Jonathan arnold

Prof. Jonathan arnold

University of Georgia
orcid

Research Focus & Metrics

Academic Career Length

47Years (1980-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 April 2004 in Journal of Web Semantics
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Journal Article
Closed access
JCJorge Cardoso
Jorge Cardoso
ASAmit Sheth
Amit Sheth
JMJohn Miller
John Miller
Jonathan arnoldJonathan arnold
Jonathan arnold
KKKrys Kochut
Krys Kochut

1 June 1984 in Journal of Molecular Evolution
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Journal Article
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JAJohn C. Avise
John C. Avise
JNJoseph E. Neigel
Joseph E. Neigel
Jonathan arnoldJonathan arnold
Jonathan arnold

11 June 1991 in Nucleic Acids Research
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Journal Article
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HBHoward Brody
Howard Brody
JGJames Griffith
James Griffith
ACAnthony J. Cuticchia
Anthony J. Cuticchia
Jonathan arnoldJonathan arnold
Jonathan arnold
WTWilliam E. Timberlake
William E. Timberlake
Development of physical genomic maps is facilitated by identification of overlapping recombinant DNA clones containing long chromosomal DNA inserts. To simplify the analysis required to determine which clones in a genomic library overlap one another, we partitioned Aspergillus nidulans cosmid libraries into chromosome-specific subcollections. The eight A. nidulans chromosomes were resolved by pulsed field gel electrophoresis and hybridized to filter replicas of cosmid libraries. The subcollections obtained appeared to be representative of the chromosomes based on the correspondence between subcollection size and chromosome length. A sufficient number of clones was obtained in each chromosome-specific subcollection to predict the overlap and assembly of individual clones into a limited number of contiguous regions. This approach should be applicable to many organisms whose genomes can be resolved by pulsed field gel electrophoresis.

11 December 2002 in Proceedings of the National Academy of Sciences
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Journal Article
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DBD. Battogtokh
D. Battogtokh
DAD. K. Asch
D. K. Asch
MCM. E. Case
M. E. Case
Jonathan arnoldJonathan arnold
Jonathan arnold
HSH.-B. Schüttler
H.-B. Schüttler
A chemical reaction network for the regulation of the quinic acid ( qa ) gene cluster of Neurospora crassa is proposed. An efficient Monte Carlo method for walking through the parameter space of possible chemical reaction networks is developed to identify an ensemble of deterministic kinetics models with rate constants consistent with RNA and protein profiling data. This method was successful in identifying a model ensemble fitting available RNA profiling data on the qa gene cluster.

1 July 1988 in Molecular Biology and Evolution
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Journal Article
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JAJ C Avise
J C Avise
RBR M Ball
R M Ball
Jonathan arnoldJonathan arnold
Jonathan arnold
Using inbreeding theory as applied to neutral alleles inherited maternally, we generate expected probability distributions of times to identity by descent for random pairs of mitochondrial genotypes within a population or within an entire species characterized by high gene flow. For comparisons with these expectations, empirical distributions of times to most recent common ancestry were calculated (by conventional mtDNA clock calibrations) from mtDNA haplotype distances observed within each of three vertebrate species--American eels, hardhead catfish, and redwinged blackbirds. These species were chosen for analysis because census population size in each is currently large and because both genetic and life-history data are consistent with the postulate that historical gene flow within these species has been high. The observed molecular distances among mtDNA lineages were two to three orders of magnitude lower than predicted from census sizes of breeding females, suggesting that rate of mtDNA evolution is decelerated in these species and/or that long-term effective population size is vastly smaller than present-day population size. Several considerations point to the latter possibility as most likely. The genetic structure of any species is greatly influenced by historical demography; even for species that are currently abundant, mtDNA gene lineages appear to have been channeled through fairly small numbers of ancestors.

29 August 2008 in PLOS ONE
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Journal Article
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WDWubei Dong
Wubei Dong
XTXiaojia Tang
Xiaojia Tang
YYYihai Yu
Yihai Yu
RNRoger Nilsen
Roger Nilsen
RKRosemary Kim
Rosemary Kim
HSH.-Bernd Schüttler
H.-Bernd Schüttler
A model-driven discovery process, Computing Life, is used to identify an ensemble of genetic networks that describe the biological clock. A clock mechanism involving the genes white-collar-1 and white-collar-2 (wc-1 and wc-2) that encode a transcriptional activator (as well as a blue-light receptor) and an oscillator frequency (frq) that encodes a cyclin that deactivates the activator is used to guide this discovery process through three cycles of microarray experiments. Central to this discovery process is a new methodology for the rational design of a Maximally Informative Next Experiment (MINE), based on the genetic network ensemble. In each experimentation cycle, the MINE approach is used to select the most informative new experiment in order to mine for clock-controlled genes, the outputs of the clock. As much as 25% of the N. crassa transcriptome appears to be under clock-control. Clock outputs include genes with products in DNA metabolism, ribosome biogenesis in RNA metabolism, cell cycle, protein metabolism, transport, carbon metabolism, isoprenoid (including carotenoid) biosynthesis, development, and varied signaling processes. Genes under the transcription factor complex WCC ( = WC-1/WC-2) control were resolved into four classes, circadian only (612 genes), light-responsive only (396), both circadian and light-responsive (328), and neither circadian nor light-responsive (987). In each of three cycles of microarray experiments data support that wc-1 and wc-2 are auto-regulated by WCC. Among 11,000 N. crassa genes a total of 295 genes, including a large fraction of phosphatases/kinases, appear to be under the immediate control of the FRQ oscillator as validated by 4 independent microarray experiments. Ribosomal RNA processing and assembly rather than its transcription appears to be under clock control, suggesting a new mechanism for the post-transcriptional control of clock-controlled genes.