What are the requirements for the write-up?
Should we use markdown, latex, word? or just submit a PDF?
Any mandatory sections to include?
Greetings,
Carlos Vega
Created by Carlos Vega carlosvega > ##Note
> Below is a template for write-ups which Challenge participants will use to describe the methods and algorithms used to compute their final submission to the Challenge. It is encouraged to include citations and links to source code repositories. We prefer to have the source code submitted through Synapse and attached to your submission page. If your code is stored outside of Synapse (e.g., GitHub, BitBucket), please provide the link to your source code accordingly.
>
> Please look at the source code by clicking 'Wiki Tools' and 'View Wiki Source'.
#Title
Authors
Affiliations
* Will you be able to make your submission public as part of the challenge archive? Yes/No
> Only participants that agree to make their submission public can be part of the consortium and authors on the challenge summary publication
*Suggested figures limit: 2 figures*
##Summary Sentence
*(suggested limit 30 words)*
Include 1 short sentence description of your method that can be used in a main text table.
##Background/Introduction
*(suggested limit 200 words)*
Please try to address the following points:
* What is the motivation for your approach? This will include any previous work and observations that you have made about the data to suggest your approach is a good one. Provide the reader with an intuition of how you approached the problem
* What is the underlying methodology used (e.g., SVM or regression)?
* Where there any novel approaches taken in regards to feature selection, data imputation, ranking, etc?
##Methods
*(suggested limit 800 words)*
The methods should cover a full description of your methods so a reader can reproduce them. Please cover how you processed the data, if any data was imputed or manipulated in any way (e.g., you mapped data onto pathways or combined different datasets), the underlying algorithm, any modifications to the underlying method of importance, the incorporation of outside data, and the approach to predict submitted data.
If you submitted multiple predictions, please specify which is the difference among them (e.g. only parameters tuning or different algorithms). If needed, you can decide to write one sub-paragraph for each submission.
##Conclusion/Discussion
*(suggested limit 200 words)*
This section should include a short summary and any insights gained during the algorithm. For example, which dataset was most informative? You can include future directions. You may also add some discussion on the general performance of your methodology (if you wish) and if there were pitfalls, what are they?
##References
*(suggested limit 10 references)*
* Don't forget to reference your specific challenge (e.g. NIEHS-NCATS-UNC DREAM Toxicogenetics Challenge (syn1761567)).
##Authors Statement
Please list all author's contributions