Automated Malware Analysis Report for Imageio-2.8.0
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Other Departments and Institutes Courses 1
Other Departments and Institutes Courses 1 Other Departments and Institutes Courses About Course Numbers: 02-250 Introduction to Computational Biology Each Carnegie Mellon course number begins with a two-digit prefix that Spring: 12 units designates the department offering the course (i.e., 76-xxx courses are This class provides a general introduction to computational tools for biology. offered by the Department of English). Although each department maintains The course is divided into two halves. The first half covers computational its own course numbering practices, typically, the first digit after the prefix molecular biology and genomics. It examines important sources of biological indicates the class level: xx-1xx courses are freshmen-level, xx-2xx courses data, how they are archived and made available to researchers, and what are sophomore level, etc. Depending on the department, xx-6xx courses computational tools are available to use them effectively in research. may be either undergraduate senior-level or graduate-level, and xx-7xx In the process, it covers basic concepts in statistics, mathematics, and courses and higher are graduate-level. Consult the Schedule of Classes computer science needed to effectively use these resources and understand (https://enr-apps.as.cmu.edu/open/SOC/SOCServlet/) each semester for their results. Specific topics covered include sequence data, searching course offerings and for any necessary pre-requisites or co-requisites. and alignment, structural data, genome sequencing, genome analysis, genetic variation, gene and protein expression, and biological networks and pathways. The second half covers computational cell biology, including biological modeling and image analysis. It includes homework requiring Computational Biology Courses modification of scripts to perform computational analyses. -
Analysis of Cell-Based Rnai Screens Comment Michael Boutros*, Lígia P Brás†‡ and Wolfgang Huber†
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Springer - Publisher Connector Open Access Software2006BoutrosetVolume al. 7, Issue 7, Article R66 Analysis of cell-based RNAi screens comment Michael Boutros*, Lígia P Brás†‡ and Wolfgang Huber† Addresses: *Signaling and Functional Genomics, German Cancer Research Center, Im Neuenheimer Feld 580, 69120 Heidelberg, Germany. †EMBL - European Bioinformatics Institute, Cambridge CB10 1SD, UK. ‡Centre for Chemical and Biological Engineering, IST, Technical University of Lisbon, Av. Rovisco Pais, P-1049-001 Lisbon, Portugal. Correspondence: Michael Boutros. Email: [email protected]. Wolfgang Huber. Email: [email protected] reviews Published: 25 July 2006 Received: 27 March 2006 Revised: 7 June 2006 Genome Biology 2006, 7:R66 (doi:10.1186/gb-2006-7-7-r66) Accepted: 25 July 2006 The electronic version of this article is the complete one and can be found online at http://genomebiology.com/2006/7/7/R66 © 2006 Boutros et al.; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. reports Analysis<p>cellHTS of cell-based is a new method RNAi screens for the analysis and documentation of RNAi screens.</p> Abstract RNA interference (RNAi) screening is a powerful technology for functional characterization of deposited research biological pathways. Interpretation of RNAi screens requires computational and statistical analysis techniques. We describe a method that integrates all steps to generate a scored phenotype list from raw data. -
Simpleitk Tutorial Image Processing for Mere Mortals
