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Jonathan Arnold

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Professor
Ph.D. (1982) Yale University
  • Member, NIH study section (Genetic Variation and Evolution), 2005-2008
  • Fellow, American Association for the Advancement of Science
  • Grant Support -
    • "Collective Behavior of Cellular Oscillators", NSF
    • "Measuring and Modeling how Clocks in Single Cells Communicate: an Interdisciplinary Approach," NSF
    • "Systems Analysis of the Beneficial Associations of Sorghum with Arbuscular Mycorrhizal Fungi...," DOE
    • “Genomics and Computational Biology: an REU Site,” NSF
    • "Finding virulence genes as therapeutic targets in Covid-19", NSF
    • “ALICE, Adaptive Learning for Interdisciplinary Collaborative Environments," NSF
    • “Population-based Multidisciplinary Study of Centenarians,” NIH
  • Research Interests -
    • My research involves work on identifying gene regulatory and biochemical networks for fundamental biological processes in fungal systems and validating these biological circuits by fitting them to genomics data in single cells. Since the discovery of the structure of DNA, biologists have been taking apart living systems on a finer and finer scale until we have been able to determine the complete genetic blueprint of many organisms. The challenge of the new millennium is "reassembling the pieces", i.e., moving from genomes to life. One approach to reassembling the pieces is to borrow a metaphor from computer science: the entire chemical reaction network describing what a cell does is a biological circuit. The theme for the genomics and computational biology part of my research is “computing life”, i.e., identifying biological circuits for fundamental processes like fungal/plant symbioses and the biological clock and validating these biological circuits by fitting them to genomics data describing what the cell is doing (i.e., RNA and protein profiling data).
Research Areas:
Research Interests:

Evolutionary genomics and systems biology: identifying gene regulatory and biochemical networks for biological processes

Selected Publications:
  • Montenegro, T. D. P., S. Kleindienst, A. E. Allen, A. M. Eren, J. McCrow, J. D. S. Calderon, J. Arnold, & S. B. Joye 2023. Species-specific responses of marine bacteria to environmental perturbation.  ISME Communications 3, 99, https://doi.org/10.1038/s43705-023-00310-z
  • Liu, Liang, Lili Yu, Shaoyuan Wu, Jonathan Arnold, Christopher Whalen, Charles Davis, & Scott V. Edwards (2023).  Short branch attraction in phylogenomic inference under the multispecies coalescent.  Frontiers Ecology and Evolution 11, doi:10.3389/fevo.2023.1134764  https://www.frontiersin.org/articles/10.3389/fevo.2023.1134764/full
  • Jialin Yang, J., Michael Skaro, M.,  Jiani Chen, J., Duna Zhan, D., Lyu, L., Gay, S., Ahmed Kandeil, A.,  Ali, M. A., Kayali, G., Stoianova, K., Ji, P., Alabady, M., Bahl, J., Liu, L.,  & J. Arnold (2023). The species coalescent indicates possible bat and pangolin origins of the COVID-19 pandemic.  Scientific Reports 13: 5571 https://rdcu.be/c9dtc
  • Al-Omari, A. M., Tawalbeh, S. M.,  Akkam, Y. H., Al-Tawalbeh, M.  Younis, S. Abdullah A. Mustafa, A. A. & J. Arnold (2023).  Big Data Bot with a Special Reference to Bioinformatics. Computers, Materials & Continua 202375(2), 4155-4173. https://doi.org/10.32604/cmc.2023.036956 
  • Wu, Y., M. T. Judge, A. S. Edison, & J. Arnold (2022).  Uncovering in vivo biochemical patterns from time-series metabolic dynamics.  PLoS ONE 17(5): e0268394. https://doi.org/10.1371/journal.pone.0268394.
