William Stafford Noble

William Stafford Noble
William Stafford Noble
Nationality	American
Alma mater	Stanford University (B.S.); University of California, San Diego (Ph.D. 1998); University of California, Santa Cruz (Postdoc)
Known for	Applying machine learning to biological data analysis; Analysis of proteomics data (Percolator); Sequence analysis (MEME suite); Kernel methods in biology
Awards	NSF CAREER Award; Sloan Research Fellowship; ISCB Innovator Award (2019) ; ISCB Fellow; Highly Cited Researcher (Clarivate Analytics) ;
	Scientific career
Fields	Bioinformatics, Computational biology, Machine learning, Genomics, Proteomics
Institutions	University of Washington; Columbia University
Website	noble.gs.washington.edu/~wnoble/

William Stafford Noble (formerly William Noble Grundy) is an American computational biologist. He is a professor in the Department of Genome Sciences and the Paul G. Allen School of Computer Science & Engineering at the University of Washington. Noble is known for developing machine learning and statistical methods for analyzing biological data, particularly in genomics and proteomics. His research includes work on sequence analysis, kernel methods, genome annotation, the 3D structure of the genome, and the analysis of shotgun proteomics data. He is a recipient of the ISCB Innovator Award and is an ISCB Fellow.