Biological sequence analysis: Advances, medical applications, and challenges
Year: 2024
Type: article
Abstract: With continuous developments in biotechnology and information technology, we are entering the era of biological sequence big data. Extracting valuable insights from large-scale data to decipher life activities presents a major challenge. Artificial intelligence, particularly big data analysis and natural language processing technologies, has emerged as a crucial tool in biological sequence analysis. These technologies facilitate pattern detection, offering new perspectives on complex biological processes. Notably, AlphaFold and ESM models have achieved significant strides in protein structure prediction and functional annotation. These breakthroughs not only accelerate fundamental biological research but also provide innovative tools and strategies for disease diagnosis and drug discovery. In this perspective, we discuss the advancements in biological sequence analysis and focus on their extensive medical applications. Additionally, we highlight relevant challenges and propose further directions, emphasizing the need for ongoing innovation in sequence analysis to fully realize its potential in biomedical research.
Source: Fundamental Research
Authors: Hang Wei, Jiangyi Shao, Bin Liu
Institutions: Xidian University, Beijing Institute of Technology
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: diamond
Awards: G1983235853, G5263694324, G7894669521
OpenAlex ID: W4405826966