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Controllability and Its Applications to Biological Networks

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Journal of Computer Science & Technology 2019年第1期34卷 16-34页

作者： Lin wu Min Li Jian-Xin Wang fang-xiang wu Division of Biomedical Engineering University of SaskatchewanSaskatoonSK STN 5A9Canada School of Information Science and Engineering Central South UniversityChangsha 410083China Department of Mechanical Engineering University of SaskatchewanSaskatoonSK STN 5A9Canada

Biological elements usually exert their functions through interactions with others to form various types of biological *** ability of controlling the dynamics of biological networks is of enormous benefits to pharmaceutical and medical industry as well as scientific *** there are many mathematical methods for steering dynamic systems towards desired states,the methods are usually not feasible for applying to complex biological *** difficulties come from the lack of accurate model that can capture the dynamics of interactions between biological elements and the fact that many mathematical methods are computationally intractable for large-scale ***,a concept in control theory --controllability,has been applied to investigate the dynamics of complex *** this article, recent advances on the controllability of complex networks and applications to biological networks are *** dynamic models is the prior concern for analyzing dynamics of biological ***,we introduce a widely used dynamic model for investigating controllability of complex *** recent studies of theorems and algorithms for having complex biological networks controllable in general or specific application scenarios are ***,applications to real biological networks manifest that investigating the controllability of biological networks can shed lights on many critical physiological or medical problems,such as revealing biological mechanisms and identifying drug targets,from a systematic perspective.

关键词： biological network network controllability steering node

A Novel Method of Gene Regulatory Network Structure Inference from Gene Knock-Out Expression Data

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Tsinghua Science and Technology 2019年第4期24卷 446-454页

作者： xiang Chen Min Li Ruiqing Zheng Siyu Zhao Jianxin Wang fang-xiang wu Yaohang Li the School of Computer Science and Engineering Central South University the Department of Mechanical Engineering and Division of Biomedical Engineering University of Saskatchewan the Department of Computer Science Old Dominion University

Inferring Gene Regulatory Networks(GRNs) structure from gene expression data has been a challenging problem in systems biology. It is critical to identify complicated regulatory relationships among genes for understanding regulatory mechanisms in cells. Various methods based on information theory have been developed to infer GRNs. However, these methods introduce many redundant regulatory relationships in the network inference process due to external noise in the original data, topology sparseness in the network structure, and non-linear dependency among genes. Especially as the network size increases, the performance of these methods decreases dramatically. In this paper, a novel network structure inference method named Loc-PCA-CMI is proposed that first identifies local overlapped gene clusters, and then infers the local network structure for each cluster by a Path Consistency Algorithm based on Conditional Mutual Information(PCA-CMI). The final structure of the GRN is denoted as dependence among genes by an ensemble of the obtained local network structures. Loc-PCA-CMI was evaluated on DREAM3 knock-out datasets, and its performance was compared to other information theorybased network inference methods including ARACNE, MRNET, PCA-CMI, and PCA-PMI. Experimental results demonstrate our novel method Loc-PCA-CMI outperforms the other four methods in DREAM3 datasets especially in size 50 and 100 networks.

关键词： gene regulatory networks network inference path consistency algorithm

A Data-Driven Clustering Recommendation Method for Single-Cell RNA-Sequencing Data

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Tsinghua Science and Technology 2021年第5期26卷 772-789页

作者： Yu Tian Ruiqing Zheng Zhenlan Liang Suning Li fang-xiang wu Min Li the Hunan Provincial Key Lab on Bioinformatics School of Computer Science and EngineeringCentral South UniversityHunan 410083China the Division of Biomedical Engineering and Department of Mechanical Engineering University of SaskatchewanSKS7N5A9Canada

