The dREG gateway is a cloud service that predicts the location of enhancers and promoters using PRO-seq, GRO-seq, or ChRO-seq data. The hosted service is developed by the Danko lab at the Baker Institute and Cornell University and supported by the SciGap (Science Gateway Platform as a Service) and XSEDE (Extreme Science and Engineering Discovery Environment).
SciGaP supports access to core infrastructure services required by Science Gateways, including: user identity, accounts, authorization, and access to multiple computational resources from XSEDE.
XSEDE provides GPU resources under the project (TG-BIO160048: dREG Science Gateway).
Danko Lab at the Cornell University studies how gene expression programs are encoded in mammalian DNA sequences, and how these ‘regulatory codes’ contribute to evolution, development, and disease. Our specialty is developing statistics and machine-learning approaches to analyze genomic sequencing data, prepared using DNase-I-seq, ATAC-seq, PRO-seq, RNA-seq, and related assays. Our tools borrow a wide variety of ideas from the fields of statistics and machine-learning, including recent uses of hidden Markov models, support vector machines, and artificial neural networks.
Apache Airavata is a software framework that enables you to compose, manage, execute, and monitor large scale applications and workflows on distributed computing resources such as local clusters, supercomputers, computational grids, and computing clouds.