BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Institute for Quantitative and Computational Biosciences - ECPv6.17.1//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:Institute for Quantitative and Computational Biosciences
X-ORIGINAL-URL:https://qcb.ucla.edu
X-WR-CALDESC:Events for Institute for Quantitative and Computational Biosciences
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/Los_Angeles
BEGIN:DAYLIGHT
TZOFFSETFROM:-0800
TZOFFSETTO:-0700
TZNAME:PDT
DTSTART:20250309T100000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0700
TZOFFSETTO:-0800
TZNAME:PST
DTSTART:20251102T090000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0800
TZOFFSETTO:-0700
TZNAME:PDT
DTSTART:20260308T100000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0700
TZOFFSETTO:-0800
TZNAME:PST
DTSTART:20261101T090000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0800
TZOFFSETTO:-0700
TZNAME:PDT
DTSTART:20270314T100000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0700
TZOFFSETTO:-0800
TZNAME:PST
DTSTART:20271107T090000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260710T160000
DTEND;TZID=America/Los_Angeles:20260710T170000
DTSTAMP:20260713T164528Z
CREATED:20260713T164528Z
LAST-MODIFIED:20260713T164528Z
UID:29175-1783699200-1783702800@qcb.ucla.edu
SUMMARY:Eric Deeds Professor\,  Vice Chair\,  Life Sciences Core - UCLA
DESCRIPTION:“A lack of distinct cellular identities in scRNA-seq data: revisiting Waddington’s landscape” \nSingle-cell RNA sequencing is revolutionizing our understanding of development\, differentiation and disease. Analysis of this data is often challenging\, however\, and tasks like clustering cells to uncover distinct cellular identities sometimes yields results that fail to align with existing biological knowledge. We analyzed publicly available data where the cell identity for each cell is known a priori\, and found that cells of very different types and lineages do not occupy distinct regions of gene expression space. Rather\, cells from different lineages overlap extensively with one another\, significantly complicating attempts to recover distinct identities within the data. Indeed\, our analysis of available epigenetic data for a wide variety of tissues\, organisms and technological measurement techniques revealed these data are not consistent with the predictions of Waddington’s landscape\, suggesting a need to revisit our picture of gene expression changes during differentiation and development.
URL:https://qcb.ucla.edu/event/eric-deeds-professor-vice-chair-life-sciences-core-ucla/
LOCATION:Boyer Hall 159
CATEGORIES:QCBio Seminar Series,Research Seminars
ATTACH;FMTTYPE=image/jpeg:https://qcb.ucla.edu/wp-content/uploads/sites/14/2026/07/eric-deeds.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260717T160000
DTEND;TZID=America/Los_Angeles:20260717T170000
DTSTAMP:20260713T164743Z
CREATED:20260713T164743Z
LAST-MODIFIED:20260713T164743Z
UID:29179-1784304000-1784307600@qcb.ucla.edu
SUMMARY:Neil Lin Assistant Professor\,  Mechanical and Aerospace Engineering  -  UCL
DESCRIPTION:“Unraveling Signaling Pathway Crosstalk Using LLMs” \nLiving cells do not process information through isolated\, linear pathways. Instead\, they rely on an intricate network of signaling crosstalk to make critical fate decisions. Deciphering this hidden cellular conversation remains one of the greatest challenges in targeted oncology and regenerative medicine. Yet traditional mechanistic models struggle to capture its complexity\, while the scale of modern single-cell datasets exceeds what can be analyzed manually. My lab asks a simple question: Can large language models\, designed to understand human language\, be repurposed to decode the language of cellular signaling? In this talk\, I will describe our efforts to develop LLMs as specialized\, locally deployed biological reasoning engines. By grounding these models in both the biomedical literature and high-dimensional single-cell data\, we show how they can identify key regulatory nodes where signaling pathways converge. Finally\, I will discuss how integrating biological knowledge with empirical data enables prediction of nonlinear cellular responses\, providing a scalable\, mechanistically informed framework for discovering novel therapeutic combinations.
URL:https://qcb.ucla.edu/event/neil-lin-assistant-professor-mechanical-and-aerospace-engineering-ucl/
LOCATION:Boyer Hall 159
CATEGORIES:QCBio Seminar Series,Research Seminars
ATTACH;FMTTYPE=image/jpeg:https://qcb.ucla.edu/wp-content/uploads/sites/14/2026/07/neil_lin_headshot.jpg-copy.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260724T160000
DTEND;TZID=America/Los_Angeles:20260724T170000
DTSTAMP:20260721T140507Z
CREATED:20260721T140448Z
LAST-MODIFIED:20260721T140507Z
UID:29189-1784908800-1784912400@qcb.ucla.edu
SUMMARY:Amy Goldberg\, Associate Professor\, Human Genetics\, UCLA
DESCRIPTION:TITLE: “Evolutionary perspectives on malaria” \nPathogen genomics increasingly guides public health decisions\, yet organisms with complex life cycles can produce genealogies that violate assumptions of standard population genetic methods. Similarly\, despite decades of population-genetic methods to infer population or adaptive histories in humans\, allele frequencies are often modeled to be roughly constant on short timescales relevant for public health. Here I discuss computational methods to leverage the growing amounts of genomic data from both host and pathogen perspectives. In particular\, I consider genomic evolution on ecologically and epidemiologically relevant timescales\, with implications for public health and basic biology.
URL:https://qcb.ucla.edu/event/amy-goldberg-associate-professor-human-genetics-ucla/
LOCATION:Boyer Hall 159
CATEGORIES:QCBio Seminar Series,Research Seminars
ATTACH;FMTTYPE=image/jpeg:https://qcb.ucla.edu/wp-content/uploads/sites/14/2026/07/PhotoHandler.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=America/Los_Angeles:20260731T160000
DTEND;TZID=America/Los_Angeles:20260731T170000
DTSTAMP:20260724T143631Z
CREATED:20260724T143631Z
LAST-MODIFIED:20260724T143631Z
UID:29193-1785513600-1785517200@qcb.ucla.edu
SUMMARY:Aaron Meyer\, Associate Professor\, Department of Bioengineering - UCLA
DESCRIPTION:“Building an Integrative View of Immunity with Data Tensors” \nHigh-throughput technologies now allow us to characterize immune responses with comprehensive scale and detail. While profiling cells across parameters like time\, perturbations\, and genetics yields rich data\, these multidimensional datasets challenge conventional analysis. Standard workflows typically flatten data into two-dimensional matrices\, sacrificing the essential context provided by the experimental structure. Instead\, I will show how tensor decompositions can preserve the structure of multidimensional studies. Choosing the right mathematical representation allows us to derive robust insights—from utilizing in vitro characterization to optimize engineered cytokines\, to identifying single-cell features that define autoimmunity. Furthermore\, these approaches enable integrative analysis that links cellular states to alterations at the tissue\, organ\, and individual scales.
URL:https://qcb.ucla.edu/event/aaron-meyer-associate-professor-department-of-bioengineering-ucla/
LOCATION:Boyer Hall 159
CATEGORIES:QCBio Seminar Series,Research Seminars
ATTACH;FMTTYPE=image/png:https://qcb.ucla.edu/wp-content/uploads/sites/14/2026/07/Meyer-8.19.53-AM.png
END:VEVENT
END:VCALENDAR