Agile Modelling of Cellular Signalling (Invited Paper)

AbstractWe illustrate with a simple example how using a rule-based approach to the modelling of protein interaction networks allows for quickly putting together models (ease of expression), and quickly modifying them (ease of variation)

Compact Representation of Photosynthesis Dynamics by Rule-based Models (Full Version)

Traditional mathematical models of photosynthesis are based on mass action kinetics of light reactions. This approach requires the modeller to enumerate all the possible state combinations of the modelled chemical species. This leads to combinatorial explosion in the number of reactions although the structure of the model could be expressed more compactly. We explore the use of rule-based modelling, in particular, a simplified variant of Kappa, to compactly capture and automatically reduce existing mathematical models of photosynthesis. Finally, the reduction procedure is implemented in BioNetGen language and demonstrated on several ODE models of photosynthesis processes. This is an extended version of the paper published in proceedings of 5th International Workshop on Static Analysis and Systems Biology (SASB) 2014.Comment: SASB 2014 full pape

Thermodynamic graph-rewriting

We develop a new thermodynamic approach to stochastic graph-rewriting. The ingredients are a finite set of reversible graph-rewriting rules called generating rules, a finite set of connected graphs P called energy patterns and an energy cost function. The idea is that the generators define the qualitative dynamics, by showing which transformations are possible, while the energy patterns and cost function specify the long-term probability $\pi$ of any reachable graph. Given the generators and energy patterns, we construct a finite set of rules which (i) has the same qualitative transition system as the generators; and (ii) when equipped with suitable rates, defines a continuous-time Markov chain of which $\pi$ is the unique fixed point. The construction relies on the use of site graphs and a technique of `growth policy' for quantitative rule refinement which is of independent interest. This division of labour between the qualitative and long-term quantitative aspects of the dynamics leads to intuitive and concise descriptions for realistic models (see the examples in S4 and S5). It also guarantees thermodynamical consistency (AKA detailed balance), otherwise known to be undecidable, which is important for some applications. Finally, it leads to parsimonious parameterizations of models, again an important point in some applications

Rule-based epidemic models

Rule-based models generalise reaction-based models with reagents that have internal state and may be bound together to form complexes, as in chemistry. An important class of system that would be intractable if expressed as reactions or ordinary differential equations can be efficiently simulated when expressed as rules. In this paper we demonstrate the utility of the rule-based approach for epidemiological modelling presenting a suite of seven models illustrating the spread of infectious disease under different scenarios: wearing masks, infection via fomites and prevention by hand-washing, the concept of vector-borne diseases, testing and contact tracing interventions, disease propagation within motif-structured populations with shared environments such as schools, and superspreading events. Rule-based models allow to combine transparent modelling approach with scalability and compositionality and therefore can facilitate the study of aspects of infectious disease propagation in a richer context than would otherwise be feasible

Turku Centre for Computer Science – Annual Report 2013

Due to a major reform of organization and responsibilities of TUCS, its role, activities, and even structures have been under reconsideration in 2013. The traditional pillar of collaboration at TUCS, doctoral training, was reorganized due to changes at both universities according to the renewed national system for doctoral education. Computer Science and Engineering and Information Systems Science are now accompanied by Mathematics and Statistics in newly established doctoral programs at both University of Turku and &Aring;bo Akademi University. Moreover, both universities granted sufficient resources to their respective programmes for doctoral training in these fields, so that joint activities at TUCS can continue. The outcome of this reorganization has the potential of proving out to be a success in terms of scientific profile as well as the quality and quantity of scientific and educational results.&nbsp; International activities that have been characteristic to TUCS since its inception continue strong. TUCS&rsquo; participation in European collaboration through EIT ICT Labs Master&rsquo;s and Doctoral School is now more active than ever. The new double degree programs at MSc and PhD level between University of Turku and Fudan University in Shaghai, P.R.China were succesfully set up and are&nbsp; now running for their first year. The joint students will add to the already international athmosphere of the ICT House.&nbsp; The four new thematic reseach programmes set up acccording to the decision by the TUCS Board have now established themselves, and a number of events and other activities saw the light in 2013. The TUCS Distinguished Lecture Series managed to gather a large audience with its several prominent speakers. The development of these and other research centre activities continue, and&nbsp; new practices and structures will be initiated to support the tradition of close academic collaboration.&nbsp; The TUCS&rsquo; slogan Where Academic Tradition Meets the Exciting Future has proven true throughout these changes. Despite of the dark clouds on the national and European economic sky, science and higher education in the field have managed to retain all the key ingredients for success. Indeed, the future of ICT and Mathematics in Turku seems exciting.</p

