## plenary speakers

**YOH IWASA**

Professor, Theoretical Biology, Kyushu University

**"Coupled social-economic and ecological dynamics: examples from lake water eutrophication, Mongolian rangeland, and illegal logging of tropical forests"**For successful ecosystem management and biodiversity conservation, in addition to ecological and evolutionary processes, we need to consider social and economic influences on the management target. Here, we introduce three models that address economic and social aspects of human society in the context of ecosystem management.

[1] Lake water pollution. Players choose between cooperative (but costly) option and economical option. Their decision is affected by the fraction of cooperators in the community and by the importance of water pollution problem. This social dynamics is coupled with the dynamics of lake water pollution. Oscillation of large amplitude is generated if social change occurs faster than ecosystem responses. If phosphorus is removed more effectively either from the inflow or from the lake water, the pollution level may increase (rather than decrease) due to the decline in people's willingness to cooperate (paradox of nutrient removal).

[2] Herders in a southern Mongolian rangeland. Herders choose foraging sites for their animals in the dry season. If grazing pressure is very strong, the grass biomass becomes depleted and more herders choose to move their animals to an alternative rangeland. They may return to the focal rangeland when the quantity and quality of the grass improves. The system may exhibit bistability with a strong dependence on the initial condition or perpetual large-amplitude fluctuation. Implications for rangeland management are discussed.

[3] Profit-sharing of plantation management. Illegal logging is a very serious threat to tropical forests. The owner chooses the age of trees to cut, and the workers choose their monitoring effort to prevent illegal logging. After the trees were removed, the owner hires workers to replant young trees. Under the presence of illegal logging pressure, the owner may find it profitable to share the income by selling logs with the workers to solicit their monitoring efforts.

[1] Lake water pollution. Players choose between cooperative (but costly) option and economical option. Their decision is affected by the fraction of cooperators in the community and by the importance of water pollution problem. This social dynamics is coupled with the dynamics of lake water pollution. Oscillation of large amplitude is generated if social change occurs faster than ecosystem responses. If phosphorus is removed more effectively either from the inflow or from the lake water, the pollution level may increase (rather than decrease) due to the decline in people's willingness to cooperate (paradox of nutrient removal).

[2] Herders in a southern Mongolian rangeland. Herders choose foraging sites for their animals in the dry season. If grazing pressure is very strong, the grass biomass becomes depleted and more herders choose to move their animals to an alternative rangeland. They may return to the focal rangeland when the quantity and quality of the grass improves. The system may exhibit bistability with a strong dependence on the initial condition or perpetual large-amplitude fluctuation. Implications for rangeland management are discussed.

[3] Profit-sharing of plantation management. Illegal logging is a very serious threat to tropical forests. The owner chooses the age of trees to cut, and the workers choose their monitoring effort to prevent illegal logging. After the trees were removed, the owner hires workers to replant young trees. Under the presence of illegal logging pressure, the owner may find it profitable to share the income by selling logs with the workers to solicit their monitoring efforts.

**EUNOK JUNG**

Professor, Department of Mathematics, Konkuk University

**"Dynamical models of tuberculosis transmission and optimal treatment strategies in the Republic of Korea and Philippines"**In this talk, we will present several mathematical models of tuberculosis (TB) based on the reported data in the Republic of Korea and Philippines, and also propose the optimal treatment strategies depending on the various scenarios in each country. Korea has ranked the highest TB incidence among members of the Organization for Economic Cooperation and Development (OECD). TB is the sixth leading cause of morbidity and mortality in the Philippines. The least-square curve fitting have been used for beat fitting the parameters in our models to the observed data. To determine the optimal intervention strategy which is reducing the number of exposed and infectious individuals and the cost of control measures, optimal control theory was used. Important issues has been addressed from our research: implementing the smoking controls, not with TB controls, can derive significant reduction of the incidence of TB transmission [1]. We suggested the rearrangement of the Korean government TB budget based on optimal treatment strategies from modeling [2]. Finally, in the Philippines enhancing active finding control is a significant control factor to curtail the spread of TB [3].

