"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