Helps to discover cell-lineage–specific genes. Nano-dissection is an iterative computational approach that predicts cell-lineage–specific expression of human genes using high-throughput genomic expression data derived from tissue homogenates. This method uses an iterative machine learning framework that makes robust predictions, even when only limited prior knowledge about cell-lineage–specific markers is available.
Division of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA; Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA; Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA; Department of Computer Science, Princeton University, Princeton, NJ, USA; Department of Genetics, The Geisel School of Medicine at Dartmouth, Hanover, NH, USA; Department of Pathology, University of Michigan, Ann Arbor, MI, USA; Laboratorio di Ricerca Nefrologica, Fondazione IRCCS CaGranda Ospedale Maggiore Policlinico, Milano, Italy; Division of Nephrology, University of Zurich, Zurich, Switzerland
Nano-dissection funding source(s)
Supported in part by R01 GM071966, by R01 HG005998, DBI0546275, P50 GM071508, R01 DK079912, P30 DK081943, and the Canadian Institute for Advanced Research.