Optimization based Long Short Term Memory Network for Protein Structure Prediction
One of the challenging tasks in computational biology is the anticipation of protein secondary structure (PSS) from amino acid sequences. Numerous computational and statistical methods are used for this purpose. With the growing attention of deep learning, models such as convolutional neural network...
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| Format: | Article |
| Language: | English |
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Universidade do Porto
2022-04-01
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| Series: | U.Porto Journal of Engineering |
| Subjects: | |
| Online Access: | https://journalengineering.fe.up.pt/index.php/upjeng/article/view/1105 |
| _version_ | 1817990113952530432 |
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| author | Pravinkumar Sonsare Gunavathi C. |
| author_facet | Pravinkumar Sonsare Gunavathi C. |
| author_sort | Pravinkumar Sonsare |
| collection | DOAJ |
| description | One of the challenging tasks in computational biology is the anticipation of protein secondary structure (PSS) from amino acid sequences. Numerous computational and statistical methods are used for this purpose. With the growing attention of deep learning, models such as convolutional neural network and recurrent neural network are also used for this prediction. But, these strategies require a lot of hyperparameters tuning to accomplish the best outcome. In this paper, we proposed a bidirectional embedded recurrent deep neural system using long short term memory (LSTM) cells with continuous coin betting optimizer (COCOB) to tune the hyperparameters for the prediction of PSS. We have performed this experiment on Nvidia DGX station. We assessed our model on a FASTA-formatted file which consists of Protein Data Bank (PDB) sequences and their relative secondary structure. We report better performance (Q3=79.01% and Q8=82.38%) than best in class (Q3=64.9% and Q8=68.2%) methods. |
| first_indexed | 2024-04-14T00:54:24Z |
| format | Article |
| id | doaj.art-4645ecd5624b43828533403788de7c7e |
| institution | Directory Open Access Journal |
| issn | 2183-6493 |
| language | English |
| last_indexed | 2024-04-14T00:54:24Z |
| publishDate | 2022-04-01 |
| publisher | Universidade do Porto |
| record_format | Article |
| series | U.Porto Journal of Engineering |
| spelling | doaj.art-4645ecd5624b43828533403788de7c7e2022-12-22T02:21:39ZengUniversidade do PortoU.Porto Journal of Engineering2183-64932022-04-018210812010.24840/2183-6493_008.002_00091276Optimization based Long Short Term Memory Network for Protein Structure PredictionPravinkumar Sonsare0https://orcid.org/0000-0002-8355-3334Gunavathi C.1https://orcid.org/0000-0002-4996-069XVellore Institute of Technology; Shri Ramdeobaba College of Engineering and Management, IndiaVellore Institute of Technology, IndiaOne of the challenging tasks in computational biology is the anticipation of protein secondary structure (PSS) from amino acid sequences. Numerous computational and statistical methods are used for this purpose. With the growing attention of deep learning, models such as convolutional neural network and recurrent neural network are also used for this prediction. But, these strategies require a lot of hyperparameters tuning to accomplish the best outcome. In this paper, we proposed a bidirectional embedded recurrent deep neural system using long short term memory (LSTM) cells with continuous coin betting optimizer (COCOB) to tune the hyperparameters for the prediction of PSS. We have performed this experiment on Nvidia DGX station. We assessed our model on a FASTA-formatted file which consists of Protein Data Bank (PDB) sequences and their relative secondary structure. We report better performance (Q3=79.01% and Q8=82.38%) than best in class (Q3=64.9% and Q8=68.2%) methods.https://journalengineering.fe.up.pt/index.php/upjeng/article/view/1105proteomicbioinformaticsdeep learningprotein secondary structurecocob |
| spellingShingle | Pravinkumar Sonsare Gunavathi C. Optimization based Long Short Term Memory Network for Protein Structure Prediction U.Porto Journal of Engineering proteomic bioinformatics deep learning protein secondary structure cocob |
| title | Optimization based Long Short Term Memory Network for Protein Structure Prediction |
| title_full | Optimization based Long Short Term Memory Network for Protein Structure Prediction |
| title_fullStr | Optimization based Long Short Term Memory Network for Protein Structure Prediction |
| title_full_unstemmed | Optimization based Long Short Term Memory Network for Protein Structure Prediction |
| title_short | Optimization based Long Short Term Memory Network for Protein Structure Prediction |
| title_sort | optimization based long short term memory network for protein structure prediction |
| topic | proteomic bioinformatics deep learning protein secondary structure cocob |
| url | https://journalengineering.fe.up.pt/index.php/upjeng/article/view/1105 |
| work_keys_str_mv | AT pravinkumarsonsare optimizationbasedlongshorttermmemorynetworkforproteinstructureprediction AT gunavathic optimizationbasedlongshorttermmemorynetworkforproteinstructureprediction |