Abstracts

Dynamic Biological Modeling: Abstractions, Algorithms & Logic

Monday, August 10th, 2015

Computational Modeling Animal Development: Towards a Whole Embryo Model of the Nematode Caenorhabditis Elegans

9:30 am–10:30 am

Speaker: Alex Hajnal, University of Zürich

The Nematode Caenorhabditis elegans is one of the best studied animal model organisms in Biology. Once the oocyte has been fertilized, it develops in with an invariant pattern of cell divisions (cell lineage) into an animal consisting of exactly 959 cells with a fixed body plan. Moreover, the development of the Caenorhabditis elegans embryo can be followed at single cell resolution while the dynamic changes in gene expression are observed in real time. We will present our efforts to create the first whole embryo computational model that incorporates the current knowledge about the genetic network controlling cellular differentiation. We are using a simple syntax to describe the cell-cell interactions that give each cell in the developing embryo its specific identity. Furthermore, we are using lineage simulations to test the effects of different perturbations on the cell division pattern. Computational modeling may be used to predict how environmental changes affect a developing embryo.

Questions & Challenges in Immunology

11:00 am–12:00 pm

Speaker: Russell Vance, UC Berkeley

The immune system is a complex biological system that is responsible for the detection and elimination of foreign invaders, including viruses, bacteria and even tumor cells. A successful immune response involves a coordinated and highly regulated response among numerous cell types and molecules in the body. In general, most immune responses are successful, and lead to elimination of the foreign invader with minimal collateral damage to the host. However, in rare cases, immune responses can fail, resulting in host damage or death. Failure can arise either because the response is insufficient, and the invader thus replicates unchecked, or because the response is overly exuberant, resulting in immune-mediated damage to the host. Successful immune responses require an optimal trade off between these two extremes. For the most part, the last century of immunology has been a highly reductionist attempt to catalog the cells of the immune system, and the molecules that regulate their function. This endeavor has been highly successful, but a systems level quantitative understanding of how all the parts of the immune system function together remains a significant challenge. In my talk I will focus on the principles governing immune activation, and will provide a specific example of a strategy the immune system might use to balance the need to respond against invaders against the risks of an overexuberant response.

Systems Biology of ncRNA– From Biology to Networks to Targets

1:30 pm–2:30 pm

Speaker: Prahlad Ram, UT MD Anderson Cancer Center

No abstract available.

Questions & Challenges in Cancer Biology

3:00 pm–4:00 pm

Speaker: Gerard Evan, University of Cambridge

No abstract available.

Questions & Challenges in Cancer Biology

Tuesday, August 11th, 2015

Challenges in Integrative Modeling of Gene Regulation, Protein Signaling, and Metabolism

9:30 am–10:30 am

Speaker: Ernest Fraenkel, Massachusetts Institute of Technology

No abstract available.

Challenges in Integrative Modeling of Gene Regulation, Protein Signaling, and Metabolism

What We Can Learn from Single-Cell Data

11:00 am–12:00 pm

Speaker: Calin Guet, IST Austria

Population level measurements are not always informative about the underlying molecular structure of biological networks. Therefore the biology of single cells is essential for understanding how cells work and ultimately indispensable for building correct mathematical models. Using bacteria as an example, I will discuss the insights that one can gain using modern technologies that probe gene expression of single cells in real time.

What We Can Measure Today, Tomorrow, and Which Experiments are Useful for Model Inference

1:30 pm–2:30 pm

Speaker: Alejandro Wolf-Yadlin, University of Washington

No abstract available.

What We Can Measure Today, Tomorrow, and Which Experiments are Useful for Model Inference

Next Steps in Functional Genomics

3:00 pm–3:30 pm

Speaker: Lior Pachter, UC Berkeley

No abstract available.

Mapping Cell Network Signaling to Clinical Outcomes

3:30 pm–4:00 pm

Speaker: Amina Qutub, Rice University

No abstract available.

