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Database Commons - LincSNP

LincSNP

Citations: 24

z-index 5.76

Short name LincSNP
Full name
Description LincSNP provides a comprehensive data source for integrating current lincRNA and GWAS SNP annotations.
URL http://bioinfo.hrbmu.edu.cn/LincSNP/
Year founded 2014
Last update & version 2016-05-30    v2.0
Availability Free to all users
University/Institution hosted Harbin Medical University
Address Harbin 150081, China.
City Harbin
Province/State Heilongjiang
Country/Region China
Contact name Xia Li
Contact email lixia@hrbmu.edu.cn
Data type(s)
Major organism(s)
Keyword(s)
  • lncRNA
  • SNP-linRNA-disease
Publication(s)
  • LincSNP 2.0: an updated database for linking disease-associated SNPs to human long non-coding RNAs and their TFBSs. [PMID: 27924020]

    Shangwei Ning, Ming Yue, Peng Wang, Yue Liu, Hui Zhi, Yan Zhang, Jizhou Zhang, Yue Gao, Maoni Guo, Dianshuang Zhou, Xin Li, Xia Li
    Nucleic acids research 2017:45(D1)
    0 Citations (Google Scholar as of 2017-02-08)

    Abstract: We describe LincSNP 2.0 (http://bioinfo.hrbmu.edu.cn/LincSNP), an updated database that is used specifically to store and annotate disease-associated single nucleotide polymorphisms (SNPs) in human long non-coding RNAs (lncRNAs) and their transcription factor binding sites (TFBSs). In LincSNP 2.0, we have updated the database with more data and several new features, including (i) expanding disease-associated SNPs in human lncRNAs; (ii) identifying disease-associated SNPs in lncRNA TFBSs; (iii) updating LD-SNPs from the 1000 Genomes Project; and (iv) collecting more experimentally supported SNP-lncRNA-disease associations. Furthermore, we developed three flexible online tools to retrieve and analyze the data. Linc-Mart is a convenient way for users to customize their own data. Linc-Browse is a tool for all data visualization. Linc-Score predicts the associations between lncRNA and disease. In addition, we provided users a newly designed, user-friendly interface to search and download all the data in LincSNP 2.0 and we also provided an interface to submit novel data into the database. LincSNP 2.0 is a continually updated database and will serve as an important resource for investigating the functions and mechanisms of lncRNAs in human diseases. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  • LincSNP: a database of linking disease-associated SNPs to human large intergenic non-coding RNAs. [PMID: 24885522]

    Shangwei Ning, Zuxianglan Zhao, Jingrun Ye, Peng Wang, Hui Zhi, Ronghong Li, Tingting Wang, Xia Li
    BMC bioinformatics 2014:15
    24 Citations (Google Scholar as of 2017-02-08)

    Abstract: Genome-wide association studies (GWAS) have successfully identified a large number of single nucleotide polymorphisms (SNPs) that are associated with a wide range of human diseases. However, many of these disease-associated SNPs are located in non-coding regions and have remained largely unexplained. Recent findings indicate that disease-associated SNPs in human large intergenic non-coding RNA (lincRNA) may lead to susceptibility to diseases through their effects on lincRNA expression. There is, therefore, a need to specifically record these SNPs and annotate them as potential candidates for disease. We have built LincSNP, an integrated database, to identify and annotate disease-associated SNPs in human lincRNAs. The current release of LincSNP contains approximately 140,000 disease-associated SNPs (or linkage disequilibrium SNPs), which can be mapped to around 5,000 human lincRNAs, together with their comprehensive functional annotations. The database also contains annotated, experimentally supported SNP-lincRNA-disease associations and disease-associated lincRNAs. It provides flexible search options for data extraction and searches can be performed by disease/phenotype name, SNP ID, lincRNA name and chromosome region. In addition, we provide users with a link to download all the data from LincSNP and have developed a web interface for the submission of novel identified SNP-lincRNA-disease associations. The LincSNP database aims to integrate disease-associated SNPs and human lincRNAs, which will be an important resource for the investigation of the functions and mechanisms of lincRNAs in human disease. The database is available at http://bioinfo.hrbmu.edu.cn/LincSNP.

