iTHEMS Biology Seminar
189 events
We are holding regular seminars and other activities on topics related to biology. Our aim is to lower the boundaries between biology and mathematics/physics, to identify common grounds between biology and mathematics/physics, and to develop ideas for new research topics at the intersection of biology and mathematics or physics.
For further details see iTHEMS Biology Seminar Study Group page.
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Seminar
A rooted phylogeny of bacteria resolves early evolution
August 25 (Thu) at 16:00 - 17:00, 2022
Adrian Davin (JSPS Research Fellow, Department of Biological Sciences, Graduate School of Science, The University of Tokyo)
Bacteria are the most diverse life forms on Earth and yet, we know surprisingly little about their early evolution. In this talk, I will explain how phylogenetic reconciliations and models of genome evolution can be used to answer some of the most interesting open questions in biology, such as the nature of the last bacterial common ancestor or whether a tree is a meaningful representation of evolution in the presence of abundant lateral gene transfer.
Venue: via Zoom
Event Official Language: English
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Seminar
Bayesian optimization of multivariate genomic prediction models based on secondary traits for improved accuracy gains and phenotyping costs
July 21 (Thu) at 16:00 - 17:00, 2022
Kosuke Hamazaki (Ph.D. Student, Graduate School of Agricultural and Life Sciences, The University of Tokyo)
In recent years, the genomic prediction that predicts phenotypic values from marker genotype data has attracted much more attention in the area of breeding. Especially, genomic selection using prediction values based on genomic prediction models has been contributing to more efficient and rapid breeding. In genomic prediction, it is important to construct the prediction model so that its accuracy becomes higher. Thus, multivariate genomic prediction models with secondary traits, such as data from various omics technologies including high-throughput phenotyping (e.g., unmanned aerial vehicle-based remote sensing), have started to be applied to many datasets because it offers improved accuracy gains compared with genomic prediction based only on marker genotypes. Although there is a trade-off between accuracy gains and phenotyping costs of secondary traits, no attempt has been made to optimize these trade-offs. In this study, we propose a novel approach to optimize multivariate genomic prediction models with secondary traits measurable at early growth stages for improved accuracy gains and phenotyping costs. The proposed approach employs Bayesian optimization for efficient Pareto frontier estimation, representing the maximum accuracy at a given cost. The proposed approach successfully estimated the optimal secondary trait combinations across a range of costs while providing genomic predictions for only about 20% of all possible combinations. The simulation results reflecting the characteristics of each scenario of the simulated target traits showed that the obtained optimal combinations were reasonable. Analysis of real-time target trait data showed that the proposed multivariate genomic prediction model had significantly superior accuracy compared to the univariate genomic prediction model.
Venue: via Zoom
Event Official Language: English
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Seminar
Dual stochasticity of neurons and synapses for sampling-based learning in the brain
July 14 (Thu) at 16:00 - 17:00, 2022
Jun-nosuke Teramae (Associate Professor, Nonlinear Physics Division, Department of Advanced Mathematical Sciences, Graduate School of Informatics, Kyoto University)
Neurons and synapses behave highly stochastically in the brain. However, how this stochasticity is beneficial for computation and learning in the brain remains largely unknown. In this presentation, we will see that the stochastic processes in neurons and synapses can be integrated into a unified framework to optimally sample events from the environments, resulting in an efficient learning algorithm consistent with various experimental results. In particular, the learning algorithm enables us to reproduce the recently discovered efficient power-law coding in the cortex. These results suggest that synapses and neurons work cooperatively to implement a fundamental method for stochastic computing in the brain.
