Selected publications in 2010

Global Gene Profiling of Laser-Captured Pollen Mother Cells Indicates Molecular Pathways and Gene Subfamilies Involved in Rice Male Meiosis.
Tang X, Zhang ZY, Zhang WJ, Zhao XM, Li X, Zhang D, Liu QQ, Tang WH.
Plant Physiology (2010)

We used laser-capture microdissection of rice (subsp. japonica) stamens to isolate PMCs and their transcripts, followed by transcriptome analysis using microarray hybridization. Using two-color probe hybridization with Agilent 60-mer oligomicroarrays, PMC transcripts were compared with transcripts from two tissues, tricellular pollen (TCP), which comprises three nondividing cells, and seedling, which contains many mitotic dividing cells.

A network approach to predict pathogenic genes for Fusarium graminearum.
Liu X, Tang WH, Zhao XM, Chen L.
PLoS ONE (2010)

In this paper, a novel systems biology approach is presented to predict pathogenic genes of F. graminearum based on molecular interaction network and gene expression data.

APIS: accurate prediction of hot spots in protein interfaces by combining protrusion index with solvent accessibility.
Xia JF, Zhao XM, Song J, Huang DS.
BMC Bioinformatics (2010)

In this work, we introduce an efficient approach that uses support vector machine (SVM) to predict hot spot residues in protein interfaces.

A Systems biology approach to identify effective cocktail drugs.
Wu Z, Zhao XM, Chen L.
BMC Systems Biology (2010)

In this paper, we presented a novel network-based systems biology approach to identify effective drug combinations by exploiting high throughput data.

FGsub: Fusarium graminearum protein subcellular localization prediction from primary structures.
Sun C, Zhao XM, Tang W, Chen L.
BMC Systems Biology (2010)

In this paper, we developed a novel predictor, namely FGsub, to predict F. graminearum protein subcellular localizations from the primary structures.

Analysis of Gene Expression Data Using RPEM Algorithm in Normal Mixture Model with Dynamic Adjustment of Learning Rate.
Zhao XM, Cheung YM, Huang DS.
International Journal of Pattern Recognition and Artificial Intelligence (2010)

In this paper, we therefore apply a one-step approach, namely Rival Penalized Expectation-Maximization (RPEM) algorithm, to analyze the gene expression data.

A discriminative approach to identifying domain-domain interactions from protein-protein interactions.
Zhao XM, Chen L, Aihara K.
Proteins (2010)

In this article, we propose a novel discriminative approach for predicting DDIs based on both protein–protein interactions (PPIs) and the derived information of non-PPIs.