检索结果-内蒙古大学图书馆

COWID: an efficient cloud-based genomics workflow for scalable identification of SARS-COV-2

Briefings in Bioinformatics 2023年第5期24卷 bbad280-bbad280页

作者： Lim, Hendrick Gao-Min Fann, Yang C Lee, Yuan-Chii Gladys Graduate Institute of Biomedical Informatics College of Medical Science and Technology Taipei Medical University Taipei 11031 Taiwan Department of Medical Research Tzu Chi Hospital Indonesia Pantai Indah Kapuk Greater Jakarta 14470 Indonesia It and Bioinformatics Program Division of Intramural National Institute of Neurological Disorders and Stroke National Institutes of Health Bethesda 20892 MD United States

Implementing a specific cloud resource to analyze extensive genomic data on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses a challenge when resources are limited. To overcome this, we repurposed a cloud platform initially designed for use in research on cancer genomics (https://***) to enable its use in research on SARS-CoV-2 to build Cloud Workflow for Viral and Variant Identification (COWID). COWID is a workflow based on the Common Workflow Language that realizes the full potential of sequencing technology for use in reliable SARS-CoV-2 identification and leverages cloud computing to achieve efficient parallelization. COWID outperformed other contemporary methods for identification by offering scalable identification and reliable variant findings with no false-positive results. COWID typically processed each sample of raw sequencing data within 5 min at a cost of only US$0.01. The COWID source code is publicly available (https://***/hendrick0403/COWID) and can be accessed on any computer with Internet access. COWID is designed to be user-friendly;it can be implemented without prior programming knowledge. Therefore, COWID is a time-efficient tool that can be used during a pandemic. © 2023 Published by Oxford University Press.

关键词： cloud repurposing cloud workflow COVID-19 Illumina sequencing parallel computation SARS-CoV-2

来源：评论

学校读者我要写书评

暂无评论

The recency and geographical origins of the bat viruses ancestral to SARS-CoV and SARS-CoV-2

引用

Cell 2025年

作者： Pekar, Jonathan E. Lytras, Spyros Ghafari, Mahan Magee, Andrew F. Parker, Edyth Wang, Yu Ji, Xiang Havens, Jennifer L. Katzourakis, Aris Vasylyeva, Tetyana I. Suchard, Marc A. Hughes, Alice C. Hughes, Joseph Rambaut, Andrew Robertson, David L. Dellicour, Simon Worobey, Michael Wertheim, Joel O. Lemey, Philippe Institute of Ecology and Evolution University of Edinburgh Edinburgh United Kingdom Bioinformatics and Systems Biology Graduate Program University of California San Diego La Jolla 92093 CA United States Department of Biomedical Informatics University of California San Diego La Jolla 92093 CA United States Department of Medicine University of California San Diego La Jolla 92093 CA United States Division of Systems Virology Department of Microbiology and Immunology The Institute of Medical Science The University of Tokyo Tokyo Japan Medical Research Council University of Glasgow Centre for Virus Research Glasgow United Kingdom Department of Biology University of Oxford Oxford United Kingdom Department of Human Genetics David Geffen School of Medicine University of California Los Angeles Los Angeles 90095 CA United States Department of Immunology and Microbiology The Scripps Research Institute La Jolla 92037 CA United States Institute of Genomics and Global Health Redeemer's University Osun State Ede Nigeria Department of Computer Science and Engineering University of California San Diego La Jolla 92093 CA United States Department of Mathematics School of Science and Engineering Tulane University New Orleans LA United States Department of Population Health and Disease Prevention University of California Irvine Irvine 92617 CA United States Department of Biostatistics Fielding School of Public Health University of California Los Angeles Los Angeles 90095 CA United States Department of Computational Medicine David Geffen School of Medicine University of California Los Angeles Los Angeles 90095 CA United States School of Biological Sciences University of Hong Kong Hong Kong Hong Kong China Biodiversity Green Development Foundation Beijing China Spatial Epidemiology Lab (SpELL) Université Libre de Bruxelles CP160/12 50 av. FD Roosevelt Bruxelles 1050 Belgium Department of Microbiology Immunology and Transplantation Rega Institute