References

[1] Sunhwa Choi, Eunok Jung, Seok-Min Lee,

[2] Sunhwa Choi, Eunok Jung

[3] Sunhwa Choi, Eunok Jung

[3] Soyoung Kim, Aurelio A. de los Reyes V, Eunok Jung,

References

[1] Sunhwa Choi, Eunok Jung, Seok-Min Lee,

*Optimal intervention strategy for prevention tuberculosis using a smoking-tuberculosis model,*JTB**380**(2015) 256-270[2] Sunhwa Choi, Eunok Jung

**,***Optimal Tuberculosis Prevention and Control Strategy from a Mathematical Model Based on Real Data*, BMB (2014)**76**:1566-1589[3] Sunhwa Choi, Eunok Jung

**,**Sungim Whang,*A dynamic model for tuberculosis transmission and optimal treatment strategies in South Korea*, JTB**279**(2011) 120-131[3] Soyoung Kim, Aurelio A. de los Reyes V, Eunok Jung,

*Mathematical Model and Intervention Strategies for Mitigating Tuberculosis in the Philippines*, JTB (2017) revision**FRANZ KAPPEL**

Em. Univ-Prof., Institute for Mathematics and Scientific Computing, University of Graz

**"Mathematical modeling as an important contribution to precision medicine and challenges arising from this fact"**TBA

**EDUARDO MENDOZA**

Adjunct Professor, University of the Philippines and De La Salle University, Philippines

Guest Scientist, Max Planck Institute of Biochemistry and Ludwig Maximillians University Munich, Germany

**"Mathematical Models of the Mammalian Cell Cycle - B. Aguda's pioneer papers (1999-2005) revisited"**Baltazar D. Aguda (“Baltz” to us) was an active member of the North American community which was the driving force for the emergence of Systems Biology at the turn of the century. His two main contributions to this community´s legacy were his intensive collaboration with the Caltech team that developed SBML (Systems Biology Markup Language) during his sabbatical there in 2001 and his pioneering papers on modeling the mammalian cell cycle between 1999 and 2005. His initial papers (1999-2001) focused on the dynamics of the cell cycle around its two main control points at G1/S and G2/M phase transitions. Together with collaborators between 2003 and 2005, he published the first mathematical models of cellular regulation of the cell cycle and apoptosis. The inclusion of apoptosis aspects also provided an initial connection to work of researchers in the Philippines, who, in collaboration with marine scientists here and pharmaceutical biologists in Munich, had begun in 2004 to model tumor apoptosis induced by marine natural products.

The talk will discuss the impact of Baltz´s pioneer papers from the perspective of the current status of mathematical modeling of the mammalian cell cycle. It will describe some initiatives which have been inspired by the review of his work. One of these activities will target using Chemical Reaction Network Theory (CRNT) methods for comparative analysis of mammalian cell cycle models, which, if successful, would be a small tribute to Baltz´s pioneer work in both areas.

The talk will discuss the impact of Baltz´s pioneer papers from the perspective of the current status of mathematical modeling of the mammalian cell cycle. It will describe some initiatives which have been inspired by the review of his work. One of these activities will target using Chemical Reaction Network Theory (CRNT) methods for comparative analysis of mammalian cell cycle models, which, if successful, would be a small tribute to Baltz´s pioneer work in both areas.

**OLAF WOLKENHAUER**

Professor, Department of Systems Biology and Bioinformatics, University of Rostock, Germany

*"Modelling whole-part relationships in living systems*

*"*With my research, I am studying how molecular, cellular and tissue-level functions emerge from the interactions between molecules and cells ... and how these emergent properties of the whole enable/constrain the behaviour of the system’s parts. In other words, I am interested in tissue organisation and whole-part relationships in living systems.

More specifically, I am here trying to understand how the functioning of epithelial cells and their intestinal tissue are related. I shall here focus on ”tissue-2-cell” determination, where the tissue provides a stimulus to the cells. Since the tissue and its cells reciprocally determine the functioning of each other, I shall focus on one half of the overall picture.

Starting with an abstract representation of the tissue as a stimulus and cellular responses, I am going to derive, step-by-step, those state space representations that we are familiar with from dynamical systems theory. The vast majority of mathematical models in the natural, physical and engineering sciences are using difference, differential equations or automata, where the behaviour of the system is captured through transitions of states.

