We are analyzing https://link.springer.com/article/10.1007/s12539-016-0198-z.

Title:
CAsubtype: An R Package to Identify Gene Sets Predictive of Cancer Subtypes and Clinical Outcomes | Interdisciplinary Sciences: Computational Life Sciences
Description:
In the past decade, molecular classification of cancer has gained high popularity owing to its high predictive power on clinical outcomes as compared with traditional methods commonly used in clinical practice. In particular, using gene expression profiles, recent studies have successfully identified a number of gene sets for the delineation of cancer subtypes that are associated with distinct prognosis. However, identification of such gene sets remains a laborious task due to the lack of tools with flexibility, integration and ease of use. To reduce the burden, we have developed an R package, CAsubtype, to efficiently identify gene sets predictive of cancer subtypes and clinical outcomes. By integrating more than 13,000 annotated gene sets, CAsubtype provides a comprehensive repertoire of candidates for new cancer subtype identification. For easy data access, CAsubtype further includes the gene expression and clinical data of more than 2000 cancer patients from TCGA. CAsubtype first employs principal component analysis to identify gene sets (from user-provided or package-integrated ones) with robust principal components representing significantly large variation between cancer samples. Based on these principal components, CAsubtype visualizes the sample distribution in low-dimensional space for better understanding of the distinction between samples and classifies samples into subgroups with prevalent clustering algorithms. Finally, CAsubtype performs survival analysis to compare the clinical outcomes between the identified subgroups, assessing their clinical value as potentially novel cancer subtypes. In conclusion, CAsubtype is a flexible and well-integrated tool in the R environment to identify gene sets for cancer subtype identification and clinical outcome prediction. Its simple R commands and comprehensive data sets enable efficient examination of the clinical value of any given gene set, thus facilitating hypothesis generating and testing in biological and clinical studies.
Website Age:
28 years and 1 months (reg. 1997-05-29).

Matching Content Categories {📚}

Education
Science
Health & Fitness

Content Management System {📝}

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 {📈}

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 7,642,828 visitors per month in the current month.

check SE Ranking
check Ahrefs
check Similarweb
check Ubersuggest
check Semrush

How Does Link.springer.com Make Money? {💸}

We're unsure if the website is profiting.

While profit motivates many websites, others exist to inspire, entertain, or provide valuable resources. Websites have a variety of goals. And this might be one of them. Link.springer.com could be secretly minting cash, but we can't detect the process.

Keywords {🔍}

article, cancer, gene, google, scholar, clinical, expression, cas, data, analysis, casubtype, package, sets, subtypes, tong, access, med, shanghai, outcomes, molecular, subtype, nat, privacy, cookies, content, research, computational, identify, classification, patients, principal, survival, signature, bioinformatics, publish, search, sciences, predictive, zhao, open, identifies, prognostic, emt, signatures, nature, grant, university, pdf, information, log,

Topics {✒️}

large-scale epigenetic alterations month download article/chapter gene expression profiles gene expression classification prognostic gene signature gene expression data gene expression signatures article interdisciplinary sciences open software development related protein expression poor-prognosis colon cancer convolutional neural networks identify gene sets easy data access scientific research foundation gene sets remains principal component analysis privacy choices/manage cookies cancer subtype prediction gene expression full article pdf cancer subtype identification high predictive power state education ministry molecularly distinct subtype related subjects comprehensive molecular portraits human breast tumors jielin sun poor clinical outcome cancer genomic data affymetrix genechip data gene set sizes molecular signatures database cancer stem cells prevalent clustering algorithms epithelial-mesenchymal transition epithelial-mesenchymal-transition censored survival data article kong oncogenic pathway signatures clinical outcome prediction computational web-sever human colon cancer european economic area traditional methods commonly laborious task due low-dimensional space facilitating hypothesis generating serrated precursor lesions

Questions {❓}

Ringnér Markus (2008) What is principal component analysis?