The emergence of SARS-CoV in 2002 and SARS-CoV-2 in 2019 led to increased sampling of sarbecoviruses circulating in horseshoe bats. Employing phylogenetic inference while accounting for recombination of bat sarbecoviruses, we find that the closest-inferred bat virus ancestors of SARS-CoV and SARS-CoV-2 existed less than a decade prior to their emergence in humans. Phylogeographic analyses show bat sarbecoviruses traveled at rates approximating their horseshoe bat hosts and circulated in Asia for millennia. We find that the direct ancestors of SARS-CoV and SARS-CoV-2 are unlikely to have reached their respective sites of emergence via dispersal in the bat reservoir alone, supporting interactions with intermediate hosts through wildlife trade playing a role in zoonotic spillover. These results can guide future sampling efforts and demonstrate that viral genomic regions extremely closely related to SARS-CoV and SARS-CoV-2 were circulating in horseshoe bats, confirming their importance as the reservoir species for SARS viruses. © 2025 The Authors

关键词： molecular epidemiology phylogeography sarbecoviruses virus evolution

来源：评论

学校读者我要写书评

暂无评论

Improving quantitation accuracy in isobaric-labeling mass spectrometry experiments with spectral library searching and feature-based peptide-spectrum match filter

引用

Scientific Reports 2023年第1期13卷 1-10页

作者： Kuo, Tzu-Yun Wang, Jen-Hung Huang, Yung-Wen Sung, Ting-Yi Chen, Ching-Tai Department of Biochemical Science and Technology National Taiwan University Taipei 10617 Taiwan Bioinformatics Program Taiwan International Graduate Program Institute of Statistical Science Academia Sinica Taipei 11529 Taiwan Institute of Information Science Academia Sinica Taipei 11529 Taiwan Institute of Biomedical Informatics National Yang Ming Chiao Tung University Taipei 11221 Taiwan Department of Computer Science and Information Engineering National Taiwan University Taipei 10617 Taiwan Department of Bioinformatics and Biomedical Engineering Asia University Taichung 41354 Taiwan Center for Precision Health Research Asia University Taichung 41354 Taiwan

Isobaric labeling relative quantitation is one of the dominating proteomic quantitation technologies. Traditional quantitation pipelines for isobaric-labeled mass spectrometry data are based on sequence database searching. In this study, we present a novel quantitation pipeline that integrates sequence database searching, spectral library searching, and a feature-based peptide-spectrum-match (PSM) filter using various spectral features for filtering. The combined database and spectral library searching results in larger quantitation coverage, and the filter removes PSMs with larger quantitation errors, retaining those with higher quantitation accuracy. Quantitation results show that the proposed pipeline can improve the overall quantitation accuracy at the PSM and protein levels. To our knowledge, this is the first study that utilizes spectral library searching to improve isobaric labeling-based quantitation. For users to conveniently perform the proposed pipeline, we have implemented the feature-based filter being executable on both Windows and Linux platforms;its executable files, user manual, and sample data sets are freely available at https://***/comics/Software_*** . Furthermore, with the developed filter, the proposed pipeline is fully compatible with the Trans-Proteomic Pipeline. © 2023, Springer Nature Limited.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Dose Optimization of rhIL-7-hyFc for Patients With Lymphopenia Using a Neonatal Fc Receptor-Mediated Recycling-Based and Target-Mediated Drug Disposition Pharmacokinetic Model

