text: user4078: I have a couple of modified ML methods that I want to test with biological binary data - specifically binary gene expression data - e.g. https://eprints.soton.ac.uk/69359/1/Thesis.pdf that might include a variable that could be used to be the target variable in ML classification. What I mean by binary data is the features are all either 0 or 1, so I expect a large dataset e.g this thesis. I am looking for any suggestions.
  
  user3828: Kaggle has a cats v dogs dataset if you want to try your hand at biological image classification: https://www.kaggle.com/c/dogs-vs-cats
  The DREAM challenge competitions are usually specifically oriented to solving biological classification or learning problems with ML: http://dreamchallenges.org/
  
original_text: 4078: <p>I have a couple of modified ML methods that I want to test with biological binary data - specifically binary gene expression data - e.g. <a href="https://eprints.soton.ac.uk/69359/1/Thesis.pdf" rel="nofollow noreferrer">https://eprints.soton.ac.uk/69359/1/Thesis.pdf</a> that might include a variable that could be used to be the target variable in ML classification. What I mean by binary data is the features are all either 0 or 1, so I expect a large dataset e.g this thesis. I am looking for any suggestions.</p>
   3828: <p>Kaggle has a cats v dogs dataset if you want to try your hand at biological image classification: <a href="https://www.kaggle.com/c/dogs-vs-cats" rel="nofollow noreferrer">https://www.kaggle.com/c/dogs-vs-cats</a></p>
  
  <p>The DREAM challenge competitions are usually specifically oriented to solving biological classification or learning problems with ML: <a href="http://dreamchallenges.org/" rel="nofollow noreferrer">http://dreamchallenges.org/</a></p>
  