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In this blog post I’m going to look at 3D-QSAR in Cresset’s software. I will share some of my experience on the best way to do it and, more importantly, what not to do. 3D-QSAR is one of those techniques that everybody loves. When it’s done well you get quantitative results, validation that the model actually has some predictive power, estimates on the limits of that predictive power and you also get interpretable pretty pictures that give a better mental picture of what the protein wants in its ligands. What’s not to like?

Digitus Usb To Serial Drivers. The flip side is that 3D-QSAR is hard. It’s difficult to get a good model, it can be difficult to interpret a model once you’ve got one and it can be frighteningly easy to obtain an invalid model if you are not careful. The reason for this is that 3D-QSAR, unlike most 2D-QSAR, has noise in the inputs. When you run a traditional 2D-QSAR model you need to select from a wide array of numerical modeling methods. Are you going to use support vector machines? Hardlock Device Driver For Windows X64 Solidworks Certification. Gaussian process models? Feed forward neural networks?