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X-ORIGINAL-URL:https://www.ibs.re.kr/bimag
X-WR-CALDESC:Events for Biomedical Mathematics Group
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BEGIN:VTIMEZONE
TZID:Asia/Seoul
BEGIN:STANDARD
TZOFFSETFROM:+0900
TZOFFSETTO:+0900
TZNAME:KST
DTSTART:20220101T000000
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END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20240426T140000
DTEND;TZID=Asia/Seoul:20240426T160000
DTSTAMP:20260423T125138
CREATED:20240326T142526Z
LAST-MODIFIED:20240423T002345Z
UID:9423-1714140000-1714147200@www.ibs.re.kr
SUMMARY:Yun Min Song\, An improved rhythmicity analysis method using Gaussian Processes detects cell-density dependent circadian oscillations in stem cells
DESCRIPTION:We will discuss about “An improved rhythmicity analysis method using Gaussian Processes detects cell-density dependent circadian oscillations in stem cells”\, ArXiv (2023). \n  \nAbstract \nDetecting oscillations in time series remains a challenging problem even after decades of research. In chronobiology\, rhythms in time series (for instance gene expression\, eclosion\, egg-laying and feeding) datasets tend to be low amplitude\, display large variations amongst replicates\, and often exhibit varying peak-to-peak distances (non-stationarity). Most currently available rhythm detection methods are not specifically designed to handle such datasets. Here we introduce a new method\, ODeGP (Oscillation Detection using Gaussian Processes)\, which combines Gaussian Process (GP) regression with Bayesian inference to provide a flexible approach to the problem. Besides naturally incorporating measurement errors and non-uniformly sampled data\, ODeGP uses a recently developed kernel to improve detection of non-stationary waveforms. An additional advantage is that by using Bayes factors instead of p-values\, ODeGP models both the null (non-rhythmic) and the alternative (rhythmic) hypotheses. Using a variety of synthetic datasets we first demonstrate that ODeGP almost always outperforms eight commonly used methods in detecting stationary as well as non-stationary oscillations. Next\, on analyzing existing qPCR datasets that exhibit low amplitude and noisy oscillations\, we demonstrate that our method is more sensitive compared to the existing methods at detecting weak oscillations. Finally\, we generate new qPCR time-series datasets on pluripotent mouse embryonic stem cells\, which are expected to exhibit no oscillations of the core circadian clock genes. Surprisingly\, we discover using ODeGP that increasing cell density can result in the rapid generation of oscillations in the Bmal1 gene\, thus highlighting our method’s ability to discover unexpected patterns. In its current implementation\, ODeGP (available as an R package) is meant only for analyzing single or a few time-trajectories\, not genome-wide datasets.
URL:https://www.ibs.re.kr/bimag/event/2024-04-26-jc/
LOCATION:B232 Seminar Room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 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:20240419T100000
DTEND;TZID=Asia/Seoul:20240419T120000
DTSTAMP:20260423T125138
CREATED:20240326T142035Z
LAST-MODIFIED:20240415T082050Z
UID:9421-1713520800-1713528000@www.ibs.re.kr
SUMMARY:Eui Min Jeong\, Phenotypic switching in gene regulatory networks
DESCRIPTION:We will discuss about “Phenotypic switching in gene regulatory networks”\, PNAS (2014). \n  \nAbstract \nNoise in gene expression can lead to reversible phenotypic switching. Several experimental studies have shown that the abundance distributions of proteins in a population of isogenic cells may display multiple distinct maxima. Each of these maxima may be associated with a subpopulation of a particular phenotype\, the quantification of which is important for understanding cellular decision-making. Here\, we devise a methodology which allows us to quantify multimodal gene expression distributions and single-cell power spectra in gene regulatory networks. Extending the commonly used linear noise approximation\, we rigorously show that\, in the limit of slow promoter dynamics\, these distributions can be systematically approximated as a mixture of Gaussian components in a wide class of networks. The resulting closed-form approximation provides a practical tool for studying complex nonlinear gene regulatory networks that have thus far been amenable only to stochastic simulation. We demonstrate the applicability of our approach in a number of genetic networks\, uncovering previously unidentified dynamical characteristics associated with phenotypic switching. Specifically\, we elucidate how the interplay of transcriptional and translational regulation can be exploited to control the multimodality of gene expression distributions in two-promoter networks. We demonstrate how phenotypic switching leads to birhythmical expression in a genetic oscillator\, and to hysteresis in phenotypic induction\, thus highlighting the ability of regulatory networks to retain memory.
URL:https://www.ibs.re.kr/bimag/event/2024-04-19-jc/
LOCATION:B232 Seminar Room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 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:20240412T110000
DTEND;TZID=Asia/Seoul:20240412T120000
DTSTAMP:20260423T125138
CREATED:20240219T043247Z
LAST-MODIFIED:20240728T142452Z
UID:9233-1712919600-1712923200@www.ibs.re.kr
SUMMARY:Michael Chee\, How Data from Sleep Trackers Can Transform Our Understanding of Sleep
DESCRIPTION:Abstract: Wearable health trackers have shifted from gadgets for sports enthusiasts to valuable health sentinels over the last few years and that transformation is gathering pace. What do these devices really measure about sleep? What types of devices are there\, and which can we trust? Which of the many sleep measures reported\, contribute to a better understanding of sleep\, sleep habits and sleep health? How can sleep data improve personal and public health? What new uses of sensor data can we look forward to in coming years? I seek to shed light on these issues in a presentation that will focus on distinguishing scientific and health-oriented perspectives from consumer-facing ones.
