Ed's Big Plans

Computing for Science and Awesome

Meeting with Chris

without comments

Chris’ project has grown to data sets of roughly three hundred exemplars for each the mouse and rat data sets– these are the sets that mapped molecules to some physiological defect, by organ or tissue. I think he’ll be onto his next phase shortly– taking the data and applying some machine learning construct to it.

I’ve recommended four papers to him to read– three of which discuss QSAR in general, and compare the performance of different approaches. The last paper explicitly uses neural networks for descriptors in regression of melting points. The use of neural networks or similar technology is something that he’s expressed a lot of interest in, so I think this selection falls in well. I’ve provided him with an adapted version of the melting point dataset where the domain is re-expressed as SMILES and InChI.

I think it might be good to set him up with NGNs for those items as well as NNs for the descriptor vector used in the melting point paper.