iTHEMS生物学セミナー
132 イベント
生物学に関連する様々なトピックを扱ったセミナーを定期的に開催しています。生物学と数学・物理学との境界を低くし、接点を見つけ出すことで、新しい学際的な研究のアイデアが生まれることを期待しています。
詳細はiTHEMS生物学セミナースタディーグループのページをご覧下さい。

Genetic Drift and Gnatural Selection
2022年9月22日(木) 16:00  17:00
トーマス・ヒッチコック (数理創造プログラム 基礎科学特別研究員)
Understanding how the various evolutionary forces of mutation, selection, and drift collectively shape the genetic composition of populations is a key goal of population genetics research. One classic method of study has been to compare different inheritance systems, and particularly popular has been the within genome comparison of autosomes and sex chromosomes. However, inferences from such comparisons can be limited by the fact that multiple factors differ between sex chromosomes and autosomes (e.g. ploidy and transmission genetics). Here, we study a group of black winged fungus gnats with a peculiar type of reproduction “digenic PGE” in which X and autosomes are inherited equally from females and males, but the X remains expressed in a haploid state in males compared to a diploid state in females. I first explain what is known about their inheritance system, and then show how we can extend classic theory to the various inheritance systems that coexists within the fungus gnats.
会場: via Zoom
イベント公式言語: 英語

セミナー
Hessian Geometric Structure of Equilibrium and Nonequilibrium Chemical Reaction Newtworks
2022年9月8日(木) 16:00  17:00
小林 徹也 (東京大学 生産技術研究所 准教授)
Cells are the basic units of all living things, and their functions are realized by circuits and networks of chemical reactions. Thus, understanding the mechanism how various cellular functions are implemented by chemical reaction networks (CRN) is the central challenge in biophysics and quantitive biology. Among various aspects of CRN, its thermodynamic property is particularly important because most of biological functions are energyconsuming nonequilibrium phenomena. However, even though the equilibrium chemical thermodynamics and kinetics of chemical reactions were founded more than one century ago, the nonequilibrium theory of CRN is still immature. One reason is the nonlinearity in the constitutive equation between chemical force and flux, which prevents us from associating the tangent and cotangent spaces of the dynamics by the usual inner product structure. In this work, we show that the nonlinear relation between chemical force and flux can be captured by Legendre transformation and the geometric aspects of CRN dynamics can be characterized by Hessian geometry. Hessian geometry is the geometry generated by Legendre dual pairs of convex functions and is the basis of dually flat structure of information geometry and also equilibrium thermodynamics. Thus, we have dually flat structures in CRN dynamics, one on the statepotential space where equilibrium and energetic aspect is formulated (1,2), and the other on the forceflux space where nonequilibrium and kinetics aspect is characterized(3). Two of them are consistently connected by topological property of the underlying hypergraph structure of CRN. We discuss potential applications of this structure not only for CRN but also for other phenomena and problems(4,5).
会場: via Zoom
イベント公式言語: 英語

Loop structure via one sided loop extrusion with twist deformation
2022年9月1日(木) 16:00  17:00
横田 宏 (数理創造プログラム 特別研究員)
During cell division, a chromatin fiber condenses into the rodlike shape which is so called chromosome. The chromosome is composed of consecutive loop structures. Many researchers have been interested in the loop formation mechanism. The loop extrusion is the one of the promising hypotheses. However, the only loop extrusion does not completely explain the chromosome condensation dynamics. In order to tackle this problem, we constructed a mechanical model of the loop formation dynamics by focusing on the twist and writhe structures in DNA or chromatin. In this talk, I would like to explain the loop extrusion mechanism and our model.
会場: via Zoom
イベント公式言語: 英語

セミナー
A rooted phylogeny of bacteria resolves early evolution
2022年8月25日(木) 16:00  17:00
Adrian Davin (東京大学 大学院理学系研究科 生物科学専攻 JSPS海外特別研究員)
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.
会場: via Zoom
イベント公式言語: 英語

セミナー
Bayesian optimization of multivariate genomic prediction models based on secondary traits for improved accuracy gains and phenotyping costs
2022年7月21日(木) 16:00  17:00
濱崎 甲資 (東京大学 大学院農学生命科学研究科 博士課程)
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 highthroughput phenotyping (e.g., unmanned aerial vehiclebased 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 tradeoff between accuracy gains and phenotyping costs of secondary traits, no attempt has been made to optimize these tradeoffs. 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 realtime target trait data showed that the proposed multivariate genomic prediction model had significantly superior accuracy compared to the univariate genomic prediction model.
会場: via Zoom
イベント公式言語: 英語

セミナー
Dual stochasticity of neurons and synapses for samplingbased learning in the brain
2022年7月14日(木) 16:00  17:00
寺前 順之介 (京都大学 大学院情報学研究科 先端数理科学専攻 非線形物理学講座 准教授)
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 powerlaw coding in the cortex. These results suggest that synapses and neurons work cooperatively to implement a fundamental method for stochastic computing in the brain.
会場: via Zoom
イベント公式言語: 英語

セミナー
Virus vs. Bacteria: Art of the war in the microbial world
2022年7月7日(木) 16:00  17:00
御手洗 菜美子 (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 phagebacteria 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.
会場: via Zoom
イベント公式言語: 英語