引用

Clinical and translational science 2025年第5期18卷 e70252页

作者： Hye Seon Jeon Sang Won Lee Woojin Jung Heeyoon Jung Donghoon Choi Mi-Sun Byun Hwi-Yeol Yun Soyoung Lee Anhye Kim Jung-Woo Chae Howard Lee College of Pharmacy Chungnam National University Daejeon Republic of Korea. Department of Pharmacology Hanyang University College of Medicine Seoul Republic of Korea. Department of Clinical Pharmacology and Therapeutics Hanyang University Seoul Hospital Seoul Republic of Korea. Population Health Sciences Program Department of Population and Quantitative Health Sciences University of Massachusetts Chan Medical School Worcester Massachusetts USA. Research Institute of NeoImmuneTech Inc. Pohang Republic of Korea. Clinical Development Department Genexine Inc. Seoul Republic of Korea. Department of Bio-AI Convergence Chungnam National University Daejeon Republic of Korea. Department of Clinical Pharmacology and Therapeutics CHA University Bundang Medical Center Seongnam Republic of Korea. Department of Pharmacology CHA University School of Medicine CHA University Seongnam Republic of Korea. Institute for Biomedical Informatics CHA University School of Medicine CHA University Seongnam Republic of Korea. Department of Clinical Pharmacology and Therapeutics Seoul National University Hospital Seoul Republic of Korea. Department of Molecular Medicine and Biopharmaceutical Sciences Graduate School of Convergence Science and Technology Seoul National University Seoul Republic of Korea. Advanced Institute of Convergence Technology Suwon Republic of Korea.

Recombinant human interleukin-7 hybrid Fc (rhIL-7-hyFc) is a homodimer of rhIL-7 fused to a hyFc. Exogenous IL-7 promotes T cell proliferation and increases lymphocyte count, making it a potential treatment option for lymphopenia and cancer. To improve therapeutic efficacy, rhIL-7-hyFc was developed as a long-acting IL-7. This study aimed to create a pharmacokinetic model for rhIL-7-hyFc by incorporating neonatal Fc receptor (FcRn)-mediated recycling and target-mediated drug disposition (TMDD) of the IL-7 receptor. Data were collected from a randomized, double-blind, placebo-controlled phase 1 trial involving 30 healthy volunteers who received single doses of rhIL-7-hyFc. Volunteers received 20 or 60 mg/kg subcutaneously, 60 mg/kg intramuscularly (IM), or a placebo. Clinical data were provided by Genexine Inc. (Seoul, Republic of Korea). A TMDD-FcRn-mediated recycling pharmacokinetic model was developed using NONMEM 7.5 software, assisted by PsN 5.3.1 software. A quasi-steady-state approximation was used to describe drug-receptor and drug-FcRn interactions. The model evaluation included goodness of fit, visual predictive checks, and bootstrap analysis. Based on the pharmacokinetic parameters of the final model, a simulation was conducted to select the dosage regimen, ensuring a probability of at least 0.8 for meeting both safety and efficacy criteria. The model successfully described the pharmacokinetic profiles of 24 patients administered rhIL-7-hyFc. Based on the simulation results, 670-800 μg/kg every 3 weeks, 1010-1530 μg/kg every 6 weeks, and 1510-2190 μg/kg every 9 weeks IM were proposed. These results may help further understand rhIL-7-hyFc characteristics and, moreover, provide guidance for selecting the appropriate dosing regimen in future clinical trials.

关键词： lymphopenia optimal dosing for clinical trials rhIL‐7‐hyFc semi‐mechanistic model

来源：评论

学校读者我要写书评

暂无评论

New Tools for Lineage Tracing in Cancer In Vivo

引用

Cancer Biology 1000年第1期7卷 111-129页

作者： Matthew G. Jones Dian Yang Jonathan S. Weissman 2Department of Cellular and Molecular Pharmacology University of California San Francisco San Francisco California USA 1Whitehead Institute for Biomedical Research Howard Hughes Medical Institute David H. Koch Institute for Integrative Cancer Research and Department of Biology Massachusetts Institute of Technology Cambridge Massachusetts USA email: weissman@wi.mit.edudyang@wi.mit.edu 4Center for Computational Biology University of California Berkeley Berkeley California USA 5Center for Personal Dynamic Regulomes Stanford University School of Medicine Stanford California USA 3Biological and Medical Informatics Graduate Program and Integrative Program in Quantitative Biology University of California San Francisco San Francisco California USA

