Sean Eddy

Sean Eddy is a Lecturer in the Department of Molecular & Cellular Biology at Harvard University. His research focuses on the development of computational methods for RNA, protein, and genome sequence analysis. He uses probabilistic modeling approaches to build statistical models of biological features and applies these models for Bayesian or likelihood-based statistical inference in large-scale genome analysis and annotation. His work includes RNA structure and function, RNA homology detection, RNA structure prediction, and remote protein homology detection, with a focus on improving methods implemented in the HMMER software package.

Sean R. Eddy is a computational biologist whose research focuses on computational genomics and RNA biology. His work includes the development of tools for genomic sequence analysis, such as tRNAscan-SE and HMMER, which are widely used for identifying RNA genes and performing sequence similarity searches. Eddy's research also involves the annotation of non-coding RNA genes and the creation of databases like Pfam, which provides protein families and clans for comparative analysis. His contributions span both theoretical and applied aspects of bioinformatics, with a strong emphasis on probabilistic models and hidden Markov models for biological sequence analysis.