BEGIN:VCALENDAR
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PRODID:-//Biomedical Mathematics Group - ECPv6.15.20//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-ORIGINAL-URL:https://www.ibs.re.kr/bimag
X-WR-CALDESC:Events for Biomedical Mathematics Group
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:Asia/Seoul
BEGIN:STANDARD
TZOFFSETFROM:+0900
TZOFFSETTO:+0900
TZNAME:KST
DTSTART:20190101T000000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20210416T120000
DTEND;TZID=Asia/Seoul:20210416T130000
DTSTAMP:20260423T115611
CREATED:20210412T110458Z
LAST-MODIFIED:20210412T110458Z
UID:4423-1618574400-1618578000@www.ibs.re.kr
SUMMARY:Synthetic multistability in mammalian cells
DESCRIPTION:We will discuss about “Synthetic multistability in mammalian cells”\, Zhu et al.\, bioRxiv (2021) \nIn multicellular organisms\, gene regulatory circuits generate thousands of molecularly distinct\, mitotically heritable states\, through the property of multistability. Designing synthetic multistable circuits would provide insight into natural cell fate control circuit architectures and allow engineering of multicellular programs that require interactions among cells in distinct states. Here we introduce MultiFate\, a naturally-inspired\, synthetic circuit that supports long-term\, controllable\, and expandable multistability in mammalian cells. MultiFate uses engineered zinc finger transcription factors that transcriptionally self-activate as homodimers and mutually inhibit one another through heterodimerization. Using model-based design\, we engineered MultiFate circuits that generate up to seven states\, each stable for at least 18 days. MultiFate permits controlled state-switching and modulation of state stability through external inputs\, and can be easily expanded with additional transcription factors. Together\, these results provide a foundation for engineering multicellular behaviors in mammalian cells. \n  \n 
URL:https://www.ibs.re.kr/bimag/event/2021-04-16/
LOCATION:B305 Seminar room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20210409T120000
DTEND;TZID=Asia/Seoul:20210409T130000
DTSTAMP:20260423T115611
CREATED:20210323T105030Z
LAST-MODIFIED:20210407T041048Z
UID:4304-1617969600-1617973200@www.ibs.re.kr
SUMMARY:Highly accurate fluorogenic DNA sequencing with information theory–based error correction
DESCRIPTION:We will discuss about “Highly accurate fluorogenic DNA sequencing with information theory–based error correction”\, Chen et al.\, Nature Biotechnology (2017) \nEliminating errors in next-generation DNA sequencing has proved challenging. Here we present error-correction code (ECC) sequencing\, a method to greatly improve sequencing accuracy by combining fluorogenic sequencing-by-synthesis (SBS) with an information theory–based error-correction algorithm. ECC embeds redundancy in sequencing reads by creating three orthogonal degenerate sequences\, generated by alternate dual-base reactions. This is similar to encoding and decoding strategies that have proved effective in detecting and correcting errors in information communication and storage. We show that\, when combined with a fluorogenic SBS chemistry with raw accuracy of 98.1%\, ECC sequencing provides single-end\, error-free sequences up to 200 bp. ECC approaches should enable accurate identification of extremely rare genomic variations in various applications in biology and medicine. \n  \n 
URL:https://www.ibs.re.kr/bimag/event/2021-04-09/
LOCATION:B305 Seminar room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20210401T120000
DTEND;TZID=Asia/Seoul:20210401T130000
DTSTAMP:20260423T115611
CREATED:20210331T003338Z
LAST-MODIFIED:20210406T075108Z
UID:4352-1617278400-1617282000@www.ibs.re.kr
SUMMARY:Yun Min Song\, A stochastic oscillator model simulates the entrainment of vertebrate cellular clocks by light
DESCRIPTION:We will discuss about “A stochastic oscillator model simulates the entrainment of vertebrate cellular clocks by light”\, Kumpost et al.\, bioRxiv (2021) \nThe circadian clock is a cellular mechanism that synchronizes various biological processes with respect to the time of the day. While much progress has been made characterizing the molecular mechanisms underlying this clock\, it is less clear how external light cues influence the dynamics of the core clock mechanism and thereby entrain it with the light-dark cycle. Zebrafish-derived cell cultures possess clocks that are directly light-entrainable\, thus providing an attractive laboratory model for circadian entrainment. Here\, we have developed a stochastic oscillator model of the zebrafish circadian clock\, which accounts for the core clock negative feedback loop\, light input\, and the proliferation of single-cell oscillator noise into population-level luminescence recordings. The model accurately predicts the entrainment dynamics observed in bioluminescent clock reporter assays upon exposure to a wide range of lighting conditions. Furthermore\, we have applied the model to obtain refitted parameter sets for cell cultures exposed to a variety of pharmacological treatments and predict changes in single-cell oscillator parameters. Our work paves the way for model-based\, large-scale screens for genetic or pharmacologically-induced modifications to the entrainment of circadian clock function.