Wednesday, August 12th, 2015

Successes and Challenges in Executable Biology

9:30 am–10:30 am

Speaker: Jasmin Fisher, Microsoft Research & University of Cambridge

No abstract available.

Opportunities in Executable Biology: Modeling Transcriptional Regulation with New Types of High-Throughput Data

11:00 am–12:00 pm

Speaker: Nir Yosef, UC Berkeley

Some of the most fundamental yet largely unresolved questions in genomic analysis revolve around how gene-regulatory “inputs” (e.g., binding by transcription factors or chromatin modifying enzymes at a certain DNA region) generate an “output” of mRNA expression. The development of new genomic technologies opens the way for addressing such questions in unprecedented detail. One recent example is Massively Parallel Reporter Assay, which allows for cost effective, high-throughput activity screening of thousands of synthetic regulatory DNA regions (promoters or enhancers). This nascent technology can be used to systematically probe the dependencies between regulatory “input” factors, thus opening the way for detailed models of combinatorial effects. Another recent technology, single-cell RNA-Seq provides a genome-scale view of cell-to-cell variability in mRNA expression. The ensuing data can be potentially utilized to calibrate models so as to capture the non-deterministic nature of transcriptional regulation. In this talk I will briefly present these two advances, discuss their potential to improve our ability to build accurate models of transcriptional regulation, and point out some of the challenges that lay ahead.

Synthesis of Executable Models

1:30 pm–2:00 pm

Speaker: Ras Bodik, University of Washington

How to Build a Living Cell in Software (Or: Can We Computerize a Bacterium?)

2:00 pm–2:45 pm

Speaker: Tom Henzinger, IST Austria

The living cell is the ultimate reactive system, reacting to physical and chemical stimuli through cellular processes such as growth, movement, signaling, and division. The standard mathematical model for well-stirred mixtures of interacting molecules is unable to capture this fundamentally reactive nature of a cell. On the other hand, a reactive model that passes a Turing-like test among biologists will rest on answers to many open questions: what is the appropriate notion of state (temporal memory) and how does it change? What roles do space, time, and probability play? What are relevant events and how do they link cellular processes? We explore these and other challenges on the way towards building a virtual molecular biology lab.

How to Build a Living Cell in Software (Or: Can We Computerize a Bacterium?)

Rule-Based Modeling of Graph-Like Systems

3:15 pm–4:00 pm

Speaker: Sandro Stucki, Ecole Polytechnique Federale de Lausanne (EPFL)

Rule-based modeling (RBM) is a paradigm for describing combinatorially complex stochastic processes with an underlying network structure through a finite set of rewrite rules. In this talk, I will give an overview of RBM -- illustrating how it can been used to model biological process in particular -- and present some recent work on generating rate-equations and ODEs tracking higher order statistics from a large class of rule-based systems.

Rule-Based Modeling of Graph-Like Systems

Thursday, August 13th, 2015

Challenges in Formal Reasoning About Signaling Networks

9:30 am–10:00 am

Speaker: Carolyn Talcott, SRI International

The key challenge to reasoning about signalling networks is obtaining networks that are grounded in experimental findings and support assembly of executable models. The talk will begin with a brief overview of the Pathway Logic representation system, analysis tools, and curated knowledge bases. Challenges to expanding the knowledge bases, assembling executable models from formal knowledge, scaling reasoning to larger models, and to moving from qualitative reasoning to semi-quantitative reasoning and analysis of specific models will be discussed.

Challenges in Formal Reasoning About Signaling Networks

Parallel Composition in Biology

10:00 am–10:30 am

Speaker: Nir Piterman, University of Leicester

Over the past decade executable biology has proven itself as a useful tool for supporting understanding of biological processes. Executable biology covers very distinct approaches to modelling that treat biology at different levels of granularity. In this talk, we will touch upon our work that sees cells as state machines and combines machines for different cells to create a larger model that allows to study cell-cell interaction and communication as well as intra-cellular processes. This level of modelling imposes certain restrictions on the way cell programs are updated in a simulation and on the types of analysis that can be applied to them. I will survey some of our approaches for putting cells together and how these affect our ability to analyze these models.

