Structural Biology Collaboratory

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Goals 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.

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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. - PowerPoint PPT Presentation

Transcript of Structural Biology Collaboratory

Page 1: Structural Biology Collaboratory

Goals

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.

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Remote access toexperimental facilities

24/7 access todata and computing

WWW Diffraction Image Viewer

Data Reductionand Structure Analysis

Synchrotron Research Resource

Data Collection

File Server and Compute Server

Crystal Mounting Robot

Structural Biology Collaboratory

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• 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

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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

Beamline Video System applications

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Archive System

• Need driven: Two new CCD detectors operational, which generate

74MB images with a readout of 1 second. Current 24/7 average duty cycle is 1% limited by

manual sample mounting and low intensity of x-ray beam

Increase of duty cycle to 20% through Structural Genomics initiative to automate sample handling and Spear3 upgrade to provide 20x increase in beam intensity by 2004

Increase to at least 6 similar systems• Objectives:

Large-volume long term data storage system. A centralized data storage system to allow users to

share data easilywith 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.

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Archive System Server

Blu-IceUnix “Uploader”

Archive System Database

SRB (Storage Res ourc e

Broker)

HPSS(High Performance

Storage System)

RAID System

WWW-GUI

SSRL or elsewhere

BLU-ICE• Automated backup during

data collection

WWW-GUI• 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

Archive System Architecture

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Automation Instrumentation

• 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

Data Driven Interfaces

High-throughput Structural Biology

• 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

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Structural Molecular Biology Macromolecular Crystallography Group at SSRL

• Peter Kuhn, Group Leader • Mike Soltis, Group Leader

• Collaboratory TeamJessica Chiu Thomas ErikssonKenneth 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