BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Sydney Precision Data Science Centre - ECPv6.17.1//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-ORIGINAL-URL:https://spds.sydney.edu.au
X-WR-CALDESC:Events for Sydney Precision Data Science Centre
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:Australia/Sydney
BEGIN:STANDARD
TZOFFSETFROM:+1100
TZOFFSETTO:+1000
TZNAME:AEST
DTSTART:20250405T160000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+1000
TZOFFSETTO:+1100
TZNAME:AEDT
DTSTART:20251004T160000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+1100
TZOFFSETTO:+1000
TZNAME:AEST
DTSTART:20260404T160000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+1000
TZOFFSETTO:+1100
TZNAME:AEDT
DTSTART:20261003T160000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+1100
TZOFFSETTO:+1000
TZNAME:AEST
DTSTART:20270403T160000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+1000
TZOFFSETTO:+1100
TZNAME:AEDT
DTSTART:20271002T160000
END:DAYLIGHT
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Australia/Sydney:20260810T130000
DTEND;TZID=Australia/Sydney:20260810T140000
DTSTAMP:20260724T064522Z
CREATED:20260724T064257Z
LAST-MODIFIED:20260724T064522Z
UID:5294-1786366800-1786370400@spds.sydney.edu.au
SUMMARY:SPEAK: Spatial Prompting with Expert Aligned Knowledge for Tissue Domain Identification in Spatial Transcriptomics
DESCRIPTION:Statistical Bioinformatics SeminarSpeaker: Dr Xiting Yan\, Yale University \n\n\n\nThis is an online event held via Zoom: https://uni-sydney.zoom.us/j/85114748391 \n\n\n\n\n\n\n\n\n\nSpatially resolved transcriptomic (SRT) data requires spatial domain identification to enable tissue microenvironment-specific downstream analyses. Here we present SPEAK (Spatial Prompting with Expert-Aligned Knowledge)\, a large language model (LLM)-based method to identify spatial domains from SRT data by taking advantage of the prior knowledge from both LLM and human experts. SPEAK constructs a spatial context prompt for each cell/spot based on cell types and marker genes of its neighboring cells\, enabling zero-shot inference\, expert-guided fine-tuning\, and prototype updating through two-stage prompting. Applications to STARmap\, Visium\, MERFISH and Xenium datasets showed advantages of SPEAK over existing spatial domain identification methods in domain prediction accuracy\, robustness to limited prior knowledge\, biological interpretability\, and capacity for efficient expert-guided fine-tuning with generalizability to other tissue sections.  \n\n\n\n\n\n\nSubscribe to our seminar mailing list\n\n\n\n\n→\n\n\n\n\n\n\n\nFind out more about the Statistical Bioinformatics seminar series\n\n\n\n\n\n→\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nDr Xiting Yan\n\n\n\nDr Yan is an Associate Professor from the Section of Pulmonary\, Critical Care and Sleep Medicine at Yale University School of Medicine\, with a secondary appointment at the Department of Biostatistics at Yale University School of Public Health. She is the Director of Data Analysis and Bioinformatics Hub at the Cent for Precision Pulmonary Medicine (P2MED). Dr Yan is a world known computational biologist\, bioinformatician and biostatistician\, with extensive research experiences in large scale multi-omic data analyses at both bulk and single-cell resolution. Her current research interest focus on two parts: (1) developing novel statistical and computational models to analyze large scale multi-omics and drug perturbation data to better understand disease pathogenesis and facilitate precision medicine development\, and (2) understanding the heterogeneity\, pathogenesis and progression of pulmonary diseases\, such as asthma\, idiopathic pulmonary fibrosis (IPF)\, sarcoidosis\, chronic obstructive pulmonary disease (COPD)\, pediatric cystic fibrosis and so on\, by tailoring statistical and computational methods based on existing biological knowledge of the diseases. She is specifically interested in development of novel analytical methods for single-cell RNA sequencing data\, spatial transcriptomic data\, drug perturbation data and integration of different omics data. In this talk\, she will introduce a recently developed method for spatial domain identification using large language model.
