Protein solubility prediction based on the raw amino acid sequence using three machine/deep learning techniques: RF, CNN, and a hybrid CNN-biLSTM model. Assessment of the performance difference between the models with evaluation metrics and statistical significance tests.
Anotace v angličtině
Protein solubility prediction based on the raw amino acid sequence using three machine/deep learning techniques: RF, CNN, and a hybrid CNN-biLSTM model. Assessment of the performance difference between the models with evaluation metrics and statistical significance tests.
Klíčová slova
protein solubility, machine learning, deep learning, CNN, LSTM
Klíčová slova v angličtině
protein solubility, machine learning, deep learning, CNN, LSTM
Rozsah průvodní práce
77 p.
Jazyk
AN
Anotace
Protein solubility prediction based on the raw amino acid sequence using three machine/deep learning techniques: RF, CNN, and a hybrid CNN-biLSTM model. Assessment of the performance difference between the models with evaluation metrics and statistical significance tests.
Anotace v angličtině
Protein solubility prediction based on the raw amino acid sequence using three machine/deep learning techniques: RF, CNN, and a hybrid CNN-biLSTM model. Assessment of the performance difference between the models with evaluation metrics and statistical significance tests.
Klíčová slova
protein solubility, machine learning, deep learning, CNN, LSTM
Klíčová slova v angličtině
protein solubility, machine learning, deep learning, CNN, LSTM
Zásady pro vypracování
-
Zásady pro vypracování
-
Seznam doporučené literatury
-
Seznam doporučené literatury
-
Přílohy volně vložené
-
Přílohy vázané v práci
grafy, schémata, tabulky
Převzato z knihovny
Ne
Plný text práce
Přílohy
Posudek(y) oponenta
Hodnocení vedoucího
Záznam průběhu obhajoby
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The appearance was solid, the student was convinced about her work done and understood the topic well.
The student addressed questions raised in the reviews of supervisor and opponent.
Used 25 iterations were already very computation power extensive.