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X-WR-CALDESC:Events for Institute for Quantitative and Computational Biosciences
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DTSTART;TZID=America/Los_Angeles:20251104T133000
DTEND;TZID=America/Los_Angeles:20251106T163000
DTSTAMP:20250825T203411Z
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LAST-MODIFIED:20250825T203411Z
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SUMMARY:W24: Cancer Genomics
DESCRIPTION:As we step into the era of precision medicine\, the need for extensive genomic data analysis is more pressing than ever. With the advent of high-throughput technologies\, a plethora of genomic\, transcriptomic\, and epigenomic datasets from cancer patients have been sequenced\, providing a wealth of data for systematic bioinformatics analysis. This workshop is tailored to assist cancer bioinformaticians\, postdoc researchers\, and graduate students who are interested in incorporating expansive cancer genomic datasets from an open-source platform – The Cancer Genome Atlas (TCGA) – into their research.\n Enrolled participants will gain insights into the fundamental principles of TCGA\, including the different data categories and structures\, methods for downloading data\, and basic pipelines for data analysis within the TCGA platform. The workshop will also provide a versatile R script scaffold for mining TCGA datasets\, empowering attendees to analyze their own unique cohorts of cancer genomic datasets.
URL:https://qcb.ucla.edu/event/w15-bacterial-genomics/
LOCATION:529 Boyer Hall\, 611 Charles E Young Dr E\,\, Los Angeles\, CA\, 90095\, United States
CATEGORIES:Workshops,Interactive Workshop
ATTACH;FMTTYPE=image/png:https://qcb.ucla.edu/wp-content/uploads/sites/14/2020/02/1dNLbh0n_400x400.png
ORGANIZER;CN="QCB Collaboratory":MAILTO:collaboratory@ucla.edu
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DTSTART;TZID=America/Los_Angeles:20251118T133000
DTEND;TZID=America/Los_Angeles:20251120T163000
DTSTAMP:20250829T180223Z
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UID:28296-1763472600-1763656200@qcb.ucla.edu
SUMMARY:W25: Population Genetics Modeling
DESCRIPTION:In order to make inferences based on genomic data\, it is useful to understand the evolutionary forces that underlie observed genetic variation. The field of population genetics offers theoretical tools to test predictions\, gain intuition\, and even generate training data for statistical and deep learning models. However\, population genetics simulations have historically been slow and complex\, making effective usage of such tools difficult. Recently\, the evolutionary simulation framework SLiM (Selection on Linked Mutations) has revolutionized the field\, making the capability to model complex evolutionary scenarios more accessible. In this workshop\, participants will be introduced to the population genetics theory underlying SLiM\, learn how to model complex scenarios\, and practice interpreting the results of their simulations to make predictions about real-world data. Participants will also be given the opportunity to bring in their own data to analyze and use as inspiration to generate models. By learning about the fundamental forces that shape genomic data and how to model them\, participants will gain a combination of both theoretical insights into evolutionary genetics and practical insights into relevant computational tools.
URL:https://qcb.ucla.edu/event/w25-population-genetics/
LOCATION:529 Boyer Hall\, 611 Charles E Young Dr E\,\, Los Angeles\, CA\, 90095\, United States
CATEGORIES:Interactive Workshop,Workshops
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ORGANIZER;CN="QCB Collaboratory":MAILTO:collaboratory@ucla.edu
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