Aging Atlas: a multi-omics database for aging biology
Abstract Organismal aging is driven by interconnected molecular changes encompassing internal and extracellular factors. Combinational analysis of high-throughput ‘multi-omics’ datasets (gathering information from genomics, epigenomics, transcriptomics, proteomics, metabolomics and pharmacogenomics)...
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| Veröffentlicht in: | Nucleic acids research 2021-01, Vol.49 (D1), p.D825-D830 |
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| creator | Liu, Guang-Hui Bao, Yiming Qu, Jing Zhang, Weiqi Zhang, Tao Kang, Wang Yang, Fei Ji, Qianzhao Jiang, Xiaoyu Ma, Yingke Ma, Shuai Liu, Zunpeng Chen, Siyu Wang, Si Sun, Shuhui Geng, Lingling Yan, Kaowen Yan, Pengze Fan, Yanling Song, Moshi Ren, Jie Wang, Qiaoran Yang, Shanshan Yang, Yuanhan Xiong, Muzhao Liang, Chuqiang Li, Lan-Zhu Cao, Tianling Hu, Jianli Yang, Ping Ping, Jiale Hu, Huifang Zheng, Yandong Sun, Guoqiang Li, Jiaming Liu, Lixiao Zou, Zhiran Ding, Yingjie Li, Mingheng Liu, Di Wang, Min Sun, Xiaoyan Wang, Cui Bi, Shijia Shan, Hezhen Zhuo, Xiao |
| description | Abstract
Organismal aging is driven by interconnected molecular changes encompassing internal and extracellular factors. Combinational analysis of high-throughput ‘multi-omics’ datasets (gathering information from genomics, epigenomics, transcriptomics, proteomics, metabolomics and pharmacogenomics), at either populational or single-cell levels, can provide a multi-dimensional, integrated profile of the heterogeneous aging process with unprecedented throughput and detail. These new strategies allow for the exploration of the molecular profile and regulatory status of gene expression during aging, and in turn, facilitate the development of new aging interventions. With a continually growing volume of valuable aging-related data, it is necessary to establish an open and integrated database to support a wide spectrum of aging research. The Aging Atlas database aims to provide a wide range of life science researchers with valuable resources that allow access to a large-scale of gene expression and regulation datasets created by various high-throughput omics technologies. The current implementation includes five modules: transcriptomics (RNA-seq), single-cell transcriptomics (scRNA-seq), epigenomics (ChIP-seq), proteomics (protein–protein interaction), and pharmacogenomics (geroprotective compounds). Aging Atlas provides user-friendly functionalities to explore age-related changes in gene expression, as well as raw data download services. Aging Atlas is freely available at https://bigd.big.ac.cn/aging/index. |
| doi_str_mv | 10.1093/nar/gkaa894 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_7779027</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><oup_id>10.1093/nar/gkaa894</oup_id><sourcerecordid>2456419580</sourcerecordid><originalsourceid>FETCH-LOGICAL-c478t-e17aaa572d1ee6bf672bd8fc7b692eb1ceadb90415b3312afd2fc97e2f3262103</originalsourceid><addsrcrecordid>eNp9kM1LwzAYxoMobk5P3qUnEaQuH23TeBDG8AsGXvQc3qRpjbbNTFph_72dm0Mvnt7D--P3PDwInRJ8RbBg0xb8tHoHyEWyh8aEZTROREb30RgznMYEJ_kIHYXwhjFJSJocohFjhAiesjFKZ5Vtq2jW1RCuI4iavu5s7BqrQ1RABwqCiUrnI_jmlHW1q1bH6KCEOpiT7Z2gl7vb5_lDvHi6f5zPFrFOeN7FhnAASDktiDGZKjNOVZGXmqtMUKOINlAogYdSamhEoSxoqQU3tGQ0owSzCbrZeJe9akyhTdt5qOXS2wb8Sjqw8u-nta-ycp-Scy4w5YPgYivw7qM3oZONDdrUNbTG9UHSJM0SItJ8nXW5QbV3IXhT7mIIluuh5TC03A490Ge_m-3Yn2UH4HwDuH75r-kLHH-IHQ</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2456419580</pqid></control><display><type>article</type><title>Aging