Venue: via Zoom
Event Official Language: English
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Seminar
Virus vs. Bacteria: Art of the war in the microbial world
July 7 (Thu) at 16:00 - 17:00, 2022
Namiko Mitarai (Associate Professor, Niels Bohr Institute, University of Copenhagen, Denmark)
A virulent phage (virus that infects bacteria) infection to a host bacterial cell results in lysis of the cell, where possibly hundreds of phage particles are released after a latency time. The phage pressure is believed to be an important factor to shape the microbial communities and a driving force of their evolution, and yet we are far from having a full picture of their warfare. In this talk, I highlight a few factors that play significant roles in phage-bacteria interactions and their coexistence, such as the effect of herd immunity and the importance of the spatial structure in a few cells scale to the colony scale. *Her talk will be accessible to physicists, mathematicians, and also biologists.
Venue: via Zoom
Event Official Language: English
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Seminar
Predicting local patterns of diversity: coexistence models, networks and wildflowers
June 30 (Thu) at 10:00 - 11:30, 2022
Margie Mayfield (Professor, University of Melbourne, Australia)
The question of how species coexist in diverse natural communities has challenged ecologists for generations. Theoretical models of species coexistence have been developed, but primarily as proof of concept for specific coexistence theories. These theories and associated models focus on coexistence between species pairs and ignore the great complexity of interactions found in most natural systems. Though useful for advancing ecological theory, these models are often of limited use for understanding and predicting diversity in real natural communities. In this talk, I explore the three main assumptions made by coexistence models developed under the framework of Modern Coexistence Theory (MCT): that only direct competition is important, that demographic variation is noise, not valuable biological information, and that only the average environment matters. Using Bayesian statistical approaches with population growth models applied to field data from the annual plant communities of the York gum woodlands of SW Western Australia, I illustrate the issues with these assumptions in predicting coexistence in diverse systems. I show how these Bayesian approaches to MCT can improve on frequentist approaches and discuss the potential value of interaction networks for studying coexistence dynamics in diverse natural systems.
Venue: Okochi Hall (Main Venue) / via Zoom
Event Official Language: English
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Mathematical modeling of understanding how adaptive evolution of sexual traits can affect coexistence
June 23 (Thu) at 16:00 - 17:00, 2022
Keiichi Morita (Ph.D. Student, School of Advanced Sciences Department of Evolutionary Studies of Biosystems, The Graduate University for Advanced Studies (SOKENDAI))
One of the challenges in ecology is understanding the processes of species coexistence. Recent studies have underlined the importance of the interaction between rapid adaptation and population dynamics (i.e., eco-evolutionary feedbacks) in coexistence. Reproductive interference may reduce population growth rate due to costs of hybridization by incomplete recognition of sexual traits such as ornaments and songs in birds. Recent theoretical studies have suggested that eco-evolutionary feedbacks in sexual traits can affect coexistence. I will present mathematical modeling for investigating how reproductive interference can affect coexistence. Furthermore, I will present an analytical method, adaptive dynamics for understanding how evolution of sexual traits can affect coexistence.
Venue: via Zoom
Event Official Language: English
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Seminar
Self-organisation of a dynamic meshwork structure in the mesoderm during the development of a chick embryo and its characterisation using persistent homology
June 16 (Thu) at 16:00 - 17:00, 2022
Mitsusuke Tarama (Research Scientist, Laboratory for Physical Biology, RIKEN Center for Biosystems Dynamics Research (BDR))
Morphogenesis is a fundamental process of development. Appropriate morphogenesis of tissues is achieved by coordinated motion of individual cells. To elucidate the mechanism behind this self-organisation of cells, one needs to develop a theoretical model based on experimental observations. In our recent study, our experimental colleague found that the mesoderm cells in early chick embryo organise into a meshwork structure, which changes dynamically. To understand the mechanism behind this dynamic meshwork structure formation, we developed an agent-based mechanical model of cells that interact through a short-range attractive interaction. To compare the simulation results with the experiment, we utilized persistent homology, a method of topological data analysis that allows to systematically characterise irregular structures. In this seminar, we will talk about the mechanical mechanism behind the mesoderm structure formation during the development of the early chick embryo, and how the persistent homology analysis is applied to our biological system.
