检索结果-南通市图书馆

Single-cell omics: experimental workflow, data analyses and applications

science China Life sciences 2025年第1期68卷 5-102页

作者： Fengying Sun Haoyan Li Dongqing Sun Shaliu Fu Lei Gu Xin Shao Qinqin Wang Xin Dong Bin Duan Feiyang Xing Jun Wu Minmin Xiao Fangqing Zhao Jing-Dong J.Han Qi Liu Xiaohui Fan Chen Li Chenfei Wang Tieliu Shi department of Clinical Laboratory the Affiliated Wuhu Hospital of East China Normal University (The Second People's Hospital of Wuhu City) Pharmaceutical Informatics Institute College of Pharmaceutical SciencesZhejiang University Key Laboratory of Spine and Spinal Cord Injury Repair and Regeneration (Tongji University) Ministry of EducationOrthopaedic DepartmentTongji HospitalBioinformatics DepartmentSchool of Life Sciences and TechnologyTongji University Frontier science center for Stem Cells School of Life Sciences and TechnologyTongji University Translational Medical center for Stem Cell Therapy and Institute for Regenerative Medicine Shanghai East HospitalBioinformatics DepartmentSchool of Life Sciences and TechnologyTongji University Research Institute of Intelligent Computing Zhejiang Lab Shanghai Research Institute for Intelligent Autonomous Systems center for Single-cell Omics School of Public HealthShanghai Jiao Tong University School of Medicine National Key Laboratory of Chinese Medicine Modernization Innovation Center of Yangtze River DeltaZhejiang University center for bioinformatics and Computational Biology Shanghai Key Laboratory of Regulatory Biologythe Institute of Biomedical Sciences and School of Life SciencesEast China Normal University Beijing Institutes of Life science Chinese Academy of Sciences Peking-Tsinghua center for Life sciences Academy for Advanced Interdisciplinary StudiesCenter for Quantitative Biology (CQB)Peking University Zhejiang Key Laboratory of Precision Diagnosis and Therapy for Major Gynecological Diseases Women's HospitalZhejiang University School of Medicine Key Laboratory of Advanced Theory and Application in Statistics and Data science-MOE School of StatisticsEast China Normal University

Cells are the fundamental units of biological systems and exhibit unique development trajectories and molecular features. Our exploration of how the genomes orchestrate the formation and maintenance of each cell, and control the cellular phenotypes of various organismsis, is both captivating and intricate. Since the inception of the first single-cell RNA technology, technologies related to single-cell sequencing have experienced rapid advancements in recent years. These technologies have expanded horizontally to include single-cell genome, epigenome,proteome, and metabolome, while vertically, they have progressed to integrate multiple omics data and incorporate additional information such as spatial sc RNA-seq and CRISPR screening. Single-cell omics represent a groundbreaking advancement in the biomedical field,offering profound insights into the understanding of complex diseases, including cancers. Here, we comprehensively summarize recent advances in single-cell omics technologies, with a specific focus on the methodology section. This overview aims to guide researchers in selecting appropriate methods for single-cell sequencing and related data analysis.

关键词： single-cell sequencing genome epigenome proteomics metabolomics multimodal spatial transcriptomics CRISPR screening

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

A Comprehensive Survey on Federated Learning Applications in Computational Mental Healthcare

引用

computer Modeling in Engineering & sciences 2025年第1期142卷 49-90页

作者： Vajratiya Vajrobol Geetika Jain Saxena Amit Pundir Sanjeev Singh Akshat Gaurav Savi Bansal Razaz Waheeb Attar Mosiur Rahman Brij B.Gupta Institute of Informatics and Communication University of DelhiDelhi110021India Maharaja Agrasen College University of DelhiDelhi110096India computer Engineering Ronin InstituteMontclairNJ 07043USA department of Research and Innovation Insights2TechinfoJaipur302001India University Centre for Research and Development(UCRD) Chandigarh UniversityChandigarh140413India Management department College of Business AdministrationPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia CCRI&department of computer science and Information Engineering Asia UniversityTaichung413Taiwan Symbiosis Centre for Information Technology(SCIT) Symbiosis International UniversityPune411057India center for interdisciplinary Research University of Petroleum and Energy Studies(UPES)Dehradun248007India

