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PRODID:-//Biomedical Mathematics Group - ECPv6.15.20//NONSGML v1.0//EN
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X-ORIGINAL-URL:https://www.ibs.re.kr/bimag
X-WR-CALDESC:Events for Biomedical Mathematics Group
REFRESH-INTERVAL;VALUE=DURATION:PT1H
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TZID:Asia/Seoul
BEGIN:STANDARD
TZOFFSETFROM:+0900
TZOFFSETTO:+0900
TZNAME:KST
DTSTART:20200101T000000
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BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20210305T130000
DTEND;TZID=Asia/Seoul:20210305T140000
DTSTAMP:20260427T231346
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:20210312T113000
DTEND;TZID=Asia/Seoul:20210312T130000
DTSTAMP:20260427T231346
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:20210319T113000
DTEND;TZID=Asia/Seoul:20210319T130000
DTSTAMP:20260427T231346
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
END:VCALENDAR