URL:https://www.ibs.re.kr/bimag/event/michael-chee-how-data-from-sleep-trackers-can-transform-our-understanding-of-sleep-2/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2024/02/Michael-Chee-e1722176681984.jpeg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20240405T110000
DTEND;TZID=Asia/Seoul:20240405T120000
DTSTAMP:20260423T125138
CREATED:20240219T043532Z
LAST-MODIFIED:20240728T142635Z
UID:9236-1712314800-1712318400@www.ibs.re.kr
SUMMARY:Brian P. Delisle\, Circadian Regulation of Cardiac Electrophysiology
DESCRIPTION:Abstract: Circadian rhythms in physiology and behavior are regulated by circadian clocks\, ubiquitous molecular transcriptional-translational feedback loops that cycle with a periodicity of ~24 hours. Circadian clocks serve as cellular timekeepers regulating important cell-type specific functions. The phase of circadian rhythms and circadian clocks throughout the body are entrained to the light cycle by signals originating in the suprachiasmatic nucleus of the hypothalamus. The functional importance of circadian clocks in cardiomyocytes is underscored by the observation that genetic disruption of the circadian clock mechanism in mouse hearts alters the electrocardiogram (ECG)\, cardiac action potential\, and size of individual ionic currents. This presentation discusses recent basic science studies showing how daily environmental\, behavioral\, and circadian rhythms impact cardiac electrophysiology and cardiac arrhythmogenesis at the systems\, tissue\, and molecular levels. These studies provide new insights into how daily environmental\, behavioral\, and circadian rhythms affect the timing of cardiovascular events\, and they are starting to identify chronotherapeutic strategies that may mitigate the risk for cardiac arrhythmias.
URL:https://www.ibs.re.kr/bimag/event/brian-p-delisle-circadian-regulation-of-cardiac-electrophysiology/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2024/02/Brian-Delisle-e1722176786315.jpeg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20240329T140000
DTEND;TZID=Asia/Seoul:20240329T160000
DTSTAMP:20260423T125138
CREATED:20240228T011339Z
LAST-MODIFIED:20240326T143210Z
UID:9279-1711720800-1711728000@www.ibs.re.kr
SUMMARY:Dongju Lim\, Anti-Windup Protection Circuits for Biomolecular Integral Controllers
DESCRIPTION:We will discuss about “Anti-Windup Protection Circuits for Biomolecular Integral Controllers”\, bioRxiv (2023). \n  \nAbstract \nRobust Perfect Adaptation (RPA) is a desired property of biological systems wherein a system’s output perfectly adapts to a steady state\, irrespective of a broad class of perturbations. Achieving RPA typically requires the deployment of integral controllers\, which continually adjust the system’s output based on the cumulative error over time. However\, the action of these integral controllers can lead to a phenomenon known as “windup”. Windup occurs when an actuator in the system is unable to respond to the controller’s commands\, often due to physical constraints\, causing the integral error to accumulate significantly. In biomolecular control systems\, this phenomenon is especially pronounced due to the positivity of molecular concentrations\, inevitable promoter saturation and resource limitations. To protect against such performance deterioration or even instability\, we present three biomolecular anti-windup topologies. The underlying architectures of these topologies are then linked to classical control-theoretic anti-windup strategies. This link is made possible due the development of a general model reduction result for chemical reaction networks with fast sequestration reactions that is valid in both the deterministic and stochastic settings. The topologies are realized as chemical reaction networks for which genetic designs\, harnessing the flexibility of inteins\, are proposed. To validate the efficacy of our designs in mitigating windup effects\, we perform simulations across a range of biological systems\, including a complex model of Type I diabetic patients and advanced biomolecular proportional-integral-derivative (PID) controllers. This work lays a foundation for developing robust and reliable biomolecular control systems\, providing necessary safety and protection against windup-induced instability.
URL:https://www.ibs.re.kr/bimag/event/dongju-lim-solving-the-time-dependent-protein-distributions-for-autoregulated-bursty-gene-expression-using-spectral-decomposition/
LOCATION:B232 Seminar Room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 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:20240322T140000
DTEND;TZID=Asia/Seoul:20240322T160000
DTSTAMP:20260423T125138
CREATED:20240228T010806Z
LAST-MODIFIED:20240326T143602Z
UID:9277-1711116000-1711123200@www.ibs.re.kr
SUMMARY:Seokjoo Chae\, Transcriptome-wide analysis of cell cycle-dependent bursty gene expression from single-cell RNA-seq data using mechanistic model-based inference
DESCRIPTION:We will discuss about “Transcriptome-wide analysis of cell cycle-dependent bursty gene expression from single-cell RNA-seq data using mechanistic model-based inference”\, bioRxiv (2024) \nAbstract \nBursty gene expression is quantified by two intuitive parameters: the burst frequency and the burst size. While these parameters are known to be cell-cycle dependent for some genes\, a transcriptome-wide picture remains missing. Here we address this question by fitting a suite of mechanistic models of gene expression to mRNA count data for thousands of mouse genes\, obtained by sequencing of single cells for which the cell-cycle position has been inferred using a deep-learning approach. This leads to the estimation of the burst frequency and size per allele in the G1 and G2/M cell-cycle phases\, hence providing insight into the global patterns of transcriptional regulation. In particular\, we identify an interesting balancing mechanism: on average\, upon DNA replication\, the burst frequency decreases by ≈ 50%\, while the burst size increases by the same amount. We also show that for accurate estimation of the ratio of burst parameters in the G1 and G2/M phases\, mechanistic models must explicitly account for gene copy number differences between cells but\, surprisingly\, additional corrections for extrinsic noise due to the coupling of transcription to cell age within the cell cycle or technical noise due to imperfect capture of RNA molecules in sequencing experiments are unnecessary. \n 
URL:https://www.ibs.re.kr/bimag/event/2024-03-22-jc/
LOCATION:B232 Seminar Room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 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:20240312T163000
DTEND;TZID=Asia/Seoul:20240312T183000
DTSTAMP:20260423T125138
CREATED:20240228T005750Z
LAST-MODIFIED:20240307T011616Z
UID:9273-1710261000-1710268200@www.ibs.re.kr
SUMMARY:Brenda Lyn Gavina\, Reduced model for female endocrine dynamics: Validation and functional variations
DESCRIPTION:We will discuss about “Reduced model for female endocrine dynamics: Validation and functional variations.” Mathematical Biosciences 358 (2023): 108979. \nAbstract \n\n\n\n\nA normally functioning menstrual cycle requires significant crosstalk between hormones originating in ovarian and brain tissues. Reproductive hormone dysregulation may cause abnormal function and sometimes infertility. The inherent complexity in this endocrine system is a challenge to identifying mechanisms of cycle disruption\, particularly given the large number of unknown parameters in existing mathematical models. We develop a new endocrine model to limit model complexity and use simulated distributions of unknown parameters for model analysis. By employing a comprehensive model evaluation\, we identify a collection of mechanisms that differentiate normal and abnormal phenotypes. We also discover an intermediate phenotype—displaying relatively normal hormone levels and cycle dynamics—that is grouped statistically with the irregular phenotype. Results provide insight into how clinical symptoms associated with ovulatory disruption may not be detected through hormone measurements alone. \n 
URL:https://www.ibs.re.kr/bimag/event/2024-03-13-jc/
LOCATION:B378 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:20240308T110000
DTEND;TZID=Asia/Seoul:20240308T120000
DTSTAMP:20260423T125138
CREATED:20240219T042938Z
LAST-MODIFIED:20240728T142756Z
UID:9230-1709895600-1709899200@www.ibs.re.kr
SUMMARY:Mark Alber\, Combined multiscale mathematical modeling and experimental study of regulation mechanisms of shape formation during tissue development
DESCRIPTION:Abstract: The regulation and maintenance of an organ’s shape and structure is a major outstanding question in developmental biology. The Drosophila wing imaginal disc serves as a powerful system for elucidating design principles of the shape formation in epithelial morphogenesis.