Mental health is a significant issue worldwide,and the utilization of technology to assist mental health has seen a growing *** aims to alleviate the workload on healthcare professionals and aid *** applications have been developed to support the challenges in intelligent healthcare ***,because mental health data is sensitive,privacy concerns have *** learning has gotten some *** research reviews the studies on federated learning and mental health related to solving the issue of intelligent healthcare *** explores various dimensions of federated learning in mental health,such as datasets(their types and sources),applications categorized based on mental health symptoms,federated mental health frameworks,federated machine learning,federated deep learning,and the benefits of federated learning in mental health *** research conducts surveys to evaluate the current state of mental health applications,mainly focusing on the role of Federated Learning(FL)and related privacy and data security *** survey provides valuable insights into how these applications are emerging and evolving,specifically emphasizing FL’s impact.

关键词： Depression emotional recognition intelligent healthcare systems mental health federated learning stress detection sleep behaviour

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Computational Challenges in Deciphering Genomic Structures of Bacteria

引用

Journal of computer science & Technology 2010年第1期25卷 53-70页

作者：徐鹰 Computational Systems Biology Laboratory Department of Biochemistry and Molecular Biology and Institute of Bioinformatics The University of Georgia BESC BioEnergy science center College of computer science and Technology Jilin University

This article addresses how the functionalities of the cellular machinery of a bacterium might have constrained the genomic arrangement of its genes during evolution and how we can study such problems using computational approaches, taking full advantage of the rapidly increasing pool of the sequenced bacterial genomes, potentially leading to a much improved understanding of why a bacterial genome is organized in the way it is. This article discusses a number of challenging computational problems in elucidating the genomic structures at multiple levels and the information that is encoded through these genomic structures, gearing towards the ultimate understanding of the governing rules of bacterial genome organization.

关键词： bioinformatics microbial genomics genome structure comparative genome analysis biological pathways

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Modeling the causal regulatory network by integrating chromatin accessibility and transcriptome data

引用

National science Review 2016年第2期3卷 240-251页

作者： Yong Wang Rui Jiang Wing Hung Wong department of Statistics Department of Biomedical Data ScienceBio-X ProgramStanford University Academy of Mathematics and Systems science National Center for Mathematics and Interdisciplinary SciencesChinese Academy of Sciences MOE Key Laboratory of bioinformatics Bioinformatics Division and Center for Synthetic and Systems BiologyTNLISTDepartment of AutomationTsinghua University

Cell packs a lot of genetic and regulatory information through a structure known as chromatin,*** is wrapped around histone proteins and is tightly packed in a remarkable *** express a gene in a specific coding region,the chromatin would open up and DNA loop may be formed by interacting enhancers and ***,the mediator and cohesion complexes,sequence-specific transcription factors,and RNA polymerase Ⅱ are recruited and work together to elaborately regulate the expression *** is in pressing need to understand how the information,about when,where,and to what degree genes should be expressed,is embedded into chromatin structure and gene regulatory *** to large consortia such as Encyclopedia of DNA Elements(ENCODE) and Roadmap Epigenomic projects,extensive data on chromatin accessibility and transcript abundance are available across many tissues and cell *** rich data offer an exciting opportunity to model the causal regulatory ***,we will review the current experimental approaches,foundational data,computational problems,interpretive frameworks,and integrative models that will enable the accurate interpretation of regulatory ***,we will discuss the efforts to organize,analyze,model,and integrate the DNA accessibility data,transcriptional data,and functional genomic regions *** believe that these efforts will eventually help us understand the information flow within the cell and will influence research directions across many fields.

