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Detection of bursts in neuronal spike trains by the mean inter-spike interval method

Progress in Natural science:Materials International 2009年第2期19卷 229-235页

作者： Lin Chena,b,Yong Deng c,Weihua Luo a,Zhen Wang a,Shaoqun Zenga,a Hubei bioinformatics and Molecular Imaging Key Laboratory,Huazhong University of science and technology,Wuhan 430074,China b college of Mechanical Engineering,Guangxi University,Nanning,530004,China c college of Optoelectronic science of Engineering,Huazhong University of science and technology,Wuhan 430074,China Hubei Bioinformatics and Molecular Imaging Key Laboratory Huazhong University of Science and Technology Wuhan 430074 China College of Mechanical Engineering Guangxi University Nanning 530004 China College of Optoelectronic Science of Engineering Huazhong University of Science and Technology Wuhan 430074 China

Bursts are electrical spikes firing with a high frequency,which are the most important property in synaptic plasticity and information processing in the central nervous system. However,bursts are difficult to identify because bursting activities or patterns vary with phys-iological conditions or external stimuli. In this paper,a simple method automatically to detect bursts in spike trains is described. This method auto-adaptively sets a parameter (mean inter-spike interval) according to intrinsic properties of the detected burst spike trains,without any arbitrary choices or any operator judgment. When the mean value of several successive inter-spike intervals is not larger than the parameter,a burst is identified. By this method,bursts can be automatically extracted from different bursting patterns of cultured neurons on multi-electrode arrays,as accurately as by visual inspection. Furthermore,significant changes of burst variables caused by electrical stimulus have been found in spontaneous activity of neuronal network. These suggest that the mean inter-spike interval method is robust for detecting changes in burst patterns and characteristics induced by environmental alterations.

关键词： Inter-spike interval Bursts Spike trains Multi-electrode arrays

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Refining biome labeling for large-scale microbial community samples:Leveraging neural networks and transfer learning

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Environmental science and Ecotechnology 2024年第1期17卷 128-137页

作者： Nan Wang Teng Wang Kang Ning Key Laboratory of Molecular Biophysics of the Ministry of Education Hubei Key Laboratory of Bioinformatics and Molecular-imagingCenter of AI BiologyDepartment of Bioinformatics and Systems BiologyCollege of Life Science and TechnologyHuazhong University of Science and TechnologyWuhan430074HubeiChina

Microbiome research has generated an extensive amount of data,resulting in a wealth of publicly accessible *** annotation of these samples is crucial for effectively utilizing microbiome data across scientific ***,a notable challenge arises from the lack of essential annotations,particularly regarding collection location and sample biome information,which significantly hinders environmental microbiome *** this study,we introduce Meta-Sorter,a novel approach utilizing neural networks and transfer learning,to enhance biome labeling for thousands of microbiome samples in the MGnify database that have incomplete *** findings demonstrate that Meta-Sorter achieved a remarkable accuracy rate of 96.7%in classifying samples among the 16,507 lacking detailed biome ***,Meta-Sorter provides precise classifications for representative environmental samples that were previously ambiguously labeled as“Marine”in MGnify,thereby elucidating their specific origins in benthic and water column ***,Meta-Sorter effectively distinguishes samples derived from human-environment interactions,enabling clear differentiation between environmental and human-related *** improving the completeness of biome label information for numerous microbial community samples,our research facilitates more accurate knowledge discovery across diverse disciplines,with particular implications for environmental research.

关键词： Microbial community Transfer learning Sample classification Environmental scientific research Novel knowledge discovery

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Graphene nanopores toward DNA sequencing： a review of experimental aspects

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science China Chemistry 2017年第6期60卷 721-729页

作者： Wei Chen Guo-Chang Liu Jun Ouyang Meng-Juan Gao Bo Liu Yuan-Di Zhao Britton Chance Center for Biomedical Photonics at Wuhan National Laboratory for Optoelectronics-Hubei Bioinformatics and Molecular Imaging Key Laboratory Department of Biomedical Engineering College of Life Science and Technology Huazhong University of Science and Technology Wuhan 430074 China

Nanopores for DNA sequencing have drawn much attention due to their potentials to achieve amplification-free, low-cost, and high-throughput analysis of nuclei acids. The material configuration and fabrication of the nanopore has become one important consideration in the nanopore based DNA sequencing research. Among various materials, the newly emerged graphene has brought more opportunities to the development of sequencing technology because of its unique structures and properties. This review mainly focuses on the experimental aspects of graphene nanopore research including the nanopore fabrication methods and processes. Meanwhile, the challenges in the present graphene nanopore research including hydrophobicity, translocation velocity and noise are also addressed and discussed.

