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  1. Analyzed Page
  2. Matching Content Categories
  3. CMS
  4. Monthly Traffic Estimate
  5. How Does Link.springer.com Make Money
  6. Keywords
  7. Topics
  8. Schema
  9. External Links
  10. Analytics And Tracking
  11. Libraries
  12. CDN Services

We are analyzing https://link.springer.com/article/10.1186/s12864-018-4772-0.

Title:
Slingshot: cell lineage and pseudotime inference for single-cell transcriptomics | BMC Genomics
Description:
Background Single-cell transcriptomics allows researchers to investigate complex communities of heterogeneous cells. It can be applied to stem cells and their descendants in order to chart the progression from multipotent progenitors to fully differentiated cells. While a variety of statistical and computational methods have been proposed for inferring cell lineages, the problem of accurately characterizing multiple branching lineages remains difficult to solve. Results We introduce Slingshot, a novel method for inferring cell lineages and pseudotimes from single-cell gene expression data. In previously published datasets, Slingshot correctly identifies the biological signal for one to three branching trajectories. Additionally, our simulation study shows that Slingshot infers more accurate pseudotimes than other leading methods. Conclusions Slingshot is a uniquely robust and flexible tool which combines the highly stable techniques necessary for noisy single-cell data with the ability to identify multiple trajectories. Accurate lineage inference is a critical step in the identification of dynamic temporal gene expression.
Website Age:
28 years and 1 months (reg. 1997-05-29).

Matching Content Categories {πŸ“š}

  • Science
  • Education
  • Graphic Design

Content Management System {πŸ“}

What CMS is link.springer.com built with?

Custom-built

No common CMS systems were detected on Link.springer.com, and no known web development framework was identified.

Traffic Estimate {πŸ“ˆ}

What is the average monthly size of link.springer.com audience?

🌠 Phenomenal Traffic: 5M - 10M visitors per month


Based on our best estimate, this website will receive around 7,542,081 visitors per month in the current month.

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How Does Link.springer.com Make Money? {πŸ’Έ}

We don’t know how the website earns money.

Not all websites are made for profit; some exist to inform or educate users. Or any other reason why people make websites. And this might be the case. Link.springer.com could be getting rich in stealth mode, or the way it's monetizing isn't detectable.

Keywords {πŸ”}

cells, lineage, lineages, slingshot, curves, methods, branching, data, pseudotime, cell, inference, principal, singlecell, method, clustering, clusters, number, monocle, cluster, analysis, additional, article, mst, dataset, results, datasets, dimensionality, file, pseudotimes, reduction, values, curve, pubmed, google, scholar, multiple, single, terminal, accuracy, figure, expression, events, fig, tscan, step, average, scores, states, event, study,

Topics {βœ’οΈ}

single-cell rna-seq profiles bird’s-eye view newly-developed single-cell assays single-cell rna-sequencing experiments single-cell rna-seq analysis single-cell rna-seq data single-cell rna-seq markov chain monte-carlo single-cell rna sequencing equiv \left\{\begin{array}{ll} 1 single-cell genomics data single-cell mrna quantification rna-seq experiment noisy single-cell data underlying temporal variable single-cell transcriptomics sandrine dudoit article download pdf functional genomics unit single-cell genomics full-quantile-normalized prior cell fate decisions highest-level branching events single-cell assays eventual cluster-based mst covariance-scaled euclidean distance original cell-level data rank correlation coefficient cell stem cell shape-sensitive distance measure highest-level branching event reduced-dimensionality space created reverse graph embedding stochastic mrna synthesis rna-seq bmc genomics 19 low-dimensional space obtained pearson correlation coefficient inferring cell lineages single-cell resolution privacy choices/manage cookies single-lineage hsmm dataset single-cell data quiescent stem cells gaussian mixture model wellcome open res creative commons license gaussian mixture modeling full size image minimum spanning tree