URL:https://www.ibs.re.kr/bimag/event/mark-alber-combined-multiscale-mathematical-modeling-and-experimental-study-of-regulation-mechanisms-of-shape-formation-during-tissue-development/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2024/02/Mark-Alber-e1722176863895.jpeg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20240223T140000
DTEND;TZID=Asia/Seoul:20240223T170000
DTSTAMP:20260423T125138
CREATED:20240127T065045Z
LAST-MODIFIED:20240222T233219Z
UID:9153-1708696800-1708707600@www.ibs.re.kr
SUMMARY:Hyun Kim\, A statistical framework for differential pseudotime analysis with multiple single-cell RNA-seq samples
DESCRIPTION:We will discuss about “A statistical framework for differential pseudotime analysis with multiple single-cell RNA-seq samples\n”\, Nature communications 14.1 (2023): 7286. \n  \nAbstract \n\n\n\nPseudotime analysis with single-cell RNA-sequencing (scRNA-seq) data has been widely used to study dynamic gene regulatory programs along continuous biological processes. While many methods have been developed to infer the pseudotemporal trajectories of cells within a biological sample\, it remains a challenge to compare pseudotemporal patterns with multiple samples (or replicates) across different experimental conditions. Here\, we introduce Lamian\, a comprehensive and statistically-rigorous computational framework for differential multi-sample pseudotime analysis. Lamian can be used to identify changes in a biological process associated with sample covariates\, such as different biological conditions while adjusting for batch effects\, and to detect changes in gene expression\, cell density\, and topology of a pseudotemporal trajectory. Unlike existing methods that ignore sample variability\, Lamian draws statistical inference after accounting for cross-sample variability and hence substantially reduces sample-specific false discoveries that are not generalizable to new samples. Using both real scRNA-seq and simulation data\, including an analysis of differential immune response programs between COVID-19 patients with different disease severity levels\, we demonstrate the advantages of Lamian in decoding cellular gene expression programs in continuous biological processes. \n\n\n\n\n 
URL:https://www.ibs.re.kr/bimag/event/2024-02-23-jc/
LOCATION:B232 Seminar Room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 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:20240216T140000
DTEND;TZID=Asia/Seoul:20240216T170000
DTSTAMP:20260423T125138
CREATED:20240127T064902Z
LAST-MODIFIED:20240215T084643Z
UID:9150-1708092000-1708102800@www.ibs.re.kr
SUMMARY:Olive Cawiding\, Anticipating the occurrence and type of critical transitions
DESCRIPTION:We will discuss about “Anticipating the occurrence and type of critical transitions”\, Science Advances 9.1 (2023): eabq4558. \n  \nAbstract \nCritical transition can occur in many real-world systems. The ability to forecast the occurrence of transition is of major interest in a range of contexts. Various early warning signals (EWSs) have been developed to anticipate the coming critical transition or distinguish types of transition. However\, no effective method allows to establish practical threshold indicating the condition when the critical transition is most likely to occur. Here\, we introduce a powerful EWS\, named dynamical eigenvalue (DEV)\, that is rooted in bifurcation theory of dynamical systems to estimate the dominant eigenvalue of the system. Theoretically\, the absolute value of DEV approaches 1 when the system approaches bifurcation\, while its position in the complex plane indicates the type of transition. We demonstrate the efficacy of the DEV approach in model systems with known bifurcation types and also test the DEV approach on various critical transitions in real-world systems. \n 
URL:https://www.ibs.re.kr/bimag/event/2024-02-16-jc/
LOCATION:B232 Seminar Room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 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:20240214T110000
DTEND;TZID=Asia/Seoul:20240214T120000
DTSTAMP:20260423T125138
CREATED:20240209T001853Z
LAST-MODIFIED:20240209T001853Z
UID:9194-1707908400-1707912000@www.ibs.re.kr
SUMMARY:Kang MIn Lee\, Oscillation in brain and its potential role in inter-areal communication
DESCRIPTION:Abstract: Through the past decades\, electrophysiological experiments have revealed that extracellular electrical potential of brain show diverse rhythmic activity. Called ‘Local Field Potential(LFP)’\, those rhythmic activities are thought to reflect populational activity of neurons. In this talk\, I will introduce basic concepts on LFP and its generation mechanisms. Then\, roles of LFP in brain inter-areal communication will be presented. Particularly\, hypothesis on frequency specific communication and their experimental evidences will be main topics.