Atlas: a multi-omics database for aging biology</title><source>Oxford Journals Open Access Collection</source><source>MEDLINE</source><source>DOAJ Directory of Open Access Journals</source><source>PubMed Central</source><source>Free Full-Text Journals in Chemistry</source><creator>Liu, Guang-Hui ; Bao, Yiming ; Qu, Jing ; Zhang, Weiqi ; Zhang, Tao ; Kang, Wang ; Yang, Fei ; Ji, Qianzhao ; Jiang, Xiaoyu ; Ma, Yingke ; Ma, Shuai ; Liu, Zunpeng ; Chen, Siyu ; Wang, Si ; Sun, Shuhui ; Geng, Lingling ; Yan, Kaowen ; Yan, Pengze ; Fan, Yanling ; Song, Moshi ; Ren, Jie ; Wang, Qiaoran ; Yang, Shanshan ; Yang, Yuanhan ; Xiong, Muzhao ; Liang, Chuqiang ; Li, Lan-Zhu ; Cao, Tianling ; Hu, Jianli ; Yang, Ping ; Ping, Jiale ; Hu, Huifang ; Zheng, Yandong ; Sun, Guoqiang ; Li, Jiaming ; Liu, Lixiao ; Zou, Zhiran ; Ding, Yingjie ; Li, Mingheng ; Liu, Di ; Wang, Min ; Sun, Xiaoyan ; Wang, Cui ; Bi, Shijia ; Shan, Hezhen ; Zhuo, Xiao</creator><creatorcontrib>Liu, Guang-Hui ; Bao, Yiming ; Qu, Jing ; Zhang, Weiqi ; Zhang, Tao ; Kang, Wang ; Yang, Fei ; Ji, Qianzhao ; Jiang, Xiaoyu ; Ma, Yingke ; Ma, Shuai ; Liu, Zunpeng ; Chen, Siyu ; Wang, Si ; Sun, Shuhui ; Geng, Lingling ; Yan, Kaowen ; Yan, Pengze ; Fan, Yanling ; Song, Moshi ; Ren, Jie ; Wang, Qiaoran ; Yang, Shanshan ; Yang, Yuanhan ; Xiong, Muzhao ; Liang, Chuqiang ; Li, Lan-Zhu ; Cao, Tianling ; Hu, Jianli ; Yang, Ping ; Ping, Jiale ; Hu, Huifang ; Zheng, Yandong ; Sun, Guoqiang ; Li, Jiaming ; Liu, Lixiao ; Zou, Zhiran ; Ding, Yingjie ; Li, Mingheng ; Liu, Di ; Wang, Min ; Sun, Xiaoyan ; Wang, Cui ; Bi, Shijia ; Shan, Hezhen ; Zhuo, Xiao ; Aging Atlas Consortium</creatorcontrib><description>Abstract
Organismal aging is driven by interconnected molecular changes encompassing internal and extracellular factors. Combinational analysis of high-throughput ‘multi-omics’ datasets (gathering information from genomics, epigenomics, transcriptomics, proteomics, metabolomics and pharmacogenomics), at either populational or single-cell levels, can provide a multi-dimensional, integrated profile of the heterogeneous aging process with unprecedented throughput and detail. These new strategies allow for the exploration of the molecular profile and regulatory status of gene expression during aging, and in turn, facilitate the development of new aging interventions. With a continually growing volume of valuable aging-related data, it is necessary to establish an open and integrated database to support a wide spectrum of aging research. The Aging Atlas database aims to provide a wide range of life science researchers with valuable resources that allow access to a large-scale of gene expression and regulation datasets created by various high-throughput omics technologies. The current implementation includes five modules: transcriptomics (RNA-seq), single-cell transcriptomics (scRNA-seq), epigenomics (ChIP-seq), proteomics (protein–protein interaction), and pharmacogenomics (geroprotective compounds). Aging Atlas provides user-friendly functionalities to explore age-related changes in gene expression, as well as raw data download services. Aging Atlas is freely available at https://bigd.big.ac.cn/aging/index.