关键词： graphene nanopore DNA sequencing nanopore fabrication

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CTFMining: A method to predict candidate disease genes based on the combined network topological features mining

CTFMining: A method to predict candidate disease genes based...

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3rd International Conference on bioinformatics and Biomedical Engineering, iCBBE 2009

作者： Lina, Chen Yan, Zhao Liangcai, Zhang Yukui, Shang Qian, Wang Wan, Li Hong, Wang Xia, Li College of Bioinformatics Science and Technology Harbin Medical University Harbin China

ISBN: (纸本)9781424429028

Genes with similar functions might lead to similar phenotypes and tend to locate in a cluster in protein- protein interaction (PPI) network. The responsible genes should be identified for cardiovascular artery disease by their combined network topological features. Here we introduced a method called CTFMining to predict candidate disease genes which based on the combined network topological features mining. Four network topological features were defined to describe the network characters of genes. And then, we used each topological feature and combined topological features to screen the disease genes by training support vector machines (SVMs), respectively. It was found that using combined feature to predicted disease genes would get a better result than using single feature and an optima combined features was found to distinguish disease genes from non-disease genes. According to the optima combined feature, each candidate disease genes were predicted, and finally the intersection of 10,000 predictions was defined to be our final prediction. Finally, 224 candidate disease genes were predicted using SVM. Nearly 86% of candidate disease genes were found to be associated with CAD, which was verified by Priortizer or PandS. Candidate disease genes were likely to share the same functions with known disease genes of CAD. Our optima combined feature could be introduced to distinguish disease genes from non-disease genes well. With the increase of interaction data and further discovery of known disease genes, our method can be applied to predict novel candidate genes better. ©2009 IEEE.

关键词： Genes

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3D genome structural variations play important roles in regulating seed oil content of Brassica napus

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Plant Communications 2024年第1期5卷 101-115页

作者： Libin Zhang Lin Liu Huaixin Li Jianjie He Hongbo Chao Shuxiang Yan Yontai Yin Weiguo Zhao Maoteng Li College of Life Science and Technology Huazhong University of Science and TechnologyWuhan 430074China Wuhan Frasergen Bioinformatics Co. Ltd.Wuhan 430075China Key Laboratory of Molecular Biophysics of the Ministry of Education Hubei Bioinformatics and Molecular Imaging Key LaboratoryWuhan 430074China

Dissecting the complex regulatory mechanism of seed oil content(SOC)is one of the main research goals in Brassica *** evidence suggests that genome architecture is linked to multiple biological ***,the effect of genome architecture on SOC regulation remains ***,we used high-throughput chromatin conformation capture to characterize differences in the three-dimen-sional(3D)landscape of genome architecture of seeds from two *** lines,N53-2(with high SOC)and Ken-C8(with low SOC).bioinformatics analysis demonstrated that differentially accessible regions and differentially expressed genes between N53-2 and Ken-C8 were preferentially enriched in regions with quantitative trait loci(QTLs)/associated genomic regions(AGRs)for SOC.A multi-omics analysis demonstrated that expression of SOC-related genes was tightly correlated with genome structural varia-tions in QTLs/AGRs of *** candidate gene BnaA09g48250D,which showed structural variation in a QTL/AGR on chrA09,was identified byfine-mapping of a KN double-haploid population derived from hybridization of N53-2 and *** and knockout of BnaA09g48250D led to significant in-creases and decreases in SOC,respectively,in the transgenic *** together,our results reveal the 3D genome architecture of *** seeds and the roles of genome structural variations in SOC regulation,enriching our understanding of the molecular mechanisms of SOC regulation from the perspective of spatial chromatin structure.

关键词： Brassica napus seed oil content Hi-C QTLfine-mapping genome structural variation

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Functional analysis of differential mRNAs in cancer peripheral blood: Reflection of population shifts in myeloid-origin and lymphoid-origin cells 8

Functional analysis of differential mRNAs in cancer peripher...

