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Patterns of somatic structural variation in human cancer genomes (vol 578, pg 112, 2020)

NATURE 2023年第7948期614卷 E38-E38页

作者： Li, Yilong Roberts, Nicola D. Wala, Jeremiah A. Shapira, Ofer Schumacher, Steven E. Kumar, Kiran Khurana, Ekta Waszak, Sebastian Korbel, Jan O. Haber, James E. Imielinski, Marcin Weischenfeldt, Joachim Beroukhim, Rameen Campbell, Peter J. Cancer Genome Project Wellcome Trust Sanger Institute Hinxton UK Totient Inc Cambridge MA USA Wellcome Sanger Institute Wellcome Genome Campus Hinxton UK Department of Haematology University of Cambridge Cambridge UK Cambridge University Hospitals NHS Foundation Trust Cambridge UK Korea Advanced Institute of Science and Technology Daejeon South Korea Department of Zoology Genetics and Physical Anthropology University of Santiago de Compostela Santiago de Compostela Spain Centre for Research in Molecular Medicine and Chronic Diseases (CIMUS) University of Santiago de Compostela Santiago de Compostela Spain The Biomedical Research Centre (CINBIO) University of Vigo Vigo Spain Centre for Research in Molecular Medicine and Chronic Diseases (CiMUS) Universidade de Santiago de Compostela Santiago de Compostela Spain Department of Zoology Genetics and Physical Anthropology (CiMUS) Universidade de Santiago de Compostela Santiago de Compostela Spain The Biomedical Research Centre (CINBIO) Universidade de Vigo Vigo Spain The Broad Institute of Harvard and MIT Cambridge MA USA Bioinformatics and Integrative Genomics Harvard University Cambridge MA USA Department of Cancer Biology Dana-Farber Cancer Institute Boston MA USA Broad Institute of MIT and Harvard Cambridge MA USA Department of Medical Oncology Dana-Farber Cancer Institute Boston MA USA Harvard Medical School Boston MA USA Massachusetts General Hospital Center for Cancer Research Charlestown MA USA Dana-Farber Cancer Institute Boston MA USA Department of Biostatistics and Computational Biology Dana-Farber Cancer Institute and Harvard Medical School Boston MA USA Weill Cornell Medical College New York NY USA Department of Physiology and Biophysics Weill Cornell Medicine New York NY USA Institute for Computational Biomedicine Weill Cornell Medicine New York NY USA Controlled Department and Institution New York NY USA Englander Institute for Precision Medicine Weill Cornell Medicine Ne

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Gel-Based Chemical Cross-Linking Analysis of 20S Proteasome Subunit-Subunit Interactions in Breast Cancer

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Journal of Huazhong University of science and technology(Medical sciences) 2016年第4期36卷 564-570页

作者：宋海熊华车婧席青松黄柳熊慧华张鹏 Department of Scientific Research and Teaching Tangshan People's Hospital Department of Oncology Tongji Hospital Tongji Medical College Huazhong University of Science and Technology National Biological Experimental Teaching Demonstration Center College of Life Sciences Wuhan University

The ubiquitin-proteasome system plays a pivotal role in breast tumorigenesis by controlling transcription factors, thus promoting cell cycle growth, and degradation of tumor suppressor proteins. However, breast cancer patients have failed to benefit from proteasome inhibitor treatment partially due to proteasome heterogeneity, which is poorly understood in malignant breast neoplasm. Chemical crosslinking is an increasingly important tool for mapping protein three-dimensional structures and proteinprotein interactions. In the present study, two cross-linkers, bis（sulfosuccinimidyl） suberate（BS3） and its water-insoluble analog disuccinimidyl suberate（DSS）, were used to map the subunit-subunit interactions in 20 S proteasome core particle（CP） from MDA-MB-231 cells. Different types of gel electrophoresis technologies were used. In combination with chemical cross-linking and mass spectrometry, we applied these gel electrophoresis technologies to the study of the noncovalent interactions among 20 S proteasome subunits. Firstly, the CP subunit isoforms were profiled. Subsequently, using native/SDSPAGE, it was observed that 0.5 mmol/L BS^3 was a relatively optimal cross-linking concentration for CP subunit-subunit interaction study. 2-DE analysis of the cross-linked CP revealed that α1 might preinteract with α2, and α3 might pre-interact with α4. Moreover, there were different subtypes of α1α2 and α3α4 due to proteasome heterogeneity. There was no significant difference in cross-linking pattern for CP subunits between BS3 and DSS. Taken together, the gel-based characterization in combination with chemical cross-linking could serve as a tool for the study of subunit interactions within a multi-subunit protein complex. The heterogeneity of 20 S proteasome subunit observed in breast cancer cells may provide some key information for proteasome inhibition strategy.

关键词： breast cancer proteasome chemical cross-linking protein-protein interaction three-dimensional gel electrophoresis

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Author Correction: Genomic footprints of activated telomere maintenance mechanisms in cancer (Dec, 10.1038/s41467-019-13824-9, 2022)

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NATURE COMMUNICATIONS 2022年第1期13卷 1-1页

作者： Sieverling, Lina Hong, Chen Koser, Sandra D. Ginsbach, Philip Kleinheinz, Kortine Hutter, Barbara Braun, Delia M. Cortes-Ciriano, Isidro Xi, Ruibin Kabbe, Rolf Park, Peter J. Eils, Roland Schlesner, Matthias Brors, Benedikt Rippe, Karsten Jones, David T. W. Feuerbach, Lars Division of Applied Bioinformatics German Cancer Research Center (DKFZ) 69120 Heidelberg Germany Faculty of Biosciences Heidelberg University 69120 Heidelberg Germany Division of Applied Bioinformatics German Cancer Research Center (DKFZ) Heidelberg Germany Faculty of Biosciences Heidelberg University Heidelberg Germany Division of Theoretical Bioinformatics German Cancer Research Center (DKFZ) 69120 Heidelberg Germany Department for Bioinformatics and Functional Genomics Institute for Pharmacy and Molecular Biotechnology (IPMB) and BioQuant 69120 Heidelberg Germany Division of Theoretical Bioinformatics German Cancer Research Center (DKFZ) Heidelberg Germany Institute of Pharmacy and Molecular Biotechnology and BioQuant Heidelberg University Heidelberg Germany German Cancer Consortium (DKTK) Heidelberg Germany National Center for Tumor Diseases (NCT) Heidelberg Heidelberg Germany Heidelberg Center for Personalized Oncology (DKFZ-HIPO) German Cancer Research Center (DKFZ) Heidelberg Germany German Cancer Consortium (DKTK) German Cancer Research Center (DKFZ) Heidelberg Germany Division of Chromatin Networks German Cancer Research Center (DKFZ) and BioQuant 69120 Heidelberg Germany Department of Biomedical Informatics Harvard Medical School Boston Massachusetts 02115 USA Department of Chemistry Centre for Molecular Science Informatics University of Cambridge Cambridge CB2 1EW UK Ludwig Center at Harvard Medical School Boston Massachusetts 02115 USA Department of Biomedical Informatics Harvard Medical School Boston MA USA Department of Chemistry Centre for Molecular Science Informatics University of Cambridge Cambridge UK Ludwig Center at Harvard Medical School Boston MA USA School of Mathematical Sciences and Center for Statistical Science Peking University Beijing 100871 China Heidelberg University Heidelberg Germany New BIH Digital Health Center Berlin Institute of Health (BIH) and Charité - Universitätsmedizin Berlin Berlin Germany Bioi

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Statistical methods to evaluate important degrees of document features 5

Statistical methods to evaluate important degrees of documen...

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5th International Conference on computer Engineering and Networks, CENet 2015

作者： Hou, Xia Li, Ning Yang, Hong-Bo Computer School Beijing Information Science and Technology University Beijing100101 China Beijing Key Laboratory of Internet Culture and Digital Dissemination Research Beijing100101 China Experimental Teaching Center of Electronics information and Control Beijing Information Science and Technology University Beijing100101 China

Documents are often analyzed based on the features. Evaluation of the degree of importance of such features is the basic work of document analysis. Now, the work is primarily done by the human beings although the workload is excessively large and the results are subjective. Three statistical methods are hereby proposed on the basis of the actual usage of features in a large number of documents. The statistical values and those from experts are contrasted and analyzed. And then a selection based on voting thus is given. Some results from 500 document samples are also given. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Statistical methods

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Author Correction: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

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Scientific data 2021年第1期8卷 72页

