Automated TLS group determination in Phenix
|
|
|
- Noreen Gordon
- 9 years ago
- Views:
Transcription
1 Computational Crystallography Initiative Automated TLS group determination in Phenix Pavel Afonine Computation Crystallography Initiative Physical Biosciences Division Lawrence Berkeley National Laboratory, Berkeley CA, USA October, 2010
2 Atomic Displacement Parameters (ADP or B-factors ) ADPs model relatively small atomic motions (within harmonic approximation) Hierarchy and anisotropy of atomic displacements atom z residue y domain molecule x crystal UTOTAL Total ADP: UGROUP ULOCAL UCRYST UTOTAL = UCRYST+UGROUP+ULOCAL isotropic anisotropic UTLS ULIB USUBGROUP
3 Atomic Displacement Parameters (ADP or B-factors ) Total ADP U TOTAL = U CRYST + U GROUP + U LOCAL U TOTAL U LOCAL U GROUP U CRYST isotropic anisotropic U TLS U LIB U SUBGROUP U CRYST overall anisotropic scale. U TLS rigid body displacements of molecules, domains, secondary structure elements. U LOCAL local vibration of individual atoms. U LIB librational motion of side chain around bond vector.
4 TLS and ADP: comprehensive overview (~50 pages)
5 Parameterization and refinement of ADP in Phenix Afonine et al (2010). On atomic displacement parameters and their parameterization in Phenix
6 TLS Using TLS in refinement requires partitioning a model into TLS groups. This is typically done by - visual model inspection and deciding which domains may be considered as rigid - using TLSMD method Painter & Merritt. (2006). Acta Cryst. D62, Painter & Merritt. (2006). J. Appl. Cryst. 39,
7 Methodology TLS contribution of an individual atom participating in a TLS group can be computed from T, L and S matrices: U TLS = T + ALA t + AS + S t A t (20 TLS parameters per TLS group)
8 Methodology (TLSMD) Split a model into 1, 2, 3,, N contiguous segments. - If n is the number of residues in the chain, m is minimum number of residues in a segment, then the number of segments is s( n,m) = n( n +1) /2 " ( n +1" i ) i=2 - For example if n=100 and m=3 (minimal number of residues so there is more observations than parameters), then we get 4853 possible partitions.! # m - Compute residual for all segment partitions: # ( 6 # ( "U i TLS ) 2 ) i=1 i R = w W U ATOM atoms in segment
9 Methodology
10 Methodology? How to pick up the right number of TLS groups?
11 Methodology? How to pick up the right number of TLS groups? One can try all 20 or choose an arbitrary break point
12 PHENIX approach to finding TLS groups Design Goals: - Have it as integrated part of PHENIX system: - No need to run external software or use web servers (=send your data somewhere, which your policy may even not allow you to do). - Use it interactively as part of refinement (update TLS group assignment as model improves during refinement). - Make it fast - Eliminate subjective decisions (procedure should give THE UNIQUE answer and not an array of possible choices leaving the room for subjective decisions).
13 PHENIX approach to finding TLS groups Step 1: For each chain find all secondary structure and unstructured elements - Number of elements defines maximum possible number of TLS groups - A secondary structure element can t be split into multiple TLS groups. Large unstructured elements, can be split into smaller pieces. Chain S U S S U S U S S Secondary structure element U Unstructured stretch of residues (loop) Step 2: Find all possible contiguous combinations S U S 3 groups S U S S U S 2 groups S U S 2 groups N ELEMENTS : N POSSIBLE PARTITIONS 3:3, 4:7, 5:15, 6:31,, 10:511,
14 PHENIX approach to finding TLS groups Step 3: For each partition fit TLS groups and compute the residual R1 R2 R3 Step 4: Find the best fit among the groups of equal number of partitions. In this example, if R3<R2: R1 Step 5: Find the best partition R3 - Challenge: we can t directly compare R1 and R3 because they are computed using different number of TLS groups (different number of parameters)
15 PHENIX approach to finding TLS groups Step 5 (continued): Find the best partition - Randomly generate a pool of partitions for each candidate, fit TLS matrices compute, average residuals, and compute score: R1 R11 R12 many (20-50) Average residuals: R1 AVERAGE Score = (R1 AVERAGE - R1)/(R1 AVERAGE + R1)*100 Do the same for the next candidate: R3 The final solution is the one that has the highest score.