Designing social media analytics tools to support non-market institutions: Four case studies using Twitter data

This research investigates the design of social media tools for non-market institutions, such as local government or community groups. At the core of this practice-based research is a software tool called LocalNets. LocalNets was developed to collect, analyse and visualise data from Twitter, thereby revealing information about community structure and community assets. It is anticipated that this information could help non- market institutions and the communities with which they work. Twitter users send messages to one another using the ‘@mention’ function. This activity is made visible publicly and has the potential to indicate a Twitter user’s participation in a ‘community structure’; that is, it can reveal an interpersonal network of social connections. Twitter activity also provides data about community assets (such as parks, shops and cinemas) when tweets mention these assets’ names. The context for this research is the Creative Exchange Hub (CX), one of four Knowledge Exchange Hubs for the Creative Economy funded by the UK Arts and Humanities Research Council (AHRC). Under the theme of ‘Digital Public Space’, the CX Hub facilitated creative research collaborations between PhD researchers, academics and non-academic institutions. Building on the CX model, this PhD research forged partnerships between local councils, non-public sector institutions that work with communities, software developers and academics with relevant subject expertise. Development of the LocalNets tool was undertaken as an integral part of the research. As the software was developed, it was deployed in relevant contexts through partnerships with a range of non-market institutions, predominantly located in the UK, to explore its use in those contexts. Four projects are presented as design case studies: 1) a prototyping phase, 2) a project with the Royal Society of Arts in the London Borough of Hounslow, 3) a multi-partner project in Peterborough, and 4) a project with Newspeak House, a technology and politics co-working space located in London. The case studies were undertaken using an Action Design Research method, as articulated by Sein et al. Findings from these case studies are grouped into two categories. The first are ‘Implementation findings’ which relate specifically to the use of data from Twitter. Second there are six ‘situated design principles’ which were developed across the case studies, and which are proposed as having potential application beyond Twitter data. The ‘Implementation findings’ include that Twitter can be effective for locating participants for focus groups on community topics, and that the opinions expressed directly in tweets are rarely sufficient for the local government of community groups to respond to. These findings could benefit designers working with Twitter data. The six situated design principles were developed through the case studies: two apply Burt’s brokerage social capital theory, describing how network structure relates to social capital; two apply Donath’s signalling theory – which suggests how social media behaviours can indicate perceptions of community assets; and two situated design principles apply Borgatti and Halgin’s network flow model – a theory which draws together brokerage social capital and signalling theory. The principles are applicable to social media analytics tools and are relevant to the goals of non-market institutions. They are situated in the context of the case studies; however, they are potentially applicable to social media platforms other than Twitter. Linders identifies a paucity of research into social media tools for non-market institutions. The findings of this research, developed by deploying and testing the LocalNets social media analytics tool with non-market institutions, aim to address that research gap and to inform practitioner designers working in this area

An Overview of Signal Processing Techniques for Joint Communication and Radar Sensing

Joint communication and radar sensing (JCR) represents an emerging research field aiming to integrate the above two functionalities into a single system, by sharing the majority of hardware, signal processing modules and, in a typical case, the transmitted signal. The close cooperation of the communication and sensing functions can enable significant improvement of spectrum efficiency, reduction of device size, cost and power consumption, and improvement of performance of both functions. Advanced signal processing techniques are critical for making the integration efficient, from transmission signal design to receiver processing. This paper provides a comprehensive overview of the state-of-the-art on JCR systems from the signal processing perspective. A balanced coverage on both transmitter and receiver is provided for three types of JCR systems, namely, communication-centric, radar-centric, and joint design and optimization

(Mathematical) Logic for Systems Biology (Invited Paper)

International audienceWe advocates here the use of (mathematical) logic for systems biology, as a unified framework well suited for both modeling the dynamic behaviour of biological systems, expressing properties of them, and verifying these properties. The potential candidate logics should have a traditional proof theoretic pedigree (including a sequent calculus presentation enjoying cut-elimination and focusing), and should come with (certified) proof tools. Beyond providing a reliable framework, this allows the adequate encodings of our biological systems. We present two candidate logics (two modal extensions of linear logic, called HyLL and SELL), along with biological examples. The examples we have considered so far are very simple ones-coming with completely formal (interactive) proofs in Coq. Future works includes using automatic provers, which would extend existing automatic provers for linear logic. This should enable us to specify and study more realistic examples in systems biology, biomedicine (diagnosis and prognosis), and eventually neuroscience