Kevin Meza Landeros

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#Automatic Extraction of "Growth Conditions (GC)" from the "Gene Expression Omnibus (GEO)".
Proyecto para extraer de manera automática las condiciones de crecimiento de todas las enterobacterias de la GEO con ayuda de "Conditional Random Fields (CRFs)".
# "Automatic Extraction of Growth Conditions (GC) from the Gene Expression Omnibus (GEO)".
Project to extract in an automatic way, the growth conditions of all enterobacteria within the GEO using "Conditional Random Fields " (CRFs).
## Prerequisites
### Programming languages
- Python (version 2.7, version 3)
- Bash
## Folder content
**CRF**
- bin
1. label-split_training_test_v1.py
2. params.py
3. training_validation_v3.py
- check
1. sentences-405-order-rep.txt
- data-sets
1. test-data-set-30.txt
2. training-data-set-70.txt
- models
1. training-data-set-70.fStopWords_False.fSymbols_False.mod
- reports
1. report_training-data-set-70.fStopWords_False.fSymbols_False.txt
2. y_pred_training-data-set-70.fStopWords_False.fSymbols_False.txt
3. y_test_training-data-set-70.fStopWords_False.fSymbols_False.txt
**CoreNLP**
- bin
1. get-raw-sentences.sh
2. single_run.sh
- input
1. raw-metadata-senteneces.txt
- output
1. raw-metadata-senteneces.txt.conll
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