Dr. Bourne Keynote Address to CPCP Retreat 2016
Video of Dr. Phil Bourne of NIH giving keynote address at the CPCP Retreat 2016.
Recent & Upcoming Events
Jun 30, 2016
CPCP Second Annual Retreat
A day-long retreat highlighting recent research in the Center; featuring talks, posters, and lunch.
Apr 21, 2016
CPCP Seminar: Mining Structures from Massive Bio-Text Data: A Data-Driven Approach by Dr. Jiawei Han
Jiawei Han from the BD2K KnowEng Center-UIUC discussed mining structures from massive bio-text data.
Nov 10, 2015
CPCP Seminar: Transforming Your Research with High-Throughput Computing by Lauren Michael
Lauren Michael from the CHTC discussed high-throughput computing approaches to Big Data.
Oct 15, 2015
Big Privacy: Policy Meets Data Science Symposium
A symposium on the legal, policy, & technical issues at the intersection of privacy and data science
CPCP Seminar: Transforming Your Research Through High Throughput Computing Seminar Video
Presented by Lauren Michael
Big Privacy Symposium: Introductory and Welcoming Remarks Symposium Video
Presented by David Page, PhD
Big Privacy Symposium: Big Data, Big Headaches: Cultivating Public Trust in an Age of Unconsented Access to Identifiable Data Symposium Video
Presented by Barbara J. Evans PhD, JD, LLM
Big Privacy Symposium: Does Publishing a Predictive Model for Precision Medicine Put Patient Privacy at Risk? Symposium Video
Presented by Matt Fredrikson, PhD
Big Privacy Symposium: Panel Discussion Symposium Video
Panel Members: Barbara Evans, Matt Fredrikson, Arvind Narayanan, Pilar Ossorio, Vitaly Shmatikov
Computational drug repositioning using continuous self-controlled case series. Kuang Z, Thomson J, Caldwell M, Peissig P, Stewart R, Page D. Proceedings of the 22nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2016
Latent variable graphical model selection using harmonic analysis: applications to the Human Connectome Project (HCP). Kim WH, Kim HJ, Adluru N, Singh V. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016
Experimental design on a budget for sparse linear models and applications. Ravi SN, Ithapu VK, Johnson SC, Singh V. Proceedings of the 33rd International Conference on Machine Learning (ICML), 2016
Coupled harmonic bases for longitudinal characterization of brain networks. Hwang SJ, Adluru N, Collins MD, Ravi SN, Bendlin BB, Johnson SC, Singh V. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016
A hierarchical framework for state space matrix inference and clustering. Zuo C, Chen K, Hewitt K, Bresnick EH, Keles S. Annals of Applied Statistics, 2016
EBSeqHMM is an R package that implements an auto-regressive hidden Markov model for identifying genes and isoforms that have expression changes in ordered RNA-seq experiments, and clustering the identified genes into paths showing similar changes. EBSeqHMM is suitable for any ordered RNA-seq experiment including time courses and spatially ordered experiments.
Oscope is a statistical pipeline for identifying oscillatory genes and characterizing one cycle of their oscillation, referred to as a base-cycle, in unsynchronized snapshot single cell RNA-seq experiments. The Oscope pipeline includes three modules: a paired-sine model module to identify candidate oscillator pairs; a clustering module to cluster candidate oscillators into groups; and an extended nearest insertion module to estimate the base-cycle oscillation within each group.
OEFinder is an R package that allows an investigator to identify genes having the so-called ordering effect in single-cell RNA-seq data generated by the Fluidigm C1 platform. This effect (Leng et al., Nature Methods, 2015) refers to significantly increased gene expression in cells captured from sites with small or large plate output IDs.
The role model is a probability model used in the context of gene set analysis to describe the functional content of a user-supplied gene list, such as one derived from a genome-wide experiment. It integrates the list with gene sets from a knowledge base (e.g. Gene Ontology) and aims to summarize gene functions that are represented at an unusually high rate on the list. Compared to other gene-set enrichment analysis schemes, role model calculations contend better with the complexity of the knowledge base, including redundancies caused by overlapping sets and the effects of set-size variation.
GADGET is a web tool that for finding and ranking genes and metabolites that are associated with a given query in the biomedical literature. It's like a version of PubMed that returns genes and metabolites instead of articles.