The human body at cellular resolution: the NIH Human Biomolecular Atlas Program
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Shila Ghazanfar | Yu Wang | Ziv Bar-Joseph | Kevin Otto | Robert F. Murphy | Katy Börner | Matthew Ruffalo | Benedict Paten | W. Christopher Lenhardt | Paula M. Mabee | Cole Trapnell | Griffin M. Weber | John C. Marioni | Kimberly Robasky | Orit Rozenblatt-Rosen | Aviv Regev | Ying Zhu | Eyal Fisher | Hayan Lee | Guo-Cheng Yuan | Sushma A. Akoju | Jocelyn Y. Kishi | Peng Yin | Carl Kingsford | Ed Esplin | Jonathan C. Silverstein | Garry P. Nolan | Ken Lau | Paul Macklin | Samuel H. Friedman | Jay Shendure | Philip D. Blood | Amir Bahmani | Sergio Maffioletti | Agnes B. Fogo | Michael P. Snyder | Peter V. Kharchenko | James P. Sluka | Randy W. Heiland | Nicholas A. Nystrom | Danielle B. Gutierrez | Bernd Bodenmiller | Ellen M. Quardokus | Sylvia K. Plevritis | Leonard E. Cross | Jeffrey M. Spraggins | Rahul Satija | Andrew Butler | Tim Stuart | Raymond Harris | Raf Van de Plas | Sarah A. Teichmann | Alexander Ropelewski | Paul D. Piehowski | Gökcen Eraslan | Kristin E. Burnum-Johnson | Nathan Heath Patterson | Sarah Black | Mark Atkinson | Chuck McCallum | Peter Chou | Tommaso Biancalani | Elizabeth L. Wilder | Richard Conroy | Nils Gehlenborg | Michael Clare-Salzler | Margaret Vella | Vishal Gautham Venkataraaman | James Anderson | James S. Hagood | Ruben Dries | William Shirey | Bruce William Herr | Shin Lin | Amanda Posgai | Jennifer Rood | Leslie Gaffney | Anna Hupalowska | Julia Laskin | Pehr Harbury | Kun Zhang | Yiing Lin | Dena Procaccini | Ananda L. Roy | Ajay Pillai | Marishka Brown | Zorina S. Galis | Long Cai | Dana Jackson | William James Greenleaf | Sara Ahadi | Stephanie A. Nevins | Christian Martijn Schuerch | Aaron Horning | Xin Sun | Sanjay Jain | Gloria Pryhuber | Todd Brusko | Harry Nick | Clive Wasserfall | Marda Jorgensen | Maigan Brusko | Richard M. Caprioli | Danielle Gutierrez | Elizabeth K. Neumann | Mark deCaestecker | Qian Zhu | Sinem K. Saka | Isabel Goldaracena | DongHye Ye | Charles Ansong | Tushar Desai | Jay Mulye | Monica Nagendran | Jian Ma | Vladimir Yu. Kiselev | Allyson Ricarte | Maria Keays | Lisel Record | Robin M. Scibek | Stavros Michailidis | Eeshit D. Vaishnav | Pothur Srinivas | Aaron Pawlyk | Salvatore Sechi | Elizabeth L. Wilder | G. Nolan | A. Regev | J. Shendure | K. Robasky | S. Teichmann | Z. Bar-Joseph | J. Marioni | S. Plevritis | Shin Lin | P. Yin | Guocheng Yuan | B. Paten | P. Kharchenko | R. Caprioli | S. Maffioletti | O. Rozenblatt-Rosen | R. Satija | M. Snyder | K. Börner | N. Gehlenborg | G. Weber | R. Murphy | Andrew Butler | Yiing Lin | R. Heiland | K. Otto | W. Greenleaf | W. Lenhardt | P. Harbury | L. Cai | V. Kiselev | T. Desai | A. Hupalowska | Qian Zhu | Ruben Dries | M. Keays | Tim Stuart | Dana L. Jackson | Sarah Black | Gökçen Eraslan | M. Atkinson | Dena Procaccini | Chuck McCallum | S. Sechi | P. Piehowski | P. Macklin | E. D. Vaishnav | Z. Galis | C. Ansong | P. Srinivas | J. Hagood | G. Pryhuber | H. Nick | R. Conroy | J. Silverstein | Carl Kingsford | K. Burnum-Johnson | A. Fogo | S. Ahadi | C. Wasserfall | C. Schuerch | T. Biancalani | S. Ghazanfar | E. Quardokus | J. Laskin | A. Posgai | T. Brusko | Monica Nagendran | A. Pawlyk | Matthew Ruffalo | Hayan Lee | E. Esplin | M. Clare-Salzler | Stephanie A. Nevins | N. H. Patterson | R. V. D. Plas | Eyal Fisher | L. Gaffney | Aaron M. Horning | Jennifer E. Rood | Ajay Pillai | Marda L. Jorgensen | Maigan A. Brusko | Kun Zhang | A. Ropelewski | C. Trapnell | Marishka Brown | M. deCaestecker | Ken Lau | Ananda L. Roy | Raymond C. Harris | Xin Sun | B. Herr | Margaret Vella | K. Burnum‐Johnson | J. Sluka | DongHye Ye | Yu Wang | I. Goldaracena | William Shirey | Guo-cheng Yuan | B. Bodenmiller | S. Jain | J. Spraggins | V. Venkataraaman | Amir Bahmani | Ying Zhu | J. Mulye | Peter Chou | Jian Ma | Allyson Ricarte | Lisel Record | Stavros Michailidis | James Anderson | Guocheng Yuan | Tommaso Biancalani
[1] Erik Schultes,et al. The FAIR Guiding Principles for scientific data management and stewardship , 2016, Scientific Data.
