As it is known, GEO Database is home to thousands of High-Throughput (HT) genetic expresison experiments. The documentation for each experiment done within the database includes the Growth Conditions (GC) used in it. Unfurtunately they are not registered in a structured way, but they are into text fragments associated with various fields (we call them metadata).
Since knowing the GCs of these experiments helps to better understand genetic regulation, it becomes important to extract these conditions. However, doing it manually requires a lot of
effort on large data sets.
Thats why, our hypothesis is that a predictive model can determine the GCs of thousands of experiments stored in the GEO. Our goal is to generate a report, that will be used by curators to review and validate the GC of the experiments.
## Metodolgy
1. Files were
1. GEO files download
2. Obtaining SOFT files and its transformation to an XML format