DoSurvive : A webtool for investigating the prognostic power of a single or combined cancer biomarker
© 2023 The Author(s)..
We present DoSurvive, a user-friendly survival analysis web tool and a cancer prognostic biomarker centered database. DoSurvive is the first database that allows users to perform multivariant survival analysis for cancers with customized gene/patient list. DoSurvive offers three survival analysis methods, Log rank test, Cox regression and accelerated failure time model (AFT), for users to analyze five types of quantitative features (mRNA, miRNA, lncRNA, protein and methylation of CpG islands) with four survival types, i.e. overall survival, disease-specific survival, disease-free interval, and progression-free interval, in 33 cancer types. Notably, the implemented AFT model provides an alternative method for genes/features which failed the proportional hazard assumption in Cox regression. With the unprecedented number of survival models implemented and high flexibility in analysis, DoSurvive is a unique platform for the identification of clinically relevant targets for cancer researcher and practitioners. DoSurvive is freely available at http://dosurvive.lab.nycu.edu.tw/.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:26 |
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| Enthalten in: |
iScience - 26(2023), 8 vom: 18. Aug., Seite 107269 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Wu, Hao-Wei [VerfasserIn] |
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| Links: |
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| Themen: |
Cancer systems biology |
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| Anmerkungen: |
Date Revised 24.08.2023 published: Electronic-eCollection Citation Status PubMed-not-MEDLINE |
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| doi: |
10.1016/j.isci.2023.107269 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM361080859 |
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| 500 | |a published: Electronic-eCollection | ||
| 500 | |a Citation Status PubMed-not-MEDLINE | ||
| 520 | |a © 2023 The Author(s). | ||
| 520 | |a We present DoSurvive, a user-friendly survival analysis web tool and a cancer prognostic biomarker centered database. DoSurvive is the first database that allows users to perform multivariant survival analysis for cancers with customized gene/patient list. DoSurvive offers three survival analysis methods, Log rank test, Cox regression and accelerated failure time model (AFT), for users to analyze five types of quantitative features (mRNA, miRNA, lncRNA, protein and methylation of CpG islands) with four survival types, i.e. overall survival, disease-specific survival, disease-free interval, and progression-free interval, in 33 cancer types. Notably, the implemented AFT model provides an alternative method for genes/features which failed the proportional hazard assumption in Cox regression. With the unprecedented number of survival models implemented and high flexibility in analysis, DoSurvive is a unique platform for the identification of clinically relevant targets for cancer researcher and practitioners. DoSurvive is freely available at http://dosurvive.lab.nycu.edu.tw/ | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Cancer systems biology | |
| 650 | 4 | |a Epigenetics | |
| 650 | 4 | |a Proteomics | |
| 650 | 4 | |a Transcriptomics | |
| 700 | 1 | |a Wu, Jian-De |e verfasserin |4 aut | |
| 700 | 1 | |a Yeh, Yen-Ping |e verfasserin |4 aut | |
| 700 | 1 | |a Wu, Timothy H |e verfasserin |4 aut | |
| 700 | 1 | |a Chao, Chi-Hong |e verfasserin |4 aut | |
| 700 | 1 | |a Wang, Weijing |e verfasserin |4 aut | |
| 700 | 1 | |a Chen, Ting-Wen |e verfasserin |4 aut | |
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