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8th International Conference on Systems Biology, ISB 2014

作者： Hong, Guini Li, Hongdong Zhang, Wenjing Guo, Zheng Chen, Beibei Xu, Hui Ao, Lu Bioinformatics Centre School of Life Science University of Electronic Science and Technology of China Chengdu China College of Bioinformatics Science and Technology Harbin Medical University Harbin China

ISBN: (纸本)9781479972944

Functional enrichment analysis is usually adopted after the identification of differentially expressed (DE) genes in studies focusing on cancer peripheral blood (PB) gene expression. However, whether the disturbed functional signals reflect the expression changes in blood cells or the cell population shifts under cancer condition remains unclear. By deconvolving the gene expression profiles of multiple cancer datasets, we showed that the proportion of myeloid-origin cells increased whereas the proportion of lymphoid-origin cells decreased in cancer PB. The DE genes between cancer PB samples and controls were highly consistent with DE genes between myeloid-origin and lymphoidorigin cells, indicating that cell population shifts contributed predominantly to the differential signals in cancer PB. All of the functional categories enriched for cancer PB DE genes were enriched for DE genes between myeloid-origin and lymphoidorigin cells, suggesting that functional signals in cancer PB probably reflect the changes of population shifts in blood cells, thus the enriched functional categories might not be able to reflect the cell type specific expression changes. Therefore, caution should be taken in translational biomarker discovery based on human PB gene expression profiles. © 2014 IEEE.

关键词： Gene expression

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Heat generation of cross fluid model over a stretching sheet with chemical reaction

Geoenergy Science and Engineering

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Geoenergy science and Engineering 2025年 253卷

作者： T. Salahuddin Adnan Maqsood Muhammad Awais Mair Khan M. Afzal Department of Mathematics Mirpur University of Science and Technology 10250 Pakistan Department of Mathematics University College Zhob BUITEMS Zhob 85200 Pakistan Department of Mathematics and Natural Sciences Center for Applied Mathematics and Bioinformatics Gulf University for Science & Technology 32093 Hawally Kuwait

This study incorporates the heat and mass transmission for the boundary layer flow of Cross nanofluid model over a heated stretching sheet. The Buongiorno's nanofluid model is considered to investigate the effects of Brownian and thermophoretic motion of nanoparticles in the Cross fluid. The thermal and solutal aspects are determined by considering the Cattaneo-Christov fluxes which introduces both thermal and solutal relaxation times, extending classical Fourier and Fick laws to finite-speed diffusion. The combined effects of Solutal and thermal stratifications are considered in this work. Moreover, recent problems extended by taking the chemical reaction and heat generation in the nano-fluid flow. The determining equations are created as partial differential equations based on the mentioned assumptions and then transformed them into ordinary differential equations by utilizing similarity transformation. Under the assumption of Cattaneo-Christov double diffusions, the performance of heat and mass is analyzed. A BVP4c buildin method is used to explore the numerical results and graphical performance by MATLAB software. As, the shear thinning behavior of Cross fluid model is the area of considered, therefore the obtained results reveals that the velocity profiles rapidly decline due to velocity power index while the Weissenberg number upturns the velocity region. The Brownian and thermophoresis motion of nanoparticles are the sources of increment in the temperature region whereas the thermal stratification parameter declines the temperature within fluid. The thermal relaxation parameter drops the temperature whereas the heat generation parameter enhances the temperature of fluid. The decrement in the concentration transfer is observed by the Brownian motion parameter, solutal relaxation parameter and chemical reaction coefficient while the opposite behavior is noted due to thermophoresis motion of nanoparticles. The double stratification and boundary layer flow of Cro

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Extracting multi-function features for cancer genes

Extracting multi-function features for cancer genes

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2010 7th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2010

作者： Maa, Wencai Guoa, Xinwu Wanga, Chenguang Gua, Yunyan Zhanga, Yuannv Xiaa, Jiguang Guoa, Zheng College of Bioinformatics Science and Technology Harbin Medical University Harbin China Bioinformatics Centre School of Life Science University of Electronic Science and Technology of China Chengdu China

ISBN: (纸本)9781424459346

The causation of cancer often involves the joint deregulation of multiple biological processes. Thus, it is interesting to extract multi-function features of cancer genes and study their functional coordination involved in tumorigenesis. Here, based on Gene Ontology, we proposed a heuristics strategy to extract multi-function features which are significantly overrepresented with cancer genes. We showed that the extracted feature combinations can provide hints for studying the functional interplay roles of multi-function genes involved in tumorigenesis. Using protein-protein interaction data, we found that the pivot genes of the obtained functional feature combinations are likely to be cancer genes, and that their alternations may play important roles in simultaneously deregulating multiple functions and thus inducing cancer. ©2010 IEEE.

