Jan T. Liphardt
PhD Research In Cambridge, he used stochastic context free grammars (SCFGs) to find patterns in genomes; the key computational problem is that some important regulatory patterns are palindromes, which are difficult (or even impossible) to detect with conventional machine learning or statistical tools. Palindromes are longer range, possibly knotted, correlations among elements within strings, genomes, or ledgers. The human brain can certainly pick out the palindrome in 1111234111114321111 (1234<->4321), but itís exceedingly difficult to do that on a conventional computer, especially with degenerate/noisy palindromes. Jan then used SCFGs to find signals in the yeast genome that may regulate translational recoding, a process in which one strand of RNA can encode two different proteins.
Postdoctoral Research After his PhD, he joined the labs of Carlos Bustamante and Nacho Tinoco, Jr. (in the UC Berkeley Physics and Chemistry Depts.). With Carlos and Nacho, he developed methods for using light to stretch single strands of RNA, and he then used these tools to study the dynamics of small, violently perturbed small systems. After 2 years as a postdoc, he became the divisional fellow of the Physical Biosciences Division at Lawrence Berkeley National Lab. He joined the Berkeley Physics faculty in 2004. Jan is now an associate professor of Bioengineering at Stanford University.
Jan is a Searle Scholar, a Sloan Research Fellow, a Hellman Fellow, and the recipient of the 2007 Mohr Davidow Ventures Innovatorís Award. Basic research in his lab is funded by federal agencies such as the NCI, NIGMS, NSF, and the DOE. Jan teaches the "Engineering Living Matter" (BioE80) course with Drew Endy and teaches the module on AI/Machine Learning in BioE301C. Jan's full publication list is at Google Scholar and his personal blog is here.
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