Living organisms have developed beautiful hierarchic network structures to transport materials necessary for maintaining life. Various morphological and functional aspects of the network have been studied. For example, from a morphological viewpoint, the L-system was invented to describe the tree shape. From a functional perspective, Murray's law has been proposed in physiology to explain the optimal shape of the vascular network. However, morphological and functional views tend to be studied independently, and their relationship needs to be better studied. In this session, we present examples of how pattern formation and function of these biological transport structures can be understood by combining experimental and theoretical approaches.

1. Dai Akita (University of Tokyo, Japan)
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2. Hiroshi Kori (University of Tokyo, Japan)
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3. Haruhiko Taneda (University of Tokyo, Japan)
   Hydraulic architecture and water transport in plants.
4. Takashi Miura (Kyushu University, Japan)
   Pattern formation of vascular network in vertebrates

To Be Announced

1. Chen-hui Chen (Academia Sinica, Taiwan)
   To Be Announced
2. Satoru Okuda (Kanazawa University, Japan)
   To Be Announced
3. Satoshi Toda (Osaka University, Japan)
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4. Tetsuya Hiraiwa (Academia Sinica, Taiwan)
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Chemical reaction networks are a universal language for studying biochemical systems mathematically. One of the main goals in this field is to find link between network structural properties and the associated dynamical features. In this session, we will discuss recent theoretical approaches, especially deterministic and stochastic modeling for chemical reaction networks. 

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This symposium will focus on controlling biological network systems across multiple scales, from gene regulatory networks within cells to ecological networks that shape biodiversity. Key topics will include understanding network dynamics, controlling system states, and designing effective interventions in networks that govern cellular processes, organismal functions, and ecological interactions. With an emphasis on analytical and graph-theoretical approaches, the symposium aims to bridge biological scales by identifying shared principles and methodologies. It will also explore real-world applications, ranging from controlling cell fates to managing ecosystems, highlighting the relevance of these approaches for advancing fundamental knowledge in biology.

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The symposium will focus on infectious disease modeling, emphasize the integration of empirical data and mathematical models to enhance our understanding of infectious diseases. Key themes include: data-driven approaches, model development, validation and calibration, predictive analytics and case studies. The symposium aims to foster collaboration among researchers, public health officials, and data scientists to leverage data and modeling techniques for effective infectious disease control and prevention. 

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Mathematical biology keeps developing rapidly in recent years. Dynamical modeling plays an important role in deciphering mechanism of complex biological systems. Big data and artificial intelligence provide new opportunities in understanding the development of life. In this minisyposium, we will invite experts to discuss the state-of-the-art advances in the dynamical modeling of biological systems and welcome all scholars to explore novel ideas in this promising area.

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The symposium "Dynamic Systems and Applications to Mathematical Biology" focuses on the intersection of dynamic systems theory and mathematical biology, exploring how mathematical modeling can elucidate complex biological phenomena. Key themes may include stability and bifurcation analysis, and their applications. The symposium seeks to highlight the role of dynamic systems in enhancing our understanding of biological processes and contributing to advancements in fields such as ecology, epidemiology, and evolutionary biology.

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Population dynamics models and mathematical techniques from dynamical systems theory have played a foundational role in shaping community and ecosystem ecology theories in the mid to late 20th century. However, since the 1990s, advancements in empirical methods have enabled the study of high-dimensional systems and ecological patterns across both larger spatial scales and finer spatial-temporal resolutions. These advances have led to new research focuses, such as high-dimensional community dynamics, community-ecosystem linkages, and transient or rapid shifts in ecosystem states, for which other quantitative approaches, such as statistical modeling and bioinformatics, sometimes provide more effective solutions than traditional population dynamics frameworks. When population dynamics models are applied to these emerging areas, researchers increasingly rely on numerical simulations, which, while powerful, often provide less quantitative insights compared to traditional mathematically tractable analyses. As community and ecosystem ecology rapidly evolves, there is a growing demand for new mathematical and modeling approaches. This symposium will present emerging approaches—such as those from statistical physics, thermodynamics, state-space reconstruction, and stochastic theory—and discuss how these tools can enhance our understanding of community and ecosystem dynamics. 

1. Joe Wan (National Taiwan University, Taiwan) 
   Coexistence theory for species pools: tractable insight from the cavity method 
2. Mayumi Seto (Nara Women's University, Japan)
   Thermodynamic and metabolic trait-based approaches to microbial community modeling
3. Ryosuke Iritani (RIKEN, Japan) 
   Majorization theory of incidence-based beta-diversity 
4. Hiroaki Fujita (Kyoto University, Japan) 
   The evaluation of microbial dynamics from two mathematical approaches 

Mathematical modeling and simulation (M&S) have become essential in advancing the discovery and clinical development of new drugs. Recent progress in the science and technology of M&S has enabled precise modeling of relationships among pharmacokinetics (PK), pharmacodynamics (PD), mechanisms of action, physiological processes, and disease progression, allowing for accurate predictions of clinical responses and true endpoints. This approach, known as Model-Informed Drug Development (MIDD), serves as a key driver for optimizing clinical study design, improving success rates of clinical studies, and accelerating the drug development process. M&S is also instrumental in precision dosing, supporting the implementation of personalized medicine in clinical settings.

In this session, we will focus on PK/PD modeling, Quantitative Systems Pharmacology (QSP), Physiologically-Based Pharmacokinetic (PBPK) modeling and disease progression modeling, all of which are key mathematical approaches within M&S that provide precise descriptions of biological systems and disease processes. We will discuss how these quantitative methods enhance drug development and healthcare, as well as how to advance current modeling methodologies.

