Spatial reconstruction of single-cell gene expression data.
about
Design and computational analysis of single-cell RNA-sequencing experimentsSingle-cell sequencing in stem cell biologySingle-cell transcriptome sequencing: recent advances and remaining challengesImplications of Epigenetic Variability within a Cell Population for "Cell Type" ClassificationDefining cell types and states with single-cell genomicsIntegrated live imaging and molecular profiling of embryoid bodies reveals a synchronized progression of early differentiation.Fourth Generation of Next-Generation Sequencing Technologies: Promise and ConsequencesSingle-Cell Transcriptomics Bioinformatics and Computational ChallengesApplication of single-cell genomics in cancer: promise and challengesHigh-throughput single-cell gene-expression profiling with multiplexed error-robust fluorescence in situ hybridizationAssociating cellular epigenetic models with human phenotypesMicrofluidic Sample Preparation for Single Cell Analysis.Root Regeneration Triggers an Embryo-like Sequence Guided by Hormonal InteractionsAn automated approach to prepare tissue-derived spatially barcoded RNA-sequencing librariesProcessing, visualising and reconstructing network models from single-cell data.FastProject: a tool for low-dimensional analysis of single-cell RNA-Seq dataModeling and high-throughput experimental data uncover the mechanisms underlying Fshb gene sensitivity to gonadotropin-releasing hormone pulse frequency.A Gene Regulatory Network Balances Neural and Mesoderm Specification during Vertebrate Trunk Development.Reconstructing cell cycle pseudo time-series via single-cell transcriptome data.Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter DropletsSingle-cell genome sequencing: current state of the science.ZIFA: Dimensionality reduction for zero-inflated single-cell gene expression analysisMeasuring Absolute RNA Copy Numbers at High Temporal Resolution Reveals Transcriptome Kinetics in Development.Whole-organism lineage tracing by combinatorial and cumulative genome editingA Multi-step Transcriptional and Chromatin State Cascade Underlies Motor Neuron Programming from Embryonic Stem Cells.Seq-Well: portable, low-cost RNA sequencing of single cells at high throughput.Single-Cell Analysis in Cancer Genomics.Response to Nodal morphogen gradient is determined by the kinetics of target gene induction.Extensive rewiring of epithelial-stromal co-expression networks in breast cancerSINCERA: A Pipeline for Single-Cell RNA-Seq Profiling AnalysisA Generic and Cell-Type-Specific Wound Response Precedes Regeneration in PlanarianspcaReduce: hierarchical clustering of single cell transcriptional profiles.A Transcriptional Lineage of the Early C. elegans Embryo.Single-Cell RNA Sequencing of Human T Cells.Quantitative approaches for investigating the spatial context of gene expression.Spatial transcriptomic analysis of cryosectioned tissue samples with Geo-seq.Geometry-dependent functional changes in iPSC-derived cardiomyocytes probed by functional imaging and RNA sequencing.Cell fixation and preservation for droplet-based single-cell transcriptomics.ASAP: a Web-based platform for the analysis and interactive visualization of single-cell RNA-seq data.Mouse embryonic fibroblasts exhibit extensive developmental and phenotypic diversity
P2860
Q26751087-738DA773-5702-4C3E-9EF7-E66FDB0E24DBQ26753145-24FF24E4-4D33-4AB6-B4C4-E65F9F5C6C1EQ26767451-E20B8D60-F47F-48D8-918F-B20238F947C6Q26770736-4881459F-427F-4098-8BFC-73FE81A8CFC1Q26782737-7E5CE8FC-6D3D-44BD-8E19-916ADB67210FQ27316950-25034347-440F-44DC-9EA8-F1F6D39FDD2CQ28068789-473299B5-C351-42AE-82B6-E99627A1D7DAQ28073365-0743E002-A0CA-4536-AC9E-C11DB8FDB633Q28085411-2D6D230F-612D-4E18-87F3-CDC3BE8AC440Q28822617-B20AC07E-B8E8-40D6-9FA6-47FF98235F62Q30224332-566EC80B-1540-4889-9149-E8E0AAA777E4Q30366102-09462313-6C97-4DE9-BC49-4A30F2840D86Q30773560-97D87776-62A4-4D1F-B49E-2D2E23749DBBQ30828826-D7E14940-9412-4548-BA26-1C434FE9DB7DQ31024831-D4892583-2476-4770-B3F3-06DD908BD54FQ31123178-476ADD45-B983-4F0D-A55D-E9116C758C76Q33365169-BEFAB979-CB3C-4407-9AF8-987F9D59CBC4Q33658152-1A90EC1D-473A-44BF-8847-6553A0F741F7Q33812762-DC81EFCE-D2A1-4E3A-95E9-4BE1DDC11365Q34044099-55B20757-F359-44D6-AB59-1C865DCD1214Q34045945-00908E01-DFF1-4849-BE78-11DFF462D9D5Q34500228-36E2BAB8-3018-4AB6-9DED-3E21D19FA765Q34509343-DAA1A2AE-33B4-489D-B2E3-E4F86681AF58Q34528428-51316115-E426-47D7-BDDA-CD935DBFD70AQ34547013-39807657-A016-4FF8-981E-BEC4BE35B857Q34551107-FD9A8263-6C62-4989-8E01-059695DDB780Q34673769-6649DAAA-9543-4E3F-AD49-5E85B6211115Q35400961-F4FE332B-5B09-48F5-B04D-8751EB8689CAQ35667722-E238CE46-BCE2-403C-95FD-E23A492F69CDQ35850720-BF01797B-2B14-46F0-9DA0-2A72EEAB95EFQ35864570-7A0FDC7D-C3FA-4C29-9004-25F2EA5DCFC4Q35966950-6A42C23F-5C4E-4DFC-B6AB-27ED33E6C923Q36111014-19814AB6-F222-4576-83BA-475D4DF36B41Q36175926-69BD28CB-2FE0-4A60-9108-EE72FADBEEFFQ36230239-4021105E-74B6-4843-BE59-A763319FB55CQ36282263-4E16EF15-A84F-4D03-97B3-4095E996F3AEQ36319651-735B5E32-2692-4395-99AB-37AA98A4F391Q36376696-1AD64547-0219-41EE-8220-2E1628006570Q36379835-90A5C125-8785-49C5-874C-667BDFFC0510Q36459354-0490C5B3-D08E-4250-AB4F-8912D1DD4EF1
P2860
Spatial reconstruction of single-cell gene expression data.
description
2015 nî lūn-bûn
@nan
2015 թուականի Ապրիլին հրատարակուած գիտական յօդուած
@hyw
2015 թվականի ապրիլին հրատարակված գիտական հոդված
@hy
2015年の論文
@ja
2015年論文
@yue
2015年論文
@zh-hant
2015年論文
@zh-hk
2015年論文
@zh-mo
2015年論文
@zh-tw
2015年论文
@wuu
name
Spatial reconstruction of single-cell gene expression data.
@ast
Spatial reconstruction of single-cell gene expression data.
@en
type
label
Spatial reconstruction of single-cell gene expression data.
@ast
Spatial reconstruction of single-cell gene expression data.
@en
prefLabel
Spatial reconstruction of single-cell gene expression data.
@ast
Spatial reconstruction of single-cell gene expression data.
@en
P2860
P50
P356
P1433
P1476
Spatial reconstruction of single-cell gene expression data.
@en
P2093
Alexander F Schier
David Gennert
P2860
P2888
P304
P356
10.1038/NBT.3192
P577
2015-04-13T00:00:00Z