URL:https://www.ibs.re.kr/bimag/event/kang-min-lee-oscillation-in-brain-and-its-potential-role-in-inter-areal-communication/
LOCATION:B232 Seminar Room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Biomedical Mathematics Seminar
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20240208T090000
DTEND;TZID=Asia/Seoul:20240208T110000
DTSTAMP:20260423T125138
CREATED:20240207T045429Z
LAST-MODIFIED:20240207T235237Z
UID:9183-1707382800-1707390000@www.ibs.re.kr
SUMMARY:IBS BIMAG 2024 Winter Internship Presentation
DESCRIPTION:Program table: \n\n\n\nTopic\nTalk+Q&A\nPresenter\nTitle\n\n\nModel reduction\n9:00-9:10\nHyeong Jun Jang\nAccurate and precise estimation in enzyme inihibition\n\n\n9:10-9:20\nSeolah Shin\nBeyond Homogeneity: Assessing the Validity of the Michaelis–Menten Rate Law in Spatially Heterogeneous Environments\n\n\nCircadian rhythms & Sleep\n9:20-9:35\nAhn Jong Seok\, Kim Ju Hyeon\nEstimating missed initial sleep data to guess accurate circadian phase marker in sleep circadian rhythm\n\n\n9:35-9:45\nJihahm Yoo\nAlertness Model Personalization via Physics-informed Neural Network\n\n\n9:45-9:55\nAbbas Abbasli\nTemperature Compensation in Circadian Clocks: Challenging the Robustness-Plasticity Relationship in PER2 Phosphoswitch\n\n\nMedical survey reduction\n10:00-10:10\nSungmun Kim\nSymScore: Bridging Machine Learning and Real-World Healthcare\n\n\n10:10-10:17\nSieun Lee\nPredicting the Risk of PTSD using Simplified Questionnaire via SymScore\n\n\nData analysis\n10:17-10:27\nKyeong Tae Ko\nEstimation of compartment E with delay in SEIR model\n\n\n10:27-10:37\nHyun Suk Choo\nInferring the network structure of a small ecosystem using time series data\n\n\n10:37-10:47\nFaeyza R. Ardi\nDevelopment of a Python-Based scLENS and Its Integration with Multiple-Clustering Packages in a Python Environment
URL:https://www.ibs.re.kr/bimag/event/ibs-bimag-winter-internship-presentation/
LOCATION:B232 Seminar Room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Lunch Lab Meeting Seminar
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20240205T140000
DTEND;TZID=Asia/Seoul:20240205T150000
DTSTAMP:20260423T125138
CREATED:20240129T052339Z
LAST-MODIFIED:20240129T052339Z
UID:9163-1707141600-1707145200@www.ibs.re.kr
SUMMARY:Jong Kyoung Kim\, Dissecting cellular heterogeneity and plasticity in adipose tissue
DESCRIPTION:Abstract: Cell-to-cell variability in gene expression exists even in a homogeneous population of cells. Dissecting such cellular heterogeneity within a biological system is a prerequisite for understanding how a biological system is developed\, homeostatically regulated\, and responds to external perturbations. Single-cell RNA sequencing (scRNA-seq) allows the quantitative and unbiased characterization of cellular heterogeneity by providing genome-wide molecular profiles from tens of thousands of individual cells. Single-cell sequencing is expanding to combine genomic\, epigenomic\, and transcriptomic features with environmental cues from the same single cell. In this talk\, I demonstrate how scRNA-seq can be applied to dissect cellular heterogeneity and plasticity of adipose tissue\, and discuss related computational challenges.
URL:https://www.ibs.re.kr/bimag/event/jong-kyoung-kim-dissecting-cellular-heterogeneity-and-plasticity-in-adipose-tissue/
LOCATION:B232 Seminar Room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Biomedical Mathematics Seminar
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20240202T140000
DTEND;TZID=Asia/Seoul:20240202T170000
DTSTAMP:20260423T125138
CREATED:20240127T064735Z
LAST-MODIFIED:20240128T132151Z
UID:9148-1706882400-1706893200@www.ibs.re.kr
SUMMARY:Yun Min Song\, A trade-off in controlling upstream and downstream noise in signaling networks
DESCRIPTION:We will discuss about “A trade-off in controlling upstream and downstream noise in signaling networks”\,  bioRxiv (2023): 2023-08. \n  \nAbstract\nSignal transduction\, underpinning the function of a variety of biological systems\, is inevitably affected by fluctuations. It remains intriguing how the timescale of a signaling network relates to its capability of noise control\, specifically\, whether long timescale can average out fluctuation or accumulate fluctuation. Here\, we consider two noise components of the signaling system: the upstream noise from the fluctuation of the input signal and the downstream noise from the stochastic fluctuations of the network. We discover a fundamental trade-off in controlling the upstream and downstream noise: a longer timescale of the signaling network can buffer upstream noise\, while accumulate downstream noise. Moreover\, we confirm that this trade-off relation exists in real biological signaling networks such as a fold-change detection circuit and the p53 activation signaling system.
URL:https://www.ibs.re.kr/bimag/event/2024-02-02-jc/
LOCATION:B232 Seminar Room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 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:20240126T140000
DTEND;TZID=Asia/Seoul:20240126T160000
DTSTAMP:20260423T125138
CREATED:20231229T030126Z
LAST-MODIFIED:20240105T093349Z
UID:8991-1706277600-1706284800@www.ibs.re.kr
SUMMARY:Eui Min Jeong\, "Linear mapping approximation of gene regulatory networks with stochastic dynamics"
DESCRIPTION:We will discuss about “Linear mapping approximation of gene regulatory networks with stochastic dynamics”\, Nature communications 9.1 (2018): 3305. \n  \nAbstract \nThe presence of protein–DNA binding reactions often leads to analytically intractable models of stochastic gene expression. Here we present the linear-mapping approximation that maps systems with protein–promoter interactions onto approximately equivalent systems with no binding reactions. This is achieved by the marriage of conditional mean-field approximation and the Magnus expansion\, leading to analytic or semi-analytic expressions for the approximate time-dependent and steady-state protein number distributions. Stochastic simulations verify the method’s accuracy in capturing the changes in the protein number distributions with time for a wide variety of networks displaying auto- and mutual-regulation of gene expression and independently of the ratios of the timescales governing the dynamics. The method is also used to study the first-passage time distribution of promoter switching\, the sensitivity of the size of protein number fluctuations to parameter perturbation and the stochastic bifurcation diagram characterizing the onset of multimodality in protein number distributions.
