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BEGIN:VEVENT
DTSTAMP:20250929T081323Z
DTSTART:20251006T130000Z
DTEND:20251006T140000Z
SUMMARY:Ava Khamseh -- Pinpointing cell (sub)types\, states and transcrip
 tion factor mechanisms via quantification of (high order) molecular depe
 ndencies [IN PERSON]
UID:{http://www.columbasystems.com/customers/uom/gpp/eventid/}qrc-mfuzp87
 n-2diehf
DESCRIPTION:Join us for this seminar by Ava Khamseh (Edinburgh) as part o
 f the Maths in the Life Sciences seminar series here in Manchester (and 
 the online North West Seminar Series in Mathematical Biology and Data Sc
 iences in collaboration with Liverpool Universities). \n\n\nTitle: Pinpo
 inting cell (sub)types\, states and transcription factor mechanisms via 
 quantification of (high order) molecular dependencies\n \nAbstract: The 
 genome contains the complete set of DNA that provides instructions for c
 ells and tissues to develop and function. Genomic medicine integrates in
 sights from the genome with information about a person’s health to desig
 n and apply improved diagnostic tools and treatments. Research in genomi
 c medicine goes beyond identification of risk factors and aims at pinpoi
 nting underlying causal mechanisms\, often at various biological scales.
  \n \nIn the first part of this talk\, we introduce Stator\, a data-driv
 en methodology that identifies cell (sub)types and states without relyin
 g on cells’ local proximity in transcriptome space\, in contrast to meth
 ods such as clustering. Stator labels the same single cell multiply\, no
 t just by type and sub-type\, but also by state such as activation\, mat
 urity or cell cycle sub-phase\, through deriving higher-order (beyond pa
 ir-wise) gene expression dependencies from a sparse gene-by-cell express
 ion matrix. We exemplify Stator in liver disease/cancer to reveal expres
 sion programmes that identify early cancer states and predict patient su
 rvival. \n \nIn the second part of the talk\, we present a novel approac
 h\, integrating population genetics\, functional genomics and targeted m
 achine learning (TarGene)\, to quantify epistatic contributions to human
  traits via transcription factor mechanisms. By taking experimentally ve
 rified differentially binding variants across 9 nuclear hormone receptor
 s as candidates and using UK Biobank data across 768 traits\, we reveal\
 , for the first time\, hundreds of epistatic interactions involving thes
 e transcription factor mechanisms.\n\n\nThe talk will be also be streame
 d via Teams\, please contact carl.whitfield@manchester.ac.uk or igor.che
 rnyavsky@manchester.ac.uk for the zoom link\, or sign up to the mailing 
 list.\n\nTo subscribe to the mailing list for this event series\, please
  send an e-mail with the phrase “subscribe math-lifesci-seminar” in the 
 message body to listserv@listserv.manchester.ac.uk
STATUS:TENTATIVE
TRANSP:TRANSPARENT
CLASS:PUBLIC
LOCATION:2.2\, Roscoe Building\, Manchester
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