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Machine Learning-Based End-To-End CRISPR/Cas9 Guide Design
- fullstackwebdev 9y agomore info? how do I use this at home? also is it broken?
- josephpmay 9y agoIt would be nice if there was an explanation on what this was
- Kodix 9y agoSounds like it's a machine learning based way to make it easier to design the guide RNA for the CRISPR protein used in gene editing, making it easier to target it the way you want to. But that's basically all I know. It really would be nice to have someone actually knowledgeable describe this better.
- nfusi 9y agoYes, this is correct. We developed a series of ML models to predict 1) whether a given guide RNA is likely to result in the knockdown of a gene 2) whether a guide RNA is likely to produce unintended effects somewhere else in the genome. Also see https://blogs.microsoft.com/ai/crispr-gene-editing/ https://blogs.microsoft.com/ai/crispr-gene-editing/
- egl2019 9y agohttps://www.microsoft.com/en-us/research/project/crispr/ https://www.microsoft.com/en-us/research/project/crispr/
- xiphias 9y agoThanks for the link, this looks like a big deal that can help bringing the cost of gene editing / writing down. The paper is here: https://www.nature.com/articles/s41551-017-0178-6.epdf?referrer_access_token=CzZ4kcHL8yKmN8MOztCoj9RgN0jAjWel9jnR3ZoTv0M7RYfesQzcP58IAz4Y2ov3FLx2VYoj8Mj9n5vnfwpipKqdCgiJ5mnmA0pV7I8JIELITWJ8KlwgeZjBdkG9OZUMSECFgFX7jxKV_et8L5xh07BV3ONcn5JG1KJHIk4IcdlMErn4t0ebE23WVfRWigFA5zq_dXZp2gX7AFr7ITdfwxwZkcrwnswQs41l9W5AFjc%3D&tracking_referrer=www.microsoft.com https://www.nature.com/articles/s41551-017-0178-6.epdf?refer...
- j7ake 9y agoThis is one situation where a “black box “ method is pointless. When you design guide RNAs you most definitely want a transparent method that you can reason and debug.
- deleted 9y ago[deleted]
- make3 9y agoI mean, if there are a billion possible good solutions that's are each costly to debug/test, using ML to find some that are the most likely to work well to reduce the cost feels extremely useful to me
- theptip 9y agoOnly if the ML algorithm can perform the task better than the human who would otherwise be doing it.
- nfusi 9y agoI'm one of the authors. Predictive models like ours are useful for sorting through thousands of potential guides/sites and scoring them. In the paper associated with the service https://www.nature.com/articles/s41551-017-0178-6 https://www.nature.com/articles/s41551-017-0178-6 (pre-print here https://www.biorxiv.org/content/early/2016/10/05/078253 https://www.biorxiv.org/content/early/2016/10/05/078253) we look closely at what the models are picking up and explain our findings in the context of the current biological knowledge.
- nonbel 9y ago>"We found that adding these same features from the CFD model further boosted performance and so also included these. The final deployed model was trained only on the Avana data (combining with Gecko did not increase cross-validation performance)." https://www.biorxiv.org/content/early/2016/10/05/078253 https://www.biorxiv.org/content/early/2016/10/05/078253 Sounds like you leaked info from the training data into validation/test data, which will make you overfit and thus overstate the accuracy. I may have missed it, but did you evaluate the skill of this model on a holdout dataset? EDIT: This link doesn't appear to work: >"All source code and a front-end website for the cloud service will be made available from http://research.microsoft.com/en-us/projects/crispr http://research.microsoft.com/en-us/projects/crispr upon publication."