SimpleITK Tutorial Image processing for mere mortals Insight Software Consortium Sept 23, 2011 (Insight Software Consortium) SimpleITK - MICCAI 2011 Sept 2011 1 / 142 This presentation is copyrighted by The Insight Software Consortium distributed under the Creative Commons by Attribution License 3.0 http://creativecommons.org/licenses/by/3.0 What this Tutorial is about Provide working knowledge of the SimpleITK platform (Insight Software Consortium) SimpleITK - MICCAI 2011 Sept 2011 3 / 142 Program Virtual Machines Preparation (10min) Introduction (15min) Basic Tutorials I (45min) Short Break (10min) Basic Tutorials II (45min) Co↵ee Break (30min) Intermediate Tutorials (45min) Short Break (10min) Advanced Topics (40min) Wrap-up (10min) (Insight Software Consortium) SimpleITK - MICCAI 2011 Sept 2011 4 / 142 Tutorial Goals Gentle introduction to ITK Introduce SimpleITK Provide hands-on experience Problem solving, not direction following ...but please follow directions! (Insight Software Consortium) SimpleITK - MICCAI 2011 Sept 2011 13 / 142 ITK Overview How many are familiar with ITK? (Insight Software Consortium) SimpleITK - MICCAI 2011 Sept 2011 14 / 142 Ever seen code like this? 1 // Setup image types. 2 typedef float InputPixelType ; 3 typedef float OutputPixelType ; 4 typedef itk ::Image<InputPixelType ,2> InputImageType ; 5 typedef itk ::Image<OutputPixelType,2> OutputImageType ; 6 // Filter type 7 typedef itk ::DiscreteGaussianImageFilter< 8 InputImageType , OutputImageType > 9 FilterType ; 10 // Create a filter 11 FilterType ::Pointer filter = FilterType ::New (); 12 // Create the pipeline 13 filter >SetInput( reader >GetOutput () ); 14 filter−>SetVariance(1.0);− 15 filter−>SetMaximumKernelWidth(5); 16 filter−>Update (); 17 OutputImageType− ::Pointer blurred = filter >GetOutput (); − (Insight Software Consortium) SimpleITK - MICCAI 2011 Sept 2011 15 / 142 We are here to tell you that you can.. -
Annexes : Installation Du Logiciel R Et Des Packages R
Annexes : Installation du logiciel R et des packages R Pr´e-requis et objectif • Aucun pr´e-requis n’est n´ecessaire.La lecture du chapitre 1 pourrait tou- tefois se r´ev´eler int´eressante. • Ce chapitre d´ecritcomment installer le logiciel R, dans sa version x (rem- placer partout dans le reste de ce document x par le num´ero de la derni`ere version disponible), sous le syst`emed’exploitation Microsoft Windows et aussi comment ajouter des packages suppl´ementaires sous Windows ou sous Linux. SECTION C.1 Installation de R sous Microsoft Windows Commencez par t´el´echarger le logiciel R (fichier R-x-win.exe o`u x est le nu- m´ero de la derni`ereversion disponible) `a l’aide de votre navigateur web usuel `a l’adresse suivante : http://cran.r-project.org/bin/windows/base/ Enregistrez ensuite ce fichier ex´ecutable sur le bureau de Windows puis double- cliquez sur le fichier R-x-win.exe dont voici l’icˆone : . Le logiciel s’installe alors et vous n’avez plus qu’`a suivre les instructions qui s’affichent et `a conserver les options propos´ees par d´efaut. Lorsque l’icˆone est ajout´ee sur le bureau, l’installation peut ˆetre consi- d´er´ee comme termin´ee. 574 Le logiciel R SECTION C.2 Installation de packages suppl´ementaires De nombreux modules (packages ou librairies) suppl´ementaires sont dispo- nibles sur le site internet : http://cran.r-project.org/web/packages/available_packages_by_name. html, ou bien encore ici : http://cran.r-project.org/bin/windows/contrib/, dans le dossier corres- pondant au num´ero x de votre version de R. -
December 2016, Volume 34 No.2
ISSN 0735-1348 Department of Physics, East Carolina University, 1000 East 5th Street, Greenville, NC 27858, USA http://www.ecu.edu/cs-cas/physics/ancient-timeline/ December 2016, Volume 34 No.2 IRSL dating of fast-fading sanidine feldspars from Sulawesi, Indonesia 1 Bo Li, Richard G. Roberts, Adam Brumm, Yu-Jie Guo, Budianto Hakim, Muhammad Ramli, Maxime Aubert, Rainer Grün, Jian-xin Zhao, E. Wahyu Saptomo Bayesian statistics in luminescence dating: The ‘baSAR’-model and its 14 implementation in the R package ‘Luminescence’ Norbert Mercier, Sebastian Kreutzer, Claire Christophe, Guillaume Guérin, Pierre Guibert, Christelle Lahaye, Philippe Lanos, Anne Philippe, and Chantal Tribolo RLumShiny - A graphical user interface for the R Package ‘Luminescence’ 22 Christoph Burow, Sebastian Kreutzer, Michael Dietze, Margret C. Fuchs, Manfred Fischer, Christoph Schmidt, Helmut Brückner Thesis abstracts 33 Bibliography 36 Ancient TL Started by the late David Zimmerman in 1977 EDITOR Regina DeWitt, Department of Physics, East Carolina University, Howell Science Complex, 1000 E. 5th Street Greenville, NC 27858, USA; Tel: +252-328-4980; Fax: +252-328-0753 ([email protected]) EDITORIAL BOARD Ian K. Bailiff, Luminescence Dating Laboratory, Univ. of Durham, Durham, UK ([email protected]) Geoff A.T. Duller, Institute of Geography and Earth Sciences, Aberystwyth University, Ceredigion, Wales, UK ([email protected]) Sheng-Hua Li, Department of Earth Sciences, The University of Hong Kong, Hong Kong, China ([email protected]) Shannon Mahan, U.S. Geological Survey, Denver Federal Center, Denver, CO, USA ([email protected]) Richard G. Roberts, School of Earth and Environmental Sciences, University of Wollongong, Australia ([email protected]) REVIEWERS PANEL Richard M. -
