Issue Solution Action

Which model should be used for what application?

Individuals with different modeling approaches to develop framework for describing models and applications

Eric Schadt, David Haussler, Dexter Pratt, Gaurav Pandey on the hook for writing a paper to map network modeling approaches to applications

What are models and how can we make them inter-operable?

Develop semantic framework to describe models

Barend Mons Spyro Mousses to convene working group to develop this framework

How do we compare modeling approaches

Need reference datasets for comparing different approaches and their ability to predict features

Sage to look into “Network Challenge” on such datasets to engage community in contributing modeling apporaches

 Main issues   Problem: Lack of understanding of rules to be followed to use

platform   Solution: Pay attention to governance rules and rules of

engagement in putting a platform together (e.g., can we use data as we please, do we need to include providers on papers, etc.)

  Problem: How do a general class of modelers get connected to those with data and those who can aid in interpreting results

  Solution: Platform needs to facilitate such matching, connecting those with data to those wanting to process data, with appropriate attributions worked in

 Main issues   Problem: Reproducible science   Solution: Platform enforces information tracking, produces a

graph that details every dataset, changes to datasets, code applied, etc. relating to a set of results

  Problem: How will I interact with the platform   Solution: Need well defined APIs; need private workspaces to

work out models and associated code and then ability to “publish” when ready

Issue: Shouldn't use the term validation as it implies some context of absolute truth that is unattainable. Rather we are striving for levels of accuracy or more important "usefulness". Experimental important here not just computational validation.

Solution: Should use 1) Usefulness; 2) Predictiveness; 3) Generalizability (less important) NOT validation

Issue: Phenotypes are the weak link in much of the data. Need better intermediate/endo phenotypes. Being able to link to intermediate phenotypes powerful for thinking about validation where things like survival hard to attain

Solution: nothing specific here!

Issue: How to engage experimentalists? Solution: Prize-based out-sourcing solutions should be tried; open up access to validation tools (SGC efforts; tapping pharma compound collections?); FNIH Biomarker consortium effort; validation tool kits - zn-finger libraries, etc.

Issue: How do we target networks? Solution: Need to think beyond single gene/node targeting. Screen for activities based on network state. Use "connectivity map" to come up with POC.

Issue: How should we use model organisms? Solution: Need to consider how to match "network states" across organisms to convince that models are good molecular reflection of human disease state.