16 PHENIX approach to finding TLS groups: examples GroEl structure (one chain): No. of Targets groups best rand.pick diff. score
17 PHENIX approach to finding TLS groups: usage Command line: phenix.find_tls_groups model.pdb nproc=n where nproc is the number of available CPUs
18 TLS groups for refinement automatically
19 Fast Automatic TLS Examples: GroEL structure (3668 residues, atoms, 7 chains): PHENIX: 135 seconds TLSMD : 3630 seconds (plus lots of clicking to upload/download the files and making arbitrary decisions) Lysozime structure: 9.5 seconds with one CPU 2.5 seconds using 10 CPUs
20 Automatic TLS Why it is faster: a) Use isotropic TLS model, b) Solve optimization problem analytically (no minimizer used) c) A secondary structure element cannot belong to more than one TLS group 7 more pages
21 ADP refinement: what goes into PDB phenix.refine outputs TOTAL B-factor (iso- and anisotropic): U TOTAL = U ATOM + U TLS + Isotropic equivalent ATOM 1 CA ALA C ANISOU 1 CA ALA C U TOTAL = U ATOM + U TLS + Atom records are self-consistent: ü Straightforward visualization (color by B-factors, or anisotropic ellipsoids) ü Straightforward computation of other statistics (R-factors, etc.) no need to use external helper programs for any conversions.
22 ADP refinement: example Synaptotagmin refinement at 3.2 Å Original refinement (PDB code: 1DQV) R-free = 34 % R = 29 % PHENIX Isotropic restrained ADP R-free = 28 % R = 23 % PHENIX TLS + Isotropic ADP R-free = 25 % R = 20 % 9% improvement in both Rwork and Rfree! TLS groups determined automatically
Neutron structure determination
Neutron structure determination An X-ray structure is always available and is used as a starting model for neutron structure determination, therefore once the neutron data is available, the main steps
Publication of small-unit-cell structures in Acta Crystallographica Michael Hoyland ECM28 University of Warwick, 2013
Publication of small-unit-cell structures in Acta Crystallographica Michael Hoyland ECM28 University of Warwick, 2013 International Union of Crystallography 5 Abbey Square Chester CH1 2HU UK International
The PHENIX graphical interface. Nathaniel Echols [email protected] [email protected] http://www.phenix-online.org
The PHENIX graphical interface Nathaniel Echols [email protected] [email protected] http://www.phenix-online.org The PHENIX Project Lawrence Berkeley Laboratory Paul Adams, Pavel Afonine, Nat Echols,
BIOC351: Proteins. PyMOL Laboratory #1. Installing and Using
BIOC351: Proteins PyMOL Laboratory #1 Installing and Using Information and figures for this handout was obtained from the following sources: Introduction to PyMOL (2009) DeLano Scientific LLC. Installing
Refinement of a pdb-structure and Convert
Refinement of a pdb-structure and Convert A. Search for a pdb with the closest sequence to your protein of interest. B. Choose the most suitable entry (or several entries). C. Convert and resolve errors
An introduction in crystal structure solution and refinement
An introduction in crystal structure solution and refinement Peter Zwart [email protected] Outline Introduction Structure solution methods Molecular placement Molecular replacement Experimental phasing Direct
Lecture 2 Mathcad Basics
Operators Lecture 2 Mathcad Basics + Addition, - Subtraction, * Multiplication, / Division, ^ Power ( ) Specify evaluation order Order of Operations ( ) ^ highest level, first priority * / next priority
Structure Factors 59-553 78
78 Structure Factors Until now, we have only typically considered reflections arising from planes in a hypothetical lattice containing one atom in the asymmetric unit. In practice we will generally deal
HYDRONMR and Fast-HYDRONMR
File:hydronmr7c-pub.doc HYDRONMR and Fast-HYDRONMR Index 1. Introduction to HYDRONMR 2. Literature 3. Running HYDRONMR. Input data file 4. Output files 5. Notes and hints 7. Release notes Version 7c, September
Structure Tools and Visualization
Structure Tools and Visualization Gary Van Domselaar University of Alberta [email protected] Slides Adapted from Michel Dumontier, Blueprint Initiative 1 Visualization & Communication Visualization
Scientific Business Intelligence using Pipeline Pilot
Scientific Business Intelligence using Pipeline Pilot Anneliese Appleton Accelrys, Sydney y What is Scientific Business Intelligence? Biz Analyst Management Scientist Engineer Biz Analyst Management Business
Gold (Genetic Optimization for Ligand Docking) G. Jones et al. 1996
Gold (Genetic Optimization for Ligand Docking) G. Jones et al. 1996 LMU Institut für Informatik, LFE Bioinformatik, Cheminformatics, Structure based methods J. Apostolakis 1 Genetic algorithms Inspired
Amino Acids. Amino acids are the building blocks of proteins. All AA s have the same basic structure: Side Chain. Alpha Carbon. Carboxyl. Group.
