Research overview

My research develops and applies computational methods to study transcriptional and epigenetic regulation. My group focuses on open-source software for epigenomics and single-cell genomics, with an emphasis on regulatory mechanisms in cancer. A current focus is developing AI agents for genomics data reuse and metadata standardization.

I developed MACS, a widely used algorithm for ChIP-seq and related assays (cited >19,000 times in Google Scholar), and contributed to development of the Cistrome platform for integrative analysis of cis-regulatory elements. I previously served in the ENCODE and modENCODE Data Analysis Center and Analysis Working Group, where I contributed to large-scale chromatin-profile analysis and comparative regulatory genomics across model organisms and human. I also contributed to community ChIP-seq best-practice guidelines.

I am the principal investigator of the MACS3 project, supported by the Chan Zuckerberg Initiative. I currently serve as technical lead for the NCI ARTNet Coordinating and Data Management Center, the NCI CAP-IT Data and Resource Coordination Center, and the NCI CIPNET Data and Resource Coordination Center. At Roswell Park, I am a member of the Developmental Therapeutics Program under the Cancer Center Support Grant (CCSG).

Current focus areas

  • Method development for ChIP-seq, CUT&RUN, ATAC-seq, and single-cell epigenomics.
  • Statistical and computational models for regulatory element detection and interpretation.
  • Integrative analysis of transcriptional and epigenetic regulation in cancer systems.
  • Scalable software and data infrastructure for reproducible genomics analysis.
  • Development of AI agents for genomics data reuse and metadata standardization.

Representative outputs

Current leadership roles

  • Technical Lead, NCI ARTNet Coordinating and Data Management Center
  • Technical Lead, NCI CAP-IT Data and Resource Coordination Center
  • Technical Lead, NCI CIPNET Data and Resource Coordination Center
  • Principal Investigator, MACS3 (Chan Zuckerberg Initiative)

Algorithm development for epigenomics data

A central component of my program is method development for high-throughput sequencing assays that profile functional regulatory elements. My colleagues and I studied technical noise in ChIP-seq and developed dynamic Poisson-model-based approaches to detect transcription factor binding sites and histone-marked regions. MACS remains an active focus in my lab, with ongoing work to improve accuracy, robustness, and computational efficiency.

Beyond ChIP-seq, we have developed methods for CUT&RUN and ATAC-seq and are extending this framework to single-cell genomic assays.

Epigenomics databases, knowledgebases, and infrastructure

I have led projects that reduce technical barriers to next-generation sequencing analysis. I led a joint Harvard–Eli Lilly team that developed the web-based Cistrome Analysis Pipeline, enabling users to upload ChIP-seq and RNA-seq data and run curated downstream analyses in an integrated environment.

With colleagues at Harvard, I also helped build downstream analysis tools, large-scale databases of public human and mouse ChIP-seq datasets, and search systems that were integrated into the broader Cistrome ecosystem.

Consortium contributions

I have participated in multiple NIH-funded consortia, including ENCODE, modENCODE, and Cancer Moonshot programs, to study transcriptional and epigenetic regulation in model organisms and human systems.

In this work, my collaborators and I reported that H3K36me3 is linked to exon-intron structure and splicing in eukaryotes. We also characterized broad chromosomal domains of histone modifications in C. elegans and examined developmental changes in genome organization. More recently, with IOTN Moonshot collaborators at Dana-Farber, we identified epigenetic roles of MUC1 in cancer stem-cell biology.

Collaborative studies of epigenetic regulation

In parallel with methods and infrastructure development, I collaborate with experimental biologists to study epigenetic regulation across tissues and developmental stages.

With collaborators at UPenn, we used mouse models to show that histone deacetylase-mediated epigenetic regulation changes across circadian time in a cell-intrinsic clock framework. In collaboration with colleagues at UB, we combined chromatin immunoprecipitation, RNA-expression assays, and single-cell experiments to study retinal ganglion cell development in mouse.