</description><identifier>ISSN: 0305-1048</identifier><identifier>EISSN: 1362-4962</identifier><identifier>DOI: 10.1093/nar/gkaa894</identifier><identifier>PMID: 33119753</identifier><language>eng</language><publisher>England: Oxford University Press</publisher><subject>Aging - genetics ; Database Issue ; Databases, Genetic ; Epigenomics ; Genomics ; Humans ; Pharmacogenetics ; Transcriptome - genetics</subject><ispartof>Nucleic acids research, 2021-01, Vol.49 (D1), p.D825-D830</ispartof><rights>The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research. 2021</rights><rights>The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c478t-e17aaa572d1ee6bf672bd8fc7b692eb1ceadb90415b3312afd2fc97e2f3262103</citedby><cites>FETCH-LOGICAL-c478t-e17aaa572d1ee6bf672bd8fc7b692eb1ceadb90415b3312afd2fc97e2f3262103</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7779027/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7779027/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,1598,27901,27902,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33119753$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Liu, Guang-Hui</creatorcontrib><creatorcontrib>Bao, Yiming</creatorcontrib><creatorcontrib>Qu, Jing</creatorcontrib><creatorcontrib>Zhang, Weiqi</creatorcontrib><creatorcontrib>Zhang, Tao</creatorcontrib><creatorcontrib>Kang, Wang</creatorcontrib><creatorcontrib>Yang, Fei</creatorcontrib><creatorcontrib>Ji, Qianzhao</creatorcontrib><creatorcontrib>Jiang, Xiaoyu</creatorcontrib><creatorcontrib>Ma, Yingke</creatorcontrib><creatorcontrib>Ma, Shuai</creatorcontrib><creatorcontrib>Liu, Zunpeng</creatorcontrib><creatorcontrib>Chen, Siyu</creatorcontrib><creatorcontrib>Wang, Si</creatorcontrib><creatorcontrib>Sun, Shuhui</creatorcontrib><creatorcontrib>Geng, Lingling</creatorcontrib><creatorcontrib>Yan, Kaowen</creatorcontrib><creatorcontrib>Yan, Pengze</creatorcontrib><creatorcontrib>Fan, Yanling</creatorcontrib><creatorcontrib>Song, Moshi</creatorcontrib><creatorcontrib>Ren, Jie</creatorcontrib><creatorcontrib>Wang, Qiaoran</creatorcontrib><creatorcontrib>Yang, Shanshan</creatorcontrib><creatorcontrib>Yang, Yuanhan</creatorcontrib><creatorcontrib>Xiong, Muzhao</creatorcontrib><creatorcontrib>Liang, Chuqiang</creatorcontrib><creatorcontrib>Li, Lan-Zhu</creatorcontrib><creatorcontrib>Cao, Tianling</creatorcontrib><creatorcontrib>Hu, Jianli</creatorcontrib><creatorcontrib>Yang, Ping</creatorcontrib><creatorcontrib>Ping, Jiale</creatorcontrib><creatorcontrib>Hu, Huifang</creatorcontrib><creatorcontrib>Zheng, Yandong</creatorcontrib><creatorcontrib>Sun, Guoqiang</creatorcontrib><creatorcontrib>Li, Jiaming</creatorcontrib><creatorcontrib>Liu, Lixiao</creatorcontrib><creatorcontrib>Zou, Zhiran</creatorcontrib><creatorcontrib>Ding, Yingjie</creatorcontrib><creatorcontrib>Li, Mingheng</creatorcontrib><creatorcontrib>Liu, Di</creatorcontrib><creatorcontrib>Wang, Min</creatorcontrib><creatorcontrib>Sun, Xiaoyan</creatorcontrib><creatorcontrib>Wang, Cui</creatorcontrib><creatorcontrib>Bi, Shijia</creatorcontrib><creatorcontrib>Shan, Hezhen</creatorcontrib><creatorcontrib>Zhuo, Xiao</creatorcontrib><creatorcontrib>Aging Atlas Consortium</creatorcontrib><title>Aging Atlas: a multi-omics database for aging biology</title><title>Nucleic acids research</title><addtitle>Nucleic Acids Res</addtitle><description>Abstract