MRI-Based Radiomics Analysis for the Pretreatment Prediction Of
cancers Article MRI-Based Radiomics Analysis for the Pretreatment Prediction of Pathologic Complete Tumor Response to Neoadjuvant Systemic Therapy in Breast Cancer Patients: A Multicenter Study Renée W. Y. Granzier 1,2,* , Abdalla Ibrahim 2,3,4,5,6,† , Sergey P. Primakov 2,4,†, Sanaz Samiei 1,2,3, Thiemo J. A. van Nijnatten 3 , Maaike de Boer 2,7, Esther M. Heuts 1 , Frans-Jan Hulsmans 8, Avishek Chatterjee 2,4 , Philippe Lambin 2,3,4 , Marc B. I. Lobbes 2,3,8 , Henry C. Woodruff 2,3,4,‡ and Marjolein L. Smidt 1,3,‡ 1 Department of Surgery, Maastricht University Medical Center+, P.O. Box 5800, 6202 AZ Maastricht, The Netherlands; [email protected] (S.S.); [email protected] (E.M.H.); [email protected] (M.L.S.) 2 GROW-School for Oncology and Developmental Biology, Maastricht University, P.O. Box 616, 6200 MD Maastricht, The Netherlands; [email protected] (A.I.); Citation: Granzier, R.W.Y.; Ibrahim, [email protected] (S.P.P.); [email protected] (M.d.B.); A.; Primakov, S.P.; Samiei, S.; van [email protected] (A.C.); [email protected] (P.L.); Nijnatten, T.J.A.; de Boer, M.; Heuts, [email protected] (M.B.I.L.); [email protected] (H.C.W.) 3 E.M.; Hulsmans, F.-J.; Chatterjee, A.; Department of Radiology and Nuclear Medicine, Maastricht University Medical Center+, P.O. Box 5800, Lambin, P.; et al. MRI-Based 6202 AZ Maastricht, The Netherlands; [email protected] 4 The D-Lab, Department of Precision Medicine, Maastricht University, Universiteitssingel -
Raluca-Maria Sandu RESEARCHER · DATA Scientist [email protected] | Rmsandu.Github.Io | Rmsandu | Rmsandu
Raluca-Maria Sandu RESEARCHER · DATA SCiENTiST [email protected] | rmsandu.github.io | rmsandu | rmsandu About Me I am a perseverant and resourceful scientific professional who just finished their PhD Degree in Biomedical Engineering at the University of Bern, previously having graduated with an MSc in the same field, and a BSc in Control Engineering and Applied Computer Science. I am specialized in working on data science and research & development projects across various topics as evidenced by my work experience and studies. Work Experience University of Bern, ARTORG Center for Biomedical Engineering Research Bern, Switzerland DOCTORAL CANDiDATE (PHD) May 2017 ‑ Feb. 2021 • Worked with data mining, image processing & registration, radiomics & feature extraction, statistics, and machine learning algorithms in the area of CT‑guided ablation treatments for liver cancer by using Python and R programming languages. • Developed a quantitative and numerical evaluation method based on DICOM image segmentations for assessing the success of liver ablation treatments which was published in a peer‑reviewed journal. More info here. Philips Research, Personal Care and Wellness Eindhoven, The Netherlands RESEARCH AND DEVELOPMENT GRADUATE STUDENT Jul. 2016 ‑ Mar. 2017 • Designed and developed a web‑based application for image annotation using JavaScript, HTML and CSS that can be found here. • Applied image processing and machine learning algorithms in Python (SVM, PCA, Random Forests) for classification of skin surface structures. Philips Research, Personal Care and Wellness Eindhoven, The Netherlands RESEARCH AND DEVELOPMENT INTERNSHiP Apr. 2016 ‑ Jun. 2016 • Contributed with exploratory 2D image analysis in Python to quantify the effect of various diets on physical appearance at skin surface. -
GNC Khan-Academy Una Estrategia.Pdf
