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Sharing the knowledge of electrophysiology data. Phillip Lord, Frank Gibson and the CARMEN Consortium. “In the standard model, one collects data, publishes a paper or papers and then gradually loses the original dataset.”

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Sharing the knowledge of electrophysiology data

Sharing the knowledge of electrophysiology data

Phillip Lord, Frank Gibson and the CARMEN Consortium


Sharing the knowledge of electrophysiology data

“In the standard model, one collects data, publishes a paper or papers and then gradually loses the original dataset.”

THE NEW KNOWLEDGE ECONOMY AND SCIENCE AND TECHNOLOGY POLICYGeoffrey Bowker, University of California, San Diego


The need for clear metadata
The need for clear metadata paper or papers and then gradually loses the original dataset.”

  • Most neurosciences data is relative simple in structure

  • But often contextually complex

  • Sometimes associated with behavioural features


Neuroscience spike data
Neuroscience spike data paper or papers and then gradually loses the original dataset.”

  • The raw data is normally a waveform

    • But, advances in instrumentation

    • High-throughput methods

  • But what is the experiment for?

    • What stimulus is the organism/tissue receiving?

    • Which channel is which

  • The data sets being produced are (reasonably) large (10’s of Gb, or 1Tb in three months)


Information extraction

http://en.wikipedia.org/wiki/Image:Brain_090407.jpg paper or papers and then gradually loses the original dataset.”

istockphoto.com

Information Extraction

  • How do we get extract the information?

http://en.wikipedia.org/wiki/Image:ATTtelephone-large.jpg


Multi author data
Multi-Author data paper or papers and then gradually loses the original dataset.”

From Katherine James, NCL


Sharing the knowledge of electrophysiology data

Author paper or papers and then gradually loses the original dataset.”

PMID

Type

Size

1

Davierwala et al

16155567

Synthetic_Lethality

627

2

Krogan et al

14759368

Affinity_Capture-MS

164

3

Hazbun et al

14690591

Affinity_Capture-MS

3210

4

Gavin et al

11805826

Affinity_Capture-MS

3596

5

Ho et al

11805837

Affinity_Capture-MS

733

6

Ito et al

11283351

Two-hybrid

275

7

Tong et al

11743205

Synthetic_Lethality

3411

8

Tong et al

14764870

Synthetic_Lethality

823

9

Uetz et al

10688190

Two-hybrid

1941

10

Miller et al

16093310

Two-hybrid

104

11

Lindstrom et al

12556496

Affinity_Capture-MS

134

12

Nissan et al

12374754

Affinity_Capture-MS

456

13

Grandi et al

12150911

Affinity_Capture-MS

150

14

Ohi et al

11884590

Affinity_Capture-MS

630

15

Krogan et al

14690608

Affinity_Capture-MS

370

16

Sanders et al

12052880

Affinity_Capture-MS

102

17

Baetz et al

14729968

Affinity_Capture-MS

258

18

Fromont-Racine et al

10900456

Two-hybrid

160

19

Fromont-Racine et al

9207794

Two-hybrid

182

20

Drees et al

11489916

Two-hybrid

232

21

Tong et al

11743162

Affinity_Capture-Western

125

22

Allen et al

11387327

Affinity_Capture-MS

116

23

Panse et al

15292183

Affinity_Capture-MS

181

24

Krogan et al

15353583

Affinity_Capture-MS

113

25

Kong et al

15563457

Protein-peptide

157

26

Hannich et al

15590687

Two-hybrid

134

27

Newman et al

11087867

Two-hybrid

464

28

Zhao et al

15766533

Reconstituted_Complex

125

29

Millson et al

15879519

Affinity_Capture-Western

369

30

Ubersax et al

14574415

Biochemical_Activity

138

31

Ingvarsdottir et al

15657441

Affinity_Capture-Western

175

32

Lesage et al

15166135

Synthetic_Lethality

292

33

Lesage et al

15715908

Synthetic_Lethality

323

34

Pan et al

15525520

Synthetic_Lethality

124

35

Loeillet et al

15725626

Synthetic_Lethality

214

36

Daniel et al

16157669

Synthetic_Lethality

4535

37

Pan et al

16487579

Synthetic_Growth_Defect

7076

38

Krogan et al

16554755

Affinity_Capture-MS

6531

39

Gavin et al

16429126

Affinity_Capture-MS

107

40

Milgrom et al

16118188

Synthetic_Lethality

215

41

Measday et al

16172405

Two-hybrid

477

42

Graumann et al

14660704

Affinity_Capture-MS

4179

43

Ptacek et al

16319894

Biochemical_Activity

103

44

Frazier et al

16476776

Co-fractionation

290

45

Ye et al

16729061

Synthetic_Rescue

3416

46

Schuldiner et al

16269340

Phenotypic_Enhancement

14421

47

Collins et al

17314980

Phenotypic_Enhancement

9064

48

Collins et al

17200106

Affinity_Capture-MS

117

49

Aronova et al

17507646

Co-fractionation

576

50

Wong et al

17634282

Two-hybrid

234


How do we represent
How do we represent… paper or papers and then gradually loses the original dataset.”