My approach is thus to start with a formal, general representation of how tissue and cells relate to each other. Zooming in to the response of the cells to the stimuli of the tissue, the derivation of the mechanistic state space representation of causal intracellular interactions, we make a surprising discovery that the tissue and cell levels are interdependent but not causally linked: While intralevel relations (e.g. intracellular relations) can be describe as ‘causal interactions’, interlevel relations between cells and their tissue are best described as ‘constituent interdependence’.

The main result that I will present here is an argument that there is no top-down causation but ‘coordination’; the cell has some degree of ‘autonomy’, it interprets its environment.

More specifically, I am here trying to understand how the functioning of epithelial cells and their intestinal tissue are related. I shall here focus on ”tissue-2-cell” determination, where the tissue provides a stimulus to the cells. Since the tissue and its cells reciprocally determine the functioning of each other, I shall focus on one half of the overall picture.

Starting with an abstract representation of the tissue as a stimulus and cellular responses, I am going to derive, step-by-step, those state space representations that we are familiar with from dynamical systems theory. The vast majority of mathematical models in the natural, physical and engineering sciences are using difference, differential equations or automata, where the behaviour of the system is captured through transitions of states.

My approach is thus to start with a formal, general representation of how tissue and cells relate to each other. Zooming in to the response of the cells to the stimuli of the tissue, the derivation of the mechanistic state space representation of causal intracellular interactions, we make a surprising discovery that the tissue and cell levels are interdependent but not causally linked: While intralevel relations (e.g. intracellular relations) can be describe as ‘causal interactions’, interlevel relations between cells and their tissue are best described as ‘constituent interdependence’.

The main result that I will present here is an argument that there is no top-down causation but ‘coordination’; the cell has some degree of ‘autonomy’, it interprets its environment.

## INVITED SPEAKERS

**RICARDO C.H. DEL ROSARIO**

Scientific Staff, Broad Institute, Boston, USA

**"Mathematical and computational analysis of a model of microRNA regulation of the R point switch of the cell cycle"**The restriction point R is a cell cycle checkpoint at the G1/S transition in which the cell decides whether to proceed to DNA replication or to enter a quiescent state. After this point, the cell commits to the remainder of the cell cycle independent of extracellular growth factors. The proper regulation of this switch is important for normal cell processes; aberrations could result in a number of diseases such as cancer, neurodegenerative disorders, stroke and myocardial infarction. The R point switch is tightly controlled by two transcription factors, Myc and E2F. MicroRNAs are short noncoding RNAs, about 22 nucleotides long that perform post-transcriptional regulation. Their effect on the expression of their targets is marginal compared to those of transcription factors, but they have important roles in regulating various developmental and physiological processes. We extended a model of the R point switch by adding microRNA regulation. Our analysis shows that microRNAs fine-tune and provide robustness to the R point switch. The bi-stability of the system is shown, agreeing with a previous 2-dimensional model of microRNA-inhibition of the Myc/E2F network.

**SHINGO IWAMI**

Associate Professor, Department of Biology, Kyushu University, Japan

*"Optimising drug combinations against hepatitis C virus infection in pre-clinical setting"*With the introduction of direct-acting antivirals (DAAs), treatment against hepatitis C virus (HCV) has significantly improved. To eradicate this worldwide infectious disease, the “best” multidrug treatment is demanded based on scientific evidence. However, there is no method available that systematically quantifies and compares the antiviral efficacy and drug-resistance profiles of drug combinations. Based on experimental anti-HCV profiles in a cell culture system, we quantified the instantaneous inhibitory potential (IIP), which is the logarithm of the reduction in viral replication events, for both single- and multiple-drug combinations. From the calculated IIP of 15 anti-HCV drugs from different classes (telaprevir, danoprevir, asunaprevir, simeprevir, sofosbuvir, VX-222, dasabuvir, nesbuvir, tegobuvir, daclatasvir, ledipasvir, interferon-α, interferon-λ1, cyclosporin A, SCY-635), we found that the nucleoside polymerase inhibitor, sofosbuvir, had one of the largest potentials to inhibit viral replication events. We also compared intrinsic antiviral activities of a panel of drug combinations. Our quantification analysis clearly indicated an advantage of triple-DAA treatments over double-DAAs, with triple-DAAs showing enhanced antiviral activity and a significantly lower probability for drug resistance to emerge at clinically relevant drug concentrations. Our novel framework provides quantitative information to consider in designing multidrug strategies prior to costly clinical trials.