Schema {πŸ—ΊοΈ}

WebPage:
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         headline:Slingshot: cell lineage and pseudotime inference for single-cell transcriptomics
         description:Single-cell transcriptomics allows researchers to investigate complex communities of heterogeneous cells. It can be applied to stem cells and their descendants in order to chart the progression from multipotent progenitors to fully differentiated cells. While a variety of statistical and computational methods have been proposed for inferring cell lineages, the problem of accurately characterizing multiple branching lineages remains difficult to solve. We introduce Slingshot, a novel method for inferring cell lineages and pseudotimes from single-cell gene expression data. In previously published datasets, Slingshot correctly identifies the biological signal for one to three branching trajectories. Additionally, our simulation study shows that Slingshot infers more accurate pseudotimes than other leading methods. Slingshot is a uniquely robust and flexible tool which combines the highly stable techniques necessary for noisy single-cell data with the ability to identify multiple trajectories. Accurate lineage inference is a critical step in the identification of dynamic temporal gene expression.
         datePublished:2018-06-19T00:00:00Z
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            RNA-Seq
            Single cell
            Lineage inference
            Pseudotime inference
            Life Sciences
            general
            Microarrays
            Proteomics
            Animal Genetics and Genomics
            Microbial Genetics and Genomics
            Plant Genetics and Genomics
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      headline:Slingshot: cell lineage and pseudotime inference for single-cell transcriptomics
      description:Single-cell transcriptomics allows researchers to investigate complex communities of heterogeneous cells. It can be applied to stem cells and their descendants in order to chart the progression from multipotent progenitors to fully differentiated cells. While a variety of statistical and computational methods have been proposed for inferring cell lineages, the problem of accurately characterizing multiple branching lineages remains difficult to solve. We introduce Slingshot, a novel method for inferring cell lineages and pseudotimes from single-cell gene expression data. In previously published datasets, Slingshot correctly identifies the biological signal for one to three branching trajectories. Additionally, our simulation study shows that Slingshot infers more accurate pseudotimes than other leading methods. Slingshot is a uniquely robust and flexible tool which combines the highly stable techniques necessary for noisy single-cell data with the ability to identify multiple trajectories. Accurate lineage inference is a critical step in the identification of dynamic temporal gene expression.
      datePublished:2018-06-19T00:00:00Z
      dateModified:2018-06-19T00:00:00Z
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      keywords:
         RNA-Seq
         Single cell
         Lineage inference
         Pseudotime inference
         Life Sciences
         general
         Microarrays
         Proteomics
         Animal Genetics and Genomics
         Microbial Genetics and Genomics
         Plant Genetics and Genomics
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                     type:PostalAddress
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            name:Nir Yosef
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                  name:University of California
                  address:
                     name:Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, USA
                     type:PostalAddress
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                  name:School of Public Health, University of California
                  address:
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                  name:University of California
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                     type:PostalAddress
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                  name:Berkeley Institute for Data Science, University of California
                  address:
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         name:QB3 Berkeley Functional Genomics Laboratory, Berkeley, USA
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      name:Diya Das
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            name:University of California
            address:
               name:Department of Molecular and Cell Biology, University of California, Berkeley, USA
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            name:Helen Wills Neuroscience Institute, University of California
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               name:Helen Wills Neuroscience Institute, University of California, Berkeley, USA
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            name:QB3 Berkeley Functional Genomics Laboratory
            address:
               name:QB3 Berkeley Functional Genomics Laboratory, Berkeley, USA
               type:PostalAddress
            type:Organization
      name:Nir Yosef
      affiliation:
            name:University of California
            address:
               name:Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, USA
               type:PostalAddress
            type:Organization
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            address:
               name:Center for Computational Biology, University of California, Berkeley, USA
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            name:University of California
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               name:Department of Statistics, University of California, Berkeley, USA
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            name:Center for Computational Biology, University of California
            address:
               name:Center for Computational Biology, University of California, Berkeley, USA
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      name:Sandrine Dudoit
      url:http://orcid.org/0000-0002-6069-8629
      affiliation:
            name:School of Public Health, University of California
            address:
               name:Division of Biostatistics, School of Public Health, University of California, Berkeley, USA
               type:PostalAddress
            type:Organization
            name:University of California
            address:
               name:Department of Statistics, University of California, Berkeley, USA
               type:PostalAddress
            type:Organization
            name:Center for Computational Biology, University of California
            address:
               name:Center for Computational Biology, University of California, Berkeley, USA
               type:PostalAddress
            type:Organization
            name:Berkeley Institute for Data Science, University of California
            address:
               name:Berkeley Institute for Data Science, University of California, Berkeley, USA
               type:PostalAddress
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      email:[email protected]
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      name:Division of Biostatistics, School of Public Health, University of California, Berkeley, USA
      name:Center for Computational Biology, University of California, Berkeley, USA
      name:Division of Biostatistics and Epidemiology, Department of Healthcare Policy and Research, Weill Cornell Medicine, New York, USA
      name:Department of Molecular and Cell Biology, University of California, Berkeley, USA
      name:Department of Molecular and Cell Biology, University of California, Berkeley, USA
      name:Berkeley Institute for Data Science, University of California, Berkeley, USA
      name:Department of Molecular and Cell Biology, University of California, Berkeley, USA
      name:Helen Wills Neuroscience Institute, University of California, Berkeley, USA
      name:QB3 Berkeley Functional Genomics Laboratory, Berkeley, USA
      name:Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, USA
      name:Center for Computational Biology, University of California, Berkeley, USA
      name:Department of Statistics, University of California, Berkeley, USA
      name:Center for Computational Biology, University of California, Berkeley, USA
      name:Division of Biostatistics, School of Public Health, University of California, Berkeley, USA
      name:Department of Statistics, University of California, Berkeley, USA
      name:Center for Computational Biology, University of California, Berkeley, USA
      name:Berkeley Institute for Data Science, University of California, Berkeley, USA

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