two views together into a coherent theory.
The paper introduces problems for biologists that have a hard time integrating computer
science. The paper also introduces problems for computer scientists as well. The programmers have to make computer programs that allow Biologists to use concepts from computer
science in an effective way. Fisher and Henzinger have written about a new model called the
hybrid model. This model ties the high-level and mathematical models together.
The “Executable Cell Biology” article can be broken into three major parts. The first part
is the introduction on a new way to perform experiments using computational models such
as Petri networks or Boolean networks, or mathematical models. The intro also presented
problems in Biology that prevent it from creating a perfect overview of a biological system.
The body of the article explains how the following models can be used in executable Biology.
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Boolean networks, Petri nets, interacting state machine models, process calculi and hybrid
models. The conclusion of the article explains some challenges that must be worked out in
order to have concepts from computer science be applied to Biology.
The article continues to explain the rest of the models. The last model they explain is
the hybrid model [Fisher and Henzinger C., 2007, p. 1245] that combines the mathematical
and computation models. I explained this earlier. The reader would be likely interested in
this because it defines a way to connect differential equations to a high-level concept.
The paper uses the analogy between computer hardware and biological models. A computer chip is made of transistors. Transistors are made of logic gates. Transistors can also be
defined by differential equations when viewed at a more detailed view. A Biological system’s
equivalent of a chip is a signalling pathway. Molecular interactions would be the transistors
of the pathway.
However, a molecular interaction does not correspond to a logic gate at a smaller level.
Molecular interactions can be explained with differential equations though. This is a problem
that Fisher and Henzinger hope to be fixed someday. “A key challenge is to identify a more
abstract level, perhaps similar to the gate level in hardware design, based on functional units
each of which involves many molecules.” [Fisher and Henzinger C., 2007, p. 1246]
Biology will become a better science once people find ways to introduce the computational
models into their work. These models will help biologists find a formal way to explain
biological systems at a high-level and more detailed levels.
Once computer scientists and biologists work together to fix the problems that Biologists
are having, biology can find new cures to diseases. Computer scientists need to remember
biologists are not armed with the concepts that programmers know. Computer programs
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created for biology must present programming in an intuitive way.
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Bibliography
Tessa E. Pronk., Andy D. Pimentel., Marco Roos., and Timo M. Breit. Taking the example
of computer systems engineering for the analysis of biological cell systems. BioSystems,
90:623–635, 2007. People are questioning current methods, foundations and other ideas
that were developed to aid biologists because they are not getting anywhere. Computer
scientists realize that they can evolve biology into a mathematical science. Computer aided
design programs are a set of tools that can greatly help biologists, once they are developed
for biology.
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Figure 1: Both cells and embedded computers are heterogeneous systems, consisting of different types of components that have to work together. Where possible, components with
similar functions in both systems are put in the same location in the figure. ‘Organelles’
and ‘Processors’ can be seen as structures performing tasks. ‘Software’ and ‘Genome’ are
the places where application is programmed. ‘Energy and Transport’ and ‘Auxiliary systems
(power, cooling)’ are the elements that make it possible for the system to function. ‘Central Processing Unit’ and ‘Networks’ take care of the regulation of actions of the system.
‘Sensors, Signals, Actuators and ‘Digital to Analogue’ converters interact with the external
environment. ‘Robustness’ and electromechanical backup and safety’ are all components to
make the systems reliable and robust. Top part adapted from Koopman (1996). Pronk.
et al. [2007]