URL:https://www.ibs.re.kr/bimag/event/2024-01-26-jc/
LOCATION:B232 Seminar Room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 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:20240119T140000
DTEND;TZID=Asia/Seoul:20240119T160000
DTSTAMP:20260423T125138
CREATED:20231229T025616Z
LAST-MODIFIED:20240105T093238Z
UID:8985-1705672800-1705680000@www.ibs.re.kr
SUMMARY:Dongju Lim\, The timing of cellular events: a stochastic vs deterministic perspective
DESCRIPTION:We will discuss about “The timing of cellular events: a stochastic vs deterministic perspective”\, bioRxiv (2023): 2023-07. \n  \nAbstract \nChanges in cell state are driven by key molecular events whose timing can often be measured experimentally. Of particular interest is the time taken for the levels of RNA or protein molecules to reach a critical threshold defining the triggering of a cellular event. While this mean trigger time can be estimated by numerical integration of deterministic models\, these ignore intrinsic noise and hence their predictions may be inaccurate. Here we study the differences between deterministic and stochastic model predictions for the mean trigger times using simple models of gene expression\, post-transcriptional feedback control\, and enzyme-mediated catalysis. By comparison of the two predictions\, we show that when promoter switching is present there exists a transition from a parameter regime where deterministic models predict a longer trigger time than stochastic models to a regime where the opposite occurs. Furthermore\, the ratio of the trigger times of the two models can be large\, particularly for auto-regulatory genetic feedback loops. Our theory provides intuitive insight into the origin of these effects and shows that deterministic predictions for cellular event timing can be highly inaccurate when molecule numbers are within the range known for many cells. \n 
URL:https://www.ibs.re.kr/bimag/event/2024-01-19-jc/
LOCATION:B232 Seminar Room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 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:20240117T110000
DTEND;TZID=Asia/Seoul:20240117T120000
DTSTAMP:20260423T125138
CREATED:20240111T072709Z
LAST-MODIFIED:20240111T073014Z
UID:9084-1705489200-1705492800@www.ibs.re.kr
SUMMARY:Junil Kim\, TENET+: a tool for reconstructing gene networks by integrating single cell expression and chromatin accessibility data
DESCRIPTION:Abstract: Reconstruction of gene regulatory networks (GRNs) is a powerful approach to capture a prioritized gene set controlling cellular processes. In our previous study\, we developed TENET a GRN reconstructor from single cell RNA sequencing (scRNAseq). TENET has a superior capability to identify key regulators compared with other algorithms. However\, accurate inference of gene regulation is still challenging. Here\, we suggest an integrative strategy called TENET+ by combining single cell transcriptome and chromatin accessibility data. TENET+ predicts target genes and open chromatin regions associated with transcription factors (TFs) and links the target regions to their corresponding target gene. As a result\, TENET+ can infer regulatory triplets of TF\, target gene\, and enhancer. By applying TENET+ to a paired scRNAseq and scATACseq dataset of human peripheral blood mononuclear cells\, we found critical regulators and their epigenetic regulations for the differentiations of CD4 T cells\, CD8 T cells\, B cells and monocytes. Interestingly\, not only did TENET+ predict several top regulators of each cell type which were not predicted by the motif-based tool SCENIC\, but we also found that TENET+ outperformed SCENIC in prioritizing critical regulators by using a cell type associated gene list. Furthermore\, utilizing and modeling regulatory triplets\, we can infer a comprehensive epigenetic GRN. In sum\, TENET+ is a tool predicting epigenetic gene regulatory programs for various types of datasets in an unbiased way\, suggesting that novel epigenetic regulations can be identified by TENET+. \nGithub page: https://github.com/hg0426/TENETPLUS.
URL:https://www.ibs.re.kr/bimag/event/junil-kim-tenet-a-tool-for-reconstructing-gene-networks-by-integrating-single-cell-expression-and-chromatin-accessibility-data/
LOCATION:B232 Seminar Room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Biomedical Mathematics Seminar
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2024/01/프로필사진-e1704958090187.jpg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20240112T140000
DTEND;TZID=Asia/Seoul:20240112T160000
DTSTAMP:20260423T125138
CREATED:20231229T025818Z
LAST-MODIFIED:20240106T124522Z
UID:8988-1705068000-1705075200@www.ibs.re.kr
SUMMARY:Seokjoo Chae\, AI Feynman: A physics-inspired method for symbolic regression
DESCRIPTION:We will discuss about “AI Feynman: A physics-inspired method for symbolic regression”\,Science Advances 6.16 (2020): eaay2631. \nAbstract \nA core challenge for both physics and artificial intelligence (AI) is symbolic regression: finding a symbolic expression that matches data from an unknown function. Although this problem is likely to be NP-hard in principle\, functions of practical interest often exhibit symmetries\, separability\, compositionality\, and other simplifying properties. In this spirit\, we develop a recursive multidimensional symbolic regression algorithm that combines neural network fitting with a suite of physics-inspired techniques. We apply it to 100 equations from the Feynman Lectures on Physics\, and it discovers all of them\, while previous publicly available software cracks only 71; for a more difficult physics-based test set\, we improve the state-of-the-art success rate from 15 to 90%.