Protein Structure Amino Acids Amino acids are the building blocks of proteins. All AA s have the same basic structure: Side Chain Alpha Carbon Amino Group Carboxyl Group Amino Acid Properties There are
Four strategies to help move beyond lean and build a competitive advantage
Discrete Manufacturing Four strategies to help move beyond lean and build a competitive advantage For companies that make complex, configurable products, lean manufacturing principles have become an integral
MATLAB Functions. function [Out_1,Out_2,,Out_N] = function_name(in_1,in_2,,in_m)
MATLAB Functions What is a MATLAB function? A MATLAB function is a MATLAB program that performs a sequence of operations specified in a text file (called an m-file because it must be saved with a file
Fourth generation techniques (4GT)
Fourth generation techniques (4GT) The term fourth generation techniques (4GT) encompasses a broad array of software tools that have one thing in common. Each enables the software engineer to specify some
Quick Start. Creating a Scoring Application. RStat. Based on a Decision Tree Model
Creating a Scoring Application Based on a Decision Tree Model This Quick Start guides you through creating a credit-scoring application in eight easy steps. Quick Start Century Corp., an electronics retailer,
ABAP for Functional Consultants
ABAP for Functional Consultants Anthony Cecchini, President, INFORMATION TECHNOLOGY PARTNERS Founded in 1993, Women Owned 8(M), Small Business Certified with a GSA IT 70 Schedule, we focus solely on SAP.
(Refer Slide Time: 2:03)
Control Engineering Prof. Madan Gopal Department of Electrical Engineering Indian Institute of Technology, Delhi Lecture - 11 Models of Industrial Control Devices and Systems (Contd.) Last time we were
Infrared Spectroscopy: Theory
u Chapter 15 Infrared Spectroscopy: Theory An important tool of the organic chemist is Infrared Spectroscopy, or IR. IR spectra are acquired on a special instrument, called an IR spectrometer. IR is used
Asset Depreciation Reports
Asset Depreciation Reports CSE s Asset Manager is able to produce management reports detailing fixed asset depreciation. These reports will aid your establishment s financial controller when updating balance
Consensus alignment server for reliable comparative modeling with distant templates
W50 W54 Nucleic Acids Research, 2004, Vol. 32, Web Server issue DOI: 10.1093/nar/gkh456 Consensus alignment server for reliable comparative modeling with distant templates Jahnavi C. Prasad 1, Sandor Vajda
Our Raison d'être. Identify major choice decision points. Leverage Analytical Tools and Techniques to solve problems hindering these decision points
Analytic 360 Our Raison d'être Identify major choice decision points Leverage Analytical Tools and Techniques to solve problems hindering these decision points Empowerment through Intelligence Our Suite
Molecular Graphics What?