**JAE KYOUNG KIM**

Assistant Professor, Department of Mathematical Sciences, Korea Advanced Institute of Science and Technology (KAIST), South Korea

**"Molecular Mechanisms Underlying the Kuramoto Model of Coupled Oscillators"**The Kuramoto model has been widely used to describe the synchronizations of a large set of coupled oscillators. In particular, the Kuramto model successfully captures the key features of synchronization of 20,000 coupled cellular rhythms in the circadian clocks of our brain. However, due to the abstractness of the Kuramoto model, specific molecular mechanisms underlying the sinusoidal coupling terms have not been identified. In this talk, I will discuss that the combination of intracellular transcriptional repression mechanisms and intercellular coupling mechanisms in the mammalian circadian clocks can lead to such sinusoidal coupling.

**YANGJIN KIM**

Associate Professor, Department of Mathematics, Konkuk University, South Korea

**"The role of microenvironment in regulation of cell infiltration in glioblastoma"**Malignant gliomas are the most common type of brain cancer, which arise from glial cells, and in their most aggressive form are called GBMs. GBMs are highly invasive and difficult to treat because cells migrate into surrounding healthy brain tissue rapidly, and thus these tumors are difficult to completely remove surgically. GIMs, which can comprise up to one third of the total tumor mass, are present in both intact glioma tissue and necrotic areas. They apparently originate from both resident brain macrophages (microglia) and newly recruited monocyte-derived macrophages from the circulation. Activated GIMs exhibit several phenotypes: one called M1 for classically activated, tumor suppressive, and another called M2 for alternatively activated, tumor promoting, and immunosuppressive. Within a tumor the balance between these phenotypes is typically shifted to the M2 form. Numerous factors secreted by glioma cells can influence GIM recruitment and phenotypic switching, including growth factors, chemokines, cytokines and matrix proteins. In this work, we focus on mutual interaction between a glioma and M1/M2 microglia mediated by CSF-1, TGFbeta, and EGF. Up-regulated TGFbeta leads to up-regulation of Smad within the tumor cells and secretion of MMPs, leading to proteolysis for EMT process and cell infiltration. The mathematical model consists of densities of glioma cells, M1 type cells, M2 type cells, and concentrations of CSF-1, EGF, TGFbeta, Extracellular matrix, and MMPs. We developed the model to investigate the mutual interactions between tumor cells in the upper chamber and microglia in the lower chamber. In the experiments, Boyden invasion assay was used to show that this mutual interaction induces glioma infiltration in vitro and in vivo. We show that our simulation results are in good agreement with the experimental data and we generate several hypotheses that should be tested in future experiments in vivo. We also apply the role of M1/M2 macrophages in OV therapy in glioma.

**MICHIO KONDOH**

Department of Environmental Solution Technology, Faculty of Science and Technology, Ryukoku University, Japan

**"Ecological networks: Linking the structural complexity to dynamic stability"**An ecological community can be viewed as a network of interacting species, where population densities of individual species change over time affected by other species’ densities. The structure of community network determines how such interspecific effects are transmitted among species and thus should be related to community responses to external disturbances. In this talk, I introduce the long-lasting debate in ecology, the effect of structural complexity on community stability, and some theoretical insights we can get through analyses of mathematical models. Recent finding we got through the analysis of real fish community data will be also introduced.

**HEE-DAE KWON**

Professor, Department of Mathematics, Inha University, South Korea

**"Estimation of effective reproduction number using Kalman filter algorithms"**Parameter estimation has one of the most crucial roles in modeling of many infectious diseases. The reproduction number, in particular, is of great interest, and provides a summary measurement of the transmission potential. However, estimating this value is very challenging owing to the characteristics of epidemic data, such as their non-reproducibility and incompleteness. In this talk, we discuss ideas and techniques related to a Kalman filter to overcome difficulties with the least squares method, a standard approach to parameter estimation. We begin with introducing a modified Kalman filter tailored to a frame involving nonlinearity, continuous-time dynamics, discrete-time measurements, and parameter estimation. Numerical simulations are conducted under various settings to analyze and compare the impact of data sampling, sensitivity to the initial values, and the effect of model choice. We observed that a Kalman filter is much more efficient and robust than the least squares method in terms of adequate data and model discrepancy.

