Data-Driven Phenotypic Dissection of AML Reveals Progenitor-like Cells that Correlate with Prognosis

[1]  Eli R. Zunder,et al.  Palladium-based mass tag cell barcoding with a doublet-filtering scheme and single-cell deconvolution algorithm , 2015, Nature Protocols.

[2]  Shawn M. Gillespie,et al.  Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma , 2014, Science.

[3]  Sean C. Bendall,et al.  Single-Cell Trajectory Detection Uncovers Progression and Regulatory Coordination in Human B Cell Development , 2014, Cell.

[4]  Sean C. Bendall,et al.  viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia , 2013, Nature Biotechnology.

[5]  Sean C. Bendall,et al.  Normalization of mass cytometry data with bead standards , 2013, Cytometry. Part A : the journal of the International Society for Analytical Cytology.

[6]  Greg Finak,et al.  Critical assessment of automated flow cytometry data analysis techniques , 2013, Nature Methods.

[7]  N. Aghaeepour.  flowType: Phenotyping Flow Cytometry Assays , 2013 .

[8]  Karen Sachs,et al.  Multiplexed mass cytometry profiling of cellular states perturbed by small-molecule regulators , 2012, Nature Biotechnology.

[9]  Erin F. Simonds,et al.  A platinum‐based covalent viability reagent for single‐cell mass cytometry , 2012, Cytometry. Part A : the journal of the International Society for Analytical Cytology.

[10]  K. Polyak,et al.  Intra-tumour heterogeneity: a looking glass for cancer? , 2012, Nature Reviews Cancer.

[11]  Stephen G. Kobourov,et al.  Spring Embedders and Force Directed Graph Drawing Algorithms , 2012, ArXiv.

[12]  Sean C. Bendall,et al.  Extracting a Cellular Hierarchy from High-dimensional Cytometry Data with SPADE , 2011, Nature Biotechnology.

[13]  Angelo J. Canty,et al.  Stem cell gene expression programs influence clinical outcome in human leukemia , 2011, Nature Medicine.

[14]  Sean C. Bendall,et al.  Single-Cell Mass Cytometry of Differential Immune and Drug Responses Across a Human Hematopoietic Continuum , 2011, Science.

[15]  K. Sachs,et al.  Single-cell phospho-specific flow cytometric analysis demonstrates biochemical and functional heterogeneity in human hematopoietic stem and progenitor compartments. , 2011, Blood.

[16]  D. Pe’er,et al.  An Integrated Approach to Uncover Drivers of Cancer , 2010, Cell.

[17]  J. Gribben,et al.  Leukemia-initiating cells from some acute myeloid leukemia patients with mutated nucleophosmin reside in the CD34(-) fraction. , 2010, Blood.

[18]  R. Scheuermann,et al.  Elucidation of seventeen human peripheral blood B‐cell subsets and quantification of the tetanus response using a density‐based method for the automated identification of cell populations in multidimensional flow cytometry data , 2010, Cytometry. Part B, Clinical cytometry.

[19]  Arvind Gupta,et al.  Data reduction for spectral clustering to analyze high throughput flow cytometry data , 2010, BMC Bioinformatics.

[20]  J. Downing,et al.  Genomic analysis reveals few genetic alterations in pediatric acute myeloid leukemia , 2009, Proceedings of the National Academy of Sciences.

[21]  Santo Fortunato,et al.  Community detection in graphs , 2009, ArXiv.

[22]  J. Mesirov,et al.  Automated high-dimensional flow cytometric data analysis , 2009, Proceedings of the National Academy of Sciences.

[23]  Ulrich Mansmann,et al.  An 86-probe-set gene-expression signature predicts survival in cytogenetically normal acute myeloid leukemia. , 2008, Blood.

[24]  J. Gribben,et al.  Anti-CD38 antibody-mediated clearance of human repopulating cells masks the heterogeneity of leukemia-initiating cells. , 2008, Blood.

[25]  Axel Benner,et al.  Mutations and treatment outcome in cytogenetically normal acute myeloid leukemia. , 2008, The New England journal of medicine.

[26]  F. Craig,et al.  Flow cytometric immunophenotyping for hematologic neoplasms. , 2008, Blood.

[27]  Jean-Loup Guillaume,et al.  Fast unfolding of communities in large networks , 2008, 0803.0476.

[28]  Geoffrey E. Hinton,et al.  Visualizing Data using t-SNE , 2008 .

[29]  J. Dick,et al.  A human colon cancer cell capable of initiating tumour growth in immunodeficient mice , 2007, Nature.

[30]  O. Yli-Harja,et al.  Global Gene Expression Profile of Human Cord Blood–Derived CD133+ Cells , 2006, Stem cells.

[31]  T. Lister,et al.  AML engraftment in the NOD/SCID assay reflects the outcome of AML: implications for our understanding of the heterogeneity of AML. , 2006, Blood.

[32]  John M. Walker,et al.  Myeloid Leukemia , 2020, Methods In Molecular Medicine™.

[33]  N. Maitland,et al.  Prospective identification of tumorigenic prostate cancer stem cells. , 2005, Cancer research.

[34]  Pablo Tamayo,et al.  Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[35]  J. Itskovitz‐Eldor,et al.  CD133-positive hematopoietic stem cell "stemness" genes contain many genes mutated or abnormally expressed in leukemia. , 2005, Stem cells.

[36]  Gábor Szabó,et al.  Structure of complex networks , 2005 .

[37]  Jonathan M Irish,et al.  Single Cell Profiling of Potentiated Phospho-Protein Networks in Cancer Cells , 2004, Cell.

[38]  Aleksey A. Nakorchevskiy,et al.  Expression deconvolution: A reinterpretation of DNA microarray data reveals dynamic changes in cell populations , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[39]  Eric R. Ziegel,et al.  The Elements of Statistical Learning , 2003, Technometrics.

[40]  Daniel G. Tenen,et al.  Disruption of differentiation in human cancer: AML shows the way , 2003, Nature Reviews Cancer.

[41]  Joydeep Ghosh,et al.  Cluster Ensembles --- A Knowledge Reuse Framework for Combining Multiple Partitions , 2002, J. Mach. Learn. Res..

[42]  M E J Newman,et al.  Community structure in social and biological networks , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[43]  B. Séraphin,et al.  Positive feedback in eukaryotic gene networks: cell differentiation by graded to binary response conversion , 2001, The EMBO journal.

[44]  M. Bhatia,et al.  Isolation and characterization of human CD34(-)Lin(-) and CD34(+)Lin(-) hematopoietic stem cells using cell surface markers AC133 and CD7. , 2000, Blood.

[45]  J E Ferrell,et al.  The biochemical basis of an all-or-none cell fate switch in Xenopus oocytes. , 1998, Science.

[46]  J. Dick,et al.  Human acute myeloid leukemia is organized as a hierarchy that originates from a primitive hematopoietic cell , 1997, Nature Medicine.

[47]  P Clark,et al.  Lymphocyte subsets in normal bone marrow. , 1986, Blood.

[48]  A. Novick,et al.  ENZYME INDUCTION AS AN ALL-OR-NONE PHENOMENON. , 1957, Proceedings of the National Academy of Sciences of the United States of America.