Regular biography
Nadav Brandes is an Assistant Professor in the Department of Biochemistry and Molecular Pharmacology at New York University. His research focuses on leveraging Artificial Intelligence to understand the human genome and address challenges in disease prediction and treatment. He has developed and applied Large Language Models to biological sequences, particularly proteins, to identify disease-causing mutations and optimize genomic sequences for therapeutic applications. His work integrates variant effect predictions into statistical genetics to advance understanding of rare variants and explore AI's potential in predicting genetic effects in non-coding regions.
Scholar-generated biography
Nadav Brandes is an Assistant Professor at New York University, specializing in computational biology and genomics. His research focuses on leveraging deep learning and natural language processing techniques to analyze protein sequences and functions, with applications in understanding genetic variation and its impact on disease. He develops models such as ProteinBERT and PWAS to predict the effects of genetic variants and link genes to phenotypes. His work also addresses challenges in data governance and batch effects in genomic studies, contributing to more accurate and reliable analyses in cancer and complex trait genetics.