During tumor evolution, cancer cells can acquire the ability to proliferate, invade neighboring tissues, evade the immune system, and spread systemically. Tracking this process remains challenging, as many key events occur stochastically and over long times, which could be addressed by studying the phylogenetic relationships among cancer cells. Several lineage tracing approaches have been developed and employed in many tumor models and contexts, providing critical insights into tumor evolution. Recent advances in single-cell lineage tracing have greatly expanded the resolution, scale, and readout of lineage tracing toolkits. In this review, we provide an overview of static lineage tracing methods, and then focus on evolving lineage tracing technologies that enable reconstruction of tumor phylogenies at unprecedented resolution. We also discuss in vivo applications of these technologies to profile subclonal dynamics, quantify tumor plasticity, and track metastasis. Finally, we highlight outstanding questions and emerging technologies for building comprehensive cancer evolution roadmaps.

关键词： cancer biology lineage tracing single-cell analysis tumor evolution cancer metastasis cell barcoding

来源：评论

学校读者我要写书评

暂无评论

Kidney multiome-based genetic scorecard reveals convergent coding and regulatory variants

引用

Science (New York, N.Y.) 2025年第6734期387卷 eadp4753页

作者： Liu, Hongbo Abedini, Amin Ha, Eunji Ma, Ziyuan Sheng, Xin Dumoulin, Bernhard Qiu, Chengxiang Aranyi, Tamas Li, Shen Dittrich, Nicole Chen, Hua-Chang Tao, Ran Tarng, Der-Cherng Hsieh, Feng-Jen Chen, Shih-Ann Yang, Shun-Fa Lee, Mei-Yueh Kwok, Pui-Yan Wu, Jer-Yuarn Chen, Chien-Hsiun Khan, Atlas Limdi, Nita A. Wei, Wei-Qi Walunas, Theresa L. Karlson, Elizabeth W. Kenny, Eimear E. Luo, Yuan Kottyan, Leah Connolly, John J. Jarvik, Gail P. Weng, Chunhua Shang, Ning Cole, Joanne B. Mercader, Josep M. Mandla, Ravi Majarian, Timothy D. Florez, Jose C. Haas, Mary E. Lotta, Luca A. Drivas, Theodore G. Vy, Ha My T Nadkarni, Girish N. Wiley, Laura K. Wilson, Melissa P. Gignoux, Christopher R. Rasheed, Humaira Thomas, Laurent F. Åsvold, Bjørn Olav Brumpton, Ben M. Hallan, Stein I. Hveem, Kristian Zheng, Jie Hellwege, Jacklyn N. Zawistowski, Matthew Zöllner, Sebastian Franceschini, Nora Hu, Hailong Zhou, Jianfu Kiryluk, Krzysztof Ritchie, Marylyn D. Palmer, Matthew Edwards, Todd L. Voight, Benjamin F. Hung, Adriana M. Susztak, Katalin Department of Medicine Renal Electrolyte and Hypertension Division University of Pennsylvania Philadelphia PA United States Institute of Diabetes Obesity and Metabolism University of Pennsylvania Philadelphia PA United States Department of Genetics University of Pennsylvania Philadelphia PA United States Penn-CHOP Kidney Innovation Center University of Pennsylvania Philadelphia PA United States Liangzhu Laboratory Zhejiang University 1369 West Wenyi Road Hangzhou Zhejiang China Department of Nephrology Children' Hospital Zhejiang University School of Medicine National Clinical Research Center for Child Health Hangzhou Zhejiang China Institute of Molecular Life Sciences HUN-REN Research Center for Natural Sciences Budapest Hungary Department of Molecular Biology Semmelweis University Budapest Hungary Department of Medicine Federal University of São Paulo São Paulo Brazil Department of Biostatistics Vanderbilt University Medical Center Nashville TN United States Vanderbilt Genetics Institute Vanderbilt University Medical Center Nashville TN United States Institute of Clinical Medicine School of Medicine National Yang Ming Chiao Tung University ROC Taipei Taiwan Division of Nephrology Department of Medicine Taipei Veterans General Hospital ROC Taipei Taiwan Institute of Biomedical Sciences Academia Sinica ROC Taipei Taiwan Cardiovascular Center Taichung Veterans General Hospital Taichung Taiwan ROC National Chung Hsing University Taichung Taiwan ROC Heart Rhythm Center Division of Cardiology Department of Medicine Taipei Veterans General Hospital ROC Taipei Taiwan Department of Internal Medicine College of Medicine National Yang Ming Chiao Tung University ROC Taipei Taiwan Institute of Medicine Chung Shan Medical University Taichung Taiwan ROC Department of Medical Research Chung Shan Medical University Hospital Taichung Taiwan ROC Division of Endocrinology and Metabolism Department of Internal Medicine Kaohsiung Medical Universit

