Selected publications in 2017

HISP: A Hybrid Intelligent Approach for Identifying Directed Signaling Pathways.
Zhao XM, Li S.
Journal of Molecular Cell Biology (2017)

In this paper, we propose a novel hybrid intelligent method, namely HISP (Hybrid Intelligent approach for identifying directed Signaling Pathways), to determine both the topologies of signaling pathways and the direction of signaling flows within a pathway based on integer linear programming and genetic algorithm. By integrating the protein−protein interaction, gene expression, and gene knockout data, our HISP approach is able to determine the optimal topologies of signaling pathways in an accurate way.

Predicting new indications of compounds with a network pharmacology approach: Liuwei Dihuang Wan as a case study.
Wang YY, Bai H, Zhang RZ, Yan H, Ning K, Zhao XM.
Oncotarget (2017)

In this paper, we introduce a new network pharmacology approach, namely PINA, to predict potential novel indications of old drugs based on the molecular networks affected by drugs and associated with diseases.

A CPU/MIC Collaborated Parallel Framework for GROMACS on Tianhe-2 Supercomputer.
Gao NL, Zhang C, Zhang Z, Hu S, Lercher MJ, Zhao XM, Bork P, Liu Z, Chen WH.
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2017)

In this paper, we propose a CPU and Intel® Xeon Phi Many Integrated Core (MIC) collaborated parallel framework to accelerate GROMACS using the offload mode on a MIC coprocessor, with which the performance of GROMACS is improved significantly, especially with the utility of Tianhe-2 supercomputer. Furthermore, we optimize GROMACS so that it can run on both the CPU and MIC at the same time. In addition, we accelerate multi-node GROMACS so that it can be used in practice.

EmDL: Extracting miRNA-Drug Interactions from Literature.
Xie WB, Yan H, Zhao XM.
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2017)

In this paper, we present a novel text mining approach, named as EmDL (Extracting miRNA-Drug interactions from Literature), to extract the relationships of miRNAs affecting drug efficacy from literature.

PCID: A Novel Approach for Predicting Disease Comorbidity by Integrating Multi-scale Data.
He F, Zhu G, Wang YY, Zhao XM.
IEEE/ACM Transactions on Computational Biology and Bioinformatics (2017)

By investigating the factors underlying disease comorbidity, e.g., mutated genes and rewired protein-protein interactions (PPIs), we here present a novel algorithm to predict disease comorbidity by integrating multi-scale data ranging from genes to phenotypes.

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

Here, we present CSTEA (Cell State Transition Expression Atlas), a webserver that organizes, analyzes and visualizes the time-course gene expression data during cell differentiation, cellular reprogramming and trans-differentiation in human and mouse.

PhosD: inferring kinase-substrate interactions based on protein domains.
Qin GM, Li RY, Zhao XM.
Bioinformatics (2017)

In this paper, we propose a novel probabilistic model named as PhosD to predict kinase–substrate relationships based on protein domains with the assumption that kinase–substrate interactions are accomplished with kinase–domain interactions.

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

Here, we present GEAR (A database of Genomic Elements Associated with drug Resistance) that aims to provide comprehensive information about genomic elements (including genes, single-nucleotide polymorphisms and microRNAs) that are responsible for drug resistance.