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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
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TZID:Asia/Seoul
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TZOFFSETFROM:+0900
TZOFFSETTO:+0900
TZNAME:KST
DTSTART:20210101T000000
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BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220414T103000
DTEND;TZID=Asia/Seoul:20220414T110000
DTSTAMP:20260424T221005
CREATED:20220413T163000Z
LAST-MODIFIED:20220130T045637Z
UID:5588-1649932200-1649934000@www.ibs.re.kr
SUMMARY:An overview of methods used for multi-scale modeling and analysis
DESCRIPTION:This talk will be presented online. Zoom link: 997 8258 4700 (pw: 1234) \nAbstract: TBA
URL:https://www.ibs.re.kr/bimag/event/2022-04-14-1/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/png:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2022/01/DK_250x250.png
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Asia/Seoul:20220414T110000
DTEND;TZID=Asia/Seoul:20220414T120000
DTSTAMP:20260424T221005
CREATED:20220413T170000Z
LAST-MODIFIED:20220224T002525Z
UID:5591-1649934000-1649937600@www.ibs.re.kr
SUMMARY:A systems biology approach using multi-scale modeling to understand the immune response to tuberculosis infection and treatment
DESCRIPTION:This talk will be presented online. Zoom link: 997 8258 4700 (pw: 1234) \nAbstract: Tuberculosis (TB) is one of the world’s deadliest infectious diseases. Caused by the pathogen Mycobacterium tuberculosis (Mtb)\, the standard regimen for treating TB consists of treatment with multiple antibiotics for at least six months. There are a number of complicating factors that contribute to the need for this long treatment duration and increase the risk of treatment failure. The structure of granulomas\, lesions forming in lungs in response to Mtb infection\, create heterogeneous antibiotic distributions that limit antibiotic exposure to Mtb.   We can use a systems biology approach pairing experimental data from non-human primates with computational modeling to represent and predict how factors impact antibiotic regimen efficacy and granuloma bacterial sterilization. We utilize an agent-based\, computational model that simulates granuloma formation\, function and treatment\, called GranSim.  A goal in improving antibiotic treatment for TB is to find regimens that can shorten the time it takes to sterilize granulomas while minimizing the amount of antibiotic required. We also created a whole host model\, called HOSTSIM\, to study Mtb dynamics within a human host.  Overall\, we use these models to help better understand TB treatment and strengthen our ability to predict regimens that can improve clinical treatment of TB.
URL:https://www.ibs.re.kr/bimag/event/2022-04-14-2/
LOCATION:ZOOM ID: 997 8258 4700 (Biomedical Mathematics Online Colloquium)\, (pw: 1234)
CATEGORIES:Biomedical Mathematics Online Colloquium
ATTACH;FMTTYPE=image/png:https://www.ibs.re.kr/bimag/cms/wp-content/uploads/2022/01/DK_250x250.png
ORGANIZER;CN="Jae Kyoung Kim":MAILTO:jaekkim@kaist.ac.kr
END:VEVENT
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