Molecular Graphics Molecular Graphics What? PDF 00-057-0248 ULM-8 A microporous florinated gallium phosphate with N 4 C 6 H 19 in the pores PDF-4 products contain data sets with atomic coordinates. Two
Data Visualization for Atomistic/Molecular Simulations. Douglas E. Spearot University of Arkansas
Data Visualization for Atomistic/Molecular Simulations Douglas E. Spearot University of Arkansas What is Atomistic Simulation? Molecular dynamics (MD) involves the explicit simulation of atomic scale particles
Polarization Dependence in X-ray Spectroscopy and Scattering. S P Collins et al Diamond Light Source UK
Polarization Dependence in X-ray Spectroscopy and Scattering S P Collins et al Diamond Light Source UK Overview of talk 1. Experimental techniques at Diamond: why we care about x-ray polarization 2. How
Molecular Visualization. Introduction
Molecular Visualization Jeffry D. Madura Department of Chemistry & Biochemistry Center for Computational Sciences Duquesne University Introduction Assessments of change, dynamics, and cause and effect
ETPL Extract, Transform, Predict and Load
ETPL Extract, Transform, Predict and Load An Oracle White Paper March 2006 ETPL Extract, Transform, Predict and Load. Executive summary... 2 Why Extract, transform, predict and load?... 4 Basic requirements
Tutorial for Assignment #2 Gantry Crane Analysis By ANSYS (Mechanical APDL) V.13.0
Tutorial for Assignment #2 Gantry Crane Analysis By ANSYS (Mechanical APDL) V.13.0 1 Problem Description Design a gantry crane meeting the geometry presented in Figure 1 on page #325 of the course textbook
Complex, true real-time analytics on massive, changing datasets.
Complex, true real-time analytics on massive, changing datasets. A NoSQL, all in-memory enabling platform technology from: Better Questions Come Before Better Answers FinchDB is a NoSQL, all in-memory
Euler s Method and Functions
Chapter 3 Euler s Method and Functions The simplest method for approximately solving a differential equation is Euler s method. One starts with a particular initial value problem of the form dx dt = f(t,
Preview of Period 2: Forms of Energy
Preview of Period 2: Forms of Energy 2.1 Forms of Energy How are forms of energy defined? 2.2 Energy Conversions What happens when energy is converted from one form into another form? 2.3 Efficiency of
Electron density is complex!
Electron density is complex! Göttingen, November 13 th 2008 George M. Sheldrick, Göttingen University http://shelx.uni-ac.gwdg.de/shelx/ Friedel s Law F h,k,l = F h, k, l and φ h,k,l = φ h, k, l Friedel
Getting Your Keywords Right
Getting Your Keywords Right Workbook How to Get Your Keywords Right The purpose of this workbook is to help marketers understand the first step in improving your organic search results. In order to drive
SAnDReS Tutorial 01 Prof. Dr. Walter F. de Azevedo Jr.
2015 Dr. Walter F. de Azevedo Jr. SAnDReS Tutorial 01 Prof. Dr. Walter F. de Azevedo Jr. 1 Running in the Windows On the Windows, left click on Command Prompt. Go to SAnDReS directory (c:\sandres) and
EZManage V4.0 Release Notes. Document revision 1.08 (15.12.2013)
EZManage V4.0 Release Notes Document revision 1.08 (15.12.2013) Release Features Feature #1- New UI New User Interface for every form including the ribbon controls that are similar to the Microsoft office
Section I Using Jmol as a Computer Visualization Tool
Section I Using Jmol as a Computer Visualization Tool Jmol is a free open source molecular visualization program used by students, teachers, professors, and scientists to explore protein structures. Section
Topic 2: Energy in Biological Systems
Topic 2: Energy in Biological Systems Outline: Types of energy inside cells Heat & Free Energy Energy and Equilibrium An Introduction to Entropy Types of energy in cells and the cost to build the parts
Objectives. Materials
Activity 4 Objectives Understand what a slope field represents in terms of Create a slope field for a given differential equation Materials TI-84 Plus / TI-83 Plus Graph paper Introduction One of the ways
Clustering & Visualization
Chapter 5 Clustering & Visualization Clustering in high-dimensional databases is an important problem and there are a number of different clustering paradigms which are applicable to high-dimensional data.
Elasticity Theory Basics
G22.3033-002: Topics in Computer Graphics: Lecture #7 Geometric Modeling New York University Elasticity Theory Basics Lecture #7: 20 October 2003 Lecturer: Denis Zorin Scribe: Adrian Secord, Yotam Gingold
Dynamic Programming. Lecture 11. 11.1 Overview. 11.2 Introduction
Lecture 11 Dynamic Programming 11.1 Overview Dynamic Programming is a powerful technique that allows one to solve many different types of problems in time O(n 2 ) or O(n 3 ) for which a naive approach
Chemistry 13: States of Matter
Chemistry 13: States of Matter Name: Period: Date: Chemistry Content Standard: Gases and Their Properties The kinetic molecular theory describes the motion of atoms and molecules and explains the properties
Study the following diagrams of the States of Matter. Label the names of the Changes of State between the different states.
