数据库和在线服务器

CSTEA
Reference: Zhu G, Yang H, Chen X, Wu J, Zhang Y, Zhao XM. CSTEA: a webserver for the Cell State Transition Expression Atlas. Nucleic Acids Research, 2017;45 (Web Server issue).

CSTEA is a web server that provides both visualization and analysis of valuable time-series gene expression data on cell state transitions.CSTEA focuses on revealing important genes, key time points, and the mechanisms during the dynamic transition processes.

mTD
Reference: Chen X, Xie WB, Xiao PP, Zhao XM, Yan H. mTD: A database of microRNAs affecting therapeutic effects of drugs. Journal of Genetics and Genomics, 2017 May 20;44(5):269-271

The database of microRNAs affecting Therapeutic effects of Drugs (mTD) aims to provide comprehensive information about the effects of miRNAs on drug therapies.

GEAR
Reference: Wang YY, Chen WH, Xiao PP, Xie WB, Luo Q, Bork P, Zhao XM. GEAR: A database of Genomic Elements Associated with drug Resistance. Scientific Reports, 2017;7:44085

The database of Genomic Elements Associated with drug Resistance (GEAR) aims to provide comprehensive information about genomic patterns associated with resistance to human drugs, including gene or microRNA mutations responsible for drug resistance.

PPIM
Reference: Zhu G, Wu A, Xu XJ, Xiao PP, Lu L, Zhao XM, et al. PPIM: A Protein-Protein Interaction Database for Maize. Plant Physiology, 2016;170(2):618-26.

Maize (Zea mays) is the plant that has the highest world-wide production among all grain crops, and maize seeds are the most important crop materials that provide resources for food, feed, biofuel, and raw material for processing. The PPIM (protein-protein interaction database for Maize) database is a free and comprehensive knowledgebase for academic use in Zea mays community.

eFG
Reference: Liu X, Zhang X, Tang WH, Chen L, Zhao XM. eFG: an electronic resource for Fusarium graminearum. Database (Oxford), 2013;2013:bat042.

eFG (ebook for Fusarium Graminearum) is an information query system for the pathogenic fungus Fusarium graminearum. It contains many information for F. graminearum that the sequences, proteins, annotations, protein-protein interaction, pathogenic genes, sub-location of proteins, transcription factors and ortholog information with other fungi.

NARROMI
Reference: Zhang X, Liu K, Liu ZP, Duval B, Richer JM, Zhao XM, Hao JK, Chen L. NARROMI: a noise and redundancy reduction technique improves accuracy of gene regulatory network inference. Bioinformatics, 2013;29(1):106-13.

NARROMI is software for improving accuracy of GRNs inference. It is a novel method combining ordinary differential equation based recursive optimization (RO) and information-theory based mutual information (MI). In this algorithm, both noisy regulations with low pair-wise correlations and redundant regulations from indirect regulators are removed by measuring MI and implementing RO, respectively. In particular, it is the first one to handle the redundancy problem in GRNs for model based network inference methods.

PCA-CMI
Reference: Zhang X, Zhao XM, He K, Lu L, Cao Y, Liu J, Hao JK, Liu ZP, Chen L. Inferring gene regulatory networks from gene expression data by path consistency algorithm based on conditional mutual information, Bioinformatics, 2012;28(1):98-104.

PCA-CMI is a MATLAB program for inferring gene regulatory networks from gene expression data. It is a novel method based on path consistency algorithm and conditional mutual information, which consider the non-linear dependence and topological structure of GRNs. In this algorithm, the (conditional) dependence between a pair of genes is represented by the CMI between them. With the general hypothesis of Gaussian distribution underlying gene expression data, CMI between a pair of genes is computed by a concise formula involving the covariance matrices of the related gene expression profiles.

DIPOS
Reference: Sapkota A, Liu X, Zhao XM, Cao Y, Liu J, Liu ZP, Chen L. DIPOS: database of interacting proteins in Oryza sativa, Molecular BioSystems, 2011;7(9):2615-21.

DIPOS provides a complete rice protein interaction database to the plant biologist to better understand the life of plants, especially for rice.

FPPI
Reference: Zhao XM, Zhang XW, Tang WH, Chen L. FPPI: Fusarium graminearum protein-protein interaction database, Journal of Proteome Research, 2009;8(10):4714-21.

FPPI is a database about protein-protein interactions for Fussarium graminearum, which contain 223,116 interactions among 7,406 proteins and 27,102 interactions among 3,745 proteins in the core PPI set. Furthermore, this database contains various different functional information for F. graminearum genes.

CMI2NI
Reference: Zhang X, Zhao XM, He K, Lu L, Cao Y, Liu J, Hao JK, Liu ZP, Chen L. Inferring gene regulatory networks from gene expression data by path consistency algorithm based on conditional mutual information, Bioinformatics, 2012;28(1):98-104.

CMI2NI is a software for inferring gene regulatory networks from gene expression data. It is a novel method using a new proposed concept of Conditional Mutual Inclusive Information (CMI2) which can accurately measure direct dependences between genes. Given the small size samples of gene expression data, CMI2NI can not only infer the correct topology of the regulation networks but also accurately quantify the dependence or regulation strength between genes. CMI2NI provides a useful tool to infer gene regulatory networks.