-
Notifications
You must be signed in to change notification settings - Fork 0
Expand file tree
/
Copy pathcell.html
More file actions
156 lines (129 loc) · 6.38 KB
/
cell.html
File metadata and controls
156 lines (129 loc) · 6.38 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
<HTML>
<CENTER><A HREF = "main.html">Return to Steve Plimpton's home page</A>
</CENTER>
<HR>
<H3>Biological Cell Modeling
</H3>
<P>Whole-cell modeling is a grand challenge for computational biology in
the 21st century (see 2001 paper with that title by M Tomita, Trends
in Biotechnology, 19, 205-210). The following images give you a sense
of what is involved for a single E. Coli cell, a cylindrical-shaped
cell 2 microns long by 1 micron wide. Click on any of them for larger
versions.
</P>
<A HREF = "images/ecoli_expt.jpg"><IMG SRC = "images/ecoli_expt_small.jpg"></A>
<A HREF = "images/ecoli_book.jpg"><IMG SRC = "images/ecoli_book_small.jpg"></A>
<A HREF = "images/ecoli_ccell.png"><IMG SRC = "images/ecoli_ccell_small.png"></A>
<P>On the left is a fluorescent image (off the WWW, sorry but I have lost
the reference). In the middle is a biologist/artist rendition by
D. S. Goodsell from the cover of his great book, The Machinery of
Life, Springer-Verlag, 1993. On the right is a snapshot of a
simulation model from ChemCell (see below).
</P>
<P>The "parts list" for what is inside an E. Coli cell is not that large:
4300 genes, 60K ribosomes, 2M proteins, a few 10M small organic
molecules, a few 100M ions, and 70% water. I say "not that large"
because big computers can now simulate particle models with billions
of particles. So if 1 particle = 1 molecule and the rules for how
such particles move and interact were understood and could be encoded
in the model (e.g. as biochemical reactions occurring at specicied
rates), then it should be possible to simulate "life", at least at the
level of an E. Coli cell as it responds to its environment, grows,
reproduces, etc. And from there it is a small conceptual leap to
using such a computational model to ask and answer "what if" questions
about how cells will respond if their genetic makeup is modified or
they are put in different environements.
</P>
<P>Of course many cells are much larger and more complex than E. Coli,
but there are a lot of years left in the 21st century.
</P>
<HR>
<P>Our small contribution to this field has been to develop a
particle-based cell simulator with spatial information, where
particles represent proteins or other biomolecules. Particles diffuse
via Brownian motion within a cellular geometry bounded by simple
geometric regions or triangulated surfaces that represent cellular or
organelle membranes. Reactions between nearby particles are carried
out via Monte Carlo rules to model an input set of chemical rate
equations. For large-scale models, these computations can be
performed in parallel, where the simulation domain and particles are
partitioned across processors.
</P>
<P>Our open-source simulator is called <A HREF = "https://sjplimp.github.io/chemcell">ChemCell</A>.
Documentation, images, movies, and download information are available
on the <A HREF = "https://sjplimp.github.io/chemcell">ChemCell website</A> and the <A HREF = "https://sjplimp.github.io/chemcell/doc/Manual.html">ChemCell doc
pages</A> describes the software in more detail.
</P>
<P>ChemCell is similar in spirit to other particle-based biological cell
simulators such as <A HREF = "http://www.mcell.cnl.salk.edu">MCell</A>, <A HREF = "http://www.smoldyn.org">Smoldyn</A>, and
<A HREF = "http://mesord.sourceforge.net">MesoRD</A>. Other popular cell simulators include VCell, which
models reaction/diffusion via continuum PDEs in a spatial
representation of a cell, and E-Cell which has a rich variety of
continuum and stochastic solvers for non-spatial cell models.
</P>
<P>Collaborators on ChemCell:
</P>
<UL><LI> Alex Slepoy, Sandia
<LI> Larry Lok and Roger Brent, TMSI
</UL>
<HR>
<P>These papers discusses results from signaling network analyses performed
with ChemCell:
</P>
<P><B>Statistical ensemble analysis for simulating extrinsic noise-driven
response in NF-kappa B signaling networks</B>, J. Joo, S. J. Plimpton,
J. L. Faulon, BMC Systems Biology, 7, 45 (2013).
(<A HREF = "abstracts/bmc13.html">abstract</A>)
</P>
<P><B>Sensitivity Analysis of a Computational Model of the IKK-NF-kB-A20
Signal Transduction Network</B>, J. Joo, S. J. Plimpton, S. Martin,
L. Swiler, J. L. Faulon, Annals of the New York Acadamey of Sciences,
Volume on Reverse Engineering Biological Networks, 1115, 221-239
(2007). (<A HREF = "abstracts/annals07.html">abstract</A>)
</P>
<P>This paper gives a brief overview of ChemCell and computational
challenges for cell modeling:
</P>
<P><B>Microbial cell modeling via reacting diffusing particles</B>,
S. J. Plimpton and A. Slepoy, Journal of Physics: Conference Series
16, 305-309 (2005). (<A HREF = "abstracts/jp05.html">abstract</A>)
</P>
<P>This paper is about our <A HREF = "http://www.genomes2life.org">Genomics:GTL (Genomes-to-Life) project</A>
funded by DOE's OBER and OASCR offices, that provided funding and
motivation for the development of ChemCell. The author list is the
entire project team!
</P>
<P><B>Carbon Sequestration in Synechococcus Sp.: From Molecular Machines to
Hierarchical Modeling</B>, G. S. Heffelfinger, ..., S. J. Plimpton, ...,
OMICS - A Journal of Integrative Biology, 6, 305-330
(2002). (<A HREF = "abstracts/omics02.html">abstract</A>)
</P>
<HR>
<P>I have also worked on agent-based modeling (ABM) of cells where an
entire cell is a single "agent" which interacts with other cells and
background extra-cellular species according to a set of complicated
rules. Our ABM was written in Python to be easily extensible, with
calls to C functions to perform numerically intensive operations.
</P>
<P>Collaborators on ABM work:
</P>
<UL><LI> Chi-Chi May (U Houston)
<LI> Cheryl Sershen (Baylor College of Medicine)
</UL>
<P>These papers describes ABM results for infection of lung tissue with
tuberculosis, and the formation of granulomas:
</P>
<P><B>A Method for Modeling Oxygen Diffusion in an Agent-based Model with
Application to Host-Pathogen Infection</B>, C. L. Sershen,
S. J. Plimpton, E. E. May, EMBC'14 Conference (36th Annual Intl Conf
of the IEEE Engineering in Medicine and Biology Society), Chicago, IL,
Aug 2014. (<A HREF = "abstracts/embc14.html">abstract</A>)
</P>
<P><B>Oxygen Modulates the Effectiveness of Granuloma Mediated Host
Response to Mycobacterium tuberculosis: A Multiscale Computational
Biology Approach</B>, C. L. Sershen, S. J. Plimpton, E. E. May, Frontiers
in Cellular and Infection Microbiology, 6,
doi:10.3389/fcimb.2016.00006 (2016).
(<A HREF = "abstracts/frontiers16.html">abstract</A>)
</P>
</HTML>