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Start Date: Jan 12, 2017
End Date: Jun 16, 2017

Love data, big and small? We do, too.              

Join the dkNET-NURSA challenge to help scientific community, and WIN BIG PRIZES while using small data to create BIG DATA!


Challenge FAQs


Webinar Announcements:

Want to learn how to use dkNET and also win big prizes?

Join our dkNET-NURSA Challenge kick-off webinar!

Date: 12:00 p.m. PT, April 27, 2017

Registration link: https://goo.gl/rkOZDw !

 New  Webinar video is now available at our YouTube channel.

 

dkNET Introductory webinar

Date: 11:00 a.m. PT, May 10, 2017

Registration link: https://goo.gl/8M8OBp

 New  Webinar video is now available at our YouTube channel.


Download Flyer Here to share dkNET-NURSA Challenge information with your students, post-docs and colleagues!


Background 

The Nuclear Receptor Signaling Atlas (NURSA) is partnering with the NIDDK Information Network (dkNET.org) to create big data from small data. Everyone is talking about Big Data. How can we ensure that the impact of individual scientists working on a myriad of small and focused studies that discover and probe new phenomena - is not lost in the Big Data world.  In fact, there is more than one way to generate big data and we would like your help in creating and expanding  “big data” for NIDDK! NURSA is curating a growing database, Transcriptomine, for global-scale expression profiling (transcriptomic) datasets relevant to nuclear receptor (NR) signaling pathways. In order to build a comprehensive "big" data set, we want to complement this transcriptomic resource with other omics datasets relevant to nuclear receptor and coregulatory pathways, and we need your help to assist the community to identify such datasets. The NIDDK Information Network (dkNET, http://dknet.org) is an open community portal that functions as a search engine for data, information, and resources that provides seamless access to large pools of data and research resources in the fields of diabetes, digestive, endocrine, metabolic, kidney, and urologic diseases. In this challenge, we encourage researchers to learn how to use dkNET to identify datasets and relevant information more efficiently and to help us make dkNET better by providing feedback.    

 

 Join Now - It's Easy!

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STEPS

1. Go to dknet.org
2. Open an account, login, and join the challenge
3. Download worksheet (located on the right side of the challenge page: DOWNLOAD WORKSHEET)
4. Search and identify "omics" datasets

c. Read tips

d. Visit Challenge FAQ page and see tutorial slides


5. Annotate many datasets
6. Receive bonus points
7. Upload worksheet (click submission under YOUR RESULTS, located on the right side of the challenge page)

8. Win prizes!



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Biocuration Challenge

Identify and annotate as many discovery-scale (omics) datasets as possible involving perturbations of nuclear receptor or coregulator signaling pathways. Required categories are cistromic (ChIP-Seq), proteomic (mass-spec-based protein-protein interaction or whole-proteome profiling), post-translatomic (phosphorylation, acetylation or other modification) or metabolomic. Here are some examples:

  1. Cistromic/ChIP-Seq  Example: MCF-7 cells are treated with 17-beta-estradiol followed by chromatin immunoprecipitation with an ER-alpha-specific antibody.
  1. Protein-protein interactomics   Example: MCF-7 cells are treated with 17-beta-estradiol, then IPd with an ER-alpha-specific antibody & subjected to mass spec analysis
  1. Post-translatomics   Example: HEK293 cells stably expressing FLAG-GR-alpha were treated for 1 h with or without 10 nM dexamethasone prior to lysis and incubation with anti-FLAG antibody followed by extraction with anti-pTyr antibody & mass spec analysis.
  1. Metabolomics    Example: MCF-7 cells are treated with 17-beta-estradiol, then subjected to metabolomic mass spec analysis.

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                                                                                                                                                         Screenshots from https://nursa.org


Award 
  • $50 gift card will be awarded to the first 20 teams (individuals or groups) who complete annotating five new datasets.
  • Annotate as many datasets as you can to receive the opportunity to win a bigger cash prize! A $500 cash prize, generously sponsored by SciCrunch Inc., will be awarded to the team who accumulates the highest number of points before the deadline. 


Dataset Requirements 

  • Datasets must involve either:
  1. Treatment with a small molecule perturbant (physiological ligand, drug, synthetic organic compound, etc) of a nuclear receptor or coregulator; OR
  2. Genetic pertubation (knockout, knock-in, knockdown, overexpression) of a nuclear receptor or coregulator.
  3. See the NURSA website for a list of NR signaling pathways and their corresponding small molecule & genetic perturbants in the current version of Transcriptomine.
  • Datasets can be generated using cultured or primary cell lines or animal models


Worksheet

After opening a dkNET account, you will be able to download an EXCEL file containing the dataset worksheet
For this challenge, you only need to fill in the information regarding each dataset in the worksheet. You don't need to upload the real dataset to the dkNET platform.  An example of the information to be filled in for each dataset is listed here:

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Points System


Tips

A good place to start is dkNET:

(1) When using dkNET to find data, search under More Resources (

https://dknet.org/data/search) instead of Community Resource to expand your search.  

(2) Use quotes around phrases you want to match exactly, such as androgen receptor. Avoid of, in.

(3) For multiple search terms, use operators such as AND, OR.  

(4) Use facet on the left side to refine your results.   

(5) Save your search to receive updates.  

(6) Check out the Challenge Help page, dkNET Help page, workshop slides, tutorials, or attend upcoming dkNET webinar to learn more.

  • More good places to start are literature reviews or repositories
  • Form a team for more efficient searching
  • Sign up for journal tables of content to identify relevant newly published studies
  • Even if a dataset is deposited, the repository accession number is not always included in the associated article.
  • Article information is not always included in repositories (esp. GEO)



Go to Challenge FAQ Page



Challenge Deadline and Contact Information


The deadline for the dkNET-NURSA Challenge is at 23:59:59 PDT June 16, 2016. If you have any questions regarding the challenge, feel free to contact us at info@dknet.org


The dkNET-NURSA challenge is a joint effort between the NIDDK Information Network (dkNET) hosted at University of California San Diego and Nuclear Receptor Signaling Atlas (NURSA) hosted at Baylor College of Medicine. dkNET is funded by the National Institute of Diabetes, Digestive and Kidney Diseases (NIDDK) DK097771. NURSA is funded by NIDDK DK097748 with supplemental funding from the National Institute of Child Health and Development (NICHD). Submissions will be reviewed for accuracy by the NURSA biocuration team.




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Join the Challenge

Download Worksheet

Worksheet
01/12/2017 to 06/16/2017
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