Eric David Scheeff
Affiliations: | 2003 | University of California, San Diego, La Jolla, CA |
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"Eric Scheeff"Mean distance: 8.4 | S | N | B | C | P |
Parents
Sign in to add mentor| J. Andrew McCammon | grad student | 2003 | UCSD | |
| (Multiple alignments of protein structures and their application to sequence annotation with hidden Markov models.) | ||||
| Philip E. Bourne | post-doc | 2003-2006 | UCSD (Computational Biology Tree) | |
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Publications
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| Manning G, Scheeff E. (2010) How the vertebrates were made: selective pruning of a double-duplicated genome. Bmc Biology. 8: 144 |
| Scheeff ED, Axelrod HL, Miller MD, et al. (2010) Genomics, evolution, and crystal structure of a new family of bacterial spore kinases. Proteins. 78: 1470-82 |
| Nathanson JL, Jappelli R, Scheeff ED, et al. (2009) Short Promoters in Viral Vectors Drive Selective Expression in Mammalian Inhibitory Neurons, but do not Restrict Activity to Specific Inhibitory Cell-Types. Frontiers in Neural Circuits. 3: 19 |
| Scheeff ED, Eswaran J, Bunkoczi G, et al. (2009) Structure of the pseudokinase VRK3 reveals a degraded catalytic site, a highly conserved kinase fold, and a putative regulatory binding site. Structure (London, England : 1993). 17: 128-38 |
| Chung JL, Beaver JE, Scheeff ED, et al. (2007) Con-Struct Map: a comparative contact map analysis tool. Bioinformatics (Oxford, England). 23: 2491-2 |
| Scheeff ED, Bourne PE. (2006) Application of protein structure alignments to iterated hidden Markov model protocols for structure prediction. Bmc Bioinformatics. 7: 410 |
| Scheeff ED, Bourne PE. (2005) Structural evolution of the protein kinase-like superfamily. Plos Computational Biology. 1: e49 |
| Guda C, Lu S, Scheeff ED, et al. (2004) CE-MC: a multiple protein structure alignment server. Nucleic Acids Research. 32: W100-3 |
| Scheeff ED, Fink JL. (2003) Fundamentals of protein structure. Methods of Biochemical Analysis. 44: 15-39 |
| Guda C, Scheeff ED, Bourne PE, et al. (2001) A new algorithm for the alignment of multiple protein structures using Monte Carlo optimization. Pacific Symposium On Biocomputing. Pacific Symposium On Biocomputing. 275-86 |