cal virus; he eventually developed the
first self-replicating program. In 1970,
mathematician John Horton Conway introduced a cellular automation system
called Conway’s Game of Life, in which a
person configures a set of circles, then
the computer embarks on a rudimentary evolutionary process.
By the 1990s, a number of researchers had begun to explore the idea of producing digital representations of biological creatures.
For scientists, the idea of creating
virtual life and artificial worlds inside
a computer is rooted in practicality: it
makes possible the study of the genetic information of an organism, or the
creation of a virtual space to study how
evolution and adaption take place. “
Researchers can run thousands and thousands of replicates simultaneously. Every computer is essentially a Petri dish,”
explains Christoph Adami, professor
of microbiology and molecular genetics at Michigan State University. This
approach also allows researchers to
isolate specific components, including
genetic coding, and “very carefully tease
apart the different elements that go into
the evolutionary process,” he says.
OpenWorm is an example of how
this new frontier of biology and computing is unfolding. So far, “several
hundred people” have contributed
to the project in some way. This includes computer scientists, mathematicians, biologists, and experts in
neuroscience. Among the core participants are more than a dozen academic and research luminaries, including
C. elegans biologists Sreekanth Cha-lasani at the Salk Institute, Michael
Francis at the University of Massachusetts Medical School, William Schafer
at University of Cambridge, and Andrew Leifer at Princeton University. In
addition, the organization has received
computing input from the likes of Netta Cohen at Leeds University and Christian Grove at the California Institute of
Technology (Cal Tech).
The Open Worm project is now nearly seven years old. Larson estimates the
project is 80% of the way toward achieving its first goal: assembling a digital
model of the worm that allows researchers to simulate movement through simulated viscous fluids. The team hopes to
achieve this milestone by late this year.
This has involved mapping cells and
functions in the worm’s body, develop-
ing software to run simulations, build-
ing a digital model of C. elegans, and
constructing an algorithm that simu-
lates the worm’s muscle movements—
including how electrical signals travel
through its brain and nervous system.
So far, researchers at Caltech have
developed the OpenWorm Browser,
which relies on a Web or iOS interface
to display a three-dimensional anatomical model and actions for C. elegans.
The browser displays different layers,
including the skin, alimentary system,
nervous system, reproductive system,
and body wall muscles. In addition, a
program called Sibernetic uses a C++
algorithm to model and simulate contractile matter and membranes within
the muscle tissue of the C. elegans. Another platform, Gepetto, provides an
open source Web-based neuroscience
simulation and visualization environment that simulates complex biological systems and their surrounding environment using multiple algorithms.
Not surprisingly, the data process-
Cracking the Code
ing challenges related to OpenWorm
and developing a life-like digital mod-
el are enormous; the overall task of
understanding things like synthesis,
reproduction, and digestion will likely
take several more years. For now, re-
searchers rely on a combination of
classical mathematical and analytics
tools along with machine learning to
decode functions at the level of ion
channels and cells. “Cells have a lot
of extra machinery in them that is dif-
ficult to detect, and many of these ac-
tivities and processes are completely
ignored by artificial neural nets,” Lar-
son says. Simply put: mountains of
data produce incremental gains, and
coordinating all the research groups
and silos is a complex endeavor. Ulti-
mately, “We may need to get to a new
type of computing process to under-
stand the exotic dynamics of natural
neural systems,” he says.
The OpenWorm project is one of several current attempts to unravel the
mysteries of living things.
For example, Virtual Fly Brain—a
joint effort involving the University of
Edinburgh, University of Cambridge,
MRC Laboratory of Molecular Biology,
Cambridge, and the European Bioinformatics Institute—is mapping the
physiology of the household fly.
In 2012, Jonathan Karr at the Institute for Genomics & Multiscale Biology Institute at the Mt. Sinai School of
Medicine in New York City assembled
the first whole-cell model of
Mycoplas-ma genitalium, a pathogenic bacterium
that resides in humans. The model
succeeded in predicting the viability of
cells after genetic mutations.
In 2016, Stanford University bioengineering professor Markus W.
Covert and a team of researchers developed a whole-cell computational
model; they used detailed information
from more than 900 scientific journals
to gain insights into previously unobserved cellular behaviors.
There’s also the work of Henry
Markram, a professor of neuroscience
at the École Polytechnique Fédérale de
Lausanne in Switzerland, director of
that institution’s Laboratory of Neural
Microcircuitry, and founder and director of the Swiss Blue Brain Project
national brain initiative. His research
has focused on synaptic plasticity and
the microcircuitry of the neocortex.
In 2005, he launched the initiative in
order to reconstruct and simulate the
mammalian brain, starting with the rodent neocortical column. Markram and
fellow researchers are now attempting
to reverse-engineer the circuitry of the
brain—something that could radically
redefine health and medicine.
Make no mistake, these projects extend far beyond a basic understanding
of physiological mechanisms. An organism’s behavior is affected by numerous
factors, ranging from its environment
to its genetics. This means that even
when scientists decode the genome of
a creature such as C. elegans, it remains
Mountains of data
all the research
groups and silos is
a complex endeavor.