Describe the strength of attractive forces between particles. Describe the amount of space between particles. Can the particles in this state be compressed? Do the particles in this state have a definite
Business Intelligence. A Presentation of the Current Lead Solutions and a Comparative Analysis of the Main Providers
60 Business Intelligence. A Presentation of the Current Lead Solutions and a Comparative Analysis of the Main Providers Business Intelligence. A Presentation of the Current Lead Solutions and a Comparative
Computer-System Architecture
Chapter 2: Computer-System Structures Computer System Operation I/O Structure Storage Structure Storage Hierarchy Hardware Protection General System Architecture 2.1 Computer-System Architecture 2.2 Computer-System
MS Windows DHCP Server Configuration
MS Windows DHCP Server Configuration Abstract This document describes how to configure option 43 on a Microsoft Windows 2000/2003 DHCP server. This information may be used in an Aruba Networks solution
Introduction to Computers and Programming. Testing
Introduction to Computers and Programming Prof. I. K. Lundqvist Lecture 13 April 16 2004 Testing Goals of Testing Classification Test Coverage Test Technique Blackbox vs Whitebox Real bugs and software
CHAPTER - 5 CONCLUSIONS / IMP. FINDINGS
CHAPTER - 5 CONCLUSIONS / IMP. FINDINGS In today's scenario data warehouse plays a crucial role in order to perform important operations. Different indexing techniques has been used and analyzed using
3.5 Dual Bay USB 3.0 RAID HDD Enclosure
3.5 Dual Bay USB 3.0 RAID HDD Enclosure User Manual August 11, 2011 v1.1 MFG Part # MT2U3-MP BARCODE Introduction 1 Introduction 1.1 System Requirements 1.1.1 PC Requirements Minimum Intel Pentium III
13.1 The Nature of Gases. What is Kinetic Theory? Kinetic Theory and a Model for Gases. Chapter 13: States of Matter. Principles of Kinetic Theory
Chapter 13: States of Matter The Nature of Gases The Nature of Gases kinetic molecular theory (KMT), gas pressure (pascal, atmosphere, mm Hg), kinetic energy The Nature of Liquids vaporization, evaporation,
FASTSTATS PEOPLESTAGE
CAMPAIGN MANAGEMENT & AUTOMATION SOFTWARE The Data Marketing Specialists BENEFITS: Define your marketing processes as diagrams Automate and coordinate complex communications Personalise each message for
CRM 360 is a web-based and Customer Relationship Management (CRM) system.
CRM 360 is a web-based and Customer Relationship Management (CRM) system. With its enormous flexibility, its functions and modules, CRM 360 is especially suitable for the use in critical environments of
A Practical Guide to Solving Single Crystal Structures. Manuel A. Fernandes. 15 Mar 2006
A Practical Guide to Solving Single Crystal Structures Manuel A. Fernandes 15 Mar 2006 School of Chemistry University of the Witwatersrand Johannesburg, South Africa, 2006 Solving Crystal Structures 1
the points are called control points approximating curve
Chapter 4 Spline Curves A spline curve is a mathematical representation for which it is easy to build an interface that will allow a user to design and control the shape of complex curves and surfaces.
