Ying Xu

Dr. Ying Xu


Research Focus & Metrics

Academic Career Length

23Years (2004-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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29 May 2012 in Nucleic Acids Research
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Journal Article
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YYYanbin Yin
Yanbin Yin
XMXizeng Mao
Xizeng Mao
JYJincai Yang
Jincai Yang
XCXin Chen
Xin Chen
FMFenglou Mao
Fenglou Mao
YXYing Xu
Ying Xu
Carbohydrate-active enzymes (CAZymes) are very important to the biotech industry, particularly the emerging biofuel industry because CAZymes are responsible for the synthesis, degradation and modification of all the carbohydrates on Earth. We have developed a web resource, dbCAN (http://csbl.bmb.uga.edu/dbCAN/annotate.php), to provide a capability for automated CAZyme signature domain-based annotation for any given protein data set (e.g. proteins from a newly sequenced genome) submitted to our server. To accomplish this, we have explicitly defined a signature domain for every CAZyme family, derived based on the CDD (conserved domain database) search and literature curation. We have also constructed a hidden Markov model to represent the signature domain of each CAZyme family. These CAZyme family-specific HMMs are our key contribution and the foundation for the automated CAZyme annotation.

6 November 2008 in Nucleic Acids Research
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Journal Article
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FMFenglou Mao
Fenglou Mao
PDPhuongan Dam
Phuongan Dam
JCJacky Chou
Jacky Chou
VOVictor Olman
Victor Olman
YXYing Xu
Ying Xu
We present a database DOOR (Database for prOkaryotic OpeRons) containing computationally predicted operons of all the sequenced prokaryotic genomes. All the operons in DOOR are predicted using our own prediction program, which was ranked to be the best among 14 operon prediction programs by a recent independent review. Currently, the DOOR database contains operons for 675 prokaryotic genomes, and supports a number of search capabilities to facilitate easy access and utilization of the information stored in it.

21 October 2010 in Nucleic Acids Research
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JCJuan Cui
Juan Cui
YCYunbo Chen
Yunbo Chen
WCWen-Chi Chou
Wen-Chi Chou
LSLiankun Sun
Liankun Sun
LCLi Chen
Li Chen
YXYing Xu
Ying Xu
This report describes an integrated study on identification of potential markers for gastric cancer in patients’ cancer tissues and sera based on: (i) genome-scale transcriptomic analyses of 80 paired gastric cancer/reference tissues and (ii) computational prediction of blood-secretory proteins supported by experimental validation. Our findings show that: (i) 715 and 150 genes exhibit significantly differential expressions in all cancers and early-stage cancers versus reference tissues, respectively; and a substantial percentage of the alteration is found to be influenced by age and/or by gender; (ii) 21 co-expressed gene clusters have been identified, some of which are specific to certain subtypes or stages of the cancer; (iii) the top-ranked gene signatures give better than 94% classification accuracy between cancer and the reference tissues, some of which are gender-specific; and (iv) 136 of the differentially expressed genes were predicted to have their proteins secreted into blood, 81 of which were detected experimentally in the sera of 13 validation samples and 29 found to have differential abundances in the sera of cancer patients versus controls. Overall, the novel information obtained in this study has led to identification of promising diagnostic markers for gastric cancer and can benefit further analyses of the key (early) abnormalities during its development.

7 November 2013 in Nucleic Acids Research
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Journal Article
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XMXizeng Mao
Xizeng Mao
QMQin Ma
Qin Ma
CZChuan Zhou
Chuan Zhou
XCXin Chen
Xin Chen
HZHanyuan Zhang
Hanyuan Zhang
YXYing Xu
Ying Xu
We have recently developed a new version of the DOOR operon database, DOOR 2.0, which is available online at http://csbl.bmb.uga.edu/DOOR/ and will be updated on a regular basis. DOOR 2.0 contains genome-scale operons for 2072 prokaryotes with complete genomes, three times the number of genomes covered in the previous version published in 2009. DOOR 2.0 has a number of new features, compared with its previous version, including (i) more than 250 000 transcription units, experimentally validated or computationally predicted based on RNA-seq data, providing a dynamic functional view of the underlying operons; (ii) an integrated operon-centric data resource that provides not only operons for each covered genome but also their functional and regulatory information such as their cis-regulatory binding sites for transcription initiation and termination, gene expression levels estimated based on RNA-seq data and conservation information across multiple genomes; (iii) a high-performance web service for online operon prediction on user-provided genomic sequences; (iv) an intuitive genome browser to support visualization of user-selected data; and (v) a keyword-based Google-like search engine for finding the needed information intuitively and rapidly in this database.

1 July 2006 in Nucleic Acids Research
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Journal Article
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Yu XueYu Xue
Yu Xue
FZFengfeng Zhou
Fengfeng Zhou
CFChuanhai Fu
Chuanhai Fu
YXYing Xu
Ying Xu
XYXuebiao Yao
Xuebiao Yao
Systematic dissection of the sumoylation proteome is emerging as an appealing but challenging research topic because of the significant roles sumoylation plays in cellular dynamics and plasticity. Although several proteome-scale analyzes have been performed to delineate potential sumoylatable proteins, the bona fide sumoylation sites still remain to be identified. Previously, we carried out a genome-wide analysis of the SUMO substrates in human nucleus using the putative motif ψ-K-X-E and evolutionary conservation. However, a highly specific predictor for in silico prediction of sumoylation sites in any individual organism is still urgently needed to guide experimental design. In this work, we present a computational system SUMOsp—SUMOylation Sites Prediction, based on a manually curated dataset, integrating the results of two methods, GPS and MotifX, which were originally designed for phosphorylation site prediction. SUMOsp offers at least as good prediction performance as the only available method, SUMOplot, on a very large test set. We expect that the prediction results of SUMOsp combined with experimental verifications will propel our understanding of sumoylation mechanisms to a new level. SUMOsp has been implemented on a freely accessible web server at: http://bioinformatics.lcd-ustc.org/sumosp/ .

31 July 2009 in BMC Plant Biology
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YYYanbin Yin
Yanbin Yin
JHJinling Huang
Jinling Huang
YXYing Xu
Ying Xu
Background: The cellulose synthase superfamily has been classified into nine cellulose synthase-like (Csl) families and one cellulose synthase (CesA) family. The Csl families have been proposed to be involved in the synthesis of the backbones of hemicelluloses of plant cell walls. With 17 plant and algal genomes fully sequenced, we sought to conduct a genome-wide and systematic investigation of this superfamily through in-depth phylogenetic analyses. Results: A single-copy gene is found in the six chlorophyte green algae, which is most closely related to the CslA and CslC families that are present in the seven land plants investigated in our analyses. Six proteins from poplar, grape and sorghum form a distinct family (CslJ), providing further support for the conclusions from two recent studies. CslB/E/G/H/J families have evolved significantly more rapidly than their widely distributed relatives, and tend to have intragenomic duplications, in particular in the grape genome. Conclusion: Our data suggest that the CslA and CslC families originated through an ancient gene duplication event in land plants. We speculate that the single-copy Csl gene in green algae may encode a mannan synthase. We confirm that the rest of the Csl families have a different evolutionary origin than CslA and CslC, and have proposed a model for the divergence order among them. Our study provides new insights about the evolution of this important gene family in plants.