Poster Presentation: Adriana Compagnoni, Paola Giannini, Catherine Kim, Matthew Milideo and Vishakha Sharma. 22nd Annual International Conference on Intelligent Systems for Molecular Biology (ISMB), Boston, MA, July 11 - 15, 2014.

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! We define BioScapeL a new agent based modeling language for the
stochastic simulation of complex systems in 3D space.
! In order to model the assemblies of configurations of polymers,
oligomers, and complexes such as microtubules or actin filaments,
existing modeling approaches require the programmer to deal with the
low level details of collision, confinement, positioning, and diffusion.
! The motivation for BioScapeL comes from the need to describe the
evolution, assembly and polymerization of complex structures of
biochemical species in space, while keeping a sufficiently high level
description, so that tedious and error prone low level details are hidden
from the programmer.
! The proposed solution is to allow the programmer to describe relative
positioning of entities through programmable locations, while keeping
collision, confinement and diffusion as part of the simulation engine, as
opposed to the model created by the programmer.
! Further new aspects of BioScapeL include random translation and scaling.
Random translation is instrumental in describing the location of new
entities relative to the old ones.
RESEARCH POSTER PRESENTATION DESIGN © 2012
www.PosterPresentations.com
! We defined BioScape2 X(x:T) = M!,",# entities have a space where they
can be !, a diffusion rate ", and a shape #.
! Where do new entities go? BioScape only allows the programmer to
describe the area where entities of a given kind are allowed to be.
Adequate for simulating many experiments.
! But the programmer has no control over the exact position or even
relative position of entities.
Bac " Bac | Bac
Bac@p
Bac@p " (Bac | Bac)@p
! The semantics takes care of
placing the product
somewhere around p.
! This works well when the behavior of different species is relatively
similar when it comes to generating new entities. (they stay close-by)
! We want a high level
modeling language that will
allow us to model
microtubules in the cell.
! Why? To model viral traffic.
Viruses ride on microtubules
towards the nucleus of
the cell.
(from www.proteinatlas.org)
Microtubules Polymerization
! Microtubules are dynamic tubulin
polymers; formed with dimers of $
and % tubulin.
! MTPart is a part that assembles to
form an assembly and represents $-
% tubulin polymers.
! MTRight – Start Piece
! MTLeft – End Piece
! MTMiddle – any number of pieces
between the start (right) and the
end (left).
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Bac()@_,_,_ =
do mov.Bac()_(this, 0)
or delay @0.005.(Bac()_this, 0)) | Hion()_(this, rB+rH))
or …..
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Random Translation
Bac()@_,_,_,max-size =
do mov.Bac()_((fst(this), 0), 1.1)
or delay @0.005.(Bac()_((fst(this), 0), 1) | Hion()_((fst(this), rB+rH), 1))
or delay @0.2.(Bac()_((fst(this), rB), 0.5) | Bac()_((fst(this), rB), 0.5))
or …..
Scaling
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! We define a high level language of entities with programmable abstract
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locations.
! Diffusion, distance and confinement remain part of the semantics of the
calculus, instead of being a burden to the programmer.
! Build a framework based on BioScapeL for the computationally assisted
development of antibacterial surfaces.
! Study adenoviral traffic in healthy/cancerous eukaryotic cells.
1. Adriana Compagnoni, Paola Giannini, Catherine Kim, Matthew Milideo, Vishakha Sharma A Calculus of
Located Entities. In the proceedings of the Ninth International Workshop on Developments in
Computational Models (DCM) 2013.
2. Adriana Compagnoni, Vishakha Sharma, Yifei Bao, Matthew Libera, Svetlana Sukhishvili. Philippe
Bidinger, Livio Bioglio and Eduardo Bonelli. BioScape: A Modeling and Simulation Language for
Bacteria-Materials Interactions. Electronic Notes in Theoretical Computer Science, 293(0): 35 - 49,
2013. Proceedings of the Third International Workshop on Interactions Between Computer Science
and Biology (CS2Bio'12).
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P, Q ::= 0 Empty Process
| X(&)& Located Entity Instance
| P | Q Parallel Composition
| ('a@&, & : chan{T}).P Restriction
M ::= (.P [+ M] Choice of Prefixed Process
( ::= delay@& Delay
| !u(&) Output
| ?u(x) Input
| mov Move
N ::= M | ('a@&, & : chan{T}).N Restricted Choice
u ::= a | b | … | x | y | … Identifiers
& ::= u | c | this | &1,...,&n | () | &.i | op(&) Expressions
' ::= a | b | … | c | () | '1,…,'n Expression Values
T ::= chan{T} | fl | T1*…*Tn | ) Expression Types
D ::= 0 | D, X (x:T) = N!,",# FV(M) ! x Entity Definitions
E ::= 0 | E, a@r, rad : chan{T} Channel Declarations
* ::= 0 | *, X:T | *, u:T Type Environment
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… there was the (-calculus
!a(y).P | ?a(x).Q " P | Q[y/x]
!a …|?a…|!b…|?b…
! Non-determinism – all communications (pairs of !/? Reduced) are equally
likely to happen.
! Explosions are fast, cell division is slow, …
! The need to talk about events that happen at different frequencies
motivated probabilistic/stochastic versions (Spi/SPiM).
!a(y).P|?a(x).Q "r P | Q[y/x]
! We can plot quantities over time. Can we display/visualize emergent
behavior?
SPiM Model of bacterial growth and antibacterial agents
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! We cannot describe complex structures: polymers/oligomers/
membranes.
! We cannot describe pre-existing/reactive environment – video games/
antibacterial.
! If we want to start in a pre existing world that has not been
stochastically assembled but designed instead, we need to extend the
language with a programmable location for each entity.
Bac " Bac | Bac
can now be written as:
Bac " Bacthis+<x1,y1,z1> | Bacthis+<x2,y2,z2>
and
Bac@p " (Bac | Bac)@p
becomes:
Bac@p " (Bacthis+<x1,y1,z1> | Bacthis+<x2,y2,z2>))@p =
Bacp+<x1,y1,z1> | Bacp+<x2,y2,z2>