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Found 4 papers, 1 papers with code
T Cell Receptor Protein Sequences and Sparse Coding: A Novel Approach to Cancer Classification
Sparse coding is a popular technique in machine learning that enables the representation of data with a set of informative features and can capture complex relationships between amino acids and identify subtle patterns in the sequence that might be missed by low-dimensional methods.
PCD2Vec: A Poisson Correction Distance-Based Approach for Viral Host Classification
Therefore, the usage of only the spike protein, instead of the full genome, provides most of the essential information for performing analyses such as host classification.
Exploring The Potential Of GANs In Biological Sequence Analysis
New tools for biological sequence analysis are provided by machine learning (ML) technologies to effectively analyze the functions and structures of the sequences.
Efficient Classification of SARS-CoV-2 Spike Sequences Using Federated Learning
This paper presents a federated learning (FL) approach to train an AI model for SARS-Cov-2 variant classification.