Recently,the emergence of single-cell RNA-sequencing(scRNA-seq)technology makes it possible to solve biological problems at the single-cell *** of the critical steps in cellular heterogeneity analysis is the cell type *** scRNA-seq clustering methods have been proposed to partition cells into *** all the methods,hierarchical clustering and spectral clustering are the most popular approaches in the downstream clustering analysis with different preprocessing strategies such as similarity learning,dropout imputation,and dimensionality *** this study,we carry out a comprehensive analysis by combining different strategies with these two categories of clustering methods on scRNA-seq datasets under different biological *** analysis results show that the methods with spectral clustering tend to perform better on datasets with continuous shapes in two-dimension,while those with hierarchical clustering achieve better results on datasets with obvious boundaries between clusters in *** by this finding,a new strategy,called QRS,is developed to quantitatively evaluate the latent representative shape of a dataset to distinguish whether it has clear boundaries or ***,a data-driven clustering recommendation method,called DDCR,is proposed to recommend hierarchical clustering or spectral clustering for scRNA-seq *** perform DDCR on two typical single cell clustering methods,SC3 and RAFSIL,and the results show that DDCR recommends a more suitable downstream clustering method for different scRNA-seq datasets and obtains more robust and accurate results.

关键词： single-cel RNA-sequencing(sc RNA-seq) cel ular heterogeneity cel type identification data latent shape clustering

NetEPD: A Network-Based Essential Protein Discovery Platform

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Tsinghua Science and Technology 2020年第4期25卷 542-552页

作者： Jiashuai Zhang Wenkai Li Min Zeng xiangmao Meng Lukasz Kurgan fang-xiang wu Min Li the School of Computer Science and Engineering Central South UniversityChangsha 410083China the Department of Computer Science Virginia Common-wealth UniversityRichmondVA 23284-2512USA the Division of Biomedical Engineering and Department of Mechanical Engineering University of SaskatchewanSaskatoonS7N 5A9Canada

Proteins drive virtually all cellular-level *** proteins that are critical to cell proliferation and survival are defined as *** essential proteins are implicated in key metabolic and regulatory networks,and are important in the context of rational drug design *** computational identification of the essential proteins benefits from the proliferation of publicly available protein interaction *** have developed several algorithms that use these interaction datasets to predict essential ***,a comprehensive web platform that facilitates the analysis and prediction of essential proteins is *** this study,we design,implement,and release Net EPD:a network-based essential protein discovery *** resource integrates data on Protein–Protein Interaction(PPI)networks,gene expression,subcellular localization,and a native set of essential *** also computes a variety of node centrality measures,evaluates the predictions of essential proteins,and visualizes PPI *** comprehensive platform functions by implementing four activities,which include the collection of datasets,computation of centrality measures,evaluation,and *** results produced by Net EPD are visualized on its website,and sent to a user-provided email,and they are available to download in a parsable *** platform is freely available at http://***/netepd.

关键词： essential proteins centrality data integration evaluation visualization

CircR2Disease v2.0:An Updated Web Server for Experimentally Validated circRNA–disease Associations and Its Application

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Genomics, Proteomics & Bioinformatics 2022年第3期20卷 435-445页

作者： Chunyan Fan Xiujuan Lei Jiaojiao Tie Yuchen Zhang fang-xiang wu Yi Pan School of Computer Science Shaanxi Normal UniversityXi’an 710119China Division of Biomedical Engineering University of SaskatchewanSaskatoonSK S7N 5A9Canada Department of Computer Science Georgia State UniversityAtlantaGA 30302USA

With accumulating dysregulated circular RNAs(circRNAs)in pathological processes,the regulatory functions of circRNAs,especially circRNAs as microRNA(miRNA)sponges and their interactions with RNA-binding proteins(RBPs),have been widely ***,the collected information on experimentally validated circRNA-disease associations is only ***,an updated CircR2Disease database providing a comprehensive resource and web tool to clarify the relationships between circRNAs and diseases in diverse species is ***,we present an updated CircR2Disease v2.0 with the increased number of circRNA-disease associations and novel ***2Disease v2.0 provides more than 5-fold experimentally validated circRNA-disease associations compared to its previous *** version includes 4201 entries between 3077 circRNAs and 312 disease ***,the information of circRNA-miRNA,circRNA-miRNA-target,and circRNA-RBP interactions has been manually collected for various ***,the gene symbols of circRNAs and disease name IDs can be linked with various nomenclature *** descriptions such as samples and journals have also been integrated into the updated ***,CircR2Disease v2.0 can serve as a platform for users to systematically investigate the roles of dysregulated circRNAs in various diseases and further explore the posttranscriptional regulatory function in ***,we propose a computational method named circDis based on the graph convolutional network(GCN)and gradient boosting decision tree(GBDT)to illustrate the applications of the CircR2Disease v2.0 ***2Disease v2.0 is available at http://***/CircR2Disease_v2.0 and https://***/bioinforlab/CircR2Disease-v2.0.

