Sheffield, Nathan C.

The accessible chromatin landscape of the human genome

Thurman, R. E., Rynes, E., Humbert, R., Vierstra, J., Maurano, M. T., Haugen, E., Sheffield, N. C., Stergachis, A. B., Wang, H., Vernot, B., et al. (2012) · Nature

Genomics and Chromatin DynamicsChromatin Remodeling and Cancer

Cited by 2,679

The chromatin accessibility landscape of primary human cancers

Corces, M. R., Granja, J. M., Shams, S., Louie, B. H., Seoane, J. A., Zhou, W., Silva, T. C., Groeneveld, C., Wong, C. K., Cho, S. W., et al. (2018) · Science

Genomics and Chromatin DynamicsChromatin Remodeling and Cancer

Cited by 1,230

ChIPmentation: fast, robust, low-input ChIP-seq for histones and transcription factors

Schmidl, C., Rendeiro, A. F., Sheffield, N. C., & Bock, C. (2015) · Nature Methods

Genomics and Chromatin DynamicsGenomics and Phylogenetic Studies

Cited by 509

Single-cell DNA methylome sequencing and bioinformatic inference of epigenomic cell-state dynamics

Farlik, M., Sheffield, N. C., Nuzzo, A., Datlinger, P., Schönegger, A., Klughammer, J., & Bock, C. (2015) · Cell Reports

Epigenetics and DNA MethylationSingle-cell and spatial transcriptomics

Cited by 422

Multimodal analysis of cell-free DNA whole-genome sequencing for pediatric cancers with low mutational burden

Peneder, P., Stütz, A. M., Surdez, D., Krumbholz, M., Semper, S., Chicard, M., Sheffield, N. C., Pierron, G., Lapouble, E., Tötzl, M., et al. (2021) · Nature Communications

Cancer Genomics and DiagnosticsSarcoma Diagnosis and Treatment

Cited by 200

Multi-omics of single cells: strategies and applications

Bock, C., Farlik, M., & Sheffield, N. C. (2016) · Trends in Biotechnology

Single-cell and spatial transcriptomicsBioinformatics and Genomic Networks

Cited by 146

Integrative single-cell meta-analysis reveals disease-relevant vascular cell states and markers in human atherosclerosis

Mosquera, J. V., Auguste, G., Wong, D., Turner, A. W., Hodonsky, C. J., Alvarez-Yela, A. C., Song, Y., Cheng, Q., Lino Cardenas, C. L., Theofilatos, K., et al. (2023) · Cell Reports

Atherosclerosis and Cardiovascular DiseasesSingle-cell and spatial transcriptomics

Cited by 123

Single-cell epigenomic variability reveals functional cancer heterogeneity

Litzenburger, U. M., Buenrostro, J. D., Wu, B., Shen, Y., Sheffield, N. C., Kathiria, A., Greenleaf, W. J., & Chang, H. Y. (2017) · Genome Biology

Epigenetics and DNA MethylationGenomics and Chromatin Dynamics

Cited by 115

AI-readiness Criteria for Biomedical Data

Clark, T., Caufield, H., Parker, J. A., Al Manir, S., Amorim, E., Eddy, J., Gim, N., Gow, B., Goar, W., Hansen, J. N., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory)

Research Data Management PracticesArtificial Intelligence in Healthcare and Education

Cited by 32

Detecting molecular subtypes from multi-omics datasets using SUMO

Sienkiewicz, K., Chen, J., Chatrath, A., Lawson, J. T., Sheffield, N. C., Zhang, L., & Ratan, A. (2022) · Cell Reports Methods

Bioinformatics and Genomic NetworksGene expression and cancer classification

Cited by 18