MLCSB 2011 starts next semester

12 October 2010

The new edition of this course for the 2010–2011 session will run in Semester 2, starting in January 2011. The course will be lectured by Professor Jane Hillston.

Link: Models and Languages for Computational Systems Biology 2010–2011

Lecture 17: Compartments in BioPEPA

18 March 2010

Working through the following paper:

  • Federica Ciocchetta and Maria Luisa Guerriero. Modelling Biological Compartments in Bio-PEPA, in MeCBIC 2008: Proceedings of the Second International Meeting on Membrane Computing and Biologically Inspired Process Calculi. Electronic Notes in Theoretical Computer Science 227:77–95, January 2009.

Adding compartments to BioPEPA: syntax; compositional operational semantics; structured locations including compartments, membranes, and the boundaries between them; appropriate kinetics; sample model of intracellular calcium oscillations.


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Lecture 16: Modelling tools for Bio-PEPA

16 March 2010

Guest lecture by Stephen Gilmore explaining and demonstrating the BioPEPA tools, principally the Eclipse plugin.

2010 Turing Lecture

15 March 2010

Embracing Uncertainty: The New Machine Intelligence

Christopher Bishop
Microsoft Research Cambridge
5.00pm / 5.30pm Thursday 18 March 2010
Appleton Tower

Computers are traditionally viewed as logical machines which follow precise, deterministic instructions.

The real world in which they operate, however, is full of complexity, ambiguity, and uncertainty. In this year’s Turing Lecture, Professor Chris Bishop discusses the field of machine learning, and shows how uncertainty can be modelled and quantified using probabilities.

He looks at the recent developments in probabilistic modelling which have greatly expanded the variety and scale of machine learning applications, and he explores the future potential for this technology.

In honour and recognition of Alan Turing’s contribution in the field of computing, the IET and the BCS established the Turing Lecture in 1999. It is a world leading event, presenting a topic from current research in computer science given by an acknowledged expert in the field.

Professor Bishop is Chief Research Scientist at the Microsoft Research Laboratory in Cambridge, and also holds a Chair in Computer Science in The University of Edinburgh School of Informatics. He presented the 2008 Royal Institution Christmas Lectures Hi-Tech Trek — The Quest for the Ultimate Computer.

He’s an excellent speaker, and this looks to be an interesting talk about recent advances in and applications of machine learning. There is a reception at 5pm, with the lecture at 5.30pm, and a ticket-only event afterwards. The lecture is free, but the IET ask for registration; which in turn means you need to create an account at the IET website; which means handing over address, phone number, eye colour, etc. Sorry about that.

Links: Registration; Video of this lecture in London; The British Computer Society on the Turing Lecture; The Institution of Engineering and Technology on the Turing Lecture.


11 March 2010

Complementary Approaches to Understanding the Plant Circadian Clock

Maria Luisa Guerriero
Centre for Systems Biology at Edinburgh
11am Friday, 12 March, 2010
Room 3.02, Informatics Forum

Links: Seminar abstract; About PEPA Club.

This talk describes a BioPEPA model for the circadian clock in the green alga Ostreococcus tauri, demonstrating in particular the use of BioPEPA to drive many different kinds of analysis of the same model.

Dr Guerriero is a researcher at CSBE working on formal verification of process algebra models for systems biology. This talk is a rehearsal for a presentation at the FTBC 2010 workshop From Biology To Concurrency and Back in Cyprus later this month.

Lecture 15: Process Algebras for Systems Biology

11 March 2010

Background on process algebras / process calculi: what they can be useful for, and various domains where they have been applied. Specific applications to systems biology; and the wide range of process calculi proposed for different aspects of biological systems.

Brief introduction to PEPA and BioPEPA, with reference to Ciocchetta and Hillston (2009).

Link: Slides.

Lecture 14: Continuous Petri Nets and Differential Equations

8 March 2010

Moving from discrete events to continuous flow: semantics of continuous Petri nets; correspondence with chemical reaction equations; deriving ordinary differential equations (ODEs); conservation laws, equilibria, numerical solutions and trajectories through phase space. Relating transition rates for discrete events to reaction rates for continuous flow; dependence on reaction stoichiometry.

Some examples, including derivation of Michaelis-Menten semantics.

Thursday’s lecture will be an introduction to BioPEPA, followed by Stephen Gilmore on Monday.

Link: Slides.


Read §§6–9 of Heiner et al., and §§1–4 of Ciocchetta and Hillston, on BioPEPA.

This earlier paper by Gilbert and Heiner also explains modelling biological processes with continuous Petri nets.

Assignment 2: Modelling in BioPEPA

5 March 2010

The second coursework assignment is now out, and due on Thursday 25 March, three weeks from now.

The assignment involves modelling a small signalling pathway using the BioPEPA language. Lecture 14, on Thursday 11 March, will include an introduction to BioPEPA; and Stephen Gilmore will give a guest lecture presenting the Eclipse plugin for BioPEPA on Monday 15 March.

The exercise is fairly open-ended, and you should feel free to modify it and follow your own investigations as you find appropriate. If you have find (or solve) any particular difficulties, especially with the modelling tools or other technical issues, please post comments below.

Links: Assignment 2; BioPEPA; The BioPEPA Eclipse plugin.

Lecture 13: More Stochastic Kinetics

5 March 2010

More on Gillespie’s algorithm for stochastic simulation, including the remainder of the slides from Gillespie’s invited CMSB talk. Various tau-leaping methods to more efficiently simulate larger systems; concerns about bounding the errors in these approximate techniques. Further approximation with continuous models, still stochastic, and then by deterministic systems of differential equations for even large scales.

This is discussed in Chapter 8 of Wilkinson’s book on stochastic modelling.

You can also read Gillespie’s own papers on this: his original SSA proposal, and a more recent survey of progress since then.

Return of coursework, and discussion of some particular issues.

  • Reachability graph for the repressilator model.
  • Drawing subnets arising from transition and place invariants.
  • Eight minimal place invariants for the ECA synthesis network; invariants for preservation of uridine, saccharide, phosphate and undecaprenyl groups.
  • Logical formulae in LTL, CTL and HML: decoding and coding them.
  • The until connective denotes that the statement will eventually hold; release may not.
  • HML must modality [a]p means that if a happens, p is then true — but it doesn’t say anything about whether a does happen, or is even possible.

Any more questions or answers about the coursework, please post on the comments below.

Lecture 12: Large Systems and Stochastic Kinetics

2 March 2010

Revisiting Kwiatkowska et al. on probabilistic model-checking for systems biology. Moving from models of a single protein to slightly larger populations, still with symbolic model-checking.

The problem of state-space explosion, and the use of simulation. Gillespie’s algorithm for stochastic simulation. I’m using the slides from Gillespie’s invited talk at CMSB 2007 in Edinburgh. So far we have covered the approximation from precise dynamic simulation of all positions and velocities, down to stochastic simulation of populations through modelling only reactive molecular collisions. This gives the exact SSA; next are various tau-leaping methods for efficient approximation.

Wilkinson’s book on stochastic modelling covers the Gillespie algorithm in §§6.2–6.5, with Chapter 8 then going on to deal with approximation strategies.

Links: Slides; Gillespie on Stochastic Chemical Kinetics; All CMSB 2007 talks.