关键词： circRNA circRNA-disease association Graph convolutional network Gradient boosting decision tree Machine learning

SSRE:Cell Type Detection Based on Sparse Subspace Representation and Similarity Enhancement

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Genomics, Proteomics & Bioinformatics 2021年第2期19卷 282-291页

作者： Zhenlan Liang Min Li Ruiqing Zheng Yu Tian Xuhua Yan Jin Chen fang-xiang wu Jianxin Wang School of Computer Science and Engineering Central South UniversityChangsha 410083China College of Medicine University of KentuckyLexingtonKY 40536USA Division of Biomedical Engineering University of SaskatchewanSaskatoonSK S7N 5A9Canada

Accurate identification of cell types from single-cell RNA sequencing(scRNA-seq)data plays a critical role in a variety of scRNA-seq analysis *** task corresponds to solving an unsupervised clustering problem,in which the similarity measurement between cells affects the result *** many approaches for cell type identification have been proposed,the accuracy still needs to be *** this study,we proposed a novel single-cell clustering framework based on similarity learning,called *** models the relationships between cells based on subspace assumption,and generates a sparse representation of the cell-to-cell *** sparse representation retains the most similar neighbors for each ***,three classical pairwise similarities are incorporated with a gene selection and enhancement strategy to further improve the effectiveness of *** on ten real scRNA-seq datasets and five simulated datasets,SSRE achieved the superior performance in most cases compared to several state-of-the-art single-cell clustering *** addition,SSRE can be extended to visualization of scRNA-seq data and identification of differentially expressed *** matlab and python implementations of SSRE are available at https://***/CSUBioGroup/SSRE.

关键词： Single-cell RNA sequencing Clustering Cell type Similarity learning Enhancement

Current challenges and solutions of de novo assembly

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Frontiers of Electrical and Electronic Engineering in China 2019年第2期7卷 90-109页

作者： Xingyu Liao Min Li You Zou fang-xiang wu Yi-Pan Jianxin Wang School of Computer Science and Engineering Central south UniversityChangsha 410083China Division of Biomedical Engineering University of SaskatchewanSaskatchewanS7N 5A9Canada Department of Computer Science Georgia State UniversityAtlantaGA 30302USA

Background:Next-generation sequencing (NGS) technologies have fostered an unprecedented proliferation of highthroughput sequencing projects and a concomitant development of novel algorithms for the assembly of short ***,numerous technical or computational challenges in de novo assembly still remain,although many new ideas and solutions have been suggested to tackle the challenges in both experimental and computational ***:In this review,we first briefly introduce some of the major challenges faced by NGS sequence ***,we analyze the characteristics of various sequencing platforms and their impact on assembly *** that,we classify de novo assemblers according to their frameworks (overlap graph-based,de Bruijn graph-based and string graph-based),and introduce the characteristics of each assembly tool and their adaptation ***,we introduce in detail the solutions to the main challenges of de novo assembly of next generation sequencing data,single-cell sequencing data and single molecule sequencing *** last,we discuss the application of SMS long reads in solving problems encountered in NGS ***:This review not only gives an overview of the latest methods and developments in assembly algorithms,but also provides guidelines to determine the optimal assembly algorithm for a given input sequencing data type.

