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MCWS-Transformers: Towards an Efficient Modeling of Protein Sequences via Multi Context-Window Based Scaled Self-Attention

  • Published:2023-03-01 Issue:2 Volume:20 Page:1188-1199
  • ISSN:1545-5963
  • Container-title:IEEE/ACM Transactions on Computational Biology and Bioinformatics
  • language:
  • Short-container-title:IEEE/ACM Trans. Comput. Biol. and Bioinf.

Author:

Ranjan Ashish1ORCID,Fahad Md Shah1,Fernández-Baca David2ORCID,Tripathi Sudhakar3ORCID,Deepak Akshay1ORCID

Affiliation:

1. Department of Computer Science and Engineering, National Institute of Technology Patna, Patna, India

2. Department of Computer Science, Iowa State University, Ames, IA, USA

3. Department of Information Technology, Rajkiya Engineering College, Ambedkar Nagar, India

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Genetics,Biotechnology

Reference37 articles.

1. Representation learning applications in biological sequence analysis

2. A literature survey on algorithms for multi-label learning;sorower;Oregon State Univ Corvallis,2010

3. Sequencing technologies — the next generation

4. UniProt: A hub for protein information;Nucleic Acids Res,2014

5. Framewise phoneme classification with bidirectional LSTM and other neural network architectures

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1. A CONSUMER SENTIMENT ANALYSIS METHOD BASED ON EEG SIGNALS AND A RESNEXT MODEL;Journal of Mechanics in Medicine and Biology;2024-03

2. MAC: EPILEPSY EEG SIGNAL RECOGNITION BASED ON THE MLP-SELF-ATTENTION MODEL AND COSINE DISTANCE;Journal of Mechanics in Medicine and Biology;2024-02-28

3. A novel hybrid CNN and BiGRU-Attention based deep learning model for protein function prediction;Statistical Applications in Genetics and Molecular Biology;2023-01-01
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