关键词： gene regulatory network open chromatin DNA accessibility transcription factor colocalization statistical model data integration

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Small extrachromosomal circular DNA in amyotrophic lateral sclerosis matter

引用

Neural Regeneration Research 2025年第5期20卷 1411-1413页

作者： Marcos J.Arauzo-Bravo Daniela Gerovska Matthias Schwab Alexandra Kretz Computational Biology and Systems Biomedicine Biodonostia Health Research InstituteSan SebastianSpain Basque Foundation for science IKERBASQUEBilbaoSpainMax Planck Institute for Molecular BiomedicineComputational Biology and Bioinformatics GroupMünsterNorth Rhine-WestphaliaGermany department of Cell Biology and Histology Faculty of Medicine and NursingUniversity of Basque Country(UPV/EHU)LeioaSpain department of Neurology Jena University HospitalJenaThuringiaGermany

Comprehensive studies identify motor neuron spectrum disorders including amyotrophic lateral sclerosis(ALS)as globally rising fatal disorders with the highest prevalence in aging populations,influenced by ethnicity and ancestry(GBD 2016 Motor Neuron Disease Colla borators,2018).While~10% of diagnoses involve a family history(fALS),most cases are considered sporadic(sALS).However,population-based studies suggest that even cases without a common index mutation impart heritability(Ryan et al.,2019),indicating a crucial role of rare and as yet unknown genetic denominators.

关键词： amyotrophic sclerosis

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

A Bayesian-based approach for extracting the pion charge radius from electron-electron scattering data

引用

Chinese Physics C 2021年第8期45卷 12-27页

作者： Alam A Hidayat Bens Pardamean bioinformatics and Data science Research center Bina Nusantara UniversityJakarta 11480Indonesia computer science department BINUS Graduate Program-Master of Computer ScienceBina Nusantara UniversityJakarta 11480Indonesia

In this study,we utilize a potentially versatile Bayesian parameter approach to compute the value of the pion charge radius and quantify its uncertainty from several experimental e^(+)e^(-) datasets for the pion vector form *** employ dispersion relations to model the pion vector form factor to extract the *** model selection is used to determine the order of polynomial appearing in the form factor formulation that can be supported by the data,adapting the computation of Bayes evidence and Bayesian effective complexity based on Occam's *** findings indicate that five out of six used datasets favor the nine-parameter model for radius extraction,and accordingly,we average the radii from the *** some inconsistencies with the most updated radius values,our approach may serve as a more intuitive method of addressing parameter estimations in dispersion theory.

关键词： Bayesian complexity dispersion hadron pion

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

GOAL: the comprehensive gene ontology analysis layer

引用

science China(Information sciences) 2016年第7期59卷 86-93页

作者： Jong Cheol JEONG George LI Xue-Wen CHEN department of Pathology Harvard Medical School Beth Israel Deaconess Medical Center bioinformatics and Computational Life sciences Laboratory University of Kansas department of computer science Wayne State University

Homogeneity or heterogeneity of cells is the most fundamental and important features of analyzing biological associations of genes and gene products. Recent bioinformatics technology requires an automated high-throughput analysis application that can handle massively produced data from next generation sequences and dramatically increased size of public proteomic/genomic databases. Although Gene ontology(GO) database has been newly spotlighted on its wide coverage of machine-readable terminologies, its complex DB schema and vast amount of applications utilizing GO without deep considerations of GO term relations dilute the actual power of GO-based analysis and resulted in misleading/under estimated outcomes. Meanwhile, our recent studies showed that BSM score, a new way of measuring functional similarity, clearly outperformed existing conventional methods. However, implementing BSM score that requires integrating multiple databases and calculating scoring matrix is not trivial and even difficult for bioinformatics experts; therefore, a web-based graphical user interface(GUI) tool, Gene Ontology Analysis Layer(GOAL: http://***/chenlab/goal) is introduced to provide user-friendly GO application powered by state of art functional similarity metric,BSM score.

关键词： gene ontology molecular function functional similarity network-based analysis BSM score

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

On the role of geometry in geo-localization

引用

Computational Visual Media 2021年第1期7卷 103-113页

作者： Moti Kadosh Yael Moses Ariel Shamir department of Electrical Engineering Tel-Aviv UniversityTel-AvivIsrael The Efi Arazi School of computer science The Interdisciplinary Center HerzliyaHerzliyaIsrael

Consider the geo-localization task of finding the pose of a camera in a large 3 D scene from a single *** existing CNN-based methods use as input textured *** aim to experimentally explore whether texture and correlation between nearby images are necessary in a CNN-based solution for the geo-localization *** do so,we consider lean images,textureless projections of a simple 3 D model of a *** only contain information related to the geometry of the scene viewed(edges,faces,and relative depth).The main contributions of this paper are:(i)to demonstrate the ability of CNNs to recover camera pose using lean images;and(ii)to provide insight into the role of geometry in the CNN learning process.