Schema {🗺️}

WebPage:
      mainEntity:
         headline:CAsubtype: An R Package to Identify Gene Sets Predictive of Cancer Subtypes and Clinical Outcomes
         description:In the past decade, molecular classification of cancer has gained high popularity owing to its high predictive power on clinical outcomes as compared with traditional methods commonly used in clinical practice. In particular, using gene expression profiles, recent studies have successfully identified a number of gene sets for the delineation of cancer subtypes that are associated with distinct prognosis. However, identification of such gene sets remains a laborious task due to the lack of tools with flexibility, integration and ease of use. To reduce the burden, we have developed an R package, CAsubtype, to efficiently identify gene sets predictive of cancer subtypes and clinical outcomes. By integrating more than 13,000 annotated gene sets, CAsubtype provides a comprehensive repertoire of candidates for new cancer subtype identification. For easy data access, CAsubtype further includes the gene expression and clinical data of more than 2000 cancer patients from TCGA. CAsubtype first employs principal component analysis to identify gene sets (from user-provided or package-integrated ones) with robust principal components representing significantly large variation between cancer samples. Based on these principal components, CAsubtype visualizes the sample distribution in low-dimensional space for better understanding of the distinction between samples and classifies samples into subgroups with prevalent clustering algorithms. Finally, CAsubtype performs survival analysis to compare the clinical outcomes between the identified subgroups, assessing their clinical value as potentially novel cancer subtypes. In conclusion, CAsubtype is a flexible and well-integrated tool in the R environment to identify gene sets for cancer subtype identification and clinical outcome prediction. Its simple R commands and comprehensive data sets enable efficient examination of the clinical value of any given gene set, thus facilitating hypothesis generating and testing in biological and clinical studies.
         datePublished:2017-01-21T00:00:00Z
         dateModified:2017-01-21T00:00:00Z
         pageStart:169
         pageEnd:175
         sameAs:https://doi.org/10.1007/s12539-016-0198-z
         keywords:
            Cancer subtype
            Clinical outcome
            R package
            Gene signature
            Gene expression profile
            Computer Appl. in Life Sciences
            Computational Biology/Bioinformatics
            Statistics for Life Sciences
            Medicine
            Health Sciences
            Theoretical and Computational Chemistry
            Theoretical
            Mathematical and Computational Physics
            Computational Science and Engineering
         image:
            https://media.springernature.com/lw1200/springer-static/image/art%3A10.1007%2Fs12539-016-0198-z/MediaObjects/12539_2016_198_Fig1_HTML.gif
            https://media.springernature.com/lw1200/springer-static/image/art%3A10.1007%2Fs12539-016-0198-z/MediaObjects/12539_2016_198_Fig2_HTML.gif
            https://media.springernature.com/lw1200/springer-static/image/art%3A10.1007%2Fs12539-016-0198-z/MediaObjects/12539_2016_198_Fig3_HTML.gif
            https://media.springernature.com/lw1200/springer-static/image/art%3A10.1007%2Fs12539-016-0198-z/MediaObjects/12539_2016_198_Fig4_HTML.gif
         isPartOf:
            name:Interdisciplinary Sciences: Computational Life Sciences
            issn:
               1867-1462
               1913-2751
            volumeNumber:10
            type:
               Periodical
               PublicationVolume
         publisher:
            name:Springer Berlin Heidelberg
            logo:
               url:https://www.springernature.com/app-sn/public/images/logo-springernature.png
               type:ImageObject
            type:Organization
         author:
               name:Hualei Kong
               affiliation:
                     name:Shanghai Jiao Tong University
                     address:
                        name:Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, China
                        type:PostalAddress
                     type:Organization
               type:Person
               name:Pan Tong
               affiliation:
                     name:The University of Texas MD Anderson Cancer Center
                     address:
                        name:Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, USA
                        type:PostalAddress
                     type:Organization
               type:Person
               name:Xiaodong Zhao
               affiliation:
                     name:Shanghai Jiao Tong University
                     address:
                        name:School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
                        type:PostalAddress
                     type:Organization
               type:Person
               name:Jielin Sun
               affiliation:
                     name:Shanghai Jiao Tong University
                     address:
                        name:Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, China
                        type:PostalAddress
                     type:Organization
               email:[email protected]
               type:Person
               name:Hua Li
               affiliation:
                     name:Shanghai Jiao Tong University
                     address:
                        name:School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
                        type:PostalAddress
                     type:Organization
               email:[email protected]
               type:Person
         isAccessibleForFree:
         hasPart:
            isAccessibleForFree:
            cssSelector:.main-content
            type:WebPageElement
         type:ScholarlyArticle
      context:https://schema.org
ScholarlyArticle:
      headline:CAsubtype: An R Package to Identify Gene Sets Predictive of Cancer Subtypes and Clinical Outcomes
      description:In the past decade, molecular classification of cancer has gained high popularity owing to its high predictive power on clinical outcomes as compared with traditional methods commonly used in clinical practice. In particular, using gene expression profiles, recent studies have successfully identified a number of gene sets for the delineation of cancer subtypes that are associated with distinct prognosis. However, identification of such gene sets remains a laborious task due to the lack of tools with flexibility, integration and ease of use. To reduce the burden, we have developed an R package, CAsubtype, to efficiently identify gene sets predictive of cancer subtypes and clinical outcomes. By integrating more than 13,000 annotated gene sets, CAsubtype provides a comprehensive repertoire of candidates for new cancer subtype identification. For easy data access, CAsubtype further includes the gene expression and clinical data of more than 2000 cancer patients from TCGA. CAsubtype first employs principal component analysis to identify gene sets (from user-provided or package-integrated ones) with robust principal components representing significantly large variation between cancer samples. Based on these principal components, CAsubtype visualizes the sample distribution in low-dimensional space for better understanding of the distinction between samples and classifies samples into subgroups with prevalent clustering algorithms. Finally, CAsubtype performs survival analysis to compare the clinical outcomes between the identified subgroups, assessing their clinical value as potentially novel cancer subtypes. In conclusion, CAsubtype is a flexible and well-integrated tool in the R environment to identify gene sets for cancer subtype identification and clinical outcome prediction. Its simple R commands and comprehensive data sets enable efficient examination of the clinical value of any given gene set, thus facilitating hypothesis generating and testing in biological and clinical studies.