URL:https://www.ibs.re.kr/bimag/event/2021-04-02/
LOCATION:B305 Seminar room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Journal Club
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20210319T113000
DTEND;TZID=Asia/Seoul:20210319T130000
DTSTAMP:20260423T115611
CREATED:20210312T062049Z
LAST-MODIFIED:20210406T075219Z
UID:4254-1616153400-1616158800@www.ibs.re.kr
SUMMARY:Seokjoo Chae\, Unified rational protein engineering with sequence-based deep representation learning
DESCRIPTION:In this presentation\, we are going to discuss the paper\, “Unified rational protein engineering with sequence-based deep representation learning” \nAbstract\nRational protein engineering requires a holistic understanding of protein function. Here\, we apply deep learning to unlabeled amino-acid sequences to distill the fundamental features of a protein into a statistical representation that is semantically rich and structurally\, evolutionarily and biophysically grounded. We show that the simplest models built on top of this unified representation (UniRep) are broadly applicable and generalize to unseen regions of sequence space. Our data-driven approach predicts the stability of natural and de novo designed proteins\, and the quantitative function of molecularly diverse mutants\, competitively with the state-of-the-art methods. UniRep further enables two orders of magnitude efficiency improvement in a protein engineering task. UniRep is a versatile summary of fundamental protein features that can be applied across protein engineering informatics.
URL:https://www.ibs.re.kr/bimag/event/2021-03-19/
LOCATION:Tea Room\, IBS\, Daejeon\, Daejeon\, 34141\, Korea\, Republic of
CATEGORIES:Journal Club,Seminar
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20210312T113000
DTEND;TZID=Asia/Seoul:20210312T130000
DTSTAMP:20260423T115611
CREATED:20210305T084406Z
LAST-MODIFIED:20210406T075224Z
UID:4227-1615548600-1615554000@www.ibs.re.kr
SUMMARY:Dae Wook Kim\, Maximum Entropy Framework for Predictive Inference of Cell Population Heterogeneity and Responses in Signaling Networks
DESCRIPTION:We will discuss about “Maximum Entropy Framework for Predictive Inference of Cell Population Heterogeneity and Responses in Signaling Networks”\, Dixit et al.\, Cell Systems (2020) \nPredictive models of signaling networks are essential for understanding cell population heterogeneity and designing rational interventions in disease. However\, using computational models to predict heterogeneity of signaling dynamics is often challenging because of the extensive variability of biochemical parameters across cell populations. Here\, we describe a maximum entropy-based framework for inference of heterogeneity in dynamics of signaling networks (MERIDIAN). MERIDIAN estimates the joint probability distribution over signaling network parameters that is consistent with experimentally measured cell-to-cell variability of biochemical species. We apply the developed approach to investigate the response heterogeneity in the EGFR/Akt signaling network. Our analysis demonstrates that a significant fraction of cells exhibits high phosphorylated Akt (pAkt) levels hours after EGF stimulation. Our findings also suggest that cells with high EGFR levels predominantly contribute to the subpopulation of cells with high pAkt activity. We also discuss how MERIDIAN can be extended to accommodate various experimental measurements. \n  \n 
URL:https://www.ibs.re.kr/bimag/event/2021-03-12/
LOCATION:Tea Room\, IBS\, Daejeon\, Daejeon\, 34141\, Korea\, Republic of
CATEGORIES:Journal Club,Seminar
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20210305T130000
DTEND;TZID=Asia/Seoul:20210305T140000
DTSTAMP:20260423T115611
CREATED:20210228T074756Z
LAST-MODIFIED:20210406T075234Z
UID:4157-1614949200-1614952800@www.ibs.re.kr
SUMMARY:Eui Min Jeong\, Pairing of segmentation clock genes drives robust pattern formation
DESCRIPTION:We will discuss about “Pairing of segmentation clock genes drives robust pattern formation”\, Zinani et al.\, Nature (2021) \nGene expression is an inherently stochastic process; however\, organismal development and homeostasis require cells to coordinate the spatiotemporal expression of large sets of genes. In metazoans\, pairs of co-expressed genes often reside in the same chromosomal neighbourhood\, with gene pairs representing 10 to 50% of all genes\, depending on the species. Because shared upstream regulators can ensure correlated gene expression\, the selective advantage of maintaining adjacent gene pairs remains unknown6. Here\, using two linked zebrafish segmentation clock genes\, her1 and her7\, and combining single-cell transcript counting\, genetic engineering\, real-time imaging and computational modelling\, we show that gene pairing boosts correlated transcription and provides phenotypic robustness for the formation of developmental patterns. Our results demonstrate that the prevention of gene pairing disrupts oscillations and segmentation\, and the linkage of her1 and her7 is essential for the development of the body axis in zebrafish embryos. We predict that gene pairing may be similarly advantageous in other organisms\, and our findings could lead to the engineering of precise synthetic clocks in embryos and organoids \n  \n 