  • Al-Omari, A. M., J. Griffith, A. Scruse, R. W. Robinson, H.-B. Schuttler, & J Arnold (2022). Ensemble methods for identifying RNA operons and Regulons in the Clock Network of Neurospora crassaIEEE Access 10: 32510-32524 , doi:10.1109/ACCESS.2022.3160481. https://ieeexplore.ieee.org/document/9737535
  • Cheong, J. W., X. Qiu, Y. Liu, A. Al-Omari, J. Griffith, H.-B. Schuttler, L. Mao, & J. Arnold (2022). The macroscopic limit to synchronization of cellular clocks in single cells of Neurospora crassa. Nature Scientific Reports 12, 6750, https://doi.org/10.1038/s41598-022-10612-2
  • Krach, E., M. Skaro, Y. Wu, & J. Arnold (2022).  Characterizing the gene-environment interaction underlying natural morphological variation in Neurospora crassa conidiophores using high-throughput phenomics and transcriptomics.  G3, https://doi.org/10.1093/g3journal/jkac050
  • Skaro, M.S., M. Hill, Y. Zhou, S. Quinn, M. Davis, L. Cai, A. Sboner, M. Murph, and J. Arnold (2021). Are we there yet? A machine learning architecture to predict organotropic metastases.  BMC Medical Genomics 14, 281, https://doi.org/10.1186/s12920-021-01122-7
  • Krach, E., Y. Wu, M. Skaro, L. Mao, & J. Arnold 2020. Wild isolates of Neurospora crassa reveal three conidiophore architectural phenotypes. Microorganisms 8: 1760 https://www.mdpi.com/2076-2607/8/11/1760
  • Caranica, C., A. Al-Omari, H.-B. Schuttler, & J. Arnold 2020.  A clock stochastic network with light entrainment is identified for single cells of Neurospora crassa by ensemble methods.  Nature Scientific Reports 10, 15168,  https://doi.org/10.1038/s41598-020-72213-1
  • Wu, Y., M. T. Judge, J. Arnold, S. M. Bhandarkar, & A. S. Edison 2020. RTextract: Time-series NMR spectra quantification based on 3D surface ridge tracking, Bioinformatics, https://doi.org/10.1093/bioinformatics/btaa631
  • Deng, Z., J. H. Cheong, C. Caranica, L. Wu, X. Qiu, M. Judge, B. Hull, C. Rodriguez, J. Griffith, A. Al-Omari, S. Arsenault, H.-B. Schuttler, L. Mao, & J. Arnold 2019.  Single cells of Neurospora crassa show circadian oscillations, light entrainment, temperature compensation, and phase synchronization.  IEEE Access 7, 49403-49417, DOI (identifier) 10.1109/ACCESS.2019.2910731
  • Judge, M. T., Y. Wu, F. Tayyari, J. Glushka, T. Ito, J. Arnold, & A. Edison 2019.  Untargeted, real-time metabolomics of single and multicellular organisms.  Frontiers Molecular Biosciences|Metabolomics 6, doi: 10.3389/fmolb.2019.00026
  • Al-Omari, A. D., J. Griffith, C. Caranica, T. Taha, H.-B. Schuttler & J. Arnold 2018.  Discovering regulators in post transcriptional control of the biological clock of Neurospora crassa using Variable Topology Ensemble Methods on GPUs.  IEEE Access 6, doi:10.1109/ACCESS.2018.2871876
  • Caranica, C, A D Al-Omari, Z Deng, J Griffith, R Nilsen, L Mao, J Arnold, and H-B Schuttler 2018.  Ensemble methods for stochastic networks with special reference to the biological clock of Neurospora crassa, PLoS ONE 13(5):e0196435
  • Deng, Z, S Arsenault, C Caranica, J Griffith, T Zhu, A Al-Omari, H-B Schuttler, J Arnold, & L Mao 2016. Synchronizing stochastic circadian oscillators in single cells of Neurospora crassa, Scientific Reports 6, 35828, DOI: 10.1038/srep35828, www.nature.com/articles/srep35828
  • Al-Omari, A, J Griffith, M Judge, T Taha, J Arnold, & H-B Schuttler 2015. Discovering regulatory network topologies using ensemble methods on GPGPUs with special reference to the biological clock of Neurospora crassa, IEEE Access 3, 27-42, DOI 10.1109/ACCESS.2015.2399854, http://ieeexplore.ieee.org/xpl/articleDetails.jsp?tp=&arnumber=7029612&queryText%3Ddiscovering+regulatory+network+topologies+with+ensemble+methods
  • Bouffier, A. M., J. Arnold, & H-Bernd Schuttler 2014. A MINE alternative to D-optimal designs for the linear model. PLoS ONE 9(10): e110234 http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0110234
  • Case, ME, J Griffith, W Dong, I Tigner, K Gaines, JC Jiang, SM Jazwinski & J Arnold for the Georgia Centenarian Study 2014. The aging biological clock in Neurospora crassa, Ecology & Evolution 4, 3494-3507, http://onlinelibrary.wiley.com/doi/10.1002/ece3.1202/full
  • Al-Omari, A., H.-B. Schuttler, J. Arnold and T. Taha. 2013. Solving nonlinear systems of first order differential equations using a Galerkin finite element method. IEEE Access 1(1): 408-417. DOI 10.1109/ACCESS.2013.2269192
  • Tang, X., W. Dong, J. Griffith, R. Nilsen, A. Mathes, K.B. Cheng, J. Reeves, H.-B. Schuttler, M.E. Case, J. Arnold and D.A. Logan 2011. Systems biology of the qa gene cluster of Neurospora crassa. PLoS ONE 6: e20671.
  • Aleman-Meza, B., Y. Yu, H.-B. Schuttler, J. Arnold and T.R. Taha. 2009. KINSOLVER: a simulator for computing large ensembles of biochemical and gene regulatory networks.  Computers and Mathematics with Applications, doi:10.1016/j.camwa.2008.10.086.
