We’ll split the introduction to UMLS into two parts: theoretical and technical. This blog will cover the theoretical aspect explaining the theory behind UMLS while the next blog will cover technical aspects of UMLS assuming that you have a running instance of the database. Feel free to read through one or both of the blogs, depending on your requirements.More …
This is a continuation of a 2 part series in predicting the products of a chemical reaction using deep learning methods. Checkout the first part here.
In part 1, we:
- First introduced the problem statement
- Then we saw how a molecule is represented in a graph network
B reacts to form the products
D. The chances are that you have encountered this type of chemical reaction in your school days. While on paper they may seem as simple as drawing a bunch of arrows, in the real world, even the simplest of those reactions, takes a long time, money, and resources to formulate. The reaction time can vary from the order of seconds to the order of months.
Extended-Connectivity Fingerprints(ECFPs) are a type of molecular fingerprint explicitly designed to capture molecular features relevant to molecular activity. They are among the most popular similarity search tools in drug discovery and they are effectively used in a wide variety of applications.More …
In RdKit, the method
SetProp is used to set an atomic property for the atoms involved in the molecule. This method takes two arguments: the peroperty to set and its value. The idea is simple: Create an rdkit mol object from SMILES string, iterate over the atoms, and set the desired property to a custom value.