You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
In reading through the Study section, I came across an area that I thought may be of interest but which was not yet covered by the review-- protein-protein interaction. Since classical machine learning approaches like SVM, random forest, etc. and things like Bayesian networks have been predominant, I think this section would be a potentially meaningful presentation of a good opportunity for deep learning. I found a few papers in which deep learning was applied to this topic and put them below.
One aspect of PPI prediction that stands out is the diversity in features used between different studies. In fact, there was a preprint just released whose purpose is to outline some of the various features for machine learning PPI prediction. This seems like a good indication in my mind that this field would be a prime target for further research that incorporates deep learning.
If this seems like a meaningful subsection to include, perhaps a suitable location would be just below the protein secondary and tertiary structure section. Right here, greenelab/deep-review/sections/04_study.md seems like it would be a logical location.
The text was updated successfully, but these errors were encountered:
@zietzm protein-protein interactions are definitely an area of interest. We had no reason to exclude this topic in the version, simply a lack of a contributor to research and write about it. Would you be interested in leading this for the revised draft?
If so, I suggest that you create separate issues for the papers above so we can discuss them individually. In addition to PPI prediction, this sub-section could also cover PPI network analysis. As @mrwns pointed out in #543, PPI networks are also popular for graph representation learning and graph convolutions, topics I'm excited about. #241 could also be reviewed to see if it fits in a new PPI sub-section.
In reading through the Study section, I came across an area that I thought may be of interest but which was not yet covered by the review-- protein-protein interaction. Since classical machine learning approaches like SVM, random forest, etc. and things like Bayesian networks have been predominant, I think this section would be a potentially meaningful presentation of a good opportunity for deep learning. I found a few papers in which deep learning was applied to this topic and put them below.
One aspect of PPI prediction that stands out is the diversity in features used between different studies. In fact, there was a preprint just released whose purpose is to outline some of the various features for machine learning PPI prediction. This seems like a good indication in my mind that this field would be a prime target for further research that incorporates deep learning.
If this seems like a meaningful subsection to include, perhaps a suitable location would be just below the protein secondary and tertiary structure section. Right here, greenelab/deep-review/sections/04_study.md seems like it would be a logical location.
The text was updated successfully, but these errors were encountered: