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Feature Tracking & Visualization in 'Visit'
FEATURE TRACKING & VISUALIZATION IN ‘VISIT’ By NAVEEN ATMAKURI A thesis submitted to the Graduate School—New Brunswick Rutgers, The State University of New Jersey in partial fulfillment of the requirements for the degree of Master of Science Graduate Program in Electrical and Computer Engineering written under the direction of Professor Deborah Silver and approved by New Brunswick, New Jersey October 2010 ABSTRACT OF THE THESIS Feature Tracking & Visualization in VisIt by Naveen Atmakuri Thesis Director: Professor Deborah Silver The study and analysis of large experimental or simulation datasets in the field of science and engineering pose a great challenge to the scientists. These complex simulations generate data varying over a period of time. Scientists need to glean large quantities of time-varying data to understand the underlying physical phenomenon. This is where visualization tools can assist scientists in their quest for analysis and understanding of scientific data. Feature Tracking, developed at Visualization & Graphics Lab (Vizlab), Rutgers University, is one such visualization tool. Feature Tracking is an automated process to isolate and analyze certain regions or objects of interest, called ‘features’ and to highlight their underlying physical processes in time-varying 3D datasets. In this thesis, we present a methodology and documentation on how to port ‘Feature Tracking’ into VisIt. VisIt is a freely available open-source visualization software package that has a rich feature set for visualizing and analyzing data. VisIt can successfully handle massive data quantities in the range of tera-scale. The technology covered by this thesis is an improvement over the previous work that focused on Feature Tracking in VisIt. -
Python for Economists Alex Bell
Python for Economists Alex Bell [email protected] http://xkcd.com/353 This version: October 2016. If you have not already done so, download the files for the exercises here. Contents 1 Introduction to Python 3 1.1 Getting Set-Up................................................. 3 1.2 Syntax and Basic Data Structures...................................... 3 1.2.1 Variables: What Stata Calls Macros ................................ 4 1.2.2 Lists.................................................. 5 1.2.3 Functions ............................................... 6 1.2.4 Statements............................................... 7 1.2.5 Truth Value Testing ......................................... 8 1.3 Advanced Data Structures .......................................... 10 1.3.1 Tuples................................................. 10 1.3.2 Sets .................................................. 11 1.3.3 Dictionaries (also known as hash maps) .............................. 11 1.3.4 Casting and a Recap of Data Types................................. 12 1.4 String Operators and Regular Expressions ................................. 13 1.4.1 Regular Expression Syntax...................................... 14 1.4.2 Regular Expression Methods..................................... 16 1.4.3 Grouping RE's ............................................ 18 1.4.4 Assertions: Non-Capturing Groups................................. 19 1.4.5 Portability of REs (REs in Stata).................................. 20 1.5 Working with the Operating System.................................... -
Open Babel Documentation Release 2.3.1
Open Babel Documentation Release 2.3.1 Geoffrey R Hutchison Chris Morley Craig James Chris Swain Hans De Winter Tim Vandermeersch Noel M O’Boyle (Ed.) December 05, 2011 Contents 1 Introduction 3 1.1 Goals of the Open Babel project ..................................... 3 1.2 Frequently Asked Questions ....................................... 4 1.3 Thanks .................................................. 7 2 Install Open Babel 9 2.1 Install a binary package ......................................... 9 2.2 Compiling Open Babel .......................................... 9 3 obabel and babel - Convert, Filter and Manipulate Chemical Data 17 3.1 Synopsis ................................................. 17 3.2 Options .................................................. 