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PIMS: The Problems of Project Management

PIMS: The Problems of Project Management. Robert Esnouf, Scientific Sponsor for PIMS OPPF/STRUBI, University of Oxford. strubi .ox.ac.uk. PIMS “mission statement”….

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PIMS: The Problems of Project Management

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  1. PIMS: The Problems ofProject Management Robert Esnouf, Scientific Sponsor for PIMS OPPF/STRUBI, University of Oxford strubi .ox.ac.uk

  2. PIMS “mission statement”… • “To produce a commercial-quality freely available laboratory information management system (LIMS) suitable for use in structural biology research laboratories” • Many (partially) failed efforts in the past • Process is very complex (by previous LIMS standards) • Research processes rapidly evolve (need configuration rather than customization) • No two laboratories have the same working practices

  3. Information to be managed… • Potential targets / bioinformatics annotation • Target selection and construct design • Project planning and progress • Experiments and protocols (templates) • Non-plate: expression, purification, “traditional” work • Plate-based: PCR, cloning, crystallization • QA: gels, mass spectroscopy, sequencing, DLS • Samples and sample descriptions (e.g. sequences) • Holders and locations • Stocks, reagents and reference data • Health and safety information • Users, roles, access / sharing and security • Databases and external references • X-ray diffraction / structure solution

  4. Functionality required… • An interface for entering data • Simple to use, intuitive • Minimal client software • Secure storage of well defined data (database) • An interface for recovering / analyzing data • An interface for project management • Administration (configuration and management roles) • Interface to external software (e.g. web services) • Integration of robotic platforms • parsing output files • producing run sequence files • direct robotic control

  5. Scientific goals for PIMS… Recording laboratory information • A lot of data recording • 10,000s of experiments • 1,000,000s of samples Data interchange and interoperation • Collaboration in protein production • Share data between stages and sites • Data transfer to beam line or NMR operations Data mining and reporting • Analysis of positive and negative results • Data deposition • Scientific publications

  6. The story of PIMS so far… • PIMS started as a loose consortium involving labs in the UK, France and elsewhere • PIMS BBSRC SPoRT grant (3.62 FTE) • in collaboration with and in support of other SPoRTaward holders (SSPF and MPSI) with heavyinvolvement of CCP4 (2 FTE), OPPF and others • PIMS effectively started 4/2005 (one post 2/2006) • Management structure re-investigated late 2005 • Part-time ‘Scientific Sponsor’ (Robert E)who works with ‘Project Manager’ (Chris M) • Version 1.0 released 15/1/2007 • Version 1.1 due 17/4/2007

  7. PIMS version 1.0: January 2007… • Improved performance • Adequate for small-to-medium scale • Barely adequate for scale of OPPF target data • 10,000 targets, 4,000 constructs imported, 3 genomes • Support for plate-based experiments • Simplified user interface • “Generic” interface became “Expert” interface • Development guided by end-user feedback • First sample tracking to link experiments together • Create a pipeline of data • Workshop to introduce users to PIMS • Now focusing on SPoRT/OPPF use

  8. PIMS management structure… Project Steering Board Major featurerequests Major featurerequests Line Man. Line Man. Robert E Local issues andrequirements;daily management Progress & issues Strategy &priorities Chris M Developer Developer Developer Developer Developer Tasks, coordinationprogress monitoring

  9. Short-term / long-term issues… • Meeting the needs of SPoRT consortia / OPPF / YSBL etc. • Implementations of established experimental procedures • Interfacing existing software • Each lab gets a custom interface • Developing a truly generic LIMS for end of project • Balancing competing interests • One size fits all/no one • Model is comprehensive/cumbersome • Interface is complex • Lack of early user input • Shared goals • Common way of representing data underneath • Contributed software • Extensible application

  10. Current interaction with CCPN… Object Domain User Interface Complete Data model Business Logic PIMS model PIMS API ‘Hibernate’ API PIMS/CCPN Autogeneration Software Hibernate Mapping Files Hibernate Persistence Layer PostgreSQL DB • Review of data model/data base • ObjectDomain has ceased trading

  11. Problems of distributed projects… • Isolated developers • Need good support • Face contradictory demands • Developers not near experimentalists • Relevance of developments • Usability of developments • Focus is provided by real use • Needs “big picture” vision to get to “real use” stage • First experience of users can be brutal • Need developers to spend time together • Code camps / teleconferencing • Email is poor communication

  12. Problems of distributed projects… • Management by a distributed PSB • Requires consent/indulgence of collaborating groups • Hard to get PSB together for meetings • Interaction between PSB and developers • Need for clear minutes/actions • Scientific sponsor could easily be full time role • Assessment by BBSRC • Review not by computer scientists (not bad!) • Original review process contained no demo (very bad!) • Visiting group assessed PIMS in November • ‘Mid-term’ review will consist of demo at BBSRC

  13. PIMS non-plate experiments…

  14. PIMS plate-based experiments…

  15. Oxford Protein Production Facility… • Example follows 96 constructs through PCR, Gateway cloning and expression screening with two cell lines and two protocols: • Top shows plate usage • Bottom shows the number of 96-lane agarose gels, 24-well colony-plate images and 26-lane SDS–PAGE gels • 96 constructs uses 34 96-well plates and 36 24-well plates… • …generates 480 images of colony wells,1536 lanes on agarose gelsand 416 lanes on SDS–PAGE gels

  16. Working with MPSI to increase use… • Target annotation (largely covered in PIMS 0.4) • Target selection (not planned for PIMS) • Construct design (using VectorNTI) • Obtain/store source strain genomic DNA • Describe selected genes • Describe primers, link to VectorNTI output • Describe entry clones as plasmids • Describe expression constructs • Describe high-throughput expression trials • Describe solubilization trials…

  17. Solubilization trials (Leeds)… • Solubilization trials performed in 96-well format • Perform 24-trials per target, therefore four targets per set Detergent concentration gradients… Det 1 Det 2 Target 1 Target 2 Det 3 Det 4 Det 1 Det 2 Target 3 Target 4 Det 3 Det 4

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