URL:https://spds.sydney.edu.au/event/speak-spatial-prompting-with-expert-aligned-knowledge-for-tissue-domain-identification-in-spatial-transcriptomics/
ATTACH;FMTTYPE=image/jpeg:https://spds.sydney.edu.au/wp-content/uploads/2025/01/Complex-systems-1-scaled.jpeg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Australia/Sydney:20260817T130000
DTEND;TZID=Australia/Sydney:20260817T140000
DTSTAMP:20260731T005319Z
CREATED:20260731T004352Z
LAST-MODIFIED:20260731T005319Z
UID:5405-1786971600-1786975200@spds.sydney.edu.au
SUMMARY:Single-cell and spatial methods to dissect complex diseases
DESCRIPTION:Judith and David Coffey SeminarSpeaker: Dr Boxiang Liu\, National University of Singapore \n\n\n\nThis is a hybrid event. In-person at the Mackenzie Seminar Room\, Level 6\, Charles Perkins CentreOnline via Zoom: https://uni-sydney.zoom.us/j/85114748391 \n\n\n\n\n\n\n\n\n\nGenome-wide association studies have identified more than a million risk variants for complex diseases\, yet fewer than 5% of complex disease loci have validated target genes. Closing this gap requires resolving genetic regulation at the right cell types\, ancestries\, and cellular contexts. In this talk\, I will present three complementary efforts from my lab. First\, AIDA — a single-cell atlas of ~1 million PBMCs from ~500 donors of diverse Asian descent profiled with 5′ chemistry — captures 4.3-fold more splice junctions than prior 3′ libraries and reveals ancestry-biased splicing events\, including an Asian-specific TCHP variant that modulates Graves’ disease risk. Second\, we developed ISSAC to map cell-state-dependent sQTLs across millions of cells and uncovers Alzheimer’s-biased sQTLs in dorsolateral prefrontal cortex snRNA-seq. Third\, we developed DIRAC to use adversarial domain-invariant representations to harmonize spatial multi-omic datasets\, enabling a high-resolution T cell development atlas in the mouse thymus. Together\, these methods chart a path from population-scale genetics to cell-state- and tissue-resolved mechanisms underlying complex diseases. \n\n\n\n\n\n\nSubscribe to our seminar mailing list\n\n\n\n\n→\n\n\n\n\n\n\n\nFind out more about the Statistical Bioinformatics seminar series\n\n\n\n\n\n→\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\nDr Boxiang Liu\n\n\n\nAs a PI and the director of the Genomic Data Science Lab in the National University of Singapore (www.boxiangliulab.com)\, Dr. Boxiang Liu advances the understanding of complex human diseases through innovative genetic\, single-cell\, and spatial transcriptomic analyses. He has published >90 publications\, including Nature\, Cell\, Nature Genetics\, and Nature Methods\, focusing on genomic and transcriptomic methodologies to dissect the genetic architecture of polygenic diseases. A significant facet of his academic endeavour includes a pivotal role in the Genotype-Tissue Expression (GTEx) Project\, contributing to a comprehensive understanding of genetic effects on molecular phenotype across diverse tissues. Additionally\, he spearheaded the single-cell splicing analysis within the Asian Immune Diversity Atlas project\, which collected >500 donors of diverse Asian ancestries. His group’s work provided the first cell-type-specific sQTL map using over 1 million PBMC single cells. He has been awarded the Presidential Young Professorship (Singapore)\, National Academy of Science Young Scientist Award (Singapore)\, National Research Foundation Fellow (Singapore)\, President’s Award in Natural Sciences and Mathematics (US)\, Charles B. Carrington Memorial Award (US)\, and the National Award for Outstanding Overseas Ph.D. Students (China). \n\n\n\nConnect with Boxiang:X: @boxiangliuBluesky: @boxiangliu.bsky.social
URL:https://spds.sydney.edu.au/event/single-cell-and-spatial-methods-to-dissect-complex-diseases/
ATTACH;FMTTYPE=image/jpeg:https://spds.sydney.edu.au/wp-content/uploads/2025/02/Complex-systems-1-edited-scaled.jpeg
END:VEVENT
END:VCALENDAR