中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
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CAS IR Grid
机构
上海营养与健康研究所 [3]
植物研究所 [2]
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OAI收割 [5]
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期刊论文 [5]
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2021 [1]
2019 [1]
2018 [1]
2017 [2]
学科主题
Biochemist... [5]
Cell Biolo... [2]
Chemistry,... [1]
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学科主题:Biochemistry & Molecular Biology
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Database Resources of the National Genomics Data Center, China National Center for Bioinformation in 2021
期刊论文
OAI收割
NUCLEIC ACIDS RESEARCH, 2021, 卷号: 49, 期号: D1, 页码: D18-D28
作者:
Xue, Yongbiao
;
Bao, Yiming
;
Zhang, Zhang
;
Zhao, Wenming
;
Xiao, Jingfa
  |  
收藏
  |  
浏览/下载:23/0
  |  
提交时间:2023/02/24
PTEN alpha and PTEN beta promote carcinogenesis through WDR5 and H3K4 trimethylation
期刊论文
OAI收割
NATURE CELL BIOLOGY, 2019, 卷号: 21, 期号: 11, 页码: 1436+
作者:
Shen, Shao-Ming
;
Zhang, Cheng
;
Ge, Meng-Kai
;
Xia, Li
;
He, Ping
  |  
收藏
  |  
浏览/下载:21/0
  |  
提交时间:2020/12/09
Alu
back-splicing
circRNA
complementary sequence
evolution
SINE
species-specific
Next Generation Sequencing-Based Molecular Marker Development: A Case Study in Betula Alnoides
期刊论文
OAI收割
MOLECULES, 2018, 卷号: 23, 期号: 11
作者:
Tan, Jing
;
Guo, Jun-Jie
;
Yin, Ming-Yu
;
Wang, Huan
;
Dong, Wen-Pan
  |  
收藏
  |  
浏览/下载:8/0
  |  
提交时间:2022/02/25
Betula alnoides
next generation sequencing (NGS)
simple sequence repeat (SSR)
polymorphism
transferability
The lncRNA H19 mediates breast cancer cell plasticity during EMT and MET plasticity by differentially sponging miR-200b/c and let-7b
期刊论文
OAI收割
SCIENCE SIGNALING, 2017, 卷号: 10, 期号: 483, 页码: -
作者:
Zhou, Wu
;
Xu, Jun
;
Cao, Ming-Guo
;
Fang, Zheng-Yu
;
Ye, Xiao-lei
  |  
收藏
  |  
浏览/下载:7/0
  |  
提交时间:2020/12/09
absorption spectrum
chemical bond
porphyrin
side chain
synthetase
The lncRNA H19 mediates breast cancer cell plasticity during EMT and MET plasticity by differentially sponging miR-200b/c and let-7b
期刊论文
OAI收割
SCIENCE SIGNALING, 2017, 卷号: 10, 期号: 483, 页码: -
作者:
Zhou, Wu
;
Xu, Jun
;
Cao, Ming-Guo
;
Fang, Zheng-Yu
;
Ye, Xiao-lei
  |  
收藏
  |  
浏览/下载:4/0
  |  
提交时间:2020/12/09
tissue-specific expressed genes
transcriptome
tissue classification
support vector machine
feature selection