Biological Sequence

Biological sequence analysis focuses on understanding the information encoded within DNA, RNA, and protein sequences to decipher biological processes and design new molecules. Current research heavily utilizes deep learning models, including transformers (like DNABERT and Nucleotide Transformer), recurrent neural networks (RNNs), and generative adversarial networks (GANs), often coupled with techniques like dimensionality reduction (t-SNE, PCA) and novel masking strategies to improve efficiency and accuracy. These advancements are significantly impacting various fields, enabling improved sequence classification for pathogen identification, drug discovery, and biodiversity analysis, as well as facilitating the design of novel biological sequences with desired properties.