セミナー
Predicting local patterns of diversity: coexistence models, networks and wildflowers
2022年6月30日(木) 10:00  11:30
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.
会場: 大河内記念ホール (メイン会場) / via Zoom
イベント公式言語: 英語

Mathematical modeling of understanding how adaptive evolution of sexual traits can affect coexistence
2022年6月23日(木) 16:00  17:00
森田 慶一 (総合研究大学院大学 先導科学研究科 生命共生体進化学専攻 博士課程)
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., ecoevolutionary 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 ecoevolutionary 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.
会場: via Zoom
イベント公式言語: 英語

セミナー
Selforganisation of a dynamic meshwork structure in the mesoderm during the development of a chick embryo and its characterisation using persistent homology
2022年6月16日(木) 16:00  17:00
多羅間 充輔 (理化学研究所 生命機能科学研究センター (BDR) フィジカルバイオロジー研究チーム 研究員)
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 selforganisation 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 agentbased mechanical model of cells that interact through a shortrange 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.
会場: via Zoom
イベント公式言語: 英語

セミナー
Mathematical Model on Evolution of Selfsustained Circadian Rhythms
2022年6月9日(木) 16:00  17:00
関 元秀 (九州大学 大学院芸術工学研究院 未来共生デザイン部門 助教)
Selfsustained oscillation is a fundamental property of circadian clocks found in many organisms. However, evolutionary advantage of the selfsustainability 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 selfsustained circadian clock, which was consistent with empirical records.
会場: via Zoom
イベント公式言語: 英語

Do the mechanisms of speciation vary with latitude? Empirical case study 1: evolution of the plant cycad genus Ceratozamia from Mexico
2022年6月2日(木) 16:00  17:00
ホセ サイード・グティエレス オルテガ (数理創造プログラム 基礎科学特別研究員)
“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 latitudeassociation 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.
会場: via Zoom
イベント公式言語: 英語

セミナー
More Data, More Problems: Big Data in Correlative Ecology
2022年5月19日(木) 16:00  17:00
Dan Warren (沖縄科学技術大学院大学 (OIST) 生物多様性・複雑性研究ユニット 研究員)
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.
会場: via Zoom
イベント公式言語: 英語

セミナー
Classical and Quantum Chaos
2022年5月12日(木) 16:00  17:00
首藤 啓 (東京都立大学 大学院理学研究科 物理学専攻 教授)
Classical and quantum mechanics in multidimensions are qualitatively different from those in onedimension 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.
会場: via Zoom
イベント公式言語: 英語

Diversity of Asgardarchaota and Theoretical verification of the endosymbiotic theory
2022年4月28日(木) 10:00  11:00
熊倉 大騎 (北海道大学 大学院生命科学院 生命科学専攻 博士課程)
How did intracellular symbiosis occur and give rise to eukaryotic ancestor? This question has been considered to the two theories as threedomain theory and eocyte theory. Here I present asgard archaea, the archaeon closest to eukaryotes. Asgard archaea is an archaeon found at a deepsea 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 eukaryoticspecific 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 branchlike 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.
会場: via Zoom
イベント公式言語: 英語

セミナー
Neurons are potential statisticians
2022年4月21日(木) 10:00  11:00
磯村 拓哉 (理化学研究所 脳神経科学研究センター (CBS) 脳型知能理論研究ユニット ユニットリーダー)
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 freeenergy 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 freeenergy 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 freeenergy principle. This equivalence speaks to the freeenergy 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 freeenergy principle, leading to future applications in the early diagnosis and treatment of psychiatric disorders, and in the development of braininspired artificial intelligence that can learn like humans.
会場: via Zoom
イベント公式言語: 英語

Coarsegrained molecular dynamics simulation via Langevin simulation
2022年4月14日(木) 10:00  11:00
横田 宏 (数理創造プログラム 特別研究員)
In the cell biology or biophysics, many mechanical properties of proteins or DNA are discussed. In order to consider the dynamics, coarsegrained molecular dynamics simulation (Langevin simulation) is useful. In this seminar, I will give you the introductory and methodology talk about the Langevin simulation.
会場: via Zoom
イベント公式言語: 英語

Journal Club: Phase separation in a manycomponent system with random interactions
2022年3月31日(木) 10:00  11:00
足立 景亮 (理化学研究所 生命機能科学研究センター (BDR) 生体非平衡物理学理研白眉研究チーム 基礎科学特別研究員)
Several kinds of protein condensates have been observed in living cells, and the liquidliquid 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 randommatrix theory to the phase separation dynamics.
会場: via Zoom
イベント公式言語: 英語

Criticality in stochastic SIR model for infectious diseases based on pathintegral approach
2022年3月24日(木) 10:00  11:00
安井 繁宏 (高知大学医学部 医療情報科学センター 助教)
The susceptibleinfectedremoved (SIR) model provides us with a basic scheme for the analysis of the epidemic infectious diseases such as the COVID19. In this presentation, we focus on the stochastic SIR model which describes the stochastic timeevolutions 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 DoiPeliti prescription, furthermore, we introduce the pathintegral formalism similar to the quantum field theory, and perform the perturbative and nonperturbative calculations for the timeevolution 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.
会場: via Zoom
イベント公式言語: 英語
132 イベント
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