URL:https://www.ibs.re.kr/bimag/event/2021-03-05/
LOCATION:Tea Room\, IBS\, Daejeon\, Daejeon\, 34141\, Korea\, Republic of
CATEGORIES:Journal Club,Seminar
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20210204T130000
DTEND;TZID=Asia/Seoul:20210204T150000
DTSTAMP:20260423T115611
CREATED:20210223T091012Z
LAST-MODIFIED:20210228T073227Z
UID:3968-1612443600-1612450800@www.ibs.re.kr
SUMMARY:Hyukpyo Hong\, Frequency Spectra and the Color of Cellular Noise
DESCRIPTION:We will discuss about “Frequency Spectra and the Color of Cellular Noise”\,  bioRxiv (2020). \nThe invention of the Fourier integral in the 19th century laid the foundation for modern spectral analysis methods. By decomposing a (time) signal into its essential frequency components\, these methods uncovered deep insights into the signal and its generating process\, precipitating tremendous inventions and discoveries in many fields of engineering\, technology\, and physical science. In systems and synthetic biology\, however\, the impact of frequency methods has been far more limited despite their huge promise. This is in large part due to the difficulty of gleaning spectral information from single-cell trajectories\, owing to their distinctive noisy character forged by the underlying discrete stochastic dynamics of the living cell\, typically modelled as a continuous-time Markov chain (CTMC). Here we draw on stochastic process theory to develop a spectral theory and computational methodologies tailored specifically to the computation and analysis of frequency spectra of noisy cellular networks. For linear networks we present exact expressions for the frequency spectrum and use them to decompose the variability of a signal into its sources. For nonlinear networks\, we develop methods to obtain accurate Padé approximants of the spectrum from a single Monte Carlo trajectory simulation. Our results provide new conceptual and practical methods for the analysis and design of noisy cellular networks based on their output frequency spectra. We illustrate this through diverse case studies in which we show that the single-cell frequency spectrum enables topology discrimination\, synthetic oscillator optimization\, cybergenetic controller design\, and systematic investigation of stochastic entrainment. \n 
URL:https://www.ibs.re.kr/bimag/event/2021-02-04/
LOCATION:KAIST E2-1 room 3221\, E2-1 building\, Daejeon\, Daejeon\, 34141\, Korea\, Republic of
CATEGORIES:Journal Club,Seminar
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20210129T140000
DTEND;TZID=Asia/Seoul:20210129T160000
DTSTAMP:20260423T115611
CREATED:20210223T092935Z
LAST-MODIFIED:20210406T075248Z
UID:3978-1611928800-1611936000@www.ibs.re.kr
SUMMARY:Yun Min Song\, On the quasi-steady-state approximation in an open Michaelis-Menten reaction mechanism
DESCRIPTION:We will discuss about “On the quasi-steady-state approximation in an open Michaelis-Menten reaction mechanism”\, bioRxiv (2021). \nThe conditions for the validity of the standard quasi-steady-state approximation in the Michaelis–Menten mechanism in a closed reaction vessel have been well studied\, but much less so the conditions for the validity of this approximation for the system with substrate inflow. We analyze quasi-steady-state scenarios for the open system attributable to singular perturbations\, as well as less restrictive conditions. For both settings we obtain distinguished invariant slow manifolds and time scale estimates\, and we highlight the special role of singular perturbation parameters in higher order approximations of slow manifolds. We close the paper with a discussion of distinguished invariant manifolds in the global phase portrait. \n 
URL:https://www.ibs.re.kr/bimag/event/2021-01-29/
LOCATION:KAIST E2-1 room 3221\, E2-1 building\, Daejeon\, Daejeon\, 34141\, Korea\, Republic of
CATEGORIES:Journal Club,Seminar
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20210121T140000
DTEND;TZID=Asia/Seoul:20210121T160000
DTSTAMP:20260423T115611
CREATED:20210223T094006Z
LAST-MODIFIED:20210406T075136Z
UID:3980-1611237600-1611244800@www.ibs.re.kr
SUMMARY:Seokjoo Chae\, Synthetic gene networks recapitulate dynamic signal decoding and differential gene expression