Parallel Composition in Biology

Successes and Challenges of Modelling and Verification at the Nanoscale

11:00 am–11:30 am

Speaker: Marta Kwiatkowska, University of Oxford

The study of molecular networks has been central to providing important insight into the nature of cellular mechanisms and their role in diseases and evolutionary processes. As well as assisting in biological advances, rigorous understanding of molecular networks is also needed when designing molecular-scale synthetic devices and nanorobots, for which a wide range of promising applications, from biosensors to smart therapeutics, have been envisaged. The inherent stochasticity of molecular networks necessitates probabilistic modelling, and to this end probabilistic verification techniques have been added to the repertoire of stochastic analysis methods, enabling the use of temporal logic to explore the network dynamics. This lecture will give an overview of how probabilistic modelling and verification techniques have been used to advance scientific discovery through predictive modelling carried out alongside experiments for molecular signalling pathways, and how this technology is being transferred to support the design processes at the nanoscale, including guiding assembly pathways of DNA origami, debugging of DNA logic circuits and ensuring reliability of computation with molecular walkers. Future research challenges in the field will also be discussed.

Successes and Challenges of Modelling and Verification at the Nanoscale

Dynamical Systems Biology

11:30 am–12:00 pm

Speaker: Oded Maler, CNRS-VERIMAG

In this talk I argue that progress in Biology requires, among other things, a more modern approach to modeling and analysis of dynamical models. Such models should not be restricted to classical dynamical systems but also involve concepts and ideas from discrete-event dynamical systems (automata) and hybrid (discrete-continuous) systems. I will present some recent techniques for exploring the dynamics of under-determined systems, that is, systems that admit uncertainty in initial conditions, parameters and environmental conditions. These techniques, inspired by formal verification, can be used to assess the robustness of proposed models and increase our confidence in their plausibility.

Dynamical Systems Biology

Combining Computational Modelling with Experimentation to Understand Immune System Function

1:30 pm–2:00 pm

Speaker: Mark Coles, University of York

Abstract: Computational and mathematical approaches when combined with experimentation can provide unique insights into mechanisms driving immunity to pathogens and formation of inflammatory and autoimmune pathology. Immune responses occur in specialised microenvironments where stochastic interactions between different immune cells and secreted factors (cytokines/chemokines), lead to the emergence of immune responses. These processes can be simulated using multiscale agent based models reproducing spatial and temporal aspects of the biology. In this talk I will discuss the modelling process, using principles from systems engineering to develop transparent models using a suite of argumentation, statistical analysis and visualisation tools. These tools permits both parameterisation of complex models and effective communication between experimental biologists and software engineers. As an experimental immunologist my research focuses is on how immune microenvironments are established, how they remodel during infection and how cellular interactions drive immune responses. In this talk I will discuss two examples where we have used a cyclical approach of hypothesis driven multi-scale agent based model with experimentation to develop new insights into immune tissue development and emergence of autoimmune disease pathology.

Select recent publications:

Using argument notation to engineer biological simulations with increased confidence. K.Alden, P.S.Andrews, F.A.C.Polack, H.Veiga-Fernandes, M.C.Coles, J.Timmis. Journal of the Royal Society Interface. doi: 10.1098/rsif.2014.1059

Determining Disease Intervention Strategies Using Spatially Resolved Simulations. M. Read, P. Andrews, J. Timmis, R. Williams, R. Greaves, H. Sheng, M. Coles and V. Kumar. PLoS ONE 8(11): e80506. doi:10.1371/journal.pone.0080506

