Foundation models in bioinformatics

With the adoption of foundation models (FMs), artificial intelligence (AI) has become increasingly significant in bioinformatics and has successfully addressed many historical challenges, such as pre-training frameworks, model evaluation and interpretability. FMs demonstrate notable proficiency in managing large-scale, unlabeled datasets, because experimental procedures are costly and labor intensive. In various downstream tasks, FMs have consistently achieved noteworthy results, demonstrating high levels of accuracy in representing biological entities. A new era in computational biology has been ushered in by the application of FMs, focusing on both general and specific biological issues. In this review, we…

• NN
  National Natural Science Foundation of China

  Awards: 62350004, 62322215, 62332020
• CS
  Central South University
• IA
  Innovation and Technology Commission

  Award: ITCPD/17-9
• HK
  Hong Kong University of Science and Technology

  Award: Z0428
• NK
  National Key Research and Development Program of China

  Award: 2021YFF1201200