Revista de Pedagogía ESCUELA DE EDUCACIÓN FACULTAD DE HUMANIDADES Y EDUCACIÓN UNIVERSIDAD CENTRAL DE VENEZUELA Depósito Legal pp. 197102DF193 ISSN N° 0798-9792 Caracas, julio-diciembre 2018, vol. 39, nº 105 Publicación semestral Director-Editor Ramón Alexander Uzcátegui Pacheco (Universidad Central de Venezuela) Consejo Editor Ángel Alvarado (Universidad Central de Venezuela) Doris Villaroel (Universidad Central de Venezuela) María Janet Ríos (Universidad Central de Venezuela) Mariángeles Payer (Universidad Central de Venezuela) Rosa Leonor Junguittu (Universidad Central de Venezuela) Eduardo Cavieres Fernández (Universidad de Playa Ancha, Chile) Maria Helena Michels (Universidade Federal de Santa Catarina, Brasil) Versión electrónica de la Revista Saber UCV, Redalyc, Revencyt y Scopus Consejo Asesor Carlos Eduardo Blanco (Universidad Central de Venezuela) Luis Bravo Jáuregui (Universidad Central de Venezuela) Aurora Lacueva (Universidad Central de Venezuela) Nacarid Rodríguez (Universidad Central de Venezuela) Juan Haro (Universidad Central de Venezuela) Alexandra Mulino (Universidad Central de Venezuela) Traducciones y Correcciones Gabriela Delgado Montoya Mariel Escuela de Educación - UCV Apoyo Secretarial y Logístico Luzmelys Martínez Judith Solórzano Consejo Asesor Honorario Internacional Martha Aguirre, Universidad Católica Boliviana “Santa Cruz” Ana Lupita Chaves Salas, Universidad de Costa Rica Carlos Miñana Blasco, Universidad Nacional de Colombia Ángel Pérez Gómez, Universidad de Málaga César Coll, Universidad de Barcelona Fernando -
Implementing the DICOM Standard for Digital Pathology
[Downloaded free from http://www.jpathinformatics.org on Tuesday, May 7, 2019, IP: 4.16.85.218] Original Article Implementing the DICOM Standard for Digital Pathology Markus D. Herrmann1, David A. Clunie2, Andriy Fedorov3,4, Sean W. Doyle1, Steven Pieper5, Veronica Klepeis4,6, Long P. Le4,6, George L. Mutter4,7, David S. Milstone4,7, Thomas J. Schultz8, Ron Kikinis3,4, Gopal K. Kotecha1, David H. Hwang4,7, Katherine P. Andriole1,4,9, A. John Iafrate4,6, James A. Brink4,10, Giles W. Boland4,9, Keith J. Dreyer1,4,10, Mark Michalski1,4,10, Jeffrey A. Golden4,7, David N. Louis4,6, Jochen K. Lennerz4,6 1MGH and BWH Center for Clinical Data Science, 3Department of Radiology, Surgical Planning Laboratory, Brigham and Women’s Hospital, 4Harvard Medical School, Departments of 6Pathology and 10Radiology, Massachusetts General Hospital, Departments of 7Pathology and 9Radiology, Brigham and Women’s Hospital, 8Enterprise Medical Imaging, Massachusetts General Hospital, Boston, MA, 5Isomics, Inc., Cambridge, MA, USA, 2PixelMed Publishing, LLC, Bangor, PA, USA Received: 30 July 2018 Accepted: 06 August 2018 Published: 02 November 2018 Abstract Background: Digital Imaging and Communications in Medicine (DICOM®) is the standard for the representation, storage, and communication of medical images and related information. A DICOM file format and communication protocol for pathology have been defined; however, adoption by vendors and in the field is pending. Here, we implemented the essential aspects of the standard and assessed its capabilities and limitations in a multisite, multivendor healthcare network. Methods: We selected relevant DICOM attributes, developed a program that extracts pixel data and pixel-related metadata, integrated patient and specimen-related metadata, populated and encoded DICOM attributes, and stored DICOM files. -
Bioconductor Annual Report 2011
Bioconductor Annual Report 2011 Martin Morgan Fred Hutchinson Cancer Research Center July 2011 Contents 1 Project Scope1 1.1 Packages................................1 1.2 Courses and Conferences.......................2 1.3 Community..............................3 1.4 Publication..............................3 1.5 Funding................................4 2 Core Tasks & Capabilities5 2.1 Automated Package Building and Testing.............5 2.2 Package submission management..................5 2.3 Annotation data package building..................6 2.4 Other Tasks..............................6 2.5 Hardware...............................6 2.6 Key Personnel.............................6 A Appendix: Proposal Specific Aims 11 1 Project Scope Bioconductor provides access to software for the analysis and comprehension of high throughput genomic data. Packages are written in the R programming lan- guage by members of the Bioconductor team and the international community. Bioconductor was started approximately 10 years ago (Fall, 2001) by Dr. Robert Gentleman and others, and now consists of >460 packages for the analysis of data ranging from expression microarrays through next-generation sequencing. 