  • Tewari, S., J. Arnold and S.M. Bhandarkar. 2008.  Likelihood of a particular order of genetic markers and the construction of genetic maps. Journal of Bioinformatics and Computational Biology 6: 125-162.
  • Dong, W., X. Tang, Y. Yu, R. Nilsen, J. Griffith, R. Kim, J. Arnold, and H.-B. Schuttler. 2008. Systems biology of the clock in Neurospora crassa. PLoS ONE 3: e3105.
  • Dai, J., L. Li, S. Kim, B. Kimball, M. Jazwinski, and J. Arnold. 2007. Exact sample size needed to detect dependence in 2 x 2 x 2 tables. Biometrics 63: 1245-1253.
  • Tewari, S., S.M. Bhandarkar and J. Arnold. 2007. Design and analysis of an efficient recursive linking algorithm for constructing likelihood based genetic maps for a large number of markers. Journal of Bioinfomatics and Computational Biology 5: 201-250.
  • Yu, Y., W. Dong, C. Altimus, X. Tang, J. Griffith, M. Morello, L. Dudek, J. Arnold, and H.-B. Schuttler. 2007. A genetic network for the clock of Neurospora crassa. PNAS USA 104: 2809-2814.
  • Cushion, M.T., A.G. Smulian, B.E. Slaven, T. Sesterhenn, J. Arnold, C. Staben, A. Porollo, R. Adamczyk and J. Meller. 2007. Transcriptome of Pneumosystis carinii during fulminate infection: carbohydrate metabolism and the concept of a compatible parasite. PloS ONE 2: e423.
  • Tewari, S., J. Arnold and S.M. Bhandarkar. 2006. "Efficient Recursive Linking Algorithm for Computing the Likelihood of an Order of a Large Number of Genetic Markers" Proc. of the IEEE LSS Computational Systems Bioinformatics Conference (CSB 2006), Aug. 14-18, 2006, Stanford University, Palo Alto, CA., P. Markstein and Y. Xu (eds), Imperial College Press, London, pp. 191-198.
  • Sanchez, M.S., C.J. Basten, A.M. Ferrenberg, M.A. Asmussen, and J. Arnold. 2006. Exact sample sizes needed to detect dependence in 2 x 3 tables. Theoretical Population Biology 69: 111-120.
  • Icenhour, C.R., J. Arnold, M. Medvedovic, and M.T. Cushion. 2006. Competitive coexistence of two Pneumocystis species. Infection, Genetics, and Evolution 6: 177-186.
  • Dai, J., A. Davey, I.C. Siegler, J. Arnold, and L.W. Poon. 2006. GCSDB: an integrated database system for the Georgia Centenarian Study. Bioinformation 1: 214-219.
  • Bhandarkar, S.M., J. Huang, and J. Arnold. 2006. An Information theoretic approach to genome reconstruction. Chapter 11 in Handbook of Computational Molecular Biology. 11-1-11-26 CRC Press, Boca Raton, FL.
  • Arnold, J., W. Dong, J. Griffith, D. Choi, J. Baldwin, L. Hilton, K. Kelps, J. McGuire, R. Morgan, M. Smith, Q. Wang, J. Liu, J. Reeves, D.A. Logan, M.E. Case, and H.-B. Schuttler. 2006. Systems Biology of the Biological Clock. IEEE Proceedings of the First International Conference on Computational Systems Biology (ICCSB-2006), pp. 119-125.
  • Xiong, M. and J. Arnold. 2006. Do genetic networks obey Kirchhoff’s and Ohm’s Laws? Proc. IASTED International Conf. on Comp. & Systems Biology, Dallas, TX, November 13-14, 2006, pp. 13-19.
  • Lott, T.J., R.E. Fundyga, R.J. Kuykendal, and J. Arnold. 2005. The human commensal yeast, Candida albicans, has an ancient origin. Fungal Genetics and Biology 42: 444-451.
  • Strobel, G.L. and J. Arnold. 2004. Essential eukaryotic core. Evolution 58: 441-446.
  • Arnold, J. H.-B. Schuttler, D. Logan, D. Battogtokh, J. Griffith, B. Arpinar, S. Bhandarkar, S. Datta, K.J. Kochut, E. Kraemer, J.A. Miller, A. Sheth, G. Strobel, T. Taha, B. Aleman-Meza, J. Doss, L. Harris and A. Nyong. 2004. Metabolomics. In: Handbook of Industrial Mycology. Marcel Dekker, NY, NY.
  • Xu Z., B. Lance, C. Vargas, B. Arpinar, S. Bhandarkar, E. Kraemer, K.J. Kochut, J.A. Miller, J.R. Wagner, M.J. Weise, J.K. Wunderlich, J. Stringