Sig paper vote

Expansion of Bio-Ontologies SIG Paper for Journal Publication

Agree to be a co-author (please put here your name and affilation as you wish to see it in the paper)

- Larisa N. Soldatova, Aberystwyth University, Wales, UK.

- Jennifer M. Fostel, Global Health Sector, SRA International, Inc, Durham, NC, USA

- Melanie Courtot, BC Cancer Agency, 675 West 10th Avenue, Vancouver, BC, Canada

- Ryan R. Brinkman, BC Cancer Agency, 675 West 10th Avenue, Vancouver, BC, Canada

- Helen Parkinson, EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK

- James Malone, EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK

- Yongqun He, University of Michigan Medical School, 1150 Medical Center Dr., Ann Arbor, MI, USA 48109-5614

- Jie Zheng, Center for Bioinformatics, Department of Genetics, University of Pennsylvania School of Medicine, PA, USA

- Christian J. Stoeckert, Jr., Center for Bioinformatics, Department of Genetics, University of Pennsylvania School of Medicine, PA, USA

- Bjoern Peters, La Jolla Institute for Allergy and Immunology, La Jolla, CA, USA

- Jessica Turner, Dept of Psychiatry and Human Behavior, University of California, Irvine, CA USA

- Phillip Lord, School of Computing Science, Newcastle University, UK

- Philippe Rocca-Serra, EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK

- Alan Ruttenberg, Science Commons, Cambridge, MA, 02155

- Susanna-Assunta Sansone, EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK

Acknowledgments

copied from the previous SIG paper section and edited.

This work is partially supported by grant funding from the National Institute of Biomedical Imaging and Bioengineering, National Human Genome Institute, NIH (R01EB005034, R01AI081062, NIH P41 HG003619, HHSN26620040006C), EC EMERALD project (LSHG-CT-2006-037686), EC MUGEN, BBSRC (BB/E025080/1, BB/C008200/1), RC UK, NERC-NEBC, EU IP CarcinoGenomics (PL 037712), EU NoE NuGO (NoE 503630), CARMEN project EPSRC (EP/E002331/1), the Michael Smith Foundation for Health Research and EMBL

- BP: HHSN26620040006C

- RC UK

- JF's contribution was supported by the Intramural Research Program of the NIH and NIEHS, under contract HHSN273200700046U.

- MC: (acknowledgment to) the Public Health Agency of Canada / Canadian Institutes of Health Research Influenza Research Network (PCIRN).

- PRS and SAS: contribution was supported by NERC-NEBC, EU IP CarcinoGenomics (PL 037712), EU NoE NuGO (NoE 503630) and BBSRC (BB/E025080/1 and BB/G000638/1).

- YH's contribution was supported by the NIH-NIAID grant R01AI081062.

- JT's contribution was supported by the NIMH (NIH) grant R01MH084812-01A1 and the NCRR (NIH) grant to the Bio-Informatics Research Network Coordinating Center (BIRN-CC), U24 RR025736-01.

The OBI SIG paper has been invited for expansion and inclusion in a special edition of JBMS http://www.jbiomedsem.com/ As we are already writing a Journal paper for publication elsewhere, there is concern that this could end up as a distraction, delaying the release manuscript and may also require considerable work so that it aligns with the ontology correctly. Furthermore, there is a lack of interest from enough parties to actually do the work for this 2nd paper. With this in mind, we require a vote on the following, NOTE: the deadline for submission to JBMS is OCTOBER 30th. Please initial your choice:

Vote

Option 1: We should not write another Journal paper for JBMS

Initials: HP (will help with SIG paper if outvoted), BP (but I am happy to be outvoted, and will then want to check on the content of the SIG paper) PRS (major issue is overlap with main manuscript and submission before the main manuscript)

Option 2^: We should write an extension paper. (if you vote for this see below)

Initials: JM, OH, JF, JZ, MC, RB, DD (as long as effort does not impact progress on bi-weekly calls/main paper), LSS, CS

The result: option 2 has won and we are working on the paper. Thank you very much to everyone!

^If you voted option 2, please indicate if you would be willing to do work on this paper and in what capactiy (e.g. JM: Willing to write a use case). By 30 October 2009

Initials:
JM - can help writing
OH - can actively work on it
JF - can contribute editing
JZ - can work on it for anything I can help
MC - happy to review and correct draft
RB - happy to review and correct draft
LSS- can actively work on it
DD - Can finish use case cognitive neuroscience - decision processing, (which I at one stage already sent to Melanie for review)
CS - happy to review and correct draft
DS - can work on it for anything I can help

Use Case: Cognitive Neuroscience

The paper represented can be found here.

About the diagrams

In short: the experiment tries studies the role of the caudate nucleus in the control of action and more specifically targets the reward factor. It is found that the caudate nucleus is active before the actual presentation of the stimulus and fires more for the reward related position.

I represented the following elements of the study:

• Study Design
• 1 subject: 'Monkey 1'
• Measurements and Stats
• Stimulus 'Left Cue'

Diagrams

Study Design

This investigation studies the role of the caudate nucleus in the expectation of reward following action (Figure 1). It is found that while the caudate nucleus responds preferentially to eye movements in different directions, and when there is expectation of reward for the preferred direction, the response begins prior to eye movement and is dramatically increased.

We are modeling only a portion of the experimental process, particularly a single trial in which the visual target is presented and the neural response is recorded. We are not modeling the changes over trials that modulate the expectation of reward for different eye movements.

This single trial model contains two processes:

• The presentation of the visual target to which the monkey makes a eye movement is modeled as a ‘presenting stimulus to subject’ process that is realized by some ‘light source’ bearing and some ‘monkey’ bearing the ‘study subject role’ . The ‘light source’ is an independent_continuant.
• ‘measuring neural activity in monkey caudate nucleus’ is modeled as a ‘extracellular electrophysiology recording’ process that has the specific input of some ‘neuron’ which has location in the ‘caudate nucleus’ which is ‘part of’ the ‘monkey’. The process of measuring neural activity has the specified output of a neuronal spike train measurement. The measurement is measured by device ‘SU device + electrodes’. The spike train measurement is then input into further data transformations, which are not modeled here.

Measurements

This represents the measurements of the experiments. I represented single unit recordings and reaction times. There is no direct access to the data, hence the figures are well represented in the diagram.

Subject

This represents the subject and its recording location. It as such does not hold a lot of information, yet it seems to be fairly easy to represent the available elements.

Stimulus 'Left Cue'

This represents the stimulus "Left Cue'. A bit more detail than previous diagram, showing how detailed you can get using OBI.

Use Case: Automated Functional Genomics

Robot Scientist “Adam” is one of the most advanced laboratory automation systems in existence [King et al 2009]. Adam is designed to measure, in high-throughput, growth curves (phenotypes) of selected microbial strains (genotypes) in a defined media (environment). Adam is able to run “lights out” for days at a time, and is capable of designing and initiating >1,000 new strain/defined growth-medium experiments each day (from a selection of several thousand yeast strains).

The Robots require a complete, precise, and fully formalised description of all experiment actions (for example, if you forgot to include an action “remove a plate lid”, it will try to pierce pipettes through the lid). Robot Scientists provide unsurpassed test beds for the development of technologies for the curation and annotation of experiment processes: for the first time it is possible to completely capture and digitally curate all aspects of the scientific process to record and fully understand how and why a particular experiment was conceived and executed, and to remove all subjectivity in experiment actions. This enables all aspects of investigation to be fully repeatable. The Robot Scientist project led to the first fully automatic discovery of new scientific knowledge, and has the potential to revolutionise the way science is done [Science, reply].

We can consider three typical processes: planning of an experiment, executing an assay, and analysing the results (fig 1,2,3). We can discuss here robot has role or function "investigator".

I can put much more here and figures are very drafty, but the main ideas are there.

Refrences: King et al. (2009) The Automation of Science. Science 324: 85-89. King, et al. (2009) Make Way for Robot Scientists. Science 325: 945. King, et al.(2009) The Robot Scientist Adam. Computer 42/8: 46-54. King et al. (2004) Functional Genomics Hypothesis Generation by a Robot Scientist, Nature 427(6971): 247-252.