In silico Analysis

Derived data

Laboratory

Experiments


View from microarrays
View from microarrays paper or papers and then gradually loses the original dataset.”

Content Standard – Minimal Information

MO -- Terminology

MAGE -- Structure

From the MGED society


The carmen approach
The CARMEN approach paper or papers and then gradually loses the original dataset.”

Content Standard – Minimal Information about a Neuroscience Investigation

OBI – Ontology for Biomedical Investigations

FuGE -- Structure


Sharing the knowledge of electrophysiology data
Minimal Information About a Neuroscience Investigation: paper or papers and then gradually loses the original dataset.”What do I have to tell you, for you to understand what I did?

  • Subdivided as;

    • Contact and context

    • Study subject

    • Recording location

    • Task

    • Stimulus

    • Behavioural event

    • Recording

    • Time series data

Study inputs

Assay inputs

Assay procedures

Data


Mini in relation to the life science reporting requirements
MINI in relation to the life-science reporting requirements paper or papers and then gradually loses the original dataset.”


Miaows
MIAOWS paper or papers and then gradually loses the original dataset.”

  • Describe essential metadata for your analysis code

    • What does it do? Objective

    • What type of input does it need

    • What type of output does it produce

    • If this information is not described, your code is of most value to yourself and much less value to the community


The carmen approach1
The CARMEN approach paper or papers and then gradually loses the original dataset.”

Content Standard – Minimal Information about a Neuroscience Investigation

OBI – Ontology for Biomedical Investigations

FuGE -- Structure


Functional genomics experiment fuge how do i tell you for you to understand
Functional Genomics Experiment paper or papers and then gradually loses the original dataset.”(FuGE)How do I tell you, for you to understand?

  • Model of common components in science investigations, such as materials, data, protocols, equipment and software.

  • Provides a framework for capturing complete laboratory workflows, enabling the integration of pre-existing data formats.


Model driven architecture symba
Model Driven Architecture -- SyMBA paper or papers and then gradually loses the original dataset.”

UML

XML

Java objects

database


Fuge community of users
FuGE community of users paper or papers and then gradually loses the original dataset.”

  • MGED (transcriptomics)

  • Proteomics Standards Initiative

  • Metabolomics Standards Initiative (NMR and sample processing groups)

  • Genomics Standards Consortium (MIGS)

  • CARMEN, Code Analysis, Repository and Modelling for e-Neuroscience

  • Flow Informatics and Computational Cytometry Society

  • MIARE: Minimum Information About an RNAi Experiment


Functional genomics experiment fuge how do i tell you for you to understand1
Functional Genomics Experiment paper or papers and then gradually loses the original dataset.”(FuGE)How do I tell you, for you to understand?

  • Model of common components in science investigations, such as materials, data, protocols, equipment and software.

  • Provides a framework for capturing complete laboratory workflows, enabling the integration of pre-existing data formats.


The carmen approach2
The CARMEN approach paper or papers and then gradually loses the original dataset.”

Content Standard – Minimal Information about a Neuroscience Investigation

OBI – Ontology for Biomedical Investigations

FuGE -- Structure


Obi ontology of biomedical investigations
OBI – Ontology of Biomedical Investigations paper or papers and then gradually loses the original dataset.”

Diversity communities

from Nutrition to Metabolomics, from Environmental to genomics to Immunology, Imaging and Data analysis

OBI branches:

development work

Protocol application branch

Data Transformation branch

Instrument branch

Biomaterial branch

Role branch

Function branch

Molecular entities

Digital entity branch

Adapted from Philippe Rocca-Serra, 2008


Summary
Summary paper or papers and then gradually loses the original dataset.”

  • We are generating metadata “standards” for neurosciences

  • We are following a well-trodden path from bioinformatics

  • We adopted FuGE and have built MINI


Future work
Future Work paper or papers and then gradually loses the original dataset.”

  • More neurosciences experimental datatypes.

  • Minimal Information about a Service

    • Describe analysis software as well as lab experiments.

  • Outreach!


Acknowledgements
Acknowledgements paper or papers and then gradually loses the original dataset.”

MINI: Frank Gibson, Paul G Overton, Tom V Smulders, Simon R Schultz, Stephen J Eglen, Colin D Ingram, Stefano Panzeri, Phil Bream, Evelyne Sernagor, Mark Cunningham, Christopher Adams, Christoph Echtermeyer, Jennifer Simonotto, Marcus Kaiser, Daniel C Swan, Martyn Fletcher, Phillip Lord

CISBAN: Anil Wipat (PI), Allyson Lister (Research Associate),

FuGE: The FuGE consortium

OBI: The OBI consortium

CARMEN: http://www.carmen.org.uk

SyMBA: http://symba.sourceforge.net

FuGE: http://fuge.sourceforge.net

OBI: http://obi.sourceforge.net


Carmen consortium
CARMEN Consortium paper or papers and then gradually loses the original dataset.”