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Structural Biology Collaboratory. Allow a team of researchers distributed anywhere in the world to perform a complete crystallographic experiment together. Enhance productivity by allowing remote collaborators to participate in experimental choices at the beam line.

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structural biology collaboratory
Structural Biology Collaboratory
  • Allow a team of researchers distributed anywhere in the world to perform a complete crystallographic experiment together.
  • Enhance productivity by allowing remote collaborators to participate in experimental choices at the beam line.
  • Facilitate collaborative experiments in such areas as drug design and structural genomics.
  • Fully utilize National resources for crystallographic experiments.


structural biology collaboratory1

Crystal Mounting Robot

WWW Diffraction

Image Viewer

Data Collection

File Server and

Compute Server

Data Reduction

and Structure Analysis

Synchrotron Research Resource

Structural Biology Collaboratory

24/7 access todata and computing

Remote access toexperimental facilities

beamline video system
Beamline Video System
  • 6 live feeds per SMB-Crystallography beamline
  • Currently available on 3 beamlines to increase to 6 over the coming 3 months
  • Critical machine surveillance for remote monitoring
  • Network limitations only allow low-quality feeds at present. Bottlenecks at SLAC and user’s institutions.
  • Benefits
  • Users can monitor sample and beam line remotely
  • Staff can troubleshoot and diagnose problems
  • Images served to automated sample alignment software
  • General features
  • A web-base GUI
  • Secure access
  • Restricted access
  • Preset positions
  • Synchrotronization of clients
  • Camera enable/disable
  • Image control
  • Snapshot
beamline video system applications
Beamline Video System applications
  • Live Live video feeds to BLU-ICE/DCS
  • Full remote control of the experiment
  • Interactive crystal alignment
  • Automated loop alignment
  • Beam line alignment
  • Beam line diagnostics and user-support
  • Robot monitoring and sample tracking
archive system
Archive System
  • Objectives:
  • Large-volume long term data storage system.
  • A centralized data storage system to allow users to share data easily
    • with their collaborators.
  • Support for the large area and fast readout detectors.
  • Meta-data catalog to allow searching of specific data sets.
  • Higher security and reliability than digital tapes.
  • Current Status:
  • A command-line based “Uploader” has been
    • developed and used by SMB staff rountinely.
  • srbBrowser provided by SDSC is currently
    • used for downloading data from SRB.
  • E-mail summaries to help book keeping.
  • System requirements were gathered from
    • users and SMB staff.
archive system architecture
Archive System Architecture

Unix “Uploader”



Archive System


Archive System


RAID System

SSRL or elsewhere


(Storage Res ourc e


  • Browse data at both SSRL and SDSC computers.
  • Upload and download data.
  • Set access permission.
  • Define, monitor and prioritize multiple arhicve jobs.
  • Searchable meta-data
  • E-mail summaries to help book-keeping
  • Automated backup during data collection


(High Performance

Storage System)

high throughput structural biology
High-throughput Structural Biology

Automation Instrumentation

  • Next generation scientific challenges
    • Structural genomics and proteomics in the post genome sequencing era
    • High-throughput structural biology for drug discovery
  • Global efforts
    • Life sciences is moving towards global collaborations in big-science efforts
    • Immense data generation and data mining at unprecedented rates

Data Driven Interfaces

  • A decade ago, interfaces were VT100-style
  • Modern interfaces are highly graphical and intuitive but are typically instrument driven
  • Next generation interfaces are data driven
structural molecular biology macromolecular crystallography group at ssrl
Structural Molecular Biology Macromolecular Crystallography Group at SSRL
  • Peter Kuhn, Group Leader
  • Mike Soltis, Group Leader
  • Collaboratory TeamJessica Chiu Thomas Eriksson
  • Kenneth Sharp
  • SMB Scientific Group: Ana Gonzalez Irimpan Mathews Ashley Deacon Jeanette Hobbs
  • StudentsJian Zhang Zepu Zhang Gilbert Martinez
  • SMB Beamlines Group: Aina Cohen Paul Ellis Mitch Miller Dan Harrington Mike Hollenbeck Paul Phizackerley Russ Floyd John KovarikJohn Coller SMB Software-Development: Tim McPhillips Scott McPhillips, Gunter Wolf Henry v.d. Bedem Hillary Yu
  • SMB Group: Linda Brinen Lisa Dunn Amanda Prado
  • Funding Support from:NIH NCRR; DOE BER; NIH NIGMS; TSRI; Stanford Graduate Program