Dharma, Arjun; Dedhia, Rahil; Waldschmidt, Thomas B.; Rose, Peter (2020). Protein Embedding Analysis. In Data Science & Engineering Master of Advanced Study (DSE MAS) Capstone Projects. UC San Diego Library Digital Collections. https://doi.org/10.6075/J0KS6Q2H

Using deep learning transformer model BERT to study protein sequences and prediction tasks such as sub-cellular location, fluorescence, and secondary structure

• 2020-01-01 to 2020-06-05

• 2020

• Dedhia, Rahil
• Dharma, Arjun
• Waldschmidt, Thomas B.

• Rose, Peter

Tasks Assessing Protein Embeddings (TAPE) use license @ https://github.com/songlab-cal/tape/blob/master/LICENSE

• DSE MAS - 2020 Cohort

• Bidirectional Encoder Representations from Transformers (BERT)
• Data Science & Engineering Master of Advanced Study (DSE MAS)
• Deep learning
• Graphics Processing Unit (GPU)
• Jupyter Notebooks
• Keras
• Language embedding
• Logistic regression
• Machine learning
• Natural Language Processing (NLP)
• Neural networks (Computer science)
• Protein analysis
• Protein embedding
• Pytorch
• SciKit Learn
• Support Vector Machine (SVM)
• Tensorflow
• Transformers
• XGBoost

• data
• software
• text

• English

Doi: https://doi.org/10.6075/J0KS6Q2H

Source data

• Tasks Assessing Protein Embeddings (TAPE): https://github.com/songlab-cal/tape

Reference

• Almagro Armenteros JJ, Sønderby CK, Sønderby SK, Nielsen H, Winther O. DeepLoc: prediction of protein subcellular localization using deep learning [published correction appears in Bioinformatics. 2017 Sep 19;:]. Bioinformatics. 2017;33(21):3387-3395. https://doi.org/10.1093/bioinformatics/btx431

Other resource

• Docker deployment for Flask app of songlab-cal TAPE repo for protein embedding analysis GitHub repository: https://github.com/rdedhia/docker-tape
• Tasks Assessing Protein Embeddings (TAPE) GitHub repository: https://github.com/rdedhia/tape

Creative Commons Attribution 4.0 International Public License

• Dharma, Arjun; Dedhia, Rahil; Waldschmidt, Thomas B.

Under copyright (US)

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2022-11-28