17 3.3 Examples ................................................. 19 3.4 Differences between babel and obabel .................................. 21 3.5 Format Options .............................................. 22 3.6 Append property values to the title .................................... 22 3.7 Filtering molecules from a multimolecule file .............................. 22 3.8 Substructure and similarity searching .................................. 25 3.9 Sorting molecules ............................................ 25 3.10 Remove duplicate molecules ....................................... 25 3.11 Aliases for chemical groups ....................................... 26 4 The Open Babel GUI 29 4.1 Basic operation .............................................. 29 4.2 Options ................................................. -
Real-Time Pymol Visualization for Rosetta and Pyrosetta
Real-Time PyMOL Visualization for Rosetta and PyRosetta Evan H. Baugh1, Sergey Lyskov1, Brian D. Weitzner1, Jeffrey J. Gray1,2* 1 Department of Chemical and Biomolecular Engineering, The Johns Hopkins University, Baltimore, Maryland, United States of America, 2 Program in Molecular Biophysics, The Johns Hopkins University, Baltimore, Maryland, United States of America Abstract Computational structure prediction and design of proteins and protein-protein complexes have long been inaccessible to those not directly involved in the field. A key missing component has been the ability to visualize the progress of calculations to better understand them. Rosetta is one simulation suite that would benefit from a robust real-time visualization solution. Several tools exist for the sole purpose of visualizing biomolecules; one of the most popular tools, PyMOL (Schro¨dinger), is a powerful, highly extensible, user friendly, and attractive package. Integrating Rosetta and PyMOL directly has many technical and logistical obstacles inhibiting usage. To circumvent these issues, we developed a novel solution based on transmitting biomolecular structure and energy information via UDP sockets. Rosetta and PyMOL run as separate processes, thereby avoiding many technical obstacles while visualizing information on-demand in real-time. When Rosetta detects changes in the structure of a protein, new coordinates are sent over a UDP network socket to a PyMOL instance running a UDP socket listener. PyMOL then interprets and displays the molecule. This implementation also allows remote execution of Rosetta. When combined with PyRosetta, this visualization solution provides an interactive environment for protein structure prediction and design. Citation: Baugh EH, Lyskov S, Weitzner BD, Gray JJ (2011) Real-Time PyMOL Visualization for Rosetta and PyRosetta. -
Lecture 1: September 8 Lecturer: Emery Berger Scribes: Bruno Silva, Gene Novark, Jim Partan
CMPSCI 377 Operating Systems Fall 2009 Lecture 1: September 8 Lecturer: Emery Berger Scribes: Bruno Silva, Gene Novark, Jim Partan 1.1 General information This class is taught by Prof. Emery Berger in ELAB 323, every Tuesday and Thursday from 9:30am to 11:00am. ELAB is the older brick building next to the computer science building. For additional information related to the course (syllabus, projects, etc), please visit www.cs.umass.edu/~emery. Although the class name is Operating Systems, this course will deal mostly with large-scale computer systems. The main question to be studied is how to build correct, reliable and high performance computer systems. In order to answer this question, problems such as memory management, concurrency, scheduling, etc, will be studied. 1.1.1 Getting help Prof. Berger is available by appointment in his office (CS344). The TA's office hours are Mondays and Wednesdays from 4:00 PM to 5:00 PM in the Edlab (LGRT 223, 225). In addition to office hours, Discussion Sections will be led by the TA on Wednesdays from 12:20pm to 1:10pm in CMPSCI 142. Attendance is very important since sample test problems will be discussed, and the main concepts presented during the last couple of classes will be reinforced. Also, students looking for help can access the course's newsgroup (look for the link at Prof. Berger's website). Lecture notes will also be available. Although this class requires no textbook, interested students might look for classics of the area, such as Operating System Concepts (Silberschatz et all), 7th Edition. -