作者： Gilberto Pastorello Carlo Trotta Eleonora Canfora Housen Chu Danielle Christianson You-Wei Cheah Cristina Poindexter Jiquan Chen Abdelrahman Elbashandy Marty Humphrey Peter Isaac Diego Polidori Markus Reichstein Alessio Ribeca Catharine van Ingen Nicolas Vuichard Leiming Zhang Brian Amiro Christof Ammann M Altaf Arain Jonas Ardö Timothy Arkebauer Stefan K Arndt Nicola Arriga Marc Aubinet Mika Aurela Dennis Baldocchi Alan Barr Eric Beamesderfer Luca Belelli Marchesini Onil Bergeron Jason Beringer Christian Bernhofer Daniel Berveiller Dave Billesbach Thomas Andrew Black Peter D Blanken Gil Bohrer Julia Boike Paul V Bolstad Damien Bonal Jean-Marc Bonnefond David R Bowling Rosvel Bracho Jason Brodeur Christian Brümmer Nina Buchmann Benoit Burban Sean P Burns Pauline Buysse Peter Cale Mauro Cavagna Pierre Cellier Shiping Chen Isaac Chini Torben R Christensen James Cleverly Alessio Collalti Claudia Consalvo Bruce D Cook David Cook Carole Coursolle Edoardo Cremonese Peter S Curtis Ettore D'Andrea Humberto da Rocha Xiaoqin Dai Kenneth J Davis Bruno De Cinti Agnes de Grandcourt Anne De Ligne Raimundo C De Oliveira Nicolas Delpierre Ankur R Desai Carlos Marcelo Di Bella Paul di Tommasi Han Dolman Francisco Domingo Gang Dong Sabina Dore Pierpaolo Duce Eric Dufrêne Allison Dunn Jiří Dušek Derek Eamus Uwe Eichelmann Hatim Abdalla M ElKhidir Werner Eugster Cacilia M Ewenz Brent Ewers Daniela Famulari Silvano Fares Iris Feigenwinter Andrew Feitz Rasmus Fensholt Gianluca Filippa Marc Fischer John Frank Marta Galvagno Mana Gharun Damiano Gianelle Bert Gielen Beniamino Gioli Anatoly Gitelson Ignacio Goded Mathias Goeckede Allen H Goldstein Christopher M Gough Michael L Goulden Alexander Graf Anne Griebel Carsten Gruening Thomas Grünwald Albin Hammerle Shijie Han Xingguo Han Birger Ulf Hansen Chad Hanson Juha Hatakka Yongtao He Markus Hehn Bernard Heinesch Nina Hinko-Najera Lukas Hörtnagl Lindsay Hutley Andreas Ibrom Hiroki Ikawa Marcin Jackowicz-Korczynski Dalibor Janouš Wilma Jans Rachhpal Jassal Shicheng Jiang Tomomichi Kato Myr Computational Research Division Lawrence Berkeley National Laboratory Berkeley CA 94720 USA. gzpastorello@lbl.gov. DIBAF University of Tuscia Viterbo 01100 Italy. Euro-Mediterranean Centre on Climate Change Foundation (CMCC) Lecce 73100 Italy. Climate & Ecosystem Sciences Division Lawrence Berkeley National Laboratory Berkeley CA 94720 USA. Computational Research Division Lawrence Berkeley National Laboratory Berkeley CA 94720 USA. Department of Civil Engineering California State University Sacramento CA 95819 USA. Department of Geography Environment and Spatial Sciences Michigan State University East Lansing MI 48823 USA. Department of Computer Science University of Virginia Charlottesville VA 22904 USA. TERN Ecosystem Processes Menzies Creek VIC3159 Australia. Max Planck Institute for Biogeochemistry Jena 07701 Germany. Laboratoire des Sciences du Climat et de l'Environnement (LSCE) CEA CNRS UVSQ UPSACLAY Gif sur Yvette 91190 France. Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 China. Department of Soil Science University of Manitoba Winnipeg MB R3T2N2 Canada. Department of Agroecology and Environment Agroscope Research Institute Zürich 8046 Switzerland. School of Geography and Earth Sciences McMaster University L8S4K1 Hamilton ON Canada. Department of Physical Geography and Ecosystem Science Lund University Lund 22362 Sweden. Department of Agronomy and Horticulture University of Nebraska-Lincoln Lincoln NE 68583 USA. School of Ecosystem and Forest Sciences The University of Melbourne Richmond VIC3121 Australia. Department of Biology Research Group PLECO University of Antwerp Antwerp 2610 Belgium. Joint Research Centre European Commission Ispra 21027 Italy. TERRA Teaching and Research Center University of Liege Gembloux B-5030 Belgium. Finnish Meteorological Institute Helsinki 00560 Finland. ES

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Pulse Diagnosis Signals Analysis of Fatty Liver Disease and Cirrhosis Patients by Using Machine Learning

Scientific World Journal

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Scientific World Journal 2015年第1期2015卷 859192页

作者： Nanyue, Wang Youhua, Yu Dawei, Huang Bin, Xu Jia, Liu Tongda, Li Liyuan, Xue Zengyu, Shan Yanping, Chen Jia, Wang Experimental Research Center China Academy of Chinese Medical Sciences Beijing 100700 China Department of Computer Science and Technology Tsinghua University Beijing 100084 China GULOU Hospital of TCM of Beijing Beijing 100009 China Tai Yang Gong Health Care Center Chaoyang District Beijing 100102 China Shi Xuemin Academician Office First Teaching Hospital Tianjin University of Traditional Chinese Medicine Tianjin 300193 China