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Accessibility

Rate of accessibility:
HTTP status codeDate requested
200 OK2018-11-20
200 OK2018-11-16
200 OK2018-11-13
200 OK2018-11-09
200 OK2018-11-06
200 OK2018-11-02
200 OK2018-10-30
200 OK2018-10-26
200 OK2018-10-23
200 OK2018-10-19
200 OK2018-10-16
200 OK2018-10-12
200 OK2018-10-09
200 OK2018-10-05
200 OK2018-10-02
200 OK2018-09-28
200 OK2018-09-25
200 OK2018-09-21
200 OK2018-09-18
200 OK2018-09-14
200 OK2018-09-11
200 OK2018-09-07
200 OK2018-09-04
200 OK2018-08-31
200 OK2018-08-28
200 OK2018-08-24
200 OK2018-08-21
200 OK2018-08-17
200 OK2018-08-14
200 OK2018-08-10
200 OK2018-08-07
200 OK2018-08-03
200 OK2018-07-31
200 OK2018-07-27
200 OK2018-07-24
200 OK2018-07-20
200 OK2018-07-17
200 OK2018-07-13
200 OK2018-07-10
200 OK2018-07-06
200 OK2018-07-03
200 OK2018-06-29
-1 Failed2018-06-26
200 OK2018-06-22
200 OK2018-06-19
200 OK2018-06-15
200 OK2018-06-12
-1 Failed2018-06-08
-1 Failed2018-06-05
-1 Failed2018-06-01
200 OK2018-05-29
200 OK2018-05-25
200 OK2018-05-22
200 OK2018-05-18
200 OK2018-05-15
200 OK2018-05-11
200 OK2018-05-08
200 OK2018-05-04
200 OK2018-05-01
200 OK2018-04-27
200 OK2018-04-24
200 OK2018-04-20
200 OK2018-04-17
200 OK2018-04-13
200 OK2018-04-10
200 OK2018-04-06
200 OK2018-04-03
200 OK2018-02-27
200 OK2018-02-23
200 OK2018-02-20
200 OK2018-02-16
200 OK2018-02-13
200 OK2018-02-09
200 OK2018-02-06
200 OK2018-02-02
200 OK2018-01-30
200 OK2018-01-26
200 OK2018-01-23
200 OK2018-01-19
200 OK2018-01-16
200 OK2018-01-12
200 OK2018-01-09
200 OK2018-01-05
200 OK2018-01-02
200 OK2017-12-29
200 OK2017-12-26
200 OK2017-12-22
200 OK2017-12-19
200 OK2017-12-15
200 OK2017-12-12
200 OK2017-12-08
200 OK2017-12-05
200 OK2017-12-01
200 OK2017-11-28
200 OK2017-11-24
200 OK2017-11-21
200 OK2017-11-17
200 OK2017-11-14
200 OK2017-11-10
200 OK2017-11-07
200 OK2017-11-03
200 OK2017-10-31
200 OK2017-10-27
200 OK2017-10-24
200 OK2017-10-20
200 OK2017-10-17
-1 Failed2017-10-13
-1 Failed2017-10-10
200 OK2017-10-06
200 OK2017-10-03
200 OK2017-09-29
200 OK2017-09-26
200 OK2017-09-22
200 OK2017-09-19
200 OK2017-09-15
200 OK2017-09-12
200 OK2017-09-08
200 OK2017-09-05
200 OK2017-09-01
200 OK2017-08-29
200 OK2017-08-25
200 OK2017-08-22
200 OK2017-08-18
-1 Failed2017-08-15
-1 Failed2017-08-11
-1 Failed2017-08-08
-1 Failed2017-08-04
-1 Failed2017-08-01
-1 Failed2017-07-28
200 OK2017-07-25
200 OK2017-07-21
200 OK2017-07-18
200 OK2017-07-14
200 OK2017-07-04
200 OK2017-06-30
200 OK2017-06-27
200 OK2017-06-23
200 OK2017-06-20
200 OK2017-06-16
200 OK2017-06-13
200 OK2017-06-09
200 OK2017-06-06
200 OK2017-06-02
200 OK2017-05-30
200 OK2017-05-26
200 OK2017-05-23
200 OK2017-05-19
200 OK2017-05-16
200 OK2017-05-12
200 OK2017-05-09
200 OK2017-05-05
200 OK2017-05-02
200 OK2017-04-28
200 OK2017-04-25
200 OK2017-04-21
200 OK2017-04-18
200 OK2017-04-14
200 OK2017-04-11