Molecular Dynamics Simulations in Drug Discovery and Pharmaceutical Development
processes Review Molecular Dynamics Simulations in Drug Discovery and Pharmaceutical Development Outi M. H. Salo-Ahen 1,2,* , Ida Alanko 1,2, Rajendra Bhadane 1,2 , Alexandre M. J. J. Bonvin 3,* , Rodrigo Vargas Honorato 3, Shakhawath Hossain 4 , André H. Juffer 5 , Aleksei Kabedev 4, Maija Lahtela-Kakkonen 6, Anders Støttrup Larsen 7, Eveline Lescrinier 8 , Parthiban Marimuthu 1,2 , Muhammad Usman Mirza 8 , Ghulam Mustafa 9, Ariane Nunes-Alves 10,11,* , Tatu Pantsar 6,12, Atefeh Saadabadi 1,2 , Kalaimathy Singaravelu 13 and Michiel Vanmeert 8 1 Pharmaceutical Sciences Laboratory (Pharmacy), Åbo Akademi University, Tykistökatu 6 A, Biocity, FI-20520 Turku, Finland; ida.alanko@abo.fi (I.A.); rajendra.bhadane@abo.fi (R.B.); parthiban.marimuthu@abo.fi (P.M.); atefeh.saadabadi@abo.fi (A.S.) 2 Structural Bioinformatics Laboratory (Biochemistry), Åbo Akademi University, Tykistökatu 6 A, Biocity, FI-20520 Turku, Finland 3 Faculty of Science-Chemistry, Bijvoet Center for Biomolecular Research, Utrecht University, 3584 CH Utrecht, The Netherlands; [email protected] 4 Swedish Drug Delivery Forum (SDDF), Department of Pharmacy, Uppsala Biomedical Center, Uppsala University, 751 23 Uppsala, Sweden; [email protected] (S.H.); [email protected] (A.K.) 5 Biocenter Oulu & Faculty of Biochemistry and Molecular Medicine, University of Oulu, Aapistie 7 A, FI-90014 Oulu, Finland; andre.juffer@oulu.fi 6 School of Pharmacy, University of Eastern Finland, FI-70210 Kuopio, Finland; maija.lahtela-kakkonen@uef.fi (M.L.-K.); tatu.pantsar@uef.fi -
Ee9e60701e814784783a672a9
International Journal of Technology (2017) 4: 611‐621 ISSN 2086‐9614 © IJTech 2017 A PRELIMINARY STUDY ON SHIFTING FROM VIRTUAL MACHINE TO DOCKER CONTAINER FOR INSILICO DRUG DISCOVERY IN THE CLOUD Agung Putra Pasaribu1, Muhammad Fajar Siddiq1, Muhammad Irfan Fadhila1, Muhammad H. Hilman1, Arry Yanuar2, Heru Suhartanto1* 1Faculty of Computer Science, Universitas Indonesia, Kampus UI Depok, Depok 16424, Indonesia 2Faculty of Pharmacy, Universitas Indonesia, Kampus UI Depok, Depok 16424, Indonesia (Received: January 2017 / Revised: April 2017 / Accepted: June 2017) ABSTRACT The rapid growth of information technology and internet access has moved many offline activities online. Cloud computing is an easy and inexpensive solution, as supported by virtualization servers that allow easier access to personal computing resources. Unfortunately, current virtualization technology has some major disadvantages that can lead to suboptimal server performance. As a result, some companies have begun to move from virtual machines to containers. While containers are not new technology, their use has increased recently due to the Docker container platform product. Docker’s features can provide easier solutions. In this work, insilico drug discovery applications from molecular modelling to virtual screening were tested to run in Docker. The results are very promising, as Docker beat the virtual machine in most tests and reduced the performance gap that exists when using a virtual machine (VirtualBox). The virtual machine placed third in test performance, after the host itself and Docker. Keywords: Cloud computing; Docker container; Molecular modeling; Virtual screening 1. INTRODUCTION In recent years, cloud computing has entered the realm of information technology (IT) and has been widely used by the enterprise in support of business activities (Foundation, 2016). -
64-194 Projekt Parallelrechnerevaluation Abschlussbericht