URL:https://www.ibs.re.kr/bimag/event/2024-01-12-jc/
LOCATION:B232 Seminar Room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, 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:20240109T100000
DTEND;TZID=Asia/Seoul:20240109T110000
DTSTAMP:20260423T125138
CREATED:20240103T102249Z
LAST-MODIFIED:20240107T033247Z
UID:9021-1704794400-1704798000@www.ibs.re.kr
SUMMARY:Hyung Jin Choi\, A Normative Framework Dissociates Need and Motivation in Hypothalamic Neurons
DESCRIPTION:Abstract: Physiological needs evoke motivational drives to produce natural behaviours for survival. However\, the temporally intertwined dynamics of need and motivation have made it challenging to differentiate these two components in previous experimental paradigms. Based on classic homeostatic theories\, we established a normative framework to derive computational models of neural activity and behaviours for need-encoding and motivation-encoding neurons during events that induce predicted gain or loss. We further developed simple and intuitive experimental paradigms that enabled us to distinguish the distinct roles of subpopulations of neurons in the hypothalamus. Our results show that AgRP neurons and LHLepR neurons are consistent with need and motivation\, respectively. Our study provides a parsimonious understanding of how distinct hypothalamic neurons separately encode need and motivation to produce adaptive behaviours for maintaining homeostasis.\n\nZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
URL:https://www.ibs.re.kr/bimag/event/hyung-jin-choi-a-normative-framework-dissociates-need-and-motivation-in-hypothalamic-neurons-3/
LOCATION:B232 Seminar Room\, IBS\, 55 Expo-ro Yuseong-gu\, Daejeon\, Daejeon\, 34126\, Korea\, Republic of
CATEGORIES:Biomedical Mathematics Seminar
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2024/01/최형진-사진-HAHN1836-실험가운-해부학-1-1-1-e1704595806914.jpg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20240105T140000
DTEND;TZID=Asia/Seoul:20240105T160000
DTSTAMP:20260423T125138
CREATED:20231130T084919Z
LAST-MODIFIED:20231215T004743Z
UID:8754-1704463200-1704470400@www.ibs.re.kr
SUMMARY:Hyeontae Jo\, Integration of Neural Network-Based Symbolic Regression in Deep Learning for Scientific Discovery
DESCRIPTION:We will discuss about “Integration of Neural Network-Based Symbolic Regression in Deep Learning for Scientific Discovery” IEEE Transactions on neural networks and learning systems 32.9 (2020): 4166-4177. \nAbstract \n\nSymbolic regression is a powerful technique to discover analytic equations that describe data\, which can lead to explainable models and the ability to predict unseen data. In contrast\, neural networks have achieved amazing levels of accuracy on image recognition and natural language processing tasks\, but they are often seen as black-box models that are difficult to interpret and typically extrapolate poorly. In this article\, we use a neural network-based architecture for symbolic regression called the equation learner (EQL) network and integrate it with other deep learning architectures such that the whole system can be trained end-to-end through backpropagation. To demonstrate the power of such systems\, we study their performance on several substantially different tasks. First\, we show that the neural network can perform symbolic regression and learn the form of several functions. Next\, we present an MNIST arithmetic task where a convolutional network extracts the digits. Finally\, we demonstrate the prediction of dynamical systems where an unknown parameter is extracted through an encoder. We find that the EQL-based architecture can extrapolate quite well outside of the training data set compared with a standard neural network-based architecture\, paving the way for deep learning to be applied in scientific exploration and discovery
URL:https://www.ibs.re.kr/bimag/event/2024-01-05-jc/
LOCATION:B378 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:20231229T140000
DTEND;TZID=Asia/Seoul:20231229T160000
DTSTAMP:20260423T125138
CREATED:20231130T085100Z
LAST-MODIFIED:20231228T025820Z
UID:8756-1703858400-1703865600@www.ibs.re.kr
SUMMARY:Hyun Kim\, MultiVI: deep generative model for the integration of multimodal data
DESCRIPTION:We will discuss about “MultiVI: deep generative model for the integration of multimodal data” Nature Methods 20.8 (2023): 1222-1231. \nAbstract \n\n\n\nJointly profiling the transcriptome\, chromatin accessibility and other molecular properties of single cells offers a powerful way to study cellular diversity. Here we present MultiVI\, a probabilistic model to analyze such multiomic data and leverage it to enhance single-modality datasets. MultiVI creates a joint representation that allows an analysis of all modalities included in the multiomic input data\, even for cells for which one or more modalities are missing. It is available at scvi-tools.org.
URL:https://www.ibs.re.kr/bimag/event/2023-12-29-jc/
LOCATION:B378 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:20231215T140000
DTEND;TZID=Asia/Seoul:20231215T160000
DTSTAMP:20260423T125138
CREATED:20231130T085305Z
LAST-MODIFIED:20231214T000605Z
UID:8758-1702648800-1702656000@www.ibs.re.kr
SUMMARY:Yun Min Song\, Pulsed stimuli entrain p53 to synchronize single cells and modulate cell-fate determination
DESCRIPTION:We will discuss about “Pulsed stimuli entrain p53 to synchronize single cells and modulate cell-fate determination” bioRxiv (2023): 2023-10. \nAbstract \n\n\nEntrainment to an external stimulus enables a synchronized oscillatory response across a population of cells\, increasing coherent responses by reducing cell-to-cell heterogeneity. It is unclear whether the property of entrainability extends to systems where responses are intrinsic to the individual cell\, rather than dependent on coherence across a population of cells. Using a combination of mathematical modeling\, time-lapse fluorescence microscopy\, and single-cell tracking\, we demonstrated that p53 oscillations triggered by DNA double-strand breaks (DSBs) can be entrained with a periodic damage stimulus\, despite such synchrony not known to function in effective DNA damage responses. Surprisingly\, p53 oscillations were experimentally entrained over a wider range of DSB frequencies than predicted by an established computational model for the system. We determined that recapitulating the increased range of entrainment frequencies required\, non-intuitively\, a less robust oscillator and wider steady-state valley on the energy landscape. Further\, we show that p53 entrainment can lead to altered expression dynamics of downstream targets responsible for cell fate in a manner dependent on target mRNA stability. Overall\, this study demonstrates that entrainment can occur in a biological oscillator despite the apparent lack of an evolutionary advantage conferred through synchronized responses and highlights the potential of externally entraining p53 dynamics to reduce cellular variability and synchronize cell-fate responses for therapeutic outcomes.