200 OK2017-04-07
200 OK2017-04-04
200 OK2017-03-31
200 OK2017-03-28
200 OK2017-03-24
200 OK2017-03-21
200 OK2017-03-17
200 OK2017-03-14
200 OK2017-03-10
200 OK2017-03-07
200 OK2017-03-03
200 OK2017-02-28
200 OK2017-02-24
200 OK2017-02-21
200 OK2017-02-17
200 OK2017-02-14
200 OK2017-02-10
200 OK2017-02-07
200 OK2017-02-03
200 OK2017-01-31
200 OK2017-01-27
200 OK2017-01-24
200 OK2017-01-20
200 OK2017-01-17
200 OK2017-01-13
200 OK2017-01-10
200 OK2017-01-06
200 OK2017-01-03
200 OK2016-12-30
200 OK2016-12-27
200 OK2016-12-23
200 OK2016-12-20
200 OK2016-12-16
200 OK2016-12-13
200 OK2016-12-09
200 OK2016-12-06
200 OK2016-12-02
200 OK2016-11-29
200 OK2016-11-25
200 OK2016-11-22
200 OK2016-11-18
200 OK2016-11-15
200 OK2016-11-11
200 OK2016-11-08
200 OK2016-11-04
200 OK2016-11-01
200 OK2016-10-28
200 OK2016-10-25
200 OK2016-10-21
200 OK2016-10-18
200 OK2016-10-14
200 OK2016-10-11
200 OK2016-10-07
200 OK2016-10-04
200 OK2016-09-30
200 OK2016-09-27
200 OK2016-09-23
200 OK2016-09-20
200 OK2016-09-16
200 OK2016-09-13
200 OK2016-09-09
200 OK2016-09-06
200 OK2016-09-02
200 OK2016-08-30
200 OK2016-08-26
200 OK2016-08-23
200 OK2016-08-19
200 OK2016-08-16
200 OK2016-08-12
200 OK2016-08-09
200 OK2016-08-05
200 OK2016-08-02
200 OK2016-07-29
200 OK2016-07-26
200 OK2016-07-22
200 OK2016-07-19
200 OK2016-07-15
200 OK2016-07-12
200 OK2016-07-08
200 OK2016-07-05
200 OK2016-07-01
200 OK2016-06-28
200 OK2016-06-24
200 OK2016-06-21
200 OK2016-06-17
200 OK2016-06-14
200 OK2016-06-10
200 OK2016-06-07
200 OK2016-06-03
200 OK2016-05-31
200 OK2016-05-27
200 OK2016-05-24
200 OK2016-05-20
200 OK2016-05-17
200 OK2016-05-13
200 OK2016-05-10
200 OK2016-05-06
200 OK2016-05-03
200 OK2016-04-29
200 OK2016-04-26
200 OK2016-04-22
200 OK2016-04-19
200 OK2016-04-15
200 OK2016-04-12
200 OK2016-04-08
200 OK2016-04-05
200 OK2016-04-01
200 OK2016-03-29
200 OK2016-03-28
200 OK2016-03-25
200 OK2016-03-23
200 OK2016-03-21
200 OK2016-03-18
200 OK2016-03-16
200 OK2016-03-14
200 OK2016-03-11
200 OK2016-03-09
200 OK2016-03-07
200 OK2016-03-04
200 OK2016-03-02
200 OK2016-02-29
200 OK2016-02-26
200 OK2016-02-24
200 OK2016-02-22
200 OK2016-02-19
200 OK2016-02-17
200 OK2016-02-15
200 OK2016-02-14
200 OK2016-02-12
200 OK2016-02-10
200 OK2016-02-08
200 OK2016-02-07
200 OK2016-02-05
200 OK2016-02-03
200 OK2016-02-01
200 OK2016-01-31
200 OK2016-01-29
200 OK2016-01-27
200 OK2016-01-25
200 OK2016-01-24
200 OK2016-01-22
200 OK2016-01-20
200 OK2016-01-18
200 OK2016-01-17
200 OK2016-01-15
200 OK2016-01-13
200 OK2016-01-11
200 OK2016-01-10
200 OK2016-01-08
200 OK2016-01-06
200 OK2016-01-04

Tags

DNA RNA
Homo sapiens
lncRNA SNP-linRNA-disease

Record metadata

  • Created on: 2015-06-30
  • Curated by:
    • Lina Ma [2017-06-21]
    • Shixiang Sun [2017-02-08]
    • Zhang Zhang [2016-04-26]
    • Chunlei Yu [2016-04-01]
    • Chunlei Yu [2015-11-20]
Stats