DESCRIPTION:We will discuss about “Synthetic gene networks recapitulate dynamic signal decoding and differential gene expression”\, Benzinger et al.\, bioRxiv (2021) \nCells live in constantly changing environments and employ dynamic signaling pathways to transduce information about the signals they encounter. However\, the mechanisms by which dynamic signals are decoded into appropriate gene expression patterns remain poorly understood. Here\, we devise networked optogenetic pathways that achieve novel dynamic signal processing functions that recapitulate cellular information processing. Exploiting light-responsive transcriptional regulators with differing response kinetics\, we build a falling-edge pulse-detector and show that this circuit can be employed to demultiplex dynamically encoded signals. We combine this demultiplexer with dCas9-based gene networks to construct pulsatile-signal filters and decoders. Applying information theory\, we show that dynamic multiplexing significantly increases the information transmission capacity from signal to gene expression state. Finally\, we use dynamic multiplexing for precise multidimensional regulation of a heterologous metabolic pathway. Our results elucidate design principles of dynamic information processing and provide original synthetic systems capable of decoding complex signals for biotechnological applications. \n 
URL:https://www.ibs.re.kr/bimag/event/2021-01-21_1/
LOCATION:KAIST E2-1 room 3221\, E2-1 building\, Daejeon\, Daejeon\, 34141\, Korea\, Republic of
CATEGORIES:Journal Club,Seminar
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20201224T130000
DTEND;TZID=Asia/Seoul:20201224T140000
DTSTAMP:20260423T115611
CREATED:20210223T094304Z
LAST-MODIFIED:20210406T075331Z
UID:3983-1608814800-1608818400@www.ibs.re.kr
SUMMARY:Seokjoo Chae\, Ligand-receptor promiscuity enables cellular addressing
DESCRIPTION:We will discuss about “Ligand-receptor promiscuity enables cellular addressing”\, Su et al.\, bioRxiv (2021) \nIn multicellular organisms\, secreted ligands selectively activate\, or “address\,” specific target cell populations to control cell fate decision-making and other processes. Key cell-cell communication pathways use multiple promiscuously interacting ligands and receptors\, provoking the question of how addressing specificity can emerge from molecular promiscuity. To investigate this issue\, we developed a general mathematical modeling framework based on the bone morphogenetic protein (BMP) pathway architecture. We find that promiscuously interacting ligand-receptor systems allow a small number of ligands\, acting in combinations\, to address a larger number of individual cell types\, each defined by its receptor expression profile. Promiscuous systems outperform seemingly more specific one-to-one signaling architectures in addressing capacity. Combinatorial addressing extends to groups of cell types\, is robust to receptor expression noise\, grows more powerful with increasing receptor multiplicity\, and is maximized by specific biochemical parameter relationships. Together\, these results identify fundamental design principles governing cell addressing by ligand combinations.
URL:https://www.ibs.re.kr/bimag/event/2020-12-24_1/
LOCATION:KAIST E2-1 room 3221\, E2-1 building\, Daejeon\, Daejeon\, 34141\, Korea\, Republic of
CATEGORIES:Journal Club,Seminar
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20201224T020000
DTEND;TZID=Asia/Seoul:20201224T150000
DTSTAMP:20260423T115611
CREATED:20210223T094556Z
LAST-MODIFIED:20210406T075337Z
UID:3985-1608775200-1608822000@www.ibs.re.kr
SUMMARY:Dae Wook Kim\, Neural network aided approximation and parameter inference of stochastic models of gene expression
DESCRIPTION:We will discuss about “Neural network aided approximation and parameter inference of stochastic models of gene expression”\, Jian et al.\, bioRxiv (2020). \nNon-Markov models of stochastic biochemical kinetics often incorporate explicit time delays to effectively model large numbers of intermediate biochemical processes. Analysis and simulation of these models\, as well as the inference of their parameters from data\, are fraught with difficulties because the dynamics depends on the system’s history. Here we use an artificial neural network to approximate the time-dependent distributions of non-Markov models by the solutions of much simpler time-inhomogeneous Markov models; the approximation does not increase the dimensionality of the model and simultaneously leads to inference of the kinetic parameters. The training of the neural network uses a relatively small set of noisy measurements generated by experimental data or stochastic simulations of the non-Markov model. We show using a variety of models\, where the delays stem from transcriptional processes and feedback control\, that the Markov models learnt by the neural network accurately reflect the stochastic dynamics across parameter space.
URL:https://www.ibs.re.kr/bimag/event/2020-12-24_2/
LOCATION:KAIST E2-1 room 3221\, E2-1 building\, Daejeon\, Daejeon\, 34141\, Korea\, Republic of
CATEGORIES:Journal Club,Seminar
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
END:VCALENDAR