关键词： Gene Ontology

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Volatilomics and Lipidomics revealed flavoring mechanism in baijiu brewed from diverse Sorghum varieties

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Food Chemistry 2025年 485卷 144503页

作者： Zhu, Hui Li, Linjuan Ma, Yi Luo, Huibo El-Sappah, Ahmed H. Liu, Ying Sun, Xiaoke Pan, Shijiang Mehmood, Muhammad Aamer Sun, Yong Wang, Ning Sichuan Province Engineering Technology Research Center of Liquor-Making Grains School of Bioengineering Sichuan University of Science and Engineering Yibin644000 China Liquor Making Biotechnology and Intelligent Manufacturing of Key Laboratory of China National Light Industry Yibin644000 China State Key Laboratory of Food Science and Resources Nanchang University Nanchang330047 China College of Agriculture Forestry and Food Engineering Yibin University Yibin644000 China Genetics Department Faculty of Agriculture Zagazig University Zagazig44511 Egypt Sichuan Yibin Hengshengfu Liquor Industry Group Co. Ltd Yibin644000 China Yibin City Agricultural and Rural Bureau Yibin644000 China Department of Bioinformatics and Biotechnology Government College University Faisalabad Faisalabad Pakistan

Sorghum is crucial in Baijiu brewing. Previous studies have shown that glutinous sorghum (LS) and non-glutinous sorghum (FS) significantly affect Zaopei's lipid metabolism and lipids affect flavor perception. This study aimed to explore the quality differences in Baijiu brewed with different sorghum varieties and the effects of lipids. Sensory evaluation, volatilomics, and lipidomics were used to analyze differences in flavors and lipids. The results showed that significant differences in flavor existed between the two types of Baijiu. The aged flavor of LS was more pronounced and its mouthfeel was smoother. However, the FS showed a more intense aroma release. In addition, FA 18:1;O3 (fatty acyls), acetaldehyde, and ethyl caprylate contributed to the smoothness and softness of Baijiu. These results suggest that the lipid composition of Baijiu affects its aroma and taste, thus providing a reference basis for selecting suitable raw sorghum materials to enhance the quality of Baijiu. © 2025 The Author(s)

关键词： Flavor compounds

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Biomedical data and AI

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science China Life sciences 2025年第5期68卷 1536-1540页

作者： Hao Xu Shibo Zhou Zefeng Zhu Vincenzo Vitelli Liangyi Chen Ziwei Dai Ning Yang Luhua Lai Shengyong Yang Sergey Ovchinnikov Zhuoran Qiao Sirui Liu Chen Song Jianfeng Pei Han Wen Jianfeng Feng Yaoyao Zhang Zhengwei Xie Yang-Yu Liu Zhiyuan Li Fulai Jin Hao Li Mohammad Lotfollahi Xuegong Zhang Ge Yang Shihua Zhang Ge Gao Pulin Li Qi Liu Jing-Dong Jackie Han Peking-Tsinghua Center for Life Sciences (CLS) Academy for Advanced Interdisciplinary StudiesPeking University Center for Quantitative Biology (CQB) Academy for Advanced Interdisciplinary StudiesPeking University Peking University-Tsinghua University-National Institute of Biological Sciences Joint Graduate Program Academy for Advanced Interdisciplinary StudiesPeking University Department of Physics University of Chicago School of Life Sciences Southern University of Science and Technology Peking University Chengdu Academy for Advanced Interdisciplinary Biotechnologies College of Chemistry and Molecular Engineering Peking University Department of Biotherapy Cancer Center and State Key Laboratory of BiotherapyWest China HospitalSichuan University Department of Biology Massachusetts Institute of Technology Lambic Therapeutics Inc. Changping Laboratory Al for Science Institute Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence Fudan University Department of Obstetrics and Gynecology West China Second University HospitalSichuan University Peking University International Cancer Institute and Peking University-Yunnan Baiyao International Medical Institute and State Key Laboratory of Natural and Biomimetic Drugs Department of Molecular and Cellular PharmacologySchool of Pharmaceutical SciencesPeking University Health Science CenterPeking University Channing Division of Network Medicine Department of MedicineBrigham and Women's Hospital and Harvard Medical School Center for Artificial Intelligence and Modeling the Carl R.Woese Institute for Genomic BiologyUniversity of Illinois Urbana-Champaign Department of Genetics and Genome Sciences School of Medicine and Department of Computer and Data Sciences and Department of Population and Quantitative Health SciencesCase Western Reserve University Department of Biochemistry and Biophysics University of California Sanger Institute Department of Automation Tsinghua University State Key Laboratory of Multimodal Artificial Intelligence Systems I

The development of artificial intelligence(AI) and the mining of biomedical data complement each other. From the direct use of computer vision results to analyze medical images for disease screening, to now integrating biological knowledge into models and even accelerating the development of new AI based on biological discoveries, the boundaries of both are constantly expanding, and their connections are becoming closer.

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