DeepAnnotator: Deep Learning Methods for Genome Annotation

python general_lstm_gene_prediction.py start/stop codon

--> time python general_lstm_start_classification.py start > train_start_codon.txt &

python evaluate_codon_classification_network.py model_name 0.50 python create_training_plot.py output_training_evaluation_testing_prediction.txt python evaluate_codon_classification_network.py start general_lstm_model_start 0.50 python create_whole_genome_prediction.py gene_prediction_lstm_model 0.50 genome

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python create_whole_genome_prediction.py gene_prediction_lstm_model 0.50 genome python create_whole_genome_prediction.py general_lstm_model_start 0.50 start python create_whole_genome_prediction.py general_lstm_model_stop 0.50 stop

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python improved_whole_genome_prediction.py gzip_file_name python intrag_coding_prediction_score.py gzip_file_name python trying_nodp_solve_gene_boundary.py gzip_file_name

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python floatpt_whole_genome_prediction.py python trying_dynp_solve_gene_boundary.py floatpt_file_name

python trying_dynp_solve_gene_boundary.py floatpt_whole_sequences_batch_4_3.gz > debug_dynp.txt