http://www.ebi.ac.uk/msd

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MSD deposition database

MSD search database

MSD production database

UniProt database

Taxonomy database

Residue mappingWeekly

Update By MSD

IncrementalUpdate

PDB weeklyUpdate

BiweeklyOracle Update

load

load

Mapping update

views

Direct bi-directional exchange via Oracle

MSD-UniProtSequence mapping

DBREF analysis

Protein Production

CrystallisationData Collection Phasing

Protein Structure

DepositionStructure analysis

TargetSelection

Overview of Protein Crystallography

The PLAYERS

SPINE

THE BIG PLAYERS – THE SYNCHROTRON STAFF

Dependencies & Standards are between independent packages

Olof Svensson

Towards automation with CCP4

An e-science resource for high throughput protein crystallography

www.e-htpx.ac.uk

e-HTPX

Java API to read/write/validate XML

Documentation available at:

– http://www.ebi.ac.uk/msd-srv/docs/ehtpx/fillon/api/

Web-based user interface Linux/Apache/PHP/PostgreSQL View your plates/crystals View individual wells

Slide-show, Zoom/Measure modes Time courses Optional email notification of imaging

OPPF & Crystallogenesis

UML Technology:Models, Views, and Diagrams

Use CaseDiagramsUse Case

DiagramsUse CaseDiagrams

ScenarioDiagramsScenario

DiagramsCollaborationDiagrams

StateDiagramsState

DiagramsComponentDiagrams

ComponentDiagramsComponent

DiagramsDeploymentDiagrams

StateDiagramsState

DiagramsObjectDiagrams

ScenarioDiagramsScenario

DiagramsStatechartDiagrams

Use CaseDiagramsUse Case

DiagramsSequenceDiagrams

StateDiagramsState

DiagramsClassDiagrams

ActivityDiagrams

Models

Sequence Diagram of the events

ScenarioDiagramsScenario

DiagramsStatechartDiagrams

causal graph

ActivityDiagrams

•At SOLEIL – Andy Thompson, D. Dalle, M. Ounsy, E. Girard, P, Legrand, L. Roussier, P. Gourhant, R. Fourme, M. Idir, T. Moreno, O. Chubar.

•At ESRF – O. Svensson, O. Hignette, M. Walsh, W. Shepard.

•At IRISA, Rennes – S. Robin, R. Quiniou, M-O. Cordier.

•At INRA, Narbonne – J-P. Steyer.

Beamline model

PXWEB Protein sample information is stored in MySQL

database allows users to link this information via BCM ProDC

Users van view/edit reports generated from data collections

Search data base for previous experiments Further development

transferred to ISPyB as a joint e-HTPX/ESRF project

Info. On current Basket + Sample

Sample Changer Graphical User Interface

Graphical representation

of Basket + Basket Selector

position

Log of events

Hardware status Change current position

ISPyB Progress to date

Data model developed Implementation of sample tracking to/from beamline Linking of crystallization database information to ISPyB

through mobile PDA

Information System for Protein crystallography Beamlines

PIMS

BBSRC Partners

Kim Henrick European Bioinformatics Institute

Colin Nave CCLRC Daresbury Laboratory

Keith Wilson The University of York

Dave Stuart Oxford Protein Production Facility

Martyn Winn CCP4

Alun Ashton Diamond Light Source Ltd

EU/HALX Partners

Anne Poupon CNRS – Université Paris-Sud

SPORT Consortia

Jim Naismith The University of St. Andrews

Neil Isaacs The University of Glasgow

Commercial Individual Step Packages

Project Management

All Projects have competing constraints

Time, Costs and Functionality

Constraints management – key to success

Must Have

Should Have MoSCow

Could Have

Some requirements may slip to meet constraints

Pareto Principle

80% benefit achieved with 20% of effort

How far do you go………and when do you stop!

SymptomA: Excessive data modeling A: People don’t return your phone callsA: New requests and innovations are sending you

back to the drawing board Diagnosis:

Advanced analysis paralysis

The Cure for Advanced analysis paralysis

Remember why we’re doing this? To have a picture of where we are goingTo be able to scope out the next projectTo understand the costs in enough detail to get to the

next stageTo be able to communicate internally and externally

When you’re there, STOP Get STARTED

Further Standardisation Efforts

REFERENCE DATAExamples: solutions.xml inclusion.xml detergents.xml buffers.xml screen.xml well.xml

Analytical Data: A Tower of Babel

0 20 40 60 80 100 120 140 160 180 200 Mass (m/z)

MSMS

12 11 10 9 8 7 6 5 4 3 2 1 0 Parts Per Million

NMRNMR 4000 3500 3000 2500 2000 1500 1000 Wavenumber (cm-1)

IRIR

.389

.863

1.24

4

1.92

7

2.83

4

.5 1 1.5 2 2.5 3 3.5 Minutes

LCLC

ANIML consortia of Waters, NIST, Shimadzu, GSK. Currently covers chromatography, MS, UV/VIS, IR and NMR. http://animl.sourceforge.net/

Defines the exchange of data defining, the sample-set, measurment data and audit trail. Evolved from Generalized Analytical Markup Language Hierarchy (GAML) for Analytical Instruments

There are specific technique definitions that include Nuclear Magnetic Resonance spectroscopy and Mass Spectroscpy. In addition the HUPO Proteomics Standards Initiative (PSI, http://psidev.sourceforge.net/) defines community standards for data representation in proteomics to facilitate data comparision, exchange and verification. PSI currenty develops standards for two key areas of proteomics, mass spectrometry and protein-protein interaction data, as well as a standardised general proteomics format.

An XML Data Model for Analytical Instruments

2 parts : Selection of the window type with a left button bar

Targets Blueprints Workflow Protocols

Associated window

Eric Oeuillet & Anne Pajon

HALX/EBI

Protocols Editer

Workflow

KEPLER

PTOLEMY II

TAVERNA

ISPyB Ludovic Launer DBDesigner 4

Enterprise Architect affordable object oriented CASE tool for the full development life-cycle.

www.ebi.ac.uk/msd-srv/docs/workflow/

Familiar Outline? Mortgage Industry

ChemCore registration Registration Capture and Share

Chemical Data Flexible to support

additional data types and business rules

Extensive ability to search and view information captured by the system

Maintain Data Integrity Enforce Data Security

Flexible business rules can restrict access to data as necessary

Logging full history of changes to information

Based on well-established UNITY™ database system and Oracle

EMBL Chemical Genomics Core Facility

Mobile Data Collection

Data Collection through the use of handheld devices

What do molecular biologists

really really want?

Expectations are High!

People with LCD’s sewn into their bodies and computers that harness the brains natural computing power

The BORG Solution for a research LIMS