Graduate Group in Genomics and Computational Biology

GCB Home » Faculty » Algorithms and machine learning

  Name Research
Yoseph Barash The lab develops machine learning algorithms that integrate high-throughput data (RNASeq, CLIPSeq , PIPSeq, etc.) to infer RNA biogenesis and function, followed by
experimental verifications of inferred mechanisms.
Mary Regina Boland Developing novel data mining and machine learning algorithms that integrate data from Electronic Health Records, observational health data and genetics.
Pablo Camara The focus of our lab is on the development and application of innovative computational approaches to the study of cellular heterogeneity and its role in disease. 
Jennifer Phillips-Cremins Epigenetics | Genomics | Systems and Synthetic Bioengineering | Experimental Neuroscience | Molecular and Cellular Engineering
Robert Babak Faryabi

Developing algorithms for integrative cancer genomics and epigenomics studies.

Casey Greene Integrative methods for noisy biological data.
John Holmes Naturally inspired algorithms for knowledge discovery and optimization including learning classifier systems, genetic algorithms, artifical immune systems, ant colony optimization, and swarm intelligence.
Sampath Kannan Algorithms and Complexity
Shane Jensen Bayesian hierarchical models and their implementation
Junhyong Kim Single cell genomics, systems biology of cell function, evolution of cell function, population genetics and phylogenetics
Jason Moore
Development of artificial intelligence and machine learning methods
Kate Nathanson Inherited and somatic genetics and genomics of cancer, developing piplines for analysis, integration of inherited and somatic genetics
David Roos
Studies in the Roos laboratory employ modern cell biological, molecular genetic, biochemical/pharmacological, immunological and genomic/bioinformatic techniques to study protozoan parasites, eukaryotic evolution, and the biology of host-pathogen interactions.
Jeffrey Saven Methods for molecular and biopolymer design
faculty photo Kai Tan
Our lab is interested in Systems Biology of gene regulation in normal and disease development.
Lyle Ungar Scalable machine learning methods for data mining and text mining
Benjamin Voight Tools for locus discovery and fine-mapping using ENCODE
faculty photo Li-San Wang Annotate non-coding RNA using RNA-Seq data; detecting enhancers from functional genomics data
Nancy Zhang Change-point methods, empirical bayes estimation, genomics., model and variable
selection, scan statistics, statistical modeling