**MAY ANNE E. MATA**

University of the Philippines Mindanao

**"How intracellular actin waves take selfies via reaction-diffusion equations"**Waves and dynamic patterns in chemical and physical systems have long interested experimentalists and

theoreticians alike. In this talk, I will showcase our investigation of a cellular phenomenon wherein waves

of actin(a major component of the cytoskeleton) and its regulators (nucleation promoting factors, NPFs) are observed experimentally. To describe the dynamics of intracellular actin waves, a minimal reaction diffusion model depicting feedback between signalling proteins and filamentous-actin (F-actin) was developed and simulated for different set of parameters. Various numerical simulations were performed giving rise to different patterns that can be explained via local perturbation analysis, a nonlinear stability method. This talk serves as an invitation to explore reaction-diffusion equations and local perturbation analysis as tools to describe and analyze waves and dynamic patterns observed in natural systems.

theoreticians alike. In this talk, I will showcase our investigation of a cellular phenomenon wherein waves

of actin(a major component of the cytoskeleton) and its regulators (nucleation promoting factors, NPFs) are observed experimentally. To describe the dynamics of intracellular actin waves, a minimal reaction diffusion model depicting feedback between signalling proteins and filamentous-actin (F-actin) was developed and simulated for different set of parameters. Various numerical simulations were performed giving rise to different patterns that can be explained via local perturbation analysis, a nonlinear stability method. This talk serves as an invitation to explore reaction-diffusion equations and local perturbation analysis as tools to describe and analyze waves and dynamic patterns observed in natural systems.

**TAKASHI MIURA**

Professor, Department of Anatomy and Cell Biology, Kyushu University Graduate School of Medical Sciences

**"Mechanism of skull suture pattern formation"**Our skull consist of several bones, and thin soft tissue at the intersection is called suture tissue. Suture tissue is wide and straight at first, but during development it start winding to generate complex winding structure. Various molecules are known to be involved in this pattern formation process, but how the interactions of them results in this pattern formation remain to be elucidated. At first we formulated this phenomenon by two species reaction-diffusion system by simplifying known molecular interactions. Next we further simplified the model using interface equation and convolution kernel to analytically obtain the dynamics of pattern formation. Finally we try to understand the formation of fractal structure by using the model with time-independent noise.

**ATSUSHI MOCHIZUKI**

Chief Scientist, Theoretical Biology Laboratory, Riken, Japan

**"Structural analysis for sensitivity of chemical reaction networks"**In living cells, chemical reactions are connected by sharing their products and substrates, and form complex network systems, e.g. metabolic network. One experimental approach to study such network systems is sensitivity analysis where the amount or activity of the enzymes is perturbed and responses (concentrations of chemicals or fluxes in the system) are measured. However, due to the complexity of the systems, it has been unclear how the network structures influence the responses of the systems. In this study, we introduce a mathematical method, named

[1] Mochizuki A., and Fiedler B. (2015) Sensitivity of chemical reaction networks: a structural approach.

[2] Okada T. and Mochizuki A. (2016) Law of Localization in Chemical Reaction Networks.

*structural sensitivity analysis*, to determine responses of chemical reaction systems to the perturbation of the enzyme amount/activity based only on network structure. From analyses we found that (1) qualitative responses at a steady state are determined from topological information of network only. We also found that (2) response patterns, e.g., distribution of nonzero responses of chemical concentrations in the network, exhibit two characteristic features, localization and hierarchy, depending on the structure of networks and position of perturbed reactions. Finally, we found (3) a general law which directly connects the network topology and the response patterns, and governs the characteristic patterns of responses. These results imply that network topology is an origin of biological adaptation and robustness. This theorem, which we call the law of localization, is not only theoretically important, but also practically useful for examining real biological systems. We apply our method to several hypothetical and real life chemical reaction networks, including the metabolic network of the E. coli metabolic network.**References**[1] Mochizuki A., and Fiedler B. (2015) Sensitivity of chemical reaction networks: a structural approach.

