This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Constructing time decompositions of time stamped documents is an important first step in extracting temporal information from a document set. Efficient algorithms are described for computing optimal lossy decompositions for a given document set, where the loss of information is constrained to be within a specified bound. A novel and efficient algorithm is proposed for computing information loss values required to construct optimal lossy decompositions. Experimental results are reported comparing optimal lossy decompositions and equal length decompositions in terms of a number of parameters such as information loss. In particular, our results show that optimal lossy decompositions outperform equal length decompositions by preserving more of the information content of the underlying document set. The results also demonstrate that permitting even small amounts of variability in the length of the subintervals of a decomposition results in capturing more of the temporal information content of a document set when compared to equal length decompositions.

Agency
National Institute of Health (NIH)
Institute
National Center for Research Resources (NCRR)
Type
Exploratory Grants (P20)
Project #
5P20RR016469-06
Application #
7381526
Study Section
Special Emphasis Panel (ZRR1-RI-7 (01))
Project Start
2006-05-01
Project End
2007-04-30
Budget Start
2006-05-01
Budget End
2007-04-30
Support Year
6
Fiscal Year
2006
Total Cost
$46,513
Indirect Cost
Name
University of Nebraska Medical Center
Department
Genetics
Type
Schools of Medicine
DUNS #
168559177
City
Omaha
State
NE
Country
United States
Zip Code
68198
Barta, Cody L; Liu, Huizhan; Chen, Lei et al. (2018) RNA-seq transcriptomic analysis of adult zebrafish inner ear hair cells. Sci Data 5:180005
Liu, Huizhan; Chen, Lei; Giffen, Kimberlee P et al. (2018) Cell-Specific Transcriptome Analysis Shows That Adult Pillar and Deiters' Cells Express Genes Encoding Machinery for Specializations of Cochlear Hair Cells. Front Mol Neurosci 11:356
Wehrkamp, Cody J; Natarajan, Sathish Kumar; Mohr, Ashley M et al. (2018) miR-106b-responsive gene landscape identifies regulation of Kruppel-like factor family. RNA Biol 15:391-403
Lopez, Wilfredo; Page, Alexis M; Carlson, Darby J et al. (2018) Analysis of immune-related genes during Nora virus infection of Drosophila melanogaster using next generation sequencing. AIMS Microbiol 4:123-139
Azadmanesh, Jahaun; Trickel, Scott R; Borgstahl, Gloria E O (2017) Substrate-analog binding and electrostatic surfaces of human manganese superoxide dismutase. J Struct Biol 199:68-75
Bonham-Carter, Oliver; Thapa, Ishwor; From, Steven et al. (2017) A study of bias and increasing organismal complexity from their post-translational modifications and reaction site interplays. Brief Bioinform 18:69-84
Donze-Reiner, Teresa; Palmer, Nathan A; Scully, Erin D et al. (2017) Transcriptional analysis of defense mechanisms in upland tetraploid switchgrass to greenbugs. BMC Plant Biol 17:46
Quispe, Cristian F; Esmael, Ahmed; Sonderman, Olivia et al. (2017) Characterization of a new chlorovirus type with permissive and non-permissive features on phylogenetically related algal strains. Virology 500:103-113
Gerald, Gary W; Thompson, Moriah M; Levine, Todd D et al. (2017) Interactive effects of leg autotomy and incline on locomotor performance and kinematics of the cellar spider, Pholcus manueli. Ecol Evol 7:6729-6735
Gong, Qiang; Wang, Chao; Zhang, Weiwei et al. (2017) Assessment of T-cell receptor repertoire and clonal expansion in peripheral T-cell lymphoma using RNA-seq data. Sci Rep 7:11301

Showing the most recent 10 out of 322 publications