Objective. To compare the signals of pulse diagnosis of fatty liver disease (FLD) patients and cirrhosis patients. Methods. After collecting the pulse waves of patients with fatty liver disease, cirrhosis patients, and healthy volunteers, we do pretreatment and parameters extracting based on harmonic fitting, modeling, and identification by unsupervised learning Principal Component Analysis (PCA) and supervised learning Least squares Regression (LS) and Least Absolute Shrinkage and Selection Operator (LASSO) with cross-validation step by step for analysis. Results. There is significant difference between the pulse diagnosis signals of healthy volunteers and patients with FLD and cirrhosis, and the result was confirmed by 3 analysis methods. The identification accuracy of the 1st principal component is about 75% without any classification formation by PCA, and supervised learning's accuracy (LS and LASSO) was even more than 93% when 7 parameters were used and was 84% when only 2 parameters were used. Conclusion. The method we built in this study based on the combination of unsupervised learning PCA and supervised learning LS and LASSO might offer some confidence for the realization of computer-aided diagnosis by pulse diagnosis in TCM. In addition, this study might offer some important evidence for the science of pulse diagnosis in TCM clinical diagnosis. © 2015 Wang Nanyue et al.

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Statistical Methods to Evaluate Important Degrees of Document Features

Statistical Methods to Evaluate Important Degrees of Documen...

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2014全国文档信息处理学术会议

作者： Xia HOU Ning LI Hong-bo YANG Experimental Teaching Center of Electronics information and Control Beijing Information Science and Technology University Beijing Key Laboratory of Internet Culture and Digital Dissemination Research Computer School Beijing Information Science and Technology UniversityBeijingChina

Documents are often analyzed based on *** of important degrees of features is a basic work of document *** this work is done mainly by human,so the workload is too large and results are *** statistical methods are proposed based on the actual usage of features in a large number of *** statistical values and those from experts are contrasted and analyzed,and then a selection result based on voting is *** results from 500 document samples are given.

关键词： document format document feature statistics document processing

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vCourse: A Course Platform Based on Virtualization technology

vCourse: A Course Platform Based on Virtualization Technolog...

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2013年教育技术与管理科学国际会议

作者： Yu Liu Jinmo Wang National Experimental Teaching Demonstration Center CSE Department Beihang University School of Computer Science and Technology Beihang University

This paper presents a platform named vCourse based on the virtualization technology. vCourse supports multiple operation systems and multiple courses online. Teachers can create a course template and deploy it as many virtual machines. Students can do their exercises on those virtual machines and interact with others and the teacher. The features, structure and key mechanisms of vCourse are discussed in this paper. Two experiments are designed to evaluate the performance of vCourse. According to the test results, vCourse can run the typical software smoothly and is not very sensitive on the virtual machine numbers.

关键词： virtualization technology virtual classroom distance education experiment education

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Reliability analysis of task model in real-time fault-tolerant systems

Reliability analysis of task model in real-time fault-tolera...

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2012 IEEE 12th International Conference on computer and Information technology, CIT 2012

作者： Gui, Shenglin Luo, Lei National Computer Experimental Teaching Demonstration Center School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu 611731 China

ISBN: (纸本)9780769548586

One notable advantage of Model-Driven Architecture(MDA) method is that software developers could do sufficient analysis and tests on software models in the design phase, which helps construct high confidence on the expected software performance and behaviors. In this paper, we present a general reliability model, based on the relationship between real-time requirements and time costs of fault tolerance, to analyze reliability of the task execution model in real-time software design phase when using MDA method. This reliability model defines arrival rates of faults and fault-tolerant mechanisms to model non-permanent faults and the corresponding fault handling costs. By analyzing the probability of tasks being schedulable in the worst-case execution scenario, reliability and schedulability are combined into an unified analysis framework, and an algorithm for reliability analysis is also given under static priority scheduling. When no assumptions of fault occurrences made on the task model, this reliability model regresses to a generic schedulability model. © 2012 IEEE.

关键词： Reliability analysis

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Performance improvement of InGaN blue light-emitting diodes with several kinds of electron-blocking layers

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Chinese Physics B 2012年第5期21卷 686-691页

作者：陈峻范广涵张运炎庞玮郑树文姚光锐 Institute of Opto-Electronic Materials and Technology South China Normal University Experimental Teaching Center Guangdong University of Technology Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology

The performance of InGaN blue light-emitting diodes（LEDs） with different kinds of electron-blocking layers is investigated *** compare the simulated emission spectra,electron and hole concentrations,energy band diagrams,electrostatic fields,and internal quantum efficiencies of the *** LED using AlGaN with gradually increasing Al content from 0% to 20% as the electron-blocking layer（EBL） has a strong spectrum intensity,mitigates efficiency droop,and possesses higher output power compared with the LEDs with the other three types of *** advantages could be because of the lower electron leakage current and more effective hole *** optical performance of the specifically designed LED is also improved in the case of large injection current.

关键词： electron-blocking layer light-emitting diode internal quantum efficiency

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