64-194 Projekt Parallelrechnerevaluation Abschlussbericht Automatisierte Build-Tests für Spack Sarah Lubitz Malte Fock [email protected] [email protected] Studiengang: LA Berufliche Schulen – Informatik Studiengang LaGym - Informatik Matr.-Nr. 6570465 Matr.-Nr. 6311966 Inhaltsverzeichnis i Inhaltsverzeichnis 1 Einleitung1 1.1 Motivation.....................................1 1.2 Vorbereitungen..................................2 1.2.1 Spack....................................2 1.2.2 Python...................................2 1.2.3 Unix-Shell.................................3 1.2.4 Slurm....................................3 1.2.5 GitHub...................................4 2 Code 7 2.1 Automatisiertes Abrufen und Installieren von Spack-Paketen.......7 2.1.1 Python Skript: install_all_packets.py..................7 2.2 Batch-Jobskripte..................................9 2.2.1 Test mit drei Paketen........................... 10 2.3 Analyseskript................................... 11 2.3.1 Test mit 500 Paketen........................... 12 2.3.2 Code zur Analyse der Error-Logs, forts................. 13 2.4 Hintereinanderausführung der Installationen................. 17 2.4.1 Wrapper Skript.............................. 19 2.5 E-Mail Benachrichtigungen........................... 22 3 Testlauf 23 3.1 Durchführung und Ergebnisse......................... 23 3.2 Auswertung und Schlussfolgerungen..................... 23 3.3 Fazit und Ausblick................................ 24 4 Schulische Relevanz 27 Literaturverzeichnis -
How to Print a Crystal Structure Model in 3D Teng-Hao Chen,*A Semin Lee, B Amar H
Electronic Supplementary Material (ESI) for CrystEngComm. This journal is © The Royal Society of Chemistry 2014 How to Print a Crystal Structure Model in 3D Teng-Hao Chen,*a Semin Lee, b Amar H. Flood b and Ognjen Š. Miljanić a a Department of Chemistry, University of Houston, 112 Fleming Building, Houston, Texas 77204-5003, United States b Department of Chemistry, Indiana University, 800 E. Kirkwood Avenue, Bloomington, Indiana 47405, United States Supporting Information Instructions for Printing a 3D Model of an Interlocked Molecule: Cyanostars .................................... S2 Instructions for Printing a "Molecular Spinning Top" in 3D: Triazolophanes ..................................... S3 References ....................................................................................................................................................................... S4 S1 Instructions for Printing a 3D Model of an Interlocked Molecule: Cyanostars Mechanically interlocked molecules such as rotaxanes and catenanes can also be easily printed in 3D. As long as the molecule is correctly designed and modeled, there is no need to assemble and glue the components after printing—they are printed inherently as mechanically interlocked molecules. We present the preparation of a cyanostar- based [3]rotaxane as an example. A pair of sandwiched cyanostars S1 (CS ) derived from the crystal structure was "cleaned up" in the molecular computation software Spartan ʹ10, i.e. disordered atoms were removed. A linear molecule was created and threaded through the cavity of two cyanostars (Figure S1a). Using a space filling view of the molecule, the three components were spaced sufficiently far apart to ensure that they did not make direct contact Figure S1 . ( a) Side and top view of two cyanostars ( CS ) with each other when they are printed. threaded with a linear molecule. ( b) Side and top view of a Bulky stoppers were added to each [3]rotaxane. -
Conformational and Chemical Selection by a Trans-Acting Editing
Correction BIOCHEMISTRY Correction for “Conformational and chemical selection by a trans- acting editing domain,” by Eric M. Danhart, Marina Bakhtina, William A. Cantara, Alexandra B. Kuzmishin, Xiao Ma, Brianne L. Sanford, Marija Kosutic, Yuki Goto, Hiroaki Suga, Kotaro Nakanishi, Ronald Micura, Mark P. Foster, and Karin Musier-Forsyth, which was first published August 2, 2017; 10.1073/pnas.1703925114 (Proc Natl Acad Sci USA 114:E6774–E6783). The authors note that Oscar Vargas-Rodriguez should be added to the author list between Brianne L. Sanford and Marija Kosutic. Oscar Vargas-Rodriguez should be credited with de- signing research, performing research, and analyzing data. The corrected author line, affiliation line, and author contributions appear below. The online version has been corrected. The authors note that the following statement should be added to the Acknowledgments: “We thank Daniel McGowan for assistance with preparing mutant proteins.” Eric M. Danharta,b, Marina Bakhtinaa,b, William A. Cantaraa,b, Alexandra B. Kuzmishina,b,XiaoMaa,b, Brianne L. Sanforda,b, Oscar Vargas-Rodrigueza,b, Marija Kosuticc,d,YukiGotoe, Hiroaki Sugae, Kotaro Nakanishia,b, Ronald Micurac,d, Mark P. Fostera,b, and Karin Musier-Forsytha,b aDepartment of Chemistry and Biochemistry, The Ohio State University, Columbus, OH 43210; bCenter for RNA Biology, The Ohio State University, Columbus, OH 43210; cInstitute of Organic Chemistry, Leopold Franzens University, A-6020 Innsbruck, Austria; dCenter for Molecular Biosciences, Leopold Franzens University, A-6020 Innsbruck, Austria; and eDepartment of Chemistry, Graduate School of Science, The University of Tokyo, Tokyo 113-0033, Japan Author contributions: E.M.D., M.B., W.A.C., B.L.S., O.V.-R., M.P.F., and K.M.-F. -
