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August 12, 2016Oncotarget523 citationsOpen Access

OASIS 2: online application for survival analysis 2 with features for the analysis of maximal lifespan and healthspan in aging research

SHSeong Kyu HanDLDong-Yeop LeeHLHeetak Lee

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Abstract

// Seong Kyu Han 1 , Dongyeop Lee 1 , Heetak Lee 1 , Donghyo Kim 1 , Heehwa G. Son 1 , Jae-Seong Yang 4 , Seung-Jae V. Lee 1,2,3 and Sanguk Kim 1,2,3 1 Department of Life Sciences, Pohang University of Science and Technology, Pohang, Korea 2 Department of IT Convergence and Engineering, Pohang University of Science and Technology, Pohang, Korea 3 School of Interdisciplinary Bioscience and Bioengineering, Pohang University of Science and Technology, Pohang, Korea 4 EMBL/CRG Systems Biology Research Unit, Centre for Genomic Regulation (CRG), Barcelona, Spain Correspondence to: Seung-Jae V. Lee, email: // Sanguk Kim, email: // Keywords : web-service, statistics, survival, maximum lifespan, healthspan Received : April 28, 2016 Accepted : July 30, 2016 Published : August 12, 2016 Abstract Online application for survival analysis (OASIS) has served as a popular and convenient platform for the statistical analysis of various survival data, particularly in the field of aging research. With the recent advances in the fields of aging research that deal with complex survival data, we noticed a need for updates to the current version of OASIS. Here, we report OASIS 2 ( http://sbi.postech.ac.kr/oasis2 ), which provides extended statistical tools for survival data and an enhanced user interface. In particular, OASIS 2 enables the statistical comparison of maximal lifespans, which is potentially useful for determining key factors that limit the lifespan of a population. Furthermore, OASIS 2 provides statistical and graphical tools that compare values in different conditions and times. That feature is useful for comparing age-associated changes in physiological activities, which can be used as indicators of “healthspan.” We believe that OASIS 2 will serve as a standard platform for survival analysis with advanced and user-friendly statistical tools for experimental biologists in the field of aging research.

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Han et al. (2016) studied this question.

synapsesocial.com/papers/6a74d30c96d04a2f43f55c60https://doi.org/10.18632/oncotarget.11269
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