关键词： next-generation sequencing single-cell sequencing single-molecule sequencing de novo assembly algorithms

Double [5]carbohelicene: facile synthesis, chiroptical properties,isomerization study, and lasing application

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Science China Chemistry 2025年第1期 233-240页

作者： Peipei Liu Yantong Li Meng-xiang wu Hao Kang Xiao-Li Zhao Lin Xu Linlin Liu Xiaodong Li Junfeng fang Zhiwei fang Ya Cheng Hai-Bo Yang Huakang Yu Xueliang Shi State Key Laboratory of Petroleum Molecular & Process Engineering Shanghai Key Laboratory of Green Chemistry and Chemical ProcessesSchool of Chemistry and Molecular Engineering East China Normal University School of Physics and Optoelectronics South China University of Technology Institute of Polymer Optoelectronic Materials & Devices State Key Laboratory of Luminescent Materials & Devices South China University of Technology School of Physics and Electronic Science Engineering Research Center of Nanophotonics & Advanced Instrument Ministry of EducationEast China Normal University State Key Laboratory of Precision Spectroscopy School of Physics and Electronic Science East China Normal University

Double carbohelicenes have attracted considerable attention due to their aesthetic structures, distinct π-conjugation extension, inherent chirality, and intriguing optical and electronic properties. Herein, the concise de novo synthesis of a new double[5]carbohelicene 1 together with its chiroptical properties, isomerization process and lasing application is presented. 1 was synthesized by a simple protocol involving the formation of a 6,6′-bipentacene as the key intermediate. It is worth noting that1 existed as two diastereomers 1-PP/MM and 1-PM, which were successfully isolated and unambiguously confirmed by Xray crystallography. The optical resolution of the racemic 1-PP/MM was successfully achieved by chiral-phase highperformance liquid chromatography（HPLC）, and 1-PP and 1-MM were characterized by circular dichroism. Interestingly, it was found that 1-PP/MM could be completely isomerized to 1-PM upon heating, and the detailed thermodynamics and kinetics of the isomerization process were systematically investigated. 1-PM exhibited deep-red luminescence with emission maximum at 723 nm and fluorescence quantum yield as high as 32.95%. Consequently, we can showcase the lasing application of 1-PM by doping with epoxy resin to assemble a bottle microlaser spontaneously, which the lasing wavelength is 796.6 nm at a threshold of 0.8 m J cm-2. We believe that our studies, including the facile synthesis methodology, detailed isomerization studies, and lasing application, will shed some light on the design and synthesis of novel carbohelical systems with more functions.

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Highly mass activity electrocatalysts with ultralow Pt loading on carbon black for hydrogen evolution reaction

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International Journal of Minerals,Metallurgy and Materials 2025年第1期32卷 182-190页

作者： Shaorou Ke Yajing Zhao Xin Min Yanghong Li Ruiyu Mi Yangai Liu Xiaowen wu Minghao fang Zhaohui Huang Engineering Research Center of Ministry of Education for Geological Carbon Storage and Low Carbon Utilization of Resources Beijing Key Laboratory of Materials Utilization of Nonmetallic Minerals and Solid WastersNational Laboratory of Mineral MaterialsSchool of Materials Science and TechnologyChina University of Geosciences(Beijing)Beijing 100083China

Pt-based nanocatalysts offer excellent prospects for various ***,the low loading of Pt with excellent performance for efficient and stable nanocatalysts still presents a considerable *** this study,nanocatalysts with ultralow Pt content,excellent performance,and carbon black as support were prepared through in-situ ***~2-nm particles uniformly and stably dispersed on carbon black because of the strong s-p-d orbital hybridizations between carbon black and Pt,which suppressed the agglomeration of Pt *** unique structure is beneficial for the hydrogen evolution *** catalysts exhibited remarkable catalytic activity for hydrogen evolution reaction,exhibiting a potential of 100 mV at 100 mA·cm^(-2),which is comparable to those of commercial Pt/C *** activity(1.61 A/mg)was four times that of a commercial Pt/C catalyst(0.37 A/mg).The ultralow Pt loading(6.84wt%)paves the way for the development of next-generation electrocatalysts.

关键词： hydrogen evolution reaction ultralow platinum in-situ synthesis ultrasound