Organismal aging is driven by interconnected molecular changes encompassing internal and extracellular factors. Combinational analysis of high-throughput ‘multi-omics’ datasets (gathering information from genomics, epigenomics, transcriptomics, proteomics, metabolomics and pharmacogenomics), at either populational or single-cell levels, can provide a multi-dimensional, integrated profile of the heterogeneous aging process with unprecedented throughput and detail. These new strategies allow for the exploration of the molecular profile and regulatory status of gene expression during aging, and in turn, facilitate the development of new aging interventions. With a continually growing volume of valuable aging-related data, it is necessary to establish an open and integrated database to support a wide spectrum of aging research. The Aging Atlas database aims to provide a wide range of life science researchers with valuable resources that allow access to a large-scale of gene expression and regulation datasets created by various high-throughput omics technologies. The current implementation includes five modules: transcriptomics (RNA-seq), single-cell transcriptomics (scRNA-seq), epigenomics (ChIP-seq), proteomics (protein–protein interaction), and pharmacogenomics (geroprotective compounds). Aging Atlas provides user-friendly functionalities to explore age-related changes in gene expression, as well as raw data download services. Aging Atlas is freely available at https://bigd.big.ac.cn/aging/index.</description><subject>Aging - genetics</subject><subject>Database Issue</subject><subject>Databases, Genetic</subject><subject>Epigenomics</subject><subject>Genomics</subject><subject>Humans</subject><subject>Pharmacogenetics</subject><subject>Transcriptome - genetics</subject><issn>0305-1048</issn><issn>1362-4962</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>TOX</sourceid><sourceid>EIF</sourceid><recordid>eNp9kM1LwzAYxoMobk5P3qUnEaQuH23TeBDG8AsGXvQc3qRpjbbNTFph_72dm0Mvnt7D--P3PDwInRJ8RbBg0xb8tHoHyEWyh8aEZTROREb30RgznMYEJ_kIHYXwhjFJSJocohFjhAiesjFKZ5Vtq2jW1RCuI4iavu5s7BqrQ1RABwqCiUrnI_jmlHW1q1bH6KCEOpiT7Z2gl7vb5_lDvHi6f5zPFrFOeN7FhnAASDktiDGZKjNOVZGXmqtMUKOINlAogYdSamhEoSxoqQU3tGQ0owSzCbrZeJe9akyhTdt5qOXS2wb8Sjqw8u-nta-ycp-Scy4w5YPgYivw7qM3oZONDdrUNbTG9UHSJM0SItJ8nXW5QbV3IXhT7mIIluuh5TC03A490Ge_m-3Yn2UH4HwDuH75r-kLHH-IHQ</recordid><startdate>20210108</startdate><enddate>20210108</enddate><creator>Liu, Guang-Hui</creator><creator>Bao, Yiming</creator><creator>Qu, Jing</creator><creator>Zhang, Weiqi</creator><creator>Zhang, Tao</creator><creator>Kang, Wang</creator><creator>Yang, Fei</creator><creator>Ji, Qianzhao</creator><creator>Jiang, Xiaoyu</creator><creator>Ma, Yingke</creator><creator>Ma, Shuai</creator><creator>Liu, Zunpeng</creator><creator>Chen, Siyu</creator><creator>Wang, Si</creator><creator>Sun, Shuhui</creator><creator>Geng, Lingling</creator><creator>Yan, Kaowen</creator><creator>Yan, Pengze</creator><creator>Fan, Yanling</creator><creator>Song, Moshi</creator><creator>Ren, Jie</creator><creator>Wang, Qiaoran</creator><creator>Yang, Shanshan</creator><creator>Yang, Yuanhan</creator><creator>Xiong, Muzhao</creator><creator>Liang, Chuqiang</creator><creator>Li, Lan-Zhu</creator><creator>Cao, Tianling</creator><creator>Hu, Jianli</creator><creator>Yang, Ping</creator><creator>Ping, Jiale</creator><creator>Hu, Huifang</creator><creator>Zheng, Yandong</creator><creator>Sun, Guoqiang</creator><creator>Li, Jiaming</creator><creator>Liu, Lixiao</creator><creator>Zou, Zhiran</creator><creator>Ding, Yingjie</creator><creator>Li, Mingheng</creator><creator>Liu, Di</creator><creator>Wang, Min</creator><creator>Sun, Xiaoyan</creator><creator>Wang, Cui</creator><creator>Bi, Shijia</creator><creator>Shan, Hezhen</creator><creator>Zhuo, Xiao</creator><general>Oxford