A data mining paradigm for identifying key factors in biological processes using gene expression data-Reference-Cited by-同舟云学术

A data mining paradigm for identifying key factors in biological processes using gene expression data

Published:2018-06-13 Issue:1 Volume:8 Page:
ISSN:2045-2322
Container-title:Scientific Reports
language:en
Short-container-title:Sci Rep

Author:

Li Jin,Zheng Le,Uchiyama Akihiko,Bin Lianghua,Mauro Theodora M.,Elias Peter M.,Pawelczyk Tadeusz^ORCID,Sakowicz-Burkiewicz Monika,Trzeciak Magdalena,Leung Donald Y. M.,Morasso Maria I.,Yu Peng

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

Link

http://www.nature.com/articles/s41598-018-27258-8.pdf

Reference34 articles.

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4. Guo, Z. et al. RNASeqMetaDB: a database and web server for navigating metadata of publicly available mouse RNA-Seq datasets. Bioinformatics 31, 4038–4040, https://doi.org/10.1093/bioinformatics/btv503 (2015).

5. Li, J. et al. SFMetaDB: a comprehensive annotation of mouse RNA splicing factor RNA-Seq datasets. Database 2017, bax071–bax071, https://doi.org/10.1093/database/bax071 (2017).

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