Research in the Sheffield lab


Nathan Sheffield, PhD

We develop and apply computational methods
to organize, analyze, and understand large epigenomic data.

Keywords

BIOLOGICAL QUESTIONS

Gene regulation
Epigenetics
Cancer

COMPUTATIONAL ANSWERS

High-performance computing
Machine learning
Data science

Biological motivation


Every cell in your body has the same genome*...

Yet your cells are diverse

Biological motivation


How can a single set of instructions
give rise to such a complex multicellular being?

Biological motivation


Through the process of differentiation,
cells assume individual functions and roles

Biological motivation


But when differentiation goes awry, disease may result

Biological motivation


Each cell-type folds DNA differently,
thereby using a different subset and
providing a molecular signature of its behavior

DNA folding can be measured by sequencing DNA





But huge, diverse datasets lead to computational challenges.

Research highlights

Defining cell type from chromatin accessibility


Sheffield et al. (2013). Genome Research.

Epigenetic heterogeneity in pediatric cancer


Sheffield et al. (2017). Nature Medicine.

Inferring regulatory activity from DNA methylation


Lawson et al. (2018). Bioinformatics.

Future projects

  • Connecting the genome to the epigenome
  • Acute Myeloid Leukemia epigenomics
  • Neuro-immuno-epigenomics
  • Standardizing metadata for big biomedical data analysis
Thanks for listening!

nsheff · databio.org · nsheffield@virginia.edu
Slides at http://databio.org/slides/research_overview.html