University Press</general><scope>TOX</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20210108</creationdate><title>Aging Atlas: a multi-omics database for aging biology</title><author>Liu, Guang-Hui ; Bao, Yiming ; Qu, Jing ; Zhang, Weiqi ; Zhang, Tao ; Kang, Wang ; Yang, Fei ; Ji, Qianzhao ; Jiang, Xiaoyu ; Ma, Yingke ; Ma, Shuai ; Liu, Zunpeng ; Chen, Siyu ; Wang, Si ; Sun, Shuhui ; Geng, Lingling ; Yan, Kaowen ; Yan, Pengze ; Fan, Yanling ; Song, Moshi ; Ren, Jie ; Wang, Qiaoran ; Yang, Shanshan ; Yang, Yuanhan ; Xiong, Muzhao ; Liang, Chuqiang ; Li, Lan-Zhu ; Cao, Tianling ; Hu, Jianli ; Yang, Ping ; Ping, Jiale ; Hu, Huifang ; Zheng, Yandong ; Sun, Guoqiang ; Li, Jiaming ; Liu, Lixiao ; Zou, Zhiran ; Ding, Yingjie ; Li, Mingheng ; Liu, Di ; Wang, Min ; Sun, Xiaoyan ; Wang, Cui ; Bi, Shijia ; Shan, Hezhen ; Zhuo, Xiao</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c478t-e17aaa572d1ee6bf672bd8fc7b692eb1ceadb90415b3312afd2fc97e2f3262103</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Aging - genetics</topic><topic>Database Issue</topic><topic>Databases, Genetic</topic><topic>Epigenomics</topic><topic>Genomics</topic><topic>Humans</topic><topic>Pharmacogenetics</topic><topic>Transcriptome - genetics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liu, Guang-Hui</creatorcontrib><creatorcontrib>Bao, Yiming</creatorcontrib><creatorcontrib>Qu, Jing</creatorcontrib><creatorcontrib>Zhang, Weiqi</creatorcontrib><creatorcontrib>Zhang, Tao</creatorcontrib><creatorcontrib>Kang, Wang</creatorcontrib><creatorcontrib>Yang, Fei</creatorcontrib><creatorcontrib>Ji, Qianzhao</creatorcontrib><creatorcontrib>Jiang, Xiaoyu</creatorcontrib><creatorcontrib>Ma, Yingke</creatorcontrib><creatorcontrib>Ma, Shuai</creatorcontrib><creatorcontrib>Liu, Zunpeng</creatorcontrib><creatorcontrib>Chen, Siyu</creatorcontrib><creatorcontrib>Wang, Si</creatorcontrib><creatorcontrib>Sun, Shuhui</creatorcontrib><creatorcontrib>Geng, Lingling</creatorcontrib><creatorcontrib>Yan, Kaowen</creatorcontrib><creatorcontrib>Yan, Pengze</creatorcontrib><creatorcontrib>Fan, Yanling</creatorcontrib><creatorcontrib>Song, Moshi</creatorcontrib><creatorcontrib>Ren, Jie</creatorcontrib><creatorcontrib>Wang, Qiaoran</creatorcontrib><creatorcontrib>Yang, Shanshan</creatorcontrib><creatorcontrib>Yang, Yuanhan</creatorcontrib><creatorcontrib>Xiong, Muzhao</creatorcontrib><creatorcontrib>Liang, Chuqiang</creatorcontrib><creatorcontrib>Li, Lan-Zhu</creatorcontrib><creatorcontrib>Cao, Tianling</creatorcontrib><creatorcontrib>Hu, Jianli</creatorcontrib><creatorcontrib>Yang, Ping</creatorcontrib><creatorcontrib>Ping, Jiale</creatorcontrib><creatorcontrib>Hu, Huifang</creatorcontrib><creatorcontrib>Zheng, Yandong</creatorcontrib><creatorcontrib>Sun, Guoqiang</creatorcontrib><creatorcontrib>Li, Jiaming</creatorcontrib><creatorcontrib>Liu, Lixiao</creatorcontrib><creatorcontrib>Zou, Zhiran</creatorcontrib><creatorcontrib>Ding, Yingjie</creatorcontrib><creatorcontrib>Li, Mingheng</creatorcontrib><creatorcontrib>Liu, Di</creatorcontrib><creatorcontrib>Wang, Min</creatorcontrib><creatorcontrib>Sun, Xiaoyan</creatorcontrib><creatorcontrib>Wang, Cui</creatorcontrib><creatorcontrib>Bi, Shijia</creatorcontrib><creatorcontrib>Shan, Hezhen</creatorcontrib><creatorcontrib>Zhuo, Xiao</creatorcontrib><creatorcontrib>Aging Atlas Consortium</creatorcontrib><collection>Oxford Journals Open Access