Bringing Big Data Modelling into the Hands of Domain Experts
Bringing Big Data Modelling into the Hands of Domain Experts David Willingham Senior Application Engineer MathWorks [email protected] 2015 The MathWorks, Inc. 1 Data is the sword of the
The CIF file, refinement details and validation of the structure
The CIF file, refinement details and validation of the structure CCCW 2011 Artefacts versus errors Artefacts in crystallography: An error which cannot be avoided, since it is inherent in the method. Examples
ERserver. iseries. Work management
ERserver iseries Work management ERserver iseries Work management Copyright International Business Machines Corporation 1998, 2002. All rights reserved. US Government Users Restricted Rights Use, duplication
Chapter 2. Atomic Structure and Interatomic Bonding
Chapter 2. Atomic Structure and Interatomic Bonding Interatomic Bonding Bonding forces and energies Primary interatomic bonds Secondary bonding Molecules Bonding Forces and Energies Considering the interaction
Chemical and Structural Classifications
Chemical and Structural Classifications What? Materials can be classified by their chemistry and structure. There are three main types of structural classifications: 1. Prototype Structure Structure prototyping
Avira Security Management Center 2.6
Avira Security Management Center 2.6 Automatic import of computers in combination with the automatic product installation: Support April 2011 www.avira.de Errors in design and contents cannot be excluded
TAUS Quality Dashboard. An Industry-Shared Platform for Quality Evaluation and Business Intelligence September, 2015
TAUS Quality Dashboard An Industry-Shared Platform for Quality Evaluation and Business Intelligence September, 2015 1 This document describes how the TAUS Dynamic Quality Framework (DQF) generates a Quality
DATA 301 Introduction to Data Analytics Microsoft Excel VBA. Dr. Ramon Lawrence University of British Columbia Okanagan
DATA 301 Introduction to Data Analytics Microsoft Excel VBA Dr. Ramon Lawrence University of British Columbia Okanagan [email protected] DATA 301: Data Analytics (2) Why Microsoft Excel Visual Basic
1) The time for one cycle of a periodic process is called the A) wavelength. B) period. C) frequency. D) amplitude.
practice wave test.. Name Use the text to make use of any equations you might need (e.g., to determine the velocity of waves in a given material) MULTIPLE CHOICE. Choose the one alternative that best completes
Dry Etching and Reactive Ion Etching (RIE)
Dry Etching and Reactive Ion Etching (RIE) MEMS 5611 Feb 19 th 2013 Shengkui Gao Contents refer slides from UC Berkeley, Georgia Tech., KU, etc. (see reference) 1 Contents Etching and its terminologies
Performance Measurement of Dynamically Compiled Java Executions
Performance Measurement of Dynamically Compiled Java Executions Tia Newhall and Barton P. Miller University of Wisconsin Madison Madison, WI 53706-1685 USA +1 (608) 262-1204 {newhall,bart}@cs.wisc.edu
Chapter 2, Lesson 5: Changing State Melting
Chapter 2, Lesson 5: Changing State Melting Key Concepts Melting is a process that causes a substance to change from a solid to a liquid. Melting occurs when the molecules of a solid speed up enough that
Learning Management System Selection with Analytic Hierarchy Process
Learning Management System Selection with Analytic Hierarchy Process Aydın Çetin 1, Ali Hakan Işık 2, İnan Güler 1 1 Gazi University, Faculty Of Technology 2 Gazi University, Institute of Information Sciences
The Impact of Big Data on Classic Machine Learning Algorithms. Thomas Jensen, Senior Business Analyst @ Expedia
The Impact of Big Data on Classic Machine Learning Algorithms Thomas Jensen, Senior Business Analyst @ Expedia Who am I? Senior Business Analyst @ Expedia Working within the competitive intelligence unit
FastStats PeopleStage. Campaign Management & Automation Software
FastStats PeopleStage Campaign Management & Automation Software With the unique power & automation of FastStats PeopleStage we can get your marketing communications flowing smoothly Visualise, implement
Big Data Analytics for Every Organization
Big Data Analytics for Every Organization Cloud-based services give you the analytic power to reach greater heights 2014 Fair Isaac Corporation. All rights reserved. 1 In every industry, a handful of competitors
1. The Kinetic Theory of Matter states that all matter is composed of atoms and molecules that are in a constant state of constant random motion
