Clustering of Multidimensional Data Sets with Applications to Spatial Distributions of Ribosomal Proteins
| dc.contributor.author | Mistry, Nil | |
| dc.contributor.author | Ramsey, Jordan | |
| dc.contributor.author | Wiley, Benjamin | |
| dc.contributor.author | Yanchuck, Jackie | |
| dc.contributor.author | Huang, Xuan | |
| dc.contributor.author | Raim, Andrew | |
| dc.contributor.author | Gobbert, Matthias K. | |
| dc.contributor.author | Neerchal, Nagaraj K. | |
| dc.contributor.author | Farabaugh, Philip J. | |
| dc.date.accessioned | 2018-10-01T13:52:51Z | |
| dc.date.available | 2018-10-01T13:52:51Z | |
| dc.date.issued | 2013 | |
| dc.description.abstract | Consider ribosomal proteins, each with a three-dimensional spatial location. Proteins related to the cofactor phenotype may be randomly or non-randomly distributed within the ribosome. To investigate this question, the Mahalanobis distance is computed between each pair of protein locations, and the optimal pairing is determined by minimizing the sum of the within-pair distances. Since no single code exists that allows for the computation of Mahalanobis distances, determining the optimal pairing, and determining whether the two groups are statistically different, we created a code that allows a user to do just this. The user can also compute an exact p-value for this distribution rather than rely on an approximation. | en_US |
| dc.description.sponsorship | These results were obtained as part of the REU Site: Interdisciplinary Program in High Performance Computing (www.umbc.edu/hpcreu) in the Department of Mathematics and Statistics at the University of Maryland, Baltimore County (UMBC) in Summer 2013. This program is funded jointly by the National Science Foundation and the National Security Agency (NSF grant no. DMS–1156976), with additional support from UMBC, the Department of Mathematics and Statistics, the Center for Interdisciplinary Research and Consulting (CIRC), and the UMBC High Performance Computing Facility (HPCF). HPCF (www.umbc.edu/hpcf) is supported by the National Science Foundation through the MRI program (grant nos. CNS–0821258 and CNS–1228778) and the SCREMS program (grant no. DMS–0821311), with additional substantial support from UMBC. Co-author Jordan Ramsey was supported, in part, by the UMBC National Security Agency (NSA) Scholars Program though a contract with the NSA. Graduate RAs Xuan Huang and Andrew Raim were supported by UMBC as HPCF RAs. | en_US |
| dc.description.uri | https://userpages.umbc.edu/~gobbert/papers/REU2013Team3Bio.pdf | en_US |
| dc.format.extent | 10 pages | en_US |
| dc.genre | techical report | en_US |
| dc.identifier | doi:10.13016/M23X83Q0K | |
| dc.identifier.uri | http://hdl.handle.net/11603/11410 | |
| dc.language.iso | en_US | en_US |
| dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
| dc.relation.ispartof | UMBC Mathematics Department Collection | |
| dc.relation.ispartof | UMBC Biological Sciences Department | |
| dc.relation.ispartof | UMBC Computer Science and Electrical Engineering Department | |
| dc.relation.ispartof | UMBC Faculty Collection | |
| dc.relation.ispartof | UMBC Student Collection | |
| dc.relation.ispartofseries | HPCF Technical Report;HPCF-2013-10 | |
| dc.rights | This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author. | |
| dc.subject | ribosomal proteins | en_US |
| dc.subject | Mahalanobis distance | en_US |
| dc.subject | UMBC High Performance Computing Facility (HPCF) | en_US |
| dc.subject | Proteins related to the cofactor phenotype | |
| dc.subject | computation of Mahalanobis distances | |
| dc.subject | determining the optimal pairing | |
| dc.title | Clustering of Multidimensional Data Sets with Applications to Spatial Distributions of Ribosomal Proteins | en_US |
| dc.type | Text | en_US |