Venue: via Zoom
Event Official Language: English
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Seminar
Mathematical Model on Evolution of Self-sustained Circadian Rhythms
June 9 (Thu) at 16:00 - 17:00, 2022
Motohide Seki (Assistant Professor, Department of Design Futures, Faculty of Design, Kyushu University)
Self-sustained oscillation is a fundamental property of circadian clocks found in many organisms. However, evolutionary advantage of the self-sustainability has been only speculatively discussed. In this seminar, I will present a simulation result of our mathematical model indicating that seasonality facilitates the evolution of the self-sustained circadian clock, which was consistent with empirical records.
Venue: via Zoom
Event Official Language: English
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Do the mechanisms of speciation vary with latitude? Empirical case study 1: evolution of the plant cycad genus Ceratozamia from Mexico
June 2 (Thu) at 16:00 - 17:00, 2022
José Said Gutiérrez-Ortega (Special Postdoctoral Researcher, iTHEMS)
“Species” form biodiversity, and “speciation” is the evolutionary process that originate them. Speciation can occur by stochastic processes —neutral theory— or through the influence of ecological factors —selection theory—. They are not competing theories, but rather explain different facets of speciation. But the mechanisms of speciation seem quite to depend on the group of study and its underlying spatial and temporal factors. Why do in some groups species are more prone to evolve via selection or stochastically than others? It does not exist a unified theory that can explain and predict events of speciation at the global level. However, I hypothesize that there is a latitude-association between two main mechanisms of speciation: 1) “allopatric speciation by means of niche conservatism” and 2) “ecological speciation by means of niche divergence”. The first is hypothetically more common at low latitudes, and the second is more common at high latitudes. In this context, I will use the recent results of my own empirical research on the plant cycad genus Ceratozamia from Mexico as an example to show how mechanisms of speciation seem to covariate with latitude. Hopefully, you can help me to formulate a theory that can explain where and under what factors speciation can occur.
Venue: via Zoom
Event Official Language: English
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Seminar
More Data, More Problems: Big Data in Correlative Ecology
May 19 (Thu) at 16:00 - 17:00, 2022
Dan Warren (Staff Scientist, Biodiversity and Biocomplexity Unit, Okinawa Institute of Science and Technology Graduate University (OIST))
The rapidly expanding pool of large data sets on species distributions, community composition, and environmental factors has been accompanied by an increasing number of methodological approaches to analyze this data. If done correctly, this represents an unprecedented opportunity for understanding ecological processes at large scales. However, it also represents an opportunity to be wrong about those same processes at a scale that was previously not possible. In this talk, I will use examples from ecology and other fields to discuss some of the issues that arise when we take big data approaches to ecological questions.
Venue: via Zoom
Event Official Language: English
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Seminar
Classical and Quantum Chaos
May 12 (Thu) at 16:00 - 17:00, 2022
Akira Shudo (Professor, Department of Physics, Graduate School of Science, Tokyo Metropolitan University)
Classical and quantum mechanics in multi-dimensions are qualitatively different from those in one-dimension since they are no more integrable in general and chaos appears in the dynamics. This brings a great deal of complexity or even richness both in classical and quantum dynamics. Especially in generic nonintegrable systems which are neither completely integrable nor fully chaotic, phase space becomes a mixture of regular and chaotic components. Such an aspect is a source of inexhaustible questions not only in the past but in the future. We here overview classical and quantum chaos in Hamiltonian systems.
