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CPCP 2017 Retreat: Improving Target-Ligand Activity Predictions by Combining Multiple Docking Scores Symposium Video

Talk by Michael Newton

CPCP 2017 Retreat: Virtual Drug Screening using Neural Networks Symposium Video

Talk by Moayad Alnammi

CPCP 2017 Retreat: MetaSRA - Normalized Sample-Specific Metadata for the Sequence Read Archive Symposium Video

Talk by Matt Bernstein

CPCP 2017 Retreat: Chromatin State and Long-Range Interaction Dynamics in Development and Disease Symposium Video

Talk by Sushmita Roy


Chromatin Module INference on Trees (CMINT) is an algorithm for learning chromatin modules, defined as groups of genomic loci that have similar chromatin states. Chromatin states in turn are defined by a combination of chromatin mark profiles.

MetaSRA: normalized human sample-specific metadata for the Sequence Read Archive

Falcon: Scaling up hands-off crowdsourced entity matching to build cloud services

Chromatin module inference on cellular trajectories identifies key transition points and poised epigenetic states in diverse developmental processes

SCnorm: robust normalization of single-cell RNA-seq data


scDD is an R package to identify genes with distributional changes across conditions in a single-cell RNA-seq experiment

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