Kidney dysfunction is a major cause of mortality, but its genetic architecture remains elusive. In this study, we conducted a multiancestry genome-wide association study in 2.2 million individuals and identified 1026 (97 previously unknown) independent loci. Ancestry-specific analysis indicated an attenuation of newly identified signals on common variants in European ancestry populations and the power of population diversity for further discoveries. We defined genotype effects on allele-specific gene expression and regulatory circuitries in more than 700 human kidneys and 237,000 cells. We found 1363 coding variants disrupting 782 genes, with 601 genes also targeted by regulatory variants and convergence in 161 genes. Integrating 32 types of genetic information, we present the "Kidney Disease Genetic Scorecard" for prioritizing potentially causal genes, cell types, and druggable targets for kidney disease.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Ten simple rules for reproducible research in jupyter notebooks

arXiv

引用

arXiv 2018年

作者： Rule, Adam Birmingham, Amanda Zuniga, Cristal Altintas, Ilkay Huang, Shih-Cheng Knight, Rob Moshiri, Niema Nguyen, Mai H. Rosenthal, Sara Brin Pérez, Fernando Rose, Peter W. Design Lab UC San Diego San DiegoCA United States Center for Computational Biology and Bioinformatics UC San Diego San DiegoCA United States Department of Pediatrics UC San Diego San DiegoCA United States Data Science Hub San Diego Supercomputer Center UC San Diego San DiegoCA United States Departments of Bioengineering and Computer Science and Engineering Center for Microbiome Innovation UC San Diego San DiegoCA United States Bioinformatics and Systems Biology Graduate Program UC San Diego San DiegoCA United States Department of Statistics Berkeley Institute for Data Science UC Berkeley Lawrence Berkeley National Laboratory BerkeleyCA United States Biomedical Informatics Graduate Program Stanford University StanfordCA United States

Reproducibility of computational studies is a hallmark of scientific methodology. It enables researchers to build with confidence on the methods and findings of others, reuse and extend computational pipelines, and thereby drive scientific progress. Since many experimental studies rely on computational analyses, biologists need guidance on how to set up and document reproducible data analyses or simulations. In this paper, we address several questions about reproducibility. For example, what are the technical and non-technical barriers to reproducible computational studies? What opportunities and challenges do computational notebooks offer to overcome some of these barriers? What tools are available and how can they be used effectively? We have developed a set of rules to serve as a guide to scientists with a specific focus on computational notebook systems, such as Jupyter Notebooks, which have become a tool of choice for many applications. Notebooks combine detailed workflows with narrative text and visualization of results. Combined with software repositories and open source licensing, notebooks are powerful tools for transparent, collaborative, reproducible, and reusable data analyses. Copyright © 2018, The Authors. All rights reserved.