Collection</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Nucleic acids research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Liu, Guang-Hui</au><au>Bao, Yiming</au><au>Qu, Jing</au><au>Zhang, Weiqi</au><au>Zhang, Tao</au><au>Kang, Wang</au><au>Yang, Fei</au><au>Ji, Qianzhao</au><au>Jiang, Xiaoyu</au><au>Ma, Yingke</au><au>Ma, Shuai</au><au>Liu, Zunpeng</au><au>Chen, Siyu</au><au>Wang, Si</au><au>Sun, Shuhui</au><au>Geng, Lingling</au><au>Yan, Kaowen</au><au>Yan, Pengze</au><au>Fan, Yanling</au><au>Song, Moshi</au><au>Ren, Jie</au><au>Wang, Qiaoran</au><au>Yang, Shanshan</au><au>Yang, Yuanhan</au><au>Xiong, Muzhao</au><au>Liang, Chuqiang</au><au>Li, Lan-Zhu</au><au>Cao, Tianling</au><au>Hu, Jianli</au><au>Yang, Ping</au><au>Ping, Jiale</au><au>Hu, Huifang</au><au>Zheng, Yandong</au><au>Sun, Guoqiang</au><au>Li, Jiaming</au><au>Liu, Lixiao</au><au>Zou, Zhiran</au><au>Ding, Yingjie</au><au>Li, Mingheng</au><au>Liu, Di</au><au>Wang, Min</au><au>Sun, Xiaoyan</au><au>Wang, Cui</au><au>Bi, Shijia</au><au>Shan, Hezhen</au><au>Zhuo, Xiao</au><aucorp>Aging Atlas Consortium</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Aging Atlas: a multi-omics database for aging biology</atitle><jtitle>Nucleic acids research</jtitle><addtitle>Nucleic Acids Res</addtitle><date>2021-01-08</date><risdate>2021</risdate><volume>49</volume><issue>D1</issue><spage>D825</spage><epage>D830</epage><pages>D825-D830</pages><issn>0305-1048</issn><eissn>1362-4962</eissn><abstract>Abstract
Organismal aging is driven by interconnected molecular changes encompassing internal and extracellular factors. Combinational analysis of high-throughput ‘multi-omics’ datasets (gathering information from genomics, epigenomics, transcriptomics, proteomics, metabolomics and pharmacogenomics), at either populational or single-cell levels, can provide a multi-dimensional, integrated profile of the heterogeneous aging process with unprecedented throughput and detail. These new strategies allow for the exploration of the molecular profile and regulatory status of gene expression during aging, and in turn, facilitate the development of new aging interventions. With a continually growing volume of valuable aging-related data, it is necessary to establish an open and integrated database to support a wide spectrum of aging research. The Aging Atlas database aims to provide a wide range of life science researchers with valuable resources that allow access to a large-scale of gene expression and regulation datasets created by various high-throughput omics technologies. The current implementation includes five modules: transcriptomics (RNA-seq), single-cell transcriptomics (scRNA-seq), epigenomics (ChIP-seq), proteomics (protein–protein interaction), and pharmacogenomics (geroprotective compounds). Aging Atlas provides user-friendly functionalities to explore age-related changes in gene expression, as well as raw data download services. Aging Atlas is freely available at https://bigd.big.ac.cn/aging/index.</abstract><cop>England</cop><pub>Oxford University Press</pub><pmid>33119753</pmid><doi>10.1093/nar/gkaa894</doi><oa>free_for_read</oa></addata></record> |
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| subjects | Aging - genetics Database Issue Databases, Genetic Epigenomics Genomics Humans Pharmacogenetics Transcriptome - genetics |
| title | Aging Atlas: a multi-omics database for aging biology |
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