Data and Dissemination Core

1. Overview and EFI Website – Heidi Imker, UIUC2. EFI LabDB LIMS – Wladek Minor, UVA

3. SFLD – Patsy Babbitt, UCSF (post lunch)

Enzyme Function Initiative (EFI)Advisory Committee Meeting

November 30, 2011

The EFI’s goal is to develop and disseminate an integrated sequence/structure‑based strategy that incorporates a spectrum of essential expertise, including high‑throughput bioinformatics, computation and structural biology that will enable focused experimental enzymology, genetics, and metabolomics.

Superfamily/Genome Core- complete curated sequence archive for EFI superfamilies- “tools” for sequence analysis (including sequence/structure similarity networks)- portal for external bioinformatic data (including genomic contexts)

Computational Core - computational models

- computational docking- virtual screening libraries

SFLD

Protein Core- cloning, expression and purification

Structure Core- screening and crystallization - ligand binding (Thermofluor)

Microbiology Core - phenotypic analysis (Biolog) - metabolomics (MS based)

Bridging Projects - assay data (5 distinct superfamilies)

Structure/Function Context for EFI Targetsusing the

Structure-Function Linkage Database

Experimental Data Managementusing the

Laboratory Information Management System (LIMS)

LabDB

EFI Data and Dissemination

EFI Dissemination Flow

General Information and Data Portal

EFI Website

TargetDB

PepCDB

PDB

Data Deposition

Annotation Transfer

Experimental

Structure/Function Context

SFLDLabDB

EFI Experiment DB

Protein Core

PSI-MR

cross-linking

EFI Website - Initial

EFI Website - Revamped

EFI Website as a Reference

• New layout

• Rotating content • Figures from recent publications

• Images from recent structures

• Frequently used external link access

UIUC Web Developer Gabriel Horton

EFI Website as a Data Portal

Streamlined Navigation

1-Click AccessHOMOLOGUE SEARCH

RESOURCES

RESOURCES

EFI Website as a Data Portal

Tutorials

EFI-QuickHelps

• Find a specific target in the experimental database (EFI-DB)• Find a specific enzyme in the bioinformatic database (SFLD• Change memory for large networks (Cytoscape)• Searching in networks (Cytoscape)• View network at more stringent E-values (Cytoscape)• Add node attribute file to network (Cytoscape)

Full Guides and Tutorials

• EFI-DB Guide• SFLD Guide• Cytoscape Wiki• Cytoscape Tutorial• Chimera Tutorial

EFI Website Stats

Outreach

Current• Journal Publications (13) • Collaborations (2 proposed)• Talks/Seminars (4+)• Posters (1st EFI Session today) • Meeting Workshops (ASBMB 2013)• EFI Wikipedia Page

Planned• (Public) Newsletters• Mini-Papers• Instructional Webinars/Videos• Intensive Workshops

Data and Dissemination Core

1. Overview and EFI Website – Heidi Imker, UIUC2. EFI LabDB LIMS – Wladek Minor, UVA3. SFLD – Patsy Babbitt, UCSF (post lunch)

Enzyme Function Initiative (EFI)Advisory Committee Meeting

November 30, 2011

EFI-DB

LabDBPrivate (EFI)

Public (Biologist)

TargetDB/PepCDB

TargetTrack

PDB

Every 60 minutes

Real-time

Once weekly

Real-time

Experimental Data Management Architecture

10 Oct 2011 Charlottesville, VA

The LabDB LIMS

• Tracks all experiments in the pipeline from cloning to structure solution– Chemicals / stock solutions – Protein production: cloning / expression / purification– Crystallization / crystal harvesting– X-ray diffraction experiments / structures

• Access control– Login required to view data– Users divided into research groups– Different users/groups have varying permissions to access

data• Designed to extract as much information directly from the

laboratory hardware as possible

chemicals,solutions

clones,expressions,purifications

crystallizationdiffraction,structures

Equipment

InterfacesXtaldb

LabDB database

HKL-3000LabDB mobile LabDB web

LabDB: automated/semi-automated import from hardware (Private)

LabDB: the private interface to the LIMS

LabDB: shipment

LabDB: export as Comma Separated Values CSV

LabDB: Kinetic assays

EFI-DB: Public

EFI-DB: Target

EFI-DB: Status of the Target

Flu

ore

scen

ce

Temperature [C]

Experimental design and plate preparation

+ SYPRO Orange

+ protein

Experiment

Data analysis

EFI-DB: Automatic data harvesting

Plate design and set-up (Mosquito)

Many drops

Many drops + control

How to measure success?

• High Throughput ?

• High Output ?

• High Impact• SG - 10% structures are published• EFI is an investment for enabling the

biological community to accomplish functional assignments in their “favorite” families and superfamilies.

Deposition -> Publication (SG)

Time between deposition and publication

0%

5%

10%

15%

20%

25%

6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96

Time (months)

fraction of papers

Electronic Structure Description (minipaper)

EFI-DB: mini-paper