Venue: via Zoom
Event Official Language: English
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Diversity of Asgardarchaota and Theoretical verification of the endosymbiotic theory
April 28 (Thu) at 10:00 - 11:00, 2022
Daiki Kumakura (Ph.D. Student, Graduate School of Life Science, Hokkaido University)
How did intracellular symbiosis occur and give rise to eukaryotic ancestor? This question has been considered to the two theories as three-domain theory and eocyte theory. Here I present asgard archaea, the archaeon closest to eukaryotes. Asgard archaea is an archaeon found at a deep-sea sampling site called Loki's castle at between Greenland and Norway. So all the closely related species are named after Norse mythology (Loki-, Thor-, Odin-, Heimdall-, etc.). Unlike other archaea, asgard archaea has many eukaryotic-specific proteins and is considered to be the closest to eukaryotes. In 2020, one of the asgard archaea species was finally successfully cultured. This archaeon was cultured and found to take on a branch-like structure. It is then hypothesized that intracellular symbiosis between this archaeon and the ancestor of mitochondria resulted in the ancestor of today's eukaryotic cells. In this talk, I would like to discuss with you the explanation of how we arrived at this hypothesis and how to construct a mathematical model.
Venue: via Zoom
Event Official Language: English
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Seminar
Neurons are potential statisticians
April 21 (Thu) at 10:00 - 11:00, 2022
Takuya Isomura (Unit Leader, Brain Intelligence Theory Unit, RIKEN Center for Brain Science (CBS))
Humans and animals can predict what will happen in the future and act appropriately by inferring how the sensory inputs were generated from underlying hidden causes. The free-energy principle is a theory of the brain that can explain how these processes occur in a unified way. However, how the fundamental units of the brain, such as the neurons and synapses, implement this principle has yet to be fully established. Here, we have mathematically shown that neural networks that minimise a cost function implicitly follow the free-energy principle and actively perform statistical inference. We have reconstructed a biologically plausible cost function for neural networks based on the equation of neural activity and shown that the reconstructed cost function is identical to variational free energy, which is the cost function of the free-energy principle. This equivalence speaks to the free-energy principle as a universal characterisation of neural networks, implying that even at the level of the neurons and synapses, the neural networks can autonomously infer the underlying causes from the observed data, just as a statistician would. The proposed theory will advance our understanding of the neuronal basis of the free-energy principle, leading to future applications in the early diagnosis and treatment of psychiatric disorders, and in the development of brain-inspired artificial intelligence that can learn like humans.
Venue: via Zoom
Event Official Language: English
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Coarse-grained molecular dynamics simulation via Langevin simulation
April 14 (Thu) at 10:00 - 11:00, 2022
Hiroshi Yokota (Postdoctoral Researcher, iTHEMS)
In the cell biology or biophysics, many mechanical properties of proteins or DNA are discussed. In order to consider the dynamics, coarse-grained molecular dynamics simulation (Langevin simulation) is useful. In this seminar, I will give you the introductory and methodology talk about the Langevin simulation.
Venue: via Zoom
Event Official Language: English
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Journal Club: Phase separation in a many-component system with random interactions
March 31 (Thu) at 10:00 - 11:00, 2022
Kyosuke Adachi (Special Postdoctoral Researcher, Nonequilibrium Physics of Living Matter RIKEN Hakubi Research Team, RIKEN Center for Biosystems Dynamics Research (BDR))
Several kinds of protein condensates have been observed in living cells, and the liquid-liquid phase separation is regarded as a basic mechanism of the condensate formation. However, given that there are thousands of protein species in a cell, it is not clear how the number and the composition of distinct condensates are controlled. One of the physics approaches to this problem is considering a model of many components with random interactions. In this Journal Club, I will introduce a recent paper [1] that applies random-matrix theory to the phase separation dynamics.
Venue: via Zoom
Event Official Language: English
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Criticality in stochastic SIR model for infectious diseases based on path-integral approach
March 24 (Thu) at 10:00 - 11:00, 2022
Shigehiro Yasui (Assistant Professor, Center of Medical Information Science, Kochi Medical School)
The susceptible-infected-removed (SIR) model provides us with a basic scheme for the analysis of the epidemic infectious diseases such as the COVID-19. In this presentation, we focus on the stochastic SIR model which describes the stochastic time-evolutions of the population sizes for the susceptible, infected, and removed individuals. We consider the master equation (Kolmogorov forward equation) for the infection transmission and recovery processes (SI->II and I->R), and transform it into the Hamiltonian formalism with the Fock space a la quantum physics. According to the Doi-Peliti prescription, furthermore, we introduce the path-integral formalism similar to the quantum field theory, and perform the perturbative and non-perturbative calculations for the time-evolution of the susceptible, infected, and removed populations. We find that the critical value Rc of the basic reproduction number, which determines the spreading or the convergence of the infectious diseases, can be modified by the stochastic effects in comparison to the Rc in the conventional deterministic SIR model.