Physical Science Period: Name: ANSWER KEY Date: Practice Test for Unit 3: Ch. 3, and some of 15 and 16: Kinetic Theory of Matter, States of matter, and and thermodynamics, and gas laws. 1. The Kinetic
Memory Management Outline. Background Swapping Contiguous Memory Allocation Paging Segmentation Segmented Paging
Memory Management Outline Background Swapping Contiguous Memory Allocation Paging Segmentation Segmented Paging 1 Background Memory is a large array of bytes memory and registers are only storage CPU can
Performance with the Oracle Database Cloud
An Oracle White Paper September 2012 Performance with the Oracle Database Cloud Multi-tenant architectures and resource sharing 1 Table of Contents Overview... 3 Performance and the Cloud... 4 Performance
Best practices for efficient HPC performance with large models
Best practices for efficient HPC performance with large models Dr. Hößl Bernhard, CADFEM (Austria) GmbH PRACE Autumn School 2013 - Industry Oriented HPC Simulations, September 21-27, University of Ljubljana,
Computational Crystallography Newsletter
Volume TWO Computational Crystallography Newsletter JULY MMXI Data viewer, MR-ROSETTA, LYSOZYME, SPOTFINDER Table of Contents PHENIX News 85 Crystallographic meetings 86 Expert Advice 86 FAQ 86 Short Communications
Share Point Document Management For Sage 100 ERP
Share Point Document Management For Sage 100 ERP 457 Palm Drive Glendale, CA 91202 818-956-3744 818-956-3746 [email protected] www.iigservices.com Share Point Document Management 2 Information in this
FIS GT.M Multi-purpose Universal NoSQL Database. K.S. Bhaskar Development Director, FIS [email protected] +1 (610) 578-4265
FIS GT.M Multi-purpose Universal NoSQL Database K.S. Bhaskar Development Director, FIS [email protected] +1 (610) 578-4265 Outline M a Universal NoSQL database Using GT.M as a Multi-purpose NoSQL
What's New in SAS Data Management
Paper SAS034-2014 What's New in SAS Data Management Nancy Rausch, SAS Institute Inc., Cary, NC; Mike Frost, SAS Institute Inc., Cary, NC, Mike Ames, SAS Institute Inc., Cary ABSTRACT The latest releases
Using Power to Improve C Programming Education
Using Power to Improve C Programming Education Jonas Skeppstedt Department of Computer Science Lund University Lund, Sweden [email protected] jonasskeppstedt.net jonasskeppstedt.net [email protected]
Unit 2 Lesson 1 Introduction to Energy. Copyright Houghton Mifflin Harcourt Publishing Company
Get Energized! What are two types of energy? Energy is the ability to cause change. Energy takes many different forms and causes many different effects. There are two general types of energy: kinetic energy
IRMAC SAS INFORMATION MANAGEMENT, TRANSFORMING AN ANALYTICS CULTURE. Copyright 2012, SAS Institute Inc. All rights reserved.
IRMAC SAS INFORMATION MANAGEMENT, TRANSFORMING AN ANALYTICS CULTURE ABOUT THE PRESENTER Marc has been with SAS for 10 years and leads the information management practice for canada. Marc s area of specialty
Big Fast Data Hadoop acceleration with Flash. June 2013
Big Fast Data Hadoop acceleration with Flash June 2013 Agenda The Big Data Problem What is Hadoop Hadoop and Flash The Nytro Solution Test Results The Big Data Problem Big Data Output Facebook Traditional
Toad for Oracle 8.6 SQL Tuning
Quick User Guide for Toad for Oracle 8.6 SQL Tuning SQL Tuning Version 6.1.1 SQL Tuning definitively solves SQL bottlenecks through a unique methodology that scans code, without executing programs, to
Big Systems, Big Data
Big Systems, Big Data When considering Big Distributed Systems, it can be noted that a major concern is dealing with data, and in particular, Big Data Have general data issues (such as latency, availability,
Monochrome Print Features: True 600 dpi print resolution Produces 3,3 A0 size prints or copies per minute 100% efficient No waste toner
KIP 3100 SERIES KIP 3100 Monochrome Print, Copy & Scan The KIP 3100 system accurately reproduces technical documents at true 600 x 600 dpi resolution. Prints and copies may be delivered to the integrated
Knowledge Discovery from patents using KMX Text Analytics
Knowledge Discovery from patents using KMX Text Analytics Dr. Anton Heijs [email protected] Treparel Abstract In this white paper we discuss how the KMX technology of Treparel can help searchers
VMware vcenter Log Insight Delivers Immediate Value to IT Operations. The Value of VMware vcenter Log Insight : The Customer Perspective
VMware vcenter Log Insight Delivers Immediate Value to IT Operations VMware vcenter Log Insight VMware vcenter Log Insight delivers a powerful real-time log management for VMware environments, with machine