URL:https://www.ibs.re.kr/bimag/event/2023-12-15-jc/
LOCATION:B378 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:20231208T153000
DTEND;TZID=Asia/Seoul:20231208T173000
DTSTAMP:20260423T125138
CREATED:20231130T084548Z
LAST-MODIFIED:20231207T014408Z
UID:8751-1702049400-1702056600@www.ibs.re.kr
SUMMARY:Olive Cawiding\, Time delays modulate the stability of complex ecosystems
DESCRIPTION:We will discuss about “Time delays modulate the stability of complex ecosystems” Nature Ecology & Evolution 7.10 (2023): 1610-1619. \nAbstract \nWhat drives the stability\, or instability\, of complex ecosystems? This question sits at the heart of community ecology and has motivated a large body of theoretical work exploring how community properties shape ecosystem dynamics. However\, the overwhelming majority of current theory assumes that species interactions are instantaneous\, meaning that changes in the abundance of one species will lead to immediate changes in the abundances of its partners. In practice\, time delays in how species respond to one another are widespread across ecological contexts\, yet the impact of these delays on ecosystems remains unclear. Here we derive a new body of theory to comprehensively study the impact of time delays on ecological stability. We find that time delays are important for ecosystem stability. Large delays are typically destabilizing but\, surprisingly\, short delays can substantially increase community stability. Moreover\, in stark contrast to delay-free systems\, delays dictate that communities with more abundant species can be less stable than ones with less abundant species. Finally\, we show that delays fundamentally shift how species interactions impact ecosystem stability\, with communities of mixed interaction types becoming the most stable class of ecosystem. Our work demonstrates that time delays can be critical for the stability of complex ecosystems. \n 
URL:https://www.ibs.re.kr/bimag/event/2023-12-08-jc/
LOCATION:B378 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:20231208T110000
DTEND;TZID=Asia/Seoul:20231208T120000
DTSTAMP:20260423T125138
CREATED:20230831T142407Z
LAST-MODIFIED:20240728T143005Z
UID:8394-1702033200-1702036800@www.ibs.re.kr
SUMMARY:Robyn P. Araujo\, Cellular cognition and the simple complexity of the networks of life
DESCRIPTION:Abstract: TBD
URL:https://www.ibs.re.kr/bimag/event/robyn-p-araujo-cellular-cognition-and-the-simple-complexity-of-the-networks-of-life/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2023/08/Robyn-Araujo-e1722176950408.jpeg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20231201T140000
DTEND;TZID=Asia/Seoul:20231201T160000
DTSTAMP:20260423T125138
CREATED:20231030T040908Z
LAST-MODIFIED:20231114T081702Z
UID:8665-1701439200-1701446400@www.ibs.re.kr
SUMMARY:Eui Min Jung\, Hard Limits and Performance Tradeoffs in a Class of Antithetic Integral Feedback Networks
DESCRIPTION:We will discuss about “Hard limits and performance tradeoffs in a class of antithetic integral feedback networks.” Cell systems 9.1 (2019): 49-63. \nAbstract \n\nFeedback regulation is pervasive in biology at both the organismal and cellular level. In this article\, we explore the properties of a particular biomolecular feedback mechanism called antithetic integral feedback\, which can be implemented using the binding of two molecules. Our work develops an analytic framework for understanding the hard limits\, performance tradeoffs\, and architectural properties of this simple model of biological feedback control. Using tools from control theory\, we show that there are simple parametric relationships that determine both the stability and the performance of these systems in terms of speed\, robustness\, steady-state error\, and leakiness. These findings yield a holistic understanding of the behavior of antithetic integral feedback and contribute to a more general theory of biological control systems.
URL:https://www.ibs.re.kr/bimag/event/2023-12-01-jc/
LOCATION:B378 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:20231124T140000
DTEND;TZID=Asia/Seoul:20231124T160000
DTSTAMP:20260423T125138
CREATED:20231030T040641Z
LAST-MODIFIED:20231114T081738Z
UID:8663-1700834400-1700841600@www.ibs.re.kr
SUMMARY:Dongju Lim\, An accurate probabilistic step finder for time-series analysis
DESCRIPTION:We will discuss about “An accurate probabilistic step finder for time-series analysis.” bioRxiv (2023): 2023-09. \nAbstract \n\n\n\n\nNoisy time-series data is commonly collected from sources including Förster Resonance Energy Transfer experiments\, patch clamp and force spectroscopy setups\, among many others. Two of the most common paradigms for the detection of discrete transitions in such time-series data include: hidden Markov models (HMMs) and step-finding algorithms. HMMs\, including their extensions to infinite state-spaces\, inherently assume in analysis that holding times in discrete states visited are geometrically–or\, loosely speaking in common language\, exponentially–distributed. Thus the determination of step locations\, especially in sparse and noisy data\, is biased by HMMs toward identifying steps resulting in geometric holding times. In contrast\, existing step-finding algorithms\, while free of this restraint\, often rely on ad hoc metrics to penalize steps recovered in time traces (by using various information criteria) and otherwise rely on approximate greedy algorithms to identify putative global optima. Here\, instead\, we devise a robust and general probabilistic (Bayesian) step-finding tool that neither relies on ad hoc metrics to penalize step numbers nor assumes geometric holding times in each state. As the number of steps themselves in a time-series are\, a priori unknown\, we treat these within a Bayesian nonparametric (BNP) paradigm. We find that the method developed\, Bayesian Nonparametric Step (BNP-Step)\, accurately determines the number and location of transitions between discrete states without any assumed kinetic model and learns the emission distribution characteristic of each state. In doing so\, we verify that BNP-Step can analyze sparser data sets containing higher noise and more closely-spaced states than otherwise resolved by current state-of-the-art methods. What is more\, BNP-Step rigorously propagates measurement uncertainty into uncertainty over state transition locations\, numbers\, and emission levels as characterized by the posterior. We demonstrate the performance of BNP-Step on both synthetic data as well as data drawn from force spectroscopy experiments. \n 
URL:https://www.ibs.re.kr/bimag/event/2023-11-24-jc/
LOCATION:B378 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:20231122T160000
DTEND;TZID=Asia/Seoul:20231122T170000
DTSTAMP:20260423T125138
CREATED:20230831T143538Z
LAST-MODIFIED:20240728T143214Z
UID:8405-1700668800-1700672400@www.ibs.re.kr
SUMMARY:Alfio Quarteroni\, Physics-based and data-driven numerical models for computational medicine
DESCRIPTION:Abstract: I will report on some recent results on modelling the heart\, the external circulation\, and their application to problems of clinical relevance. I will show that a proper integration between PDE-based and machine-learning algorithms can improve the computational efficiency and enhance the generality of our iHEART simulator.
