A joint-L2,1-norm-constraint-based semi-supervised feature extraction for RNA-Seq data analysis-Reference-Cited by-同舟云学术

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A joint-L2,1-norm-constraint-based semi-supervised feature extraction for RNA-Seq data analysis

Published:2017-03 Issue: Volume:228 Page:263-269
ISSN:0925-2312
Container-title:Neurocomputing
language:en
Short-container-title:Neurocomputing

Author:

Liu Jin-Xing,Wang Dong,Gao Ying-Lian,Zheng Chun-Hou,Shang Jun-Liang,Liu Feng,Xu Yong

Funder

National Natural Science Foundation of China

Award Foundation Project of Excellent Young Scientists in Shandong Province

Shenzhen Municipal Science and Technology Innovation Council

Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference42 articles.

1. Oases: robust de novo RNA-seq assembly across the dynamic range of expression levels;Schulz;Bioinformatics,2012

2. Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks;Trapnell;Nat. Protoc.,2012

3. ReCount: a multi-experiment resource of analysis-ready RNA-seq gene count datasets;Frazee;BMC Bioinform.,2011

4. Mapping and quantifying mammalian transcriptomes by RNA-Seq;Mortazavi;Nat. Methods,2008

5. Prediction of protein-protein interactions from amino acid sequences using a novel multi-scale continuous and discontinuous feature set;You;BMC Bioinform.,2014

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