iTHEMS Biology Seminar
193 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
Extremely low-coverage whole genome sequencing (XLC-WGS) as a cost-effective tool for pharmacogenomic profiling: Advantages and Challenges
October 6 (Thu) at 10:00 - 11:00, 2022
Lazaro-Guevara Jose Miguel (Postdoctoral Researcher, Department of Botany, The University of British Columbia, Canada)
Despite more than 10 years have passed since the first FDA labeling for pharmacogenomics (PGx), factors like the continuous updates on PGx related SNVs and the high cost for PGx testing have challenged its clinical implementation. However, next generation sequencing technologies like extremely low coverage whole genome sequencing (XLC-WGS) could overcome these difficulties. Our purpose is to explore the potential use of XLC-WGS as a cost-effective way for generate reliable PGx profiles that can be applied in preemptive and clinical scenarios. We sequenced 195 patients enrolled to the Utah Diabetes and Diabetic Complications Study using XLC-WGS, for further PGx Profiles generation. Additionally, we sequenced a subset of 190 individuals using Illumina CoreExome-24 v1.3 microarray and 50 individuals using Deep Coverage Whole Genome Sequencing (DC-WGS) for cross-platform comparisons. We built the Pharmacogenomic profiles extracting the genetic information from XLC-WGS in accordance to the extended manifest of the commercially available PGx microarray PharmacoScan. Once the PGx profiles were generated we perform a preemptive analysis using the Clinical Pharmacogenetics Implementation Consortium (CPIC®) Gene-Drugs interaction with “A” level. The cross-platform comparison revealed that genetic concordance between XLC-WGS, DC-WGS and Microarray platforms ranged from 98.25% to 99.7%. The preemptive PGx profiles identified patients at risk of potential adverse effects for intake of commonly prescribed medications, including 4 homozygote carriers of rs4149056 (in SLCO1B1) which has previously been associated with statin-related myopathy. As well as 25 homozygote carriers of rs9923231 (in VKORC1) that increased risk of Hemorrhage when starting Warfarin intake without dose adjustment/reduction.
Venue: via Zoom
Event Official Language: English
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Seminar
Discrete Stochastic Model for the Co-infection Dynamics with Defective Interfering Particles
September 26 (Mon) at 16:00 - 17:00, 2022
Jizhou Li (Postdoctoral Researcher, RIKEN Interdisciplinary Theoretical and Mathematical Sciences Program (iTHEMS))
Defective interfering particle (DIP) in the context of influenza A virus is a virion with a significantly shortened RNA segment substituting one of its eight full-length parent RNA segments, such that it is preferentially amplified during replications. Therefore, a cell co-infected by standard viruses (STVs) and DIPs will produce mainly DIPs, suppressing the STV yield and displaying nontrivial co-infection dynamics. An important approach to quantifying the co-infection dynamics is mathematical modeling with ordinary differential equations (ODEs), which treat relevant quantities (such as numbers of target cells, STVs, and DIPs) as continuous numbers evolving with prescribed physical laws. However, the ODE models are mean-field in nature that is only valid for scenarios with large numbers of STVs and DIPs. For small-number scenarios, the infection outcomes can be dominated by random fluctuations and stochasticity, which cannot be captured by ODE models. In this week’s biology seminar, we introduce a new Discrete Stochastic Model (DSM) aimed to rectify the shortcomings of the ODEs by treating the co-infection dynamics as stochastic processes. As we will show, the new DSM is consistent with the ODE model in the large number regime. In the low number regime, the DSM yields bi-modal distributions for the infection outcomes (extinct vs established infections) that are otherwise unattainable by ODE models.
Venue: via Zoom
Event Official Language: English
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Seminar
Genetic Drift and Gnatural Selection
September 22 (Thu) at 16:00 - 17:00, 2022
Thomas Hitchcock (Special Postdoctoral Researcher, RIKEN Interdisciplinary Theoretical and Mathematical Sciences Program (iTHEMS))
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.
Venue: via Zoom
Event Official Language: English
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Seminar
Hessian Geometric Structure of Equilibrium and Nonequilibrium Chemical Reaction Newtworks
September 8 (Thu) at 16:00 - 17:00, 2022
Tetsuya Kobayashi (Associate Professor, Institute of Industrial Science, The University of Tokyo)
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 energy-consuming 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 state-potential space where equilibrium and energetic aspect is formulated (1,2), and the other on the force-flux 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).
Venue: via Zoom
Event Official Language: English
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Seminar
Loop structure via one sided loop extrusion with twist deformation
September 1 (Thu) at 16:00 - 17:00, 2022
Hiroshi Yokota (Postdoctoral Researcher, RIKEN Interdisciplinary Theoretical and Mathematical Sciences Program (iTHEMS))
During cell division, a chromatin fiber condenses into the rod-like 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.
Venue: via Zoom
Event Official Language: English
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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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Seminar
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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Seminar
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, RIKEN Interdisciplinary Theoretical and Mathematical Sciences Program (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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Seminar
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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Seminar
Coarse-grained molecular dynamics simulation via Langevin simulation
April 14 (Thu) at 10:00 - 11:00, 2022
Hiroshi Yokota (Postdoctoral Researcher, RIKEN Interdisciplinary Theoretical and Mathematical Sciences Program (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
193 events