Hu Y, Ma S, Kartha VK, et al. Single-cell multi-scale footprinting reveals the modular organization of DNA regulatory elements. bioRxiv : the preprint server for biology. 2023. doi:10.1101/2023.03.28.533945
Publications
Zhang H, Kelly K, Lee J, et al. Self-delivering CRISPR RNAs for AAV Co-delivery and Genome Editing . bioRxiv : the preprint server for biology. 2023. doi:10.1101/2023.03.20.533459
Lee J, Gilliland T, Koyama S, et al. Integrative metabolomics differentiate coronary artery disease, peripheral artery disease, and venous thromboembolism risks. medRxiv : the preprint server for health sciences. 2023. doi:10.1101/2023.06.21.23291103
Yurkovetskiy L, Egri S, Kurhade C, et al. S:D614G and S:H655Y are gateway mutations that act epistatically to promote SARS-CoV-2 variant fitness. bioRxiv : the preprint server for biology. 2023. doi:10.1101/2023.03.30.535005
Shiau C, Cao J, Gregory MT, et al. Therapy-associated remodeling of pancreatic cancer revealed by single-cell spatial transcriptomics and optimal transport analysis. bioRxiv : the preprint server for biology. 2023. doi:10.1101/2023.06.28.546848
Mitchell W, Goeminne LJE, Tyshkovskiy A, et al. Multi-omics characterization of partial chemical reprogramming reveals evidence of cell rejuvenation. bioRxiv : the preprint server for biology. 2023. doi:10.1101/2023.06.30.546730
Lu W, Gauthier LD, Poterba T, et al. CHARR efficiently estimates contamination from DNA sequencing data. bioRxiv : the preprint server for biology. 2023. doi:10.1101/2023.06.28.545801
Reedy JL, Crossen AJ, Ward RA, et al. Cross-kingdom anti-inflammatory effects of fungal melanin on airway epithelium by post-translational blockade of chemokine secretion. bioRxiv : the preprint server for biology. 2023. doi:10.1101/2023.03.28.534632
Harada T, Kalfon J, Perez MW, et al. Leukemia core transcriptional circuitry is a sparsely interconnected hierarchy stabilized by incoherent feed-forward loops. bioRxiv : the preprint server for biology. 2023. doi:10.1101/2023.03.13.532438
Shaban M, Bai Y, Qiu H, et al. MAPS: Pathologist-level cell type annotation from tissue images through machine learning. bioRxiv : the preprint server for biology. 2023. doi:10.1101/2023.06.25.546474