Venue: via Zoom
Event Official Language: English
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Phylogenomics revealed one of the problems for phylogeny –The monophyly of Archaeplastida including land plant-
March 17 (Thu) at 10:00 - 11:00, 2022
Euki Yazaki (Postdoctoral Researcher, iTHEMS)
There are many problems between large eukaryotic lineages. One of these is the monophyly of Archaeplastida to which land plants and other photosynthetic organisms belong. Although it has been believed that the Archaeplastida are monophyletic because they share common chloroplast structures, several large-scale molecular phylogenetic analyses have failed to reproduce this phylogenetic relationship. In this study, by enhancing the taxon sampling of the data set, the monophyly of Archaeplastida was successfully reconstructed, showing that the taxa critical for the reconstruction are present. Through detailed molecular phylogenetic and statistical analyses, it was estimated that the lack of monophyly ofArchaeplastida is due to the specific evolutionary signals of certain taxa.
Venue: via Zoom
Event Official Language: English
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Independent regulation of multiple checkpoints in cell-cycle network system -Biological function originated in the law of localization-
March 10 (Thu) at 10:00 - 11:00, 2022
Atsushi Mochizuki (Professor, Institute for Frontier Life and Medical Sciences, Kyoto University)
In cell cycle, G1-S and G2-M checkpoints are regulated by different protein complexes, Cdc2-Cdc13 and Cdc2-Cig2, respectively. For a normal mitosis, activity of two complexes should rise specifically at different timing. However, the complex formations share common species of proteins and activation reactions conform a complicated network. We study how independent regulation of two checkpoints is realized in the network system by “structural sensitivity analysis”, which was previously established by us. The analyses clarified that activities of two complexes are regulated by disjoint sets of reaction parameters in the system. A series of non-trivial behaviors are generated by “buffering structures with an intersection”, which can generally appear in chemical reaction network including complex formation.
Venue: via Zoom
Event Official Language: English
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Stator dynamics of the bacterial flagellar motor
February 24 (Thu) at 17:00 - 18:00, 2022
Ashley Nord (Researcher, Centre de Biologie Structurale, CNRS, France)
Rubén Pérez-Carrasco (Lecturer in Theoretical Systems Biology, Faculty of Natural Sciences, Department of Life Sciences, Imperial College London, UK)The bacterial flagellar motor is the membrane-embedded rotary molecular motor which turns the flagellum that provides thrust to many bacteria for swimming, swarming, and chemotaxis. This large multimeric complex, composed of a few dozen constituent proteins, is a hallmark of dynamic subunit exchange. The stator units are inner-membrane ion channels which dynamically bind to the cell wall and convert electrochemical energy into torque which is applied to the rotor. The dynamic exchange of stator units is a function of the viscous load on the flagellum, allowing the bacterium to adapt to its local environment, though the molecular mechanisms of this mechanosensitivity remain unknown. Previously, we have shown that stator units behave as a catch bond, a counterintuitive bond which becomes stronger under applied tension. Here, by actively perturbing the steady-state stator stoichiometry of individual motors, we reveal a stoichiometry-dependent asymmetry in stator remodeling kinetics. We interrogate the potential effect of next-neighbor interactions and local stator unit depletion and find that neither can explain the observed asymmetry. We then simulate and fit two mechanistically diverse models which recapitulate the asymmetry, finding assembly dynamics to be particularly well described by a two-state catch-bond mechanism.
Venue: via Zoom
Event Official Language: English
189 events
Events
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