Oracle Solaris Containers Data Sheet
ORACLE DATA SHEET ORACLE SOLARIS 8 CONTAINERS AND ORACLE SOLARIS 9 CONTAINERS KEY BENEFITS Oracle Solaris 8 Containers and Oracle Solaris 9 Containers let you migrate !"Quickly deploy Oracle Solaris 8 or Oracle Solaris 8 and Oracle Solaris 9 applications and environments to the Oracle Solaris 9 applications on Oracle Solaris 10 latest SPARC systems running Oracle Solaris 10. These environments can later !"Lower costs through consolidation onto be updated, at your own pace, to Oracle Solaris 10 Containers. With migration newer systems assistance from Oracle Advanced Customer Services, take advantage of Oracle !"Mitigate risks with expert assistance Solaris 8 Containers and Oracle Solaris 9 Containers to reduce the effort and !"Implement your solution for a single risk associated with migrating to the latest network computing environments. application or as part of a larger virtualization strategy Deploy Previous-Version Oracle Solaris Applications on Oracle Solaris 10 Oracle Solaris 8 Containers and Oracle Solaris 9 Containers serve as transition tools, decoupling your hardware upgrade from the operating system (OS) and applications, giving you more time to upgrade your applications to Oracle Solaris 10. Oracle guarantees application compatibility between OS releases, and builds on that by adding the ability to capture and transfer the surrounding configuration, data, and other elements of the OS. You can rapidly upgrade to new Oracle hardware and Oracle Solaris 10 while providing the Oracle Solaris 8 or Oracle Solaris 9 runtime environment as needed. Lower Costs by Consolidating Systems Today’s systems can be many times more powerful, space-efficient, and cost-efficient than earlier generations. However, hardware upgrades often demand OS as well as application upgrades. -
Developing for Industrial Iot with Embedded Linux OS on Dragonboard™ 410C by Timesys University
Qualcomm Developer Network Presents Developing for Industrial IoT with Embedded Linux OS on DragonBoard™ 410c by Timesys University Co-sponsored by Qualcomm Technologies, Inc. and Arrow Electronics Session 3 Building a Cutting-Edge User Interface with Qt® Maciej Halasz, Vice President of Technology Timesys Corporation Maurice Kalinowski, Principal Software Engineer Qt Company www.timesys.com ©2017 Timesys Corp. 3 Webinar Series . Session 1: Introduction to DragonBoard 410 SoC and Starting Development of Your Embedded Linux based “Industrial Internet of Things” (IIoT) Device • Setup for designing IIoT products • How to assemble and deploy initial BSP . Session 2: Application Development for Embedded Linux • Application development environment setup • How to reflect product requirements in the BSP • Communication in the IIoT system . Session 3: Building a Cutting-Edge User Interface with Qt® • Developing modern, rich UIs for factory terminals . Session 4: Embedded Products Security • Designing security-rich devices www.timesys.com ©2017 Timesys Corp. 4 Session 2 recap . What we did • Reflected API requirements in OpenEmbedded RPB Linux BSP • Talked about BSP customizations – New meta-layer – New recipe – Modified image . Application Development • SDK setup on a host • Used IDE to develop/deploy/debug code on DragonBoard 410c • We looked briefly at a BLE protocol • Programmed an application that received info from a sensor board – Temperature, Luminosity, FreeFall . Key takeaways • Its very straight forward to develop C/C++ application code for the 410c • IDEs accelerate development process • When working with Linaro BSP, customers can leverage meta layer library on OpenEmbedded https://layers.openembedded.org www.timesys.com ©2017 Timesys Corp. 5 Session 3 — Agenda . Sharing information in an IoT system .