      datePublished:2017-01-21T00:00:00Z
      dateModified:2017-01-21T00:00:00Z
      pageStart:169
      pageEnd:175
      sameAs:https://doi.org/10.1007/s12539-016-0198-z
      keywords:
         Cancer subtype
         Clinical outcome
         R package
         Gene signature
         Gene expression profile
         Computer Appl. in Life Sciences
         Computational Biology/Bioinformatics
         Statistics for Life Sciences
         Medicine
         Health Sciences
         Theoretical and Computational Chemistry
         Theoretical
         Mathematical and Computational Physics
         Computational Science and Engineering
      image:
         https://media.springernature.com/lw1200/springer-static/image/art%3A10.1007%2Fs12539-016-0198-z/MediaObjects/12539_2016_198_Fig1_HTML.gif
         https://media.springernature.com/lw1200/springer-static/image/art%3A10.1007%2Fs12539-016-0198-z/MediaObjects/12539_2016_198_Fig2_HTML.gif
         https://media.springernature.com/lw1200/springer-static/image/art%3A10.1007%2Fs12539-016-0198-z/MediaObjects/12539_2016_198_Fig3_HTML.gif
         https://media.springernature.com/lw1200/springer-static/image/art%3A10.1007%2Fs12539-016-0198-z/MediaObjects/12539_2016_198_Fig4_HTML.gif
      isPartOf:
         name:Interdisciplinary Sciences: Computational Life Sciences
         issn:
            1867-1462
            1913-2751
         volumeNumber:10
         type:
            Periodical
            PublicationVolume
      publisher:
         name:Springer Berlin Heidelberg
         logo:
            url:https://www.springernature.com/app-sn/public/images/logo-springernature.png
            type:ImageObject
         type:Organization
      author:
            name:Hualei Kong
            affiliation:
                  name:Shanghai Jiao Tong University
                  address:
                     name:Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, China
                     type:PostalAddress
                  type:Organization
            type:Person
            name:Pan Tong
            affiliation:
                  name:The University of Texas MD Anderson Cancer Center
                  address:
                     name:Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, USA
                     type:PostalAddress
                  type:Organization
            type:Person
            name:Xiaodong Zhao
            affiliation:
                  name:Shanghai Jiao Tong University
                  address:
                     name:School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
                     type:PostalAddress
                  type:Organization
            type:Person
            name:Jielin Sun
            affiliation:
                  name:Shanghai Jiao Tong University
                  address:
                     name:Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, China
                     type:PostalAddress
                  type:Organization
            email:[email protected]
            type:Person
            name:Hua Li
            affiliation:
                  name:Shanghai Jiao Tong University
                  address:
                     name:School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
                     type:PostalAddress
                  type:Organization
            email:[email protected]
            type:Person
      isAccessibleForFree:
      hasPart:
         isAccessibleForFree:
         cssSelector:.main-content
         type:WebPageElement
["Periodical","PublicationVolume"]:
      name:Interdisciplinary Sciences: Computational Life Sciences
      issn:
         1867-1462
         1913-2751
      volumeNumber:10
Organization:
      name:Springer Berlin Heidelberg
      logo:
         url:https://www.springernature.com/app-sn/public/images/logo-springernature.png
         type:ImageObject
      name:Shanghai Jiao Tong University
      address:
         name:Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, China
         type:PostalAddress
      name:The University of Texas MD Anderson Cancer Center
      address:
         name:Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, USA
         type:PostalAddress
      name:Shanghai Jiao Tong University
      address:
         name:School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
         type:PostalAddress
      name:Shanghai Jiao Tong University
      address:
         name:Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, China
         type:PostalAddress
      name:Shanghai Jiao Tong University
      address:
         name:School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
         type:PostalAddress
ImageObject:
      url:https://www.springernature.com/app-sn/public/images/logo-springernature.png
Person:
      name:Hualei Kong
      affiliation:
            name:Shanghai Jiao Tong University
            address:
               name:Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, China
               type:PostalAddress
            type:Organization
      name:Pan Tong
      affiliation:
            name:The University of Texas MD Anderson Cancer Center
            address:
               name:Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, USA
               type:PostalAddress
            type:Organization
      name:Xiaodong Zhao
      affiliation:
            name:Shanghai Jiao Tong University
            address:
               name:School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
               type:PostalAddress
            type:Organization
      name:Jielin Sun
      affiliation:
            name:Shanghai Jiao Tong University
            address:
               name:Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, China
               type:PostalAddress
            type:Organization
      email:[email protected]
      name:Hua Li
      affiliation:
            name:Shanghai Jiao Tong University
            address:
               name:School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
               type:PostalAddress
            type:Organization
      email:[email protected]
PostalAddress:
      name:Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, China
      name:Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, USA
      name:School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
      name:Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, China
      name:School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, China
WebPageElement:
      isAccessibleForFree:
      cssSelector:.main-content

External Links {🔗}(87)

Analytics and Tracking {📊}

Google Tag Manager

Libraries {📚}

Clipboard.js
Prism.js

CDN Services {📦}

Crossref

6.09s.

LINK . SPRINGER . COM {}