Bayesian model calibration and sensitivity analysis for oscillating biochemical experiments

B305 Seminar room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Korea, Republic of

Abstract: Most organisms exhibit various endogenous oscillating behaviors, which provides crucial information about how the internal biochemical processes are connected and regulated. Along with physical experiments, studying such periodicity of organisms often utilizes computer experiments relying on ordinary differential equations (ODE) because configuring the internal processes is difficult. Simultaneously utilizing both experiments, however, poses a

Cellular signaling beyond the Wiener-Kolmogorov limit

B305 Seminar room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Korea, Republic of

We will discuss about "Cellular signaling beyond the Wiener-Kolmogorov limit", Weisenberger et al., bioRxiv, 2021 Abstract: Accurate propagation of signals through stochastic biochemical networks involves significant expenditure of cellular resources. The same is true for regulatory mechanisms that suppress fluctuations in biomolecular populations. Wiener-Kolmogorov (WK) optimal noise filter theory, originally developed for engineering problems, has

Exploiting evolution to design better cancer therapies

ZOOM ID: 709 120 4849 (ibsbimag) (pw: 1234)

This talk will be presented online. Zoom link: 709 120 4849 (pw: 1234) Abstract: Our current approach to cancer treatment has been largely driven by finding molecular targets, those patients fortunate enough to have a targetable mutation will receive a fixed treatment schedule designed to deliver the maximum tolerated dose (MTD). These therapies generally achieve

Machine learning of stochastic gene network phenotypes

B305 Seminar room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Korea, Republic of

We will discuss about "Machine learning of stochastic gene network phenotypes", Park et al., bioRxiv, 2019 Abstract: A recurrent challenge in biology is the development of predictive quantitative models because most molecular and cellular parameters have unknown values and realistic models are analytically intractable. While the dynamics of the system can be analyzed via computer

Canceled

[CANCELED] Approaches to understanding tumour-immune interactions

ZOOM ID: 709 120 4849 (ibsbimag) (pw: 1234)

CANCELED due to unexpected circumstances This talk will be presented online. Zoom link: 709 120 4849 (pw: 1234) Abstract: While the presence of immune cells within solid tumours was initially viewed positively, as the host fighting to rid itself of a foreign body, we now know that the tumour can manipulate immune cells so that

Nonlinear delay differential equations and their application to modeling biological network motifs

B305 Seminar room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Korea, Republic of

We will discuss about “Nonlinear delay differential equations and their application to modeling biological network motifs”, Glass et al., Nature Communications, 2021 Abstract: Biological regulatory systems, such as cell signaling networks, nervous systems and ecological webs, consist of complex dynamical interactions among many components. Network motif models focus on small sub-networks to provide quantitative insight

COVID19 – Mathematical Modeling and Machine Learning

B305 Seminar room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Korea, Republic of

Abstract This presentation include the following two topics. First of all, we consider a spread model of COVID-19 with time-dependent parameters via deep learning. We developed a SIR model with time-dependent parameters via deep learning methods. Furthermore, we validated the model with the conventional model to confirm its convergent nature. Next, We also developed a

Stochastic processes as scientific instruments: efficient inference based on stochastic dynamical systems

ZOOM ID: 709 120 4849 (ibsbimag) (pw: 1234)

This talk will be presented online. Zoom link: 709 120 4849 (pw: 1234) Abstract: Questions about the mechanistic operation of biological systems are naturally formulated as stochastic processes, but confronting such models with data can be challenging.  In this talk, I describe the essence of the difficulty, highlighting both the technical issues and the importance

The Oscillation Amplitude, Not the Frequency of Cytosolic Calcium, Regulates Apoptosis Induction

B305 Seminar room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Korea, Republic of

We will discuss about “The Oscillation Amplitude, Not the Frequency of Cytosolic Calcium, Regulates Apoptosis Induction ”, Qi et al., iScience, 2020 Abstract: Although a rising concentration of cytosolic Ca2+ has long been recognized as an essential signal for apoptosis, the dynamical mechanisms by which Ca2+ regulates apoptosis are not clear yet. To address this, we constructed

A spatio-temporal model to reveal oscillator phenotypes in molecular clocks: Parameter estimation elucidates circadian gene transcription dynamics in single-cells

B305 Seminar room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Korea, Republic of

We will discuss about “A spatio-temporal model to reveal oscillator phenotypes in molecular clocks: Parameter estimation elucidates circadian gene transcription dynamics in single-cells”, Unosson et al., bioRxiv, 2021 We propose a stochastic distributed delay model together with a Markov random field prior and a measurement model for bioluminescence-reporting to analyse spatiotemporal gene expression in intact

A temporal signaling code to specify immune responses

ZOOM ID: 709 120 4849 (ibsbimag) (pw: 1234)

This talk will be presented online. Zoom link: 709 120 4849 (pw: 1234) Abstract: Immune sentinel cells must initiate the appropriate immune response upon sensing the presence of diverse pathogens or immune stimuli. To generate stimulus-specific gene expression responses, immune sentinel cells have evolved a temporal code in the dynamics of stimulus responsive transcription factors.

Balanced truncation for model reduction of biological oscillators

B378 Seminar room, IBS 55 Expo-ro Yuseong-gu, Daejeon, Korea, Republic of

We will discuss about “Balanced truncation for model reduction of biological oscillators”, Padoan et al., Biological Cybernetics, 2021 Model reduction is a central problem in mathematical biology. Reduced order models enable modeling of a biological system at different levels of complexity and the quantitative analysis of its properties, like sensitivity to parameter variations and resilience

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IBS Biomedical Mathematics Group (BIMAG)
Institute for Basic Science (IBS)
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