1.1 Packages R software packages represent the primary product of the Bioconductor project. Packages are produced by the Bioconductor team or are from international con- tributors. Table1 summarizes growth in the number of packages hosted by 1 Table 1: Number of contributed packages included in each Bioconductor release. Releases occur twice per year. Release N Release N Release N 2002 1.0 15 2006 1.8 172 2010 2.6 389 1.1 20 1.9 188 2.7 419 2003 1.2 30 2007 2.0 214 2011 2.8 467 1.3 49 2.1 233 2004 1.4 81 2008 2.2 260 1.5 100 2.3 294 2005 1.6 123 2009 2.4 320 1.7 141 2.5 352 Bioconductor, with 467 packages available in the current release. -
Virtual Communities for Parents of Children with Special Needs in Taiwan: Emotional Support, Information, and Advocacy
Virtual communities for parents of children with special needs in Taiwan: Emotional support, information, and advocacy A thesis submitted to the University of Manchester for the degree of Doctor of Philosophy in the Faculty of Humanities 2017 I-Jung, Lu Manchester Institute of Education School of Environment, Education and Development List of Contents LIST OF CONTENTS ................................................................................................. 1 LIST OF TABLES ....................................................................................................... 6 LIST OF FIGURES ..................................................................................................... 7 ABSTRACT .................................................................................................................. 8 DECLARATION.......................................................................................................... 9 COPYRIGHT STATEMENT ..................................................................................... 9 ACKNOWLEDGEMENT ......................................................................................... 10 GLOSSARY................................................................................................................ 11 CHAPTER 1. INTRODUCTION ............................................................................. 14 1.1 Parents in the virtual world ................................................................... 14 1.2 Support for parents .................................................................................. -
3D Slicer Documentation
3D Slicer Documentation Slicer Community Sep 25, 2021 CONTENTS 1 About 3D Slicer 3 1.1 What is 3D Slicer?............................................3 1.2 License..................................................4 1.3 How to cite................................................5 1.4 Acknowledgments............................................7 1.5 Commercial Use.............................................8 1.6 Contact us................................................9 2 Getting Started 11 2.1 System requirements........................................... 11 2.2 Installing 3D Slicer............................................ 12 2.3 Using Slicer............................................... 14 2.4 Glossary................................................. 19 3 Get Help 23 3.1 I need help in using Slicer........................................ 23 3.2 I want to report a problem........................................ 23 3.3 I would like to request enhancement or new feature........................... 24 3.4 I would like to let the Slicer community know, how Slicer helped me in my research......... 24 3.5 Troubleshooting............................................. 24 4 User Interface 27 4.1 Application overview........................................... 27 4.2 Review loaded data............................................ 29 4.3 Interacting with views.......................................... 31 4.4 Mouse & Keyboard Shortcuts...................................... 35 5 Data Loading and Saving 37 5.1 DICOM data..............................................