[2] Dmitri D. Pervouchine,et al. A benchmark for RNA-seq quantification pipelines , 2016, Genome Biology.
[3] Mary Goldman,et al. Toil enables reproducible, open source, big biomedical data analyses , 2017, Nature Biotechnology.
[4] Eric P Skaar,et al. Next‐generation technologies for spatial proteomics: Integrating ultra‐high speed MALDI‐TOF and high mass resolution MALDI FTICR imaging mass spectrometry for protein analysis , 2016, Proteomics.
[5] F. Arnaud,et al. From core referencing to data re-use: two French national initiatives to reinforce paleodata stewardship (National Cyber Core Repository and LTER France Retro-Observatory) , 2017 .
[6] L. Cai,et al. In Situ Transcription Profiling of Single Cells Reveals Spatial Organization of Cells in the Mouse Hippocampus , 2016, Neuron.
[7] Guo-Cheng Yuan,et al. Transcriptome-scale super-resolved imaging in tissues by RNA seqFISH+ , 2019, Nature.
[8] Salil S. Bhate,et al. Deep Profiling of Mouse Splenic Architecture with CODEX Multiplexed Imaging , 2017, Cell.
[9] Nicola J. Rinaldi,et al. Genetic effects on gene expression across human tissues , 2017, Nature.
[10] J Mazziotta,et al. A probabilistic atlas and reference system for the human brain: International Consortium for Brain Mapping (ICBM). , 2001, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.
[11] Benedict Paten,et al. The Dockstore: enabling modular, community-focused sharing of Docker-based genomics tools and workflows , 2017, F1000Research.
[12] X. Zhuang,et al. Spatially resolved, highly multiplexed RNA profiling in single cells , 2015, Science.
[13] Howard Y. Chang,et al. Single-cell chromatin accessibility reveals principles of regulatory variation , 2015, Nature.
[14] Interactive human protein atlas launches. , 2015, Cancer discovery.
[15] Mark D. Robinson,et al. Compensation of Signal Spillover in Suspension and Imaging Mass Cytometry , 2018, Cell systems.
[16] Alfons Buekens,et al. Book Review: Assessment of the Performance of Engineered Waste Containment Barriers by National Research Council of the National Academies , 2010 .
[17] Ian R. Wickersham,et al. The BRAIN Initiative Cell Census Consortium: Lessons Learned toward Generating a Comprehensive Brain Cell Atlas , 2017, Neuron.
[18] Karl Deisseroth,et al. An interactive framework for whole-brain maps at cellular resolution , 2017, Nature Neuroscience.
[19] Guocheng Yuan,et al. Identification of spatially associated subpopulations by combining scRNA-seq and sequential fluorescence in situ hybridization data , 2018, Nature Biotechnology.
[20] J. Michael Cherry,et al. Principles of metadata organization at the ENCODE data coordination center , 2016, Database J. Biol. Databases Curation.
[21] Yu Wang,et al. Immuno-SABER enables highly multiplexed and amplified protein imaging in tissues , 2019, Nature Biotechnology.
[22] Richard M. Caprioli,et al. Fusion of mass spectrometry and microscopy: a multi-modality paradigm for molecular tissue mapping , 2015, Nature Methods.
[23] Richard M Caprioli,et al. Analysis of tissue specimens by matrix-assisted laser desorption/ionization imaging mass spectrometry in biological and clinical research. , 2013, Chemical reviews.
[24] Andrew C. Adey,et al. Single-Cell Transcriptional Profiling of a Multicellular Organism , 2017 .
