Personal Information
Entreprise/Lieu de travail
Philadelphia, PA United States
Secteur d’activité
Technology / Software / Internet
Site Web
www.greenelab.com
À propos
Casey is an assistant professor in the Department of Systems Pharmacology and Translational Therapeutics in the Perelman School of Medicine at the University of Pennsylvania. His lab develops deep learning methods that integrate distinct large-scale datasets to extract the rich and intrinsic information embedded in such integrated data. This approach reveals underlying principles of an organism’s genetics, its environment, and its response to that environment. Extracting this key contextual information reveals where the data’s context doesn’t fit existing models and raises the questions that a complete collection of publicly available data indicates researchers should be asking.
Mots-clés
bioinformatics
genomics
big data
gene expression
neural networks
machine learning
networks
denoising autoencoders
computational biology
data science
data integration
open source
parasite award
research parasite
reproducibility
adage
unsupervised
pathway
cancer
ehr
tissue-specific
netwas
systems biology
genetic epidemiology
gwas
microbiology
deep learning
rocky2015
Tout plus
Présentations
(8)Personal Information
Entreprise/Lieu de travail
Philadelphia, PA United States
Secteur d’activité
Technology / Software / Internet
Site Web
www.greenelab.com
À propos
Casey is an assistant professor in the Department of Systems Pharmacology and Translational Therapeutics in the Perelman School of Medicine at the University of Pennsylvania. His lab develops deep learning methods that integrate distinct large-scale datasets to extract the rich and intrinsic information embedded in such integrated data. This approach reveals underlying principles of an organism’s genetics, its environment, and its response to that environment. Extracting this key contextual information reveals where the data’s context doesn’t fit existing models and raises the questions that a complete collection of publicly available data indicates researchers should be asking.
Mots-clés
bioinformatics
genomics
big data
gene expression
neural networks
machine learning
networks
denoising autoencoders
computational biology
data science
data integration
open source
parasite award
research parasite
reproducibility
adage
unsupervised
pathway
cancer
ehr
tissue-specific
netwas
systems biology
genetic epidemiology
gwas
microbiology
deep learning
rocky2015
Tout plus