*J. Theor. Biol.***367**: 189-202.[2] Okada T. and Mochizuki A. (2016) Law of Localization in Chemical Reaction Networks.

*Phys. Rev. Lett.***117**, 048101.**SHINJI NAKAOKA**

University of Tokyo, Japan

*"Mathematical and**informations**analysis of community composition change of the gut microbiota"*Recent advance and popularity of next generation sequencing enable us to obtain the composition and abundance of the gut bacterial species from fecal samples, known as microbiome data. Although resident bacterial species in the gut are often maintained stably in a healthy condition, a variety of abnormal conditions such as ulcerative colitis and obesity have shown the compositional change of bacterial species toward decreasing diversity, referred to dysbiosis. The objective of this talk is to introduce our recent progress on analyzing the microbiome data reflecting dysbiotic change of the gut microbiota caused by dietary habit. Based on several informatics and statistical analyses, we could successfully extract a cluster of bacterial species which could characterize the gut condition post dietary habit change. Potential therapeutic intervention will be discussed based on our findings. We will further propose and show our progress on mathematical modeling approach to investigate key driving factors that mediate community composition change by dietary habits.

**JOMAR F. RABAJANTE**

Associate Professor, Institute of Mathematical Sciences and Physics

University of the Philippines Los Banos, Philippines

**"Possible causes and implications of parasite aggregation: ecological, epidemiological, evolutionary and mathematical insights"**Parasite aggregation refers to the situation where a small number of individual hosts harbor large number of parasites while the rest of the host population have low or zero parasite burden. It has been shown in various

*in situ*data that this heterogeneity in parasite distribution is common in nature. In this talk, I am going to discuss some of the possible ecological causes, and the possible implications of parasite aggregation in epidemiology and host/parasite evolution. Using host-centric and parasite-centric perspectives, I will present mathematical models of host-parasite interaction to describe the ecological causes, and to predict the implications of parasite aggregation. The flow of the presentation and discussion in this talk will follow the mathematical modeling process to provide ideas to the participants of the workshop on how to carry out collaborative research.**MASASHI TACHIKAWA**

Researcher, Theoretical Biology Laboratory, Riken, Japan

**"Biophysical simulation of Golgi formation process"**Golgi body is a membrane-bound organelle in eukaryotic cells, which works as the hub of the cellular logistics. Golgi body has a characteristic morphology; several flattened of lipid membrane sacs (cisternae) stacking to each other. Although the morphology is thought to be important for its function, no valid mechanisms to generate and maintain it have been proposed. There is no experimental method for examination of detailed morphological dynamics of a cellular

organelle, because of the small size.

In this study, we aim to demonstrate a process to generate Golgi body by physical model simulations of coarse-grained lipid membrane system and propose a possible mechanism to produce the characteristic shape. To overcome this situation, we propose an alternative approach in which we reproduce the dynamics of organelles using computer simulations with physical models. In the simulations, arbitrary shape of curved membrane surface is approximately represented by a triangulated polygon and the energy stored in the membrane is calculated. The temporal shape change is performed using Monte Carlo method. Applying this approach to the Golgi reassembly process in mitotic cells, we reconstructed the three-dimensional morphological dynamics generating the characteristic layered shapes from

aggregations of vesicles. We also revealed the self-organising nature of the process.

organelle, because of the small size.

In this study, we aim to demonstrate a process to generate Golgi body by physical model simulations of coarse-grained lipid membrane system and propose a possible mechanism to produce the characteristic shape. To overcome this situation, we propose an alternative approach in which we reproduce the dynamics of organelles using computer simulations with physical models. In the simulations, arbitrary shape of curved membrane surface is approximately represented by a triangulated polygon and the energy stored in the membrane is calculated. The temporal shape change is performed using Monte Carlo method. Applying this approach to the Golgi reassembly process in mitotic cells, we reconstructed the three-dimensional morphological dynamics generating the characteristic layered shapes from

aggregations of vesicles. We also revealed the self-organising nature of the process.