Furthermore, we aim to foster collaboration between pharmaceutical researchers and academic experts in mathematical biology and applied mathematics, encouraging mutual understanding of research objectives and exploring ways to bring new hope to patients and families awaiting innovative treatments.

1. Shinichi Tsuchiwata (Pfizer R&D Japan, Japan)
   A Century of MIDD and Future Perspectives of QSP
2. Daichi Yamaguchi (SHIONOGI & CO., LTD., Japan)
   The estimation of the transmission mitigation of patients with COVID 19 by ensitrelvir treatment based on SARS-CoV-2 viral dynamic model
3. Raiki Yoshimura (Nagoya University, Japan)
   To Be Announced
4. Yasunori Komori (Chugai pharmaceutical co., ltd., Japan)
   Human projection of antibody drug pharmacokinetics using a physiologically based pharmacokinetic model coupled with multi-omics data
5. Ryuta Saito (Mitsubishi Tanabe Pharma Corporation, Japan)
   To Be Announced
6. Masato Fukae (Daiichi Sankyo Co., Ltd., Japan)
   Bayesian sparse regression for exposure–response analyses of valemetostat for adult T-cell leukemia/lymphoma
   
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Epidemic Modeling: Advances in Disease Control and Future Challenges" underscores the essential role of mathematical and computational models in managing infectious diseases. These models predict disease spread, identify hotspots, and evaluate intervention effectiveness, guiding policymakers in resource allocation and public health measures. With advancements in methodologies, such as machine learning and network theory, models have become more accurate and realistic. They also enable real-time surveillance and adaptive management of outbreaks, while anticipating future challenges like antimicrobial resistance and zoonotic diseases. Additionally, the field promotes interdisciplinary collaboration, enhancing model robustness and improving public understanding of health risks, ultimately strengthening disease control efforts. 

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Diverse biological rhythms can be found in nature. These rhythms regulate various biological functions of organisms such as development, physiology, and reproduction. For example, a developmental clock with a period of tens of minutes regulates formation of vertebrate body segments. Gene expression rhythms with a 24-hour period function as a circadian clock that regulates daily behavioral and physiological rhythms of organisms. Furthermore, rhythms can be synchronized locally and globally, forming collective patterns with spatial scales ranging several orders of magnitude. How should we tackle such diverse biological rhythms to understand general principles? Here we invite cutting-edge researchers to discuss biological rhythms in various aspects. We aim to cover several different approaches including dynamical systems theory, statistical physics, experimental biology, and data science. We emphasize the importance of interdisciplinary approaches to biological rhythms.

1. Koichiro Uriu (Institute of Science Tokyo, Japan)
   Statistical description of vertebrate segmentation clock 
2. Gen Kurosawa (RIKEN, Japan)
   A data-driven approach to understanding mammalian hibernation
3. Hiromi Shimojo (Osaka University, Japan)
   Gene expression dynamics during mammalian neural development 
4. Jihwan Myung (Taipei Medical University, Taiwan)
   Intrinsic bifurcation in the choroid plexus as the earliest brain clock
5. Shuichi Kudo (Kyushu University, Japan)
   Seasonal rhythms in genome-wide gene expression in forest trees

The recent COVID-19 epidemic has made it more apparent that the suppression and control of infectious diseases is an urgent issue for humanity. After nearly 100 years since the SIR was firstly proposed by Kermack and Mckendrick, mathematical models of infectious diseases are still evolving. In this session, we invite researchers working in this field from various perspectives and discuss the latest theoretical developments. As the mathematical modeling of infectious diseases enters a new century, we would like to look back on its history and to discuss new directions that will be needed in the future. 

1. Jomar Fajardo Rabajante (University of the Philippines Los Baños)
   A Logistic Regression Approach for Estimating the Basic Reproduction Number (R0) in Compartmental Infectious Disease Models.
2. Toshikazu Kuniya (Kobe University)
   Application of type reproduction number to evaluation of target-specific intervention
3. Satoru Morita (Shizuoka University)
   Epidemic Models on Networks and the Basic Reproduction Number. 
4. Akira Sasaki (SOKENDAI)
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To Be Announced

1. Kohei Tamura (Tohoku Univerisity) 
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Biological oscillations are a fundamental feature of living systems and can be observed across a wide range of scales, from the molecular level, such as gene expression and protein dynamics, to much larger, complex systems like ecosystems. These oscillations are crucial for maintaining homeostasis, coordinating cellular processes, and supporting broader ecological interactions. With recent breakthroughs in observational technologies, including advances in high-resolution imaging, genome-wide analysis, and real-time ecological monitoring, we have gained unprecedented insights into the intricate and diverse nature of these oscillations across different levels of biological organization. This symposium aims to present and discuss the theoretical frameworks that are emerging to analyze these rich new datasets. By applying novel computational models and mathematical approaches, we will be able to explore how oscillations across multiple biological scales can be studied in a more integrated and comprehensive way. 

1. Aneta Stefanovska (Lancaster University, UK)
   Non-autonomous oscillators through time-varying phase 
2. Kanako Sekimoto (Yokohama City University, Japan)
   Real-time monitoring of day-night oscillations of biogenic volatile compounds in forest ecosystems
3. Naoki Masuda (State University of New York at Buffalo, USA)
   Anticipating regime shifts in biological complex systems using network analysis 
4. Akiko Satake (Kyushu University, Japan) 
   Evolution of coordinated gene expression in seasonal and tropical environments