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Hua Yu 0004

dblp:02/2407-4 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2019
0000-0001-6691-1139ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 4 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › gene expression analysis › gene co-expression analysis
co-expression module detection
0.412019
Systematic discovery of novel and valuable plant gene modules by large-scale RNA-seq samples · Bioinform. 2019
Bioinformatics and computational biology › network bioinformatics › biological network analysis
gene co-expression network analysis
0.412019
Systematic discovery of novel and valuable plant gene modules by large-scale RNA-seq samples · Bioinform. 2019
Bioinformatics and computational biology › gene expression analysis › gene co-expression analysis
gene module discovery
0.412019
Systematic discovery of novel and valuable plant gene modules by large-scale RNA-seq samples · Bioinform. 2019
Bioinformatics and computational biology › genomics
plant genomics
0.412019
Systematic discovery of novel and valuable plant gene modules by large-scale RNA-seq samples · Bioinform. 2019

Methods — techniques the papers use, named apart from their topics

module subdivision · 0.4gene co-expression network construction · 0.4
YearPublicationVenuePosition
2019 Systematic discovery of novel and valuable plant gene modules by large-scale RNA-seq samples
abstract
Motivation: The complex cellular networks underlying phenotypes are formed by the interacting gene modules. Building and analyzing genome-wide and high-quality Gene Co-expression Networks (GCNs) is useful for uncovering these modules and understanding the phenotypes of an organism. Results: Using large-scale RNA-seq samples, we constructed high coverage and confident GCNs in two monocot species rice and maize, and two eudicot species Arabidopsis and soybean, and subdivided them into co-expressed gene modules. Taking rice as an example, we discovered many interesting and valuable modules, for instance, pollen-specific modules and starch biosynthesis module. We explored the regulatory mechanism of modules and revealed synergistic effects of gene expression regulation. In addition, we discovered that the modules conserved among plants participated in basic biological processes, whereas the species-specific modules were involved in spatiotemporal-specific processes linking genotypes to phenotypes. Our study suggests gene regulatory relationships and modules relating to cellular activities and agronomic traits in several model and crop plants, and thus providing a valuable data source for plant genetics research and breeding. Availability and implementation: The analyzed gene expression data, reconstructed GCNs, modules and detailed annotations can be freely downloaded from ftp://47.94.193.106/pub. Supplementary information: Supplementary data are available at Bioinformatics online.
Hua Yu 0004, Bingke Jiao, Chengzhi Liang
Bioinform.1