Exploring Potential Transcription Factors and Their Regulatory Relationships Based on Asymmetric Covariance Natural Vector Encoding Method and Machine Learning Algorithms

Explore advanced computational methods for identifying transcription factors and understanding their regulatory networks through this 52-minute conference talk from ICBS2025 presented by BIMSA. Learn how asymmetric covariance natural vector encoding methods can be combined with machine learning algorithms to analyze gene regulation mechanisms. Discover innovative approaches to decoding the complex relationships between transcription factors and their target genes, gaining insights into cutting-edge bioinformatics techniques used in molecular biology research. Understand how these computational tools can advance our knowledge of gene expression control and regulatory pathway analysis in biological systems.