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UID:6248@i2m.univ-amu.fr
DTSTART;TZID=Europe/Paris:20211129T150000
DTEND;TZID=Europe/Paris:20211129T160000
DTSTAMP:20241120T200944Z
URL:https://www.i2m.univ-amu.fr/evenements/inferring-differentially-active
 -biological-processes-from-small-sample-gene-expression-data-sets-with-a-t
 ransfer-learning-approach-to-matrix-factorization/
SUMMARY:David Hirst (PhD at NSDB\, Aix-Marseille Université): Inferring di
 fferentially active biological processes\, from small sample gene expressi
 on data sets\, with a transfer learning approach to matrix factorization
DESCRIPTION:David Hirst: Matrix factorization can be applied to RNA gene ex
 pression data to identify sets of genes that jointly participate in biolog
 ical processes. This can help in inferring the extent to which the activit
 y of these processes varies across biological conditions. When a gene expr
 ession data set has only a limited number of samples\, the effectiveness o
 f matrix factorization is restricted. Therefore\, a transfer learning appr
 oach to matrix factorization has been proposed. Such an approach involves\
 , for a small target data set\, inferring scores associated with a latent 
 space that has been learned from a large heterogeneous learning data set.\
 nIn this study\, I used simulated data to explore how a transfer learning 
 approach to matrix factorization might improve the detection of differenti
 ally active gene sets. The matrix factorization methods I evaluated were s
 parse principal components\, independent component analysis\, non-negative
  matrix factorization and iCluster. In all cases the transfer learning app
 roach outperformed the direct factorization of target data sets with limit
 ed numbers of samples.\nI then applied matrix factorization to a subset of
  a large\, heterogeneous compendium of RNA-Seq data\, to learn a latent sp
 ace representative of functionally related gene sets. A small RNA-Seq data
  set\, comprised of samples taken from patients with either Facioscapulohu
 meral muscular dystrophy or Bosma arhinia microphthalmia syndrome\, or fro
 m healthy controls\, was projected onto the learned latent space. This app
 roach led to the detection of biological processes inferred as differentia
 lly active across disease groups.\n 
CATEGORIES:Séminaire,Hybrid,MABioS
LOCATION:I2M Luminy - Ancienne BU\, Salle Séminaire CIELL (1er étage)\, 1
 63 Avenue de Luminy\, 13009 Marseille\, France\, Salle 216\, France
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 9 Marseille\, France\, Salle 216\, France;X-APPLE-RADIUS=100;X-TITLE=I2M L
 uminy - Ancienne BU\, Salle Séminaire CIELL (1er étage):geo:0,0
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