关键词： geo-localization geometry CNN-based solutions synthetic lean images

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Dropout training for SVMs with data augmentation

引用

Frontiers of computer science 2018年第4期12卷 694-713页

作者： Ning CHEN Jun ZHU Jianfei CHEN Ting CHEN MOE Key lab of bioinformatics Bioinformatics Division and Center for Synthetic and Systems Biology TNLIST Tsinghua University Beijing 100084 China State Key Lab of Intelligent Technology and Systems Department of Computer Science and Technology Tsinghua University Beijing 100084 China

Dropout and other feature noising schemes have shown promise in controlling over-fitting by artificially corrupting the training data. Though extensive studies have been performed for generalized linear models, little has been done for support vector machines （SVMs）, one of the most successful approaches for supervised learning. This paper presents dropout training for both linear SVMs and the nonlinear extension with latent representation learning. For linear SVMs, to deal with the intractable expectation of the non-smooth hinge loss under corrupting distributions, we develop an iteratively re-weighted least square （IRLS） algorithm by exploring data augmentation techniques. Our algorithm iteratively minimizes the expectation of a re- weighted least square problem, where the re-weights are analytically updated. For nonlinear latent SVMs, we con- sider learning one layer of latent representations in SVMs and extend the data augmentation technique in conjunction with first-order Taylor-expansion to deal with the intractable expected hinge loss and the nonlinearity of latent representa- tions. Finally, we apply the similar data augmentation ideas to develop a new IRLS algorithm for the expected logistic loss under corrupting distributions, and we further develop a non-linear extension of logistic regression by incorporating one layer of latent representations. Our algorithms offer insights on the connection and difference between the hinge loss and logistic loss in dropout training. Empirical results on several real datasets demonstrate the effectiveness of dropout training on significantly boosting the classification accuracy of both linear and nonlinear SVMs.

关键词： dropout SVMs logistic regression data aug- mentation iteratively reweighted least square

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Characterizing RNA Pseudouridylation by Convolutional Neural Networks

引用

Genomics, Proteomics & bioinformatics 2021年第5期19卷 815-833页

作者： Xuan He Sai Zhang Yanqing Zhang Zhixin Lei Tao Jiang Jianyang Zeng Institute for interdisciplinary Information sciences Tsinghua UniversityBeijing 100084China Peking-Tsinghua center for Life sciences Peking UniversityBeijing 100871China Academy for Advanced interdisciplinary Studies Peking UniversityBeijing 100871China department of computer science and Engineering University of CaliforniaRiversideCA 92521USA MOE Key Lab of bioinformatics and bioinformatics Division BNRIST/Department of Computer Science and TechnologyTsinghua UniversityBeijing 100084China Institute of Integrative Genome Biology University of CaliforniaRiversideCA 92521USA MOE Key Laboratory of bioinformatics Tsinghua UniversityBeijing 100084China

Pseudouridine(Ψ)is the most prevalent post-transcriptional RNA modification and is widespread in small cellular RNAs and m ***,the functions,mechanisms,and precise distribution ofΨs(especially in m RNAs)still remain largely *** landscape ofΨs across the transcriptome has not yet been fully ***,we present a highly effective model based on a convolutional neural network(CNN),called Pseudo Uridy Lation Site Estimator(PULSE),to analyze large-scale profiling data ofΨsites and characterize the contextual sequence features of ***,consisting of two alternatively-stacked convolution and pooling layers followed by a fully-connected neural network,can automatically learn the hidden patterns of pseudouridylation from the local sequence *** validation tests demonstrated that PULSE can outperform other state-of-the-art prediction methods and achieve high prediction accuracy,thus enabling us to further characterize the transcriptome-wide landscape ofΨ*** further showed that the prediction results derived from PULSE can provide novel insights into understanding the functional roles of pseudouridylation,such as the regulations of RNA secondary structure,codon usage,translation,and RNA stability,and the connection to single nucleotide *** source code and final model for PULSE are available at https://***/mlcb-thu/PULSE.

关键词： Pseudouridylation Convolution neural network Sequence motif Translation RNA stability

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：