SPARTAN: A Comprehensive Tool for Understanding Uncertainty in Simulations of Biological Systems. K. Alden, M. Read, J. Timmis, P.S. Andrews, H. Veiga-Fernandes, M.C. Coles. PLoS Comput Biol 9(2): e1002916. doi:10.1371/journal.pcbi.1002916

Differential RET signaling responses orchestrate lymphoid and nervous enteric system development. A. Patel, N. Harker, L. Moreira-Santos, M. Ferreira, K. Alden, J. Timmis, K. Foster, A. Garefalaki, P. Pachnis, P.S. Andrews, H. Enomoto, J. Milbrandt, V. Pachnis, M.C. Coles, D. Kioussis, H. Veiga-Fernandes. Science Signalling, Volume 5, Issue 235. doi: 10.1126/scisignal.2002734

Pairing experimentation and computational modelling to understand the role of tissue inducer cells in the development of lymphoid organs. K. Alden, J. Timmis, P.S. Andrews, H. Veiga-Fernandes, M.C Coles. Frontiers in Immunology. Volume 3:172. doi: doi: 10.3389/fimmu.2012.00172.

Combining Computational Modelling with Experimentation to Understand Immune System Function

Questions and Challenges in Tissue and Whole Organ Modeling

2:00 pm–2:30 pm

Speaker: Radu Grosu, Technical University of Vienna

One of the greatest challenges in systems biology is the prediction and control of abnormal cardiac behaviour in humans. The dimension of this challenge can be better appreciated if one considers that five billion cells synchronise within a very intricate electrical, mechanical, and vascular system, in order to jointly achieve what is commonly known as a heart beat, pumping the blood through the entire organism. Modelling, analysis and control of this multi-scale system is a multidisciplinary activity, requiring the interaction between physicians, biologists, physicists, engineers and computer scientists. Two common themes of this joint activity are abstraction and composition. The first allows to ignore the aspects of a system which are irrelevant for a particular question. The second allows to divide and conquer the complexity of a system. In this talk I will revise the cardiac abstractions and composition-techniques developed so far, review their strengths and weaknesses, and give a short outlook for the future work

Questions and Challenges in Tissue and Whole Organ Modeling

Challenges in Network Biology

3:00 pm–3:30 pm

Speaker: Roded Sharan, Tel Aviv University

Protein networks have become the workhorse of biological research in recent years, providing mechanistic explanations for basic cellular processes in health and disease. However, these explanations remain topological in nature as the underlying logic of these networks is to the most part unknown. In this talk I will describe the work in my group toward the automated learning of the Boolean rules that govern network behavior under varying conditions. I will highlight the algorithmic problems involved and demonstrate how they can be tackled using integer linear programming techniques.

Challenges in Network Biology

Levels of Abstraction: From Stochastic to Continuous to Discrete

3:30 pm–4:00 pm

Speaker: David Dill, Stanford University

For several years, we have been investigating the hypothesis that some biological control systems, such as that of the cell cycle, can be modeled as asynchronous circuits. Most digital systems are synchronous, meaning that there is a regular global clock that keeps everything in time. Asynchronous circuts are an alternative style digital circuit where individual components are assumed to react after arbitrary delays. It is unlikely that cells have a global clock to control timing, and so, if they are digital, they must be more like asynchronous than synchronous circuits.

However, we have recently observed discrepancies between our digital models and the actual behavior of bacterial cells in experiments. In several cases, the model predicts that knocking out a key signal would halt the cell cycle at a particular stage, but, in experiments, the cell cycle is temporarily suspended and then resumes. This behavior is interesting because it makes cells robust to inactivation or deletion of key genes.

One explanation for this behavior is that the digital abstraction breaks down because "false" is not quite false. Transcription sometimes continues at low levels, leading to slow buildup of a transcription factor which, under normal circumstances, has no effect, but, when the cell cycle is abnormally halted, can result in resumption of a stalled process. This effect can occur in both continuous and stochastic models.