URL:https://www.ibs.re.kr/bimag/event/alfio-quarteroni-physics-based-and-data-driven-numerical-models-for-computational-medicine/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2023/08/Alfio-Quarteroni-e1722177125537.jpeg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20231117T110000
DTEND;TZID=Asia/Seoul:20231117T120000
DTSTAMP:20260423T125138
CREATED:20230831T143713Z
LAST-MODIFIED:20240728T143844Z
UID:8408-1700218800-1700222400@www.ibs.re.kr
SUMMARY:Samuel Isaacson\, Spatial Particle Modeling of Immune Processes
DESCRIPTION:Abstract: \nSurface Plasmon Resonance (SPR) assays are a standard approach for quantifying kinetic parameters in antibody-antigen binding reactions. Classical SPR approaches ignore the bivalent structure of antibodies\, and use simplified ODE models to estimate effective reaction rates for such interactions. In this work we develop a new SPR protocol\, coupling a model that explicitly accounts for the bivalent nature of such interactions and the limited spatial distance over which such interactions can occur\, to a SPR assay that provides more features in the generated data. Our approach allows the estimation of bivalent binding kinetics and the spatial extent over which antibodies and antigens can interact\, while also providing substantially more robust fits to experimental data compared to classical ODE models. I will present our new modeling and parameter estimation approach\, and demonstrate how it is being used to study interactions between antibodies and spike protein. I will also explain how we make the overall parameter estimation problem computationally feasible via the construction of a surrogate approximation to the (computationally-expensive) particle model. The latter enables fitting of model parameters via standard optimization approaches. \nTime-permitting\, I will also give an introduction to our Catalyst.jl symbolic chemical reaction modeling library\, which we have recently demonstrated outperforms a number of popular systems biology simulation packages in solving ODE and stochastic reaction models. A distinguishing feature of Catalyst is the ease with which it integrates with other Julia libraries to enable sensitivity analysis\, parameter estimation studies\, structural identifiability analysis\, bifurcation analysis\, solution of the chemical master equation\, and a variety of higher-level functionality.
URL:https://www.ibs.re.kr/bimag/event/samuel-isaacson-spatial-particle-modeling-of-immune-processes/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2023/08/Samuel-Isaacson-scaled-e1722177501809.jpeg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20231110T140000
DTEND;TZID=Asia/Seoul:20231110T160000
DTSTAMP:20260423T125138
CREATED:20231030T040327Z
LAST-MODIFIED:20231109T000051Z
UID:8661-1699624800-1699632000@www.ibs.re.kr
SUMMARY:Seokjoo Chae\, Uncertainty quantified discovery of chemical reaction systems via Bayesian scientific machine learning
DESCRIPTION:We will discuss about “Uncertainty quantified discovery of chemical reaction systems via Bayesian scientific machine learning.” bioRxiv (2023): 2023-09. \n  \nAbstract \nThe recently proposed Chemical Reaction Neural Network (CRNN) discovers chemical reaction pathways from time resolved species concentration data in a deterministic manner. Since the weights and biases of a CRNN are physically interpretable\, the CRNN acts as a digital twin of a classical chemical reaction network. In this study\, we employ a Bayesian inference analysis coupled with neural ordinary differential equations (ODEs) on this digital twin to discover chemical reaction pathways in a probabilistic manner. This allows for estimation of the uncertainty surrounding the learned reaction network. To achieve this\, we propose an algorithm which combines neural ODEs with a preconditioned stochastic gradient langevin descent (pSGLD) Bayesian framework\, and ultimately performs posterior sampling on the neural network weights. We demonstrate the successful implementation of this algorithm on several reaction systems by not only recovering the chemical reaction pathways but also estimating the uncertainty in our predictions. We compare the results of the pSGLD with that of the standard SGLD and show that this optimizer more efficiently and accurately estimates the posterior of the reaction network parameters. Additionally\, we demonstrate how the embedding of scientific knowledge improves extrapolation accuracy by comparing results to purely data-driven machine learning methods. Together\, this provides a new framework for robust\, autonomous Bayesian inference on unknown or complex chemical and biological reaction systems. \n  \n 
URL:https://www.ibs.re.kr/bimag/event/2023-11-10-jc/
LOCATION:B378 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:20231110T110000
DTEND;TZID=Asia/Seoul:20231110T120000
DTSTAMP:20260423T125138
CREATED:20230831T142922Z
LAST-MODIFIED:20240728T144105Z
UID:8399-1699614000-1699617600@www.ibs.re.kr
SUMMARY:Matthew Simpson\, Efficient prediction\, estimation and identifiability analysis with mechanistic mathematical models
DESCRIPTION:Abstract: Interpreting data using mechanistic mathematical models provides a foundation for discovery and decision-making in all areas of science and engineering. Key steps in using mechanistic mathematical models to interpret data include: (i) identifiability analysis; (ii) parameter estimation; and (iii) model prediction. Here we present a systematic\, computationally efficient likelihood-based workflow that addresses all three steps in a unified way. Recently developed methods for constructing profile-wise prediction intervals enable this workflow and provide the central linkage between different workflow components. These methods propagate profile-likelihood-based confidence sets for model parameters to predictions in a way that isolates how different parameter combinations affect model predictions. We show how to extend these profile-wise prediction intervals to two-dimensional interest parameters\, and then combine profile-wise prediction confidence sets to give an overall prediction confidence set that approximates the full likelihood-based prediction confidence set well. We apply our methods to a range of synthetic data and real-world ecological data describing re-growth of coral reefs on the Great Barrier Reef after some external disturbance\, such as a tropical cyclone or coral bleaching event.
URL:https://www.ibs.re.kr/bimag/event/matthew-simpson-efficient-prediction-estimation-and-identifiability-analysis-with-mechanistic-mathematical-models/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/jpeg:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2023/08/Matthew-Simpson-e1722177652995.jpeg
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
END:VCALENDAR