[25] Sarah A. Teichmann,et al. Faculty Opinions recommendation of histoCAT: analysis of cell phenotypes and interactions in multiplex image cytometry data. , 2017 .
[26] Tiffany Philips,et al. Factors That Influence the Quality of RNA From the Pancreas of Organ Donors , 2017, Pancreas.
[27] Peng Yin,et al. SABER enables highly multiplexed and amplified detection of DNA and RNA in cells and tissues , 2018, bioRxiv.
[28] Marco Laumanns,et al. CellCycleTRACER accounts for cell cycle and volume in mass cytometry data , 2018, Nature Communications.
[29] Arthur W. Toga,et al. A Probabilistic Atlas of the Human Brain: Theory and Rationale for Its Development The International Consortium for Brain Mapping (ICBM) , 1995, NeuroImage.
[30] Nuno A. Fonseca,et al. Expression Atlas update—an integrated database of gene and protein expression in humans, animals and plants , 2015, Nucleic Acids Res..
[31] Timur Zhiyentayev,et al. Single-cell in situ RNA profiling by sequential hybridization , 2014, Nature Methods.
[32] A. Tanay,et al. Single-cell epigenomics: techniques and emerging applications , 2015, Nature Reviews Genetics.
[33] Richard M Caprioli,et al. Next Generation Histology-Directed Imaging Mass Spectrometry Driven by Autofluorescence Microscopy. , 2018, Analytical chemistry.
[34] Paul Hoffman,et al. Integrating single-cell transcriptomic data across different conditions, technologies, and species , 2018, Nature Biotechnology.
[35] Ronald J. Moore,et al. Nanodroplet processing platform for deep and quantitative proteome profiling of 10–100 mammalian cells , 2018, Nature Communications.
[36] Peng Yin,et al. SABER enables amplified and multiplexed imaging of RNA and DNA in cells and tissues , 2019, Nature Methods.
[37] George M. Church,et al. Highly multiplexed in situ protein imaging with signal amplification by Immuno-SABER , 2018, bioRxiv.
[38] Julia Laskin,et al. High Spatial Resolution Imaging of Mouse Pancreatic Islets Using Nanospray Desorption Electrospray Ionization Mass Spectrometry. , 2018, Analytical chemistry.
[39] Alistair A. Young,et al. The Cardiac Atlas Project—an imaging database for computational modeling and statistical atlases of the heart , 2011, Bioinform..
[40] Long Cai,et al. seqFISH Accurately Detects Transcripts in Single Cells and Reveals Robust Spatial Organization in the Hippocampus , 2017, Neuron.
[41] Andrew C. Adey,et al. Multiplex single-cell profiling of chromatin accessibility by combinatorial cellular indexing , 2015, Science.
[42] Clive Wasserfall,et al. The Juvenile Diabetes Research Foundation Network for Pancreatic Organ Donors with Diabetes (nPOD) Program: goals, operational model and emerging findings , 2013, Pediatric diabetes.
[43] Valentine Svensson,et al. Power Analysis of Single Cell RNA-Sequencing Experiments , 2016, Nature Methods.
[44] Michael B. Stadler,et al. An Immune Atlas of Clear Cell Renal Cell Carcinoma , 2017, Cell.
[45] M. Atkinson,et al. Network for Pancreatic Organ Donors with Diabetes (nPOD): developing a tissue biobank for type 1 diabetes , 2012, Diabetes/metabolism research and reviews.
[46] A. Regev,et al. Scaling single-cell genomics from phenomenology to mechanism , 2017, Nature.
[47] P. Harbury,et al. Ultrasensitive optical imaging with lanthanide lumiphores , 2017, Nature chemical biology.
[48] Bernd Bodenmiller,et al. miCAT: A toolbox for analysis of cell phenotypes and interactions in multiplex image cytometry data , 2017, Nature Methods.
[49] Xintao Wei,et al. Erratum: A benchmark for RNA-seq quantification pipelines [Genome Biol. (2016), 17, 74], DOI: 10.1186/s13059-016-0940-1 , 2016 .
[50] Fabian J Theis,et al. The Human Cell Atlas , 2017, bioRxiv.
[51] Laleh Haghverdi,et al. Batch effects in single-cell RNA-sequencing data are corrected by matching mutual nearest neighbors , 2018, Nature Biotechnology.
[52] Bernd Bodenmiller,et al. Simultaneous Multiplexed Imaging of mRNA and Proteins with Subcellular Resolution in Breast Cancer Tissue Samples by Mass Cytometry , 2017, Cell systems.
[53] William S. DeWitt,et al. A Single-Cell Atlas of In Vivo Mammalian Chromatin Accessibility , 2018, Cell.