Samuel Sylvester Anim-Yeboah

This research focuses on advancing our understanding of complex biological systems through interdisciplinary approaches that integrate traditional biological methodologies with cutting-edge computational techniques. By combining deep learning models, sequence analysis, and machine learning algorithms, the researcher explores how these tools can uncover hidden patterns and relationships in biological data, particularly in areas such as transcriptional regulation, protein function, gene regulatory networks, neurodegenerative diseases, epigenetic regulation, multi-scale modeling for metabolic phenotypes, and molecular mechanics.