关键词： Digital storage

来源：评论

学校读者我要写书评

暂无评论

Nuclear cardiology image enhancement using wavelet transform analysis

引用

Physica Medica 2014年 30卷 e30-e30页

作者： A. Poulakis S. Angelakis G. Fountos G.S. Panagiotakis I. Asteriadis I. Valais Department of Biomedical Engineering Technological Educational Institute of Athens 12210 Athens Greece Biomedical Informatics and Technology Graduate Program School of Computer Science University of Crete Department of Medical Physics Medical School University of Patras 265 00 Patras Greece Department of Nuclear Medicine General Hospital of Kavala 65 500 Kavala Greece

来源：评论

学校读者我要写书评

暂无评论

An artificial intelligence method for vessel detection in images of cardiac catheterization

引用

informatics in Medicine Unlocked 2023年 39卷

作者： Chien, Ting-Ying Ting, Hsien-Wei Li, Hao-Wei Chang, Hsiao-Huang Department of Computer Science and Engineering Yuan Ze University 320 Taoyuan City Taiwan Graduate Program in Biomedical Informatics Yuan Ze University 320 Taoyuan City Taiwan Innovation Center for Big Data and Digital Convergence Yuan Ze University 320 Taoyuan City Taiwan Department of Neurosurgery Taipei Hospital Ministry of Health and Welfare 242 New Taipei City Taiwan Division of Cardiovascular Surgery Department of Surgery Taipei Veterans General Hospital Taipei 11217 Taiwan Department of Surgery School of Medicine College of Medicine Taipei Medical University Taipei 11031 Taiwan

Coronary artery disease (CAD) is one of the top ten leading causes of death in countries worldwide. There are several methods used by physicians to diagnose CAD. One common method is the use of X-ray angiogram (XRA) images. When employing a computer-aided automatic analysis method to locate blood vessels in XRA images, problems such as complex background noise, low contrast, and difficulty in separating blood vessels from the background are encountered, especially for blood vessels with a low contrast to the background noise. In this study, we used various image preprocessing methods to highlight blood vessels from complex backgrounds and different types of blood vessel, followed by the employment of four superpixel segmentation methods to partition an image into multiple segments, and finally the utilization of Weighted Voting to determine the best superpixel algorithm. A genetic algorithm was used to identify the best weights by which to determine the locations of blood vessels in images of cardiac catheterization. Our proposed method achieved an average F1-score of 73.4% in the analysis of five patients, which was better than the other superpixel algorithms tested. The results of this research will be helpful for future SYNTAX score analysis. © 2023

关键词：

来源：评论

学校读者我要写书评

暂无评论

Clinical use of current polygenic risk scores may exacerbate health disparities (vol 51, pg 584, 2019)

引用

NATURE GENETICS 2021年第5期53卷 763-763页

作者： Martin, Alicia R. Kanai, Masahiro Kamatani, Yoichiro Okada, Yukinori Neale, Benjamin M. Daly, Mark J. Analytic and Translational Genetics Unit Massachusetts General Hospital Boston MA USA Program in Medical and Population Genetics Broad Institute of Harvard and MIT Cambridge MA USA Stanley Center for Psychiatric Research Broad Institute of Harvard and MIT Cambridge MA USA Department of Biomedical Informatics Harvard Medical School Boston MA USA Laboratory for Statistical Analysis RIKEN Center for Integrative Medical Sciences Yokohama Japan Institute for Molecular Medicine Finland (FIMM) University of Helsinki Helsinki Finland Kyoto–McGill International Collaborative School in Genomic Medicine Kyoto University Graduate School of Medicine Kyoto Japan Department of Statistical Genetics Osaka University Graduate School of Medicine Suita Japan Laboratory of Statistical Immunology Immunology Frontier Research Center (WPI-IFReC) Osaka University Suita Japan

来源：评论

学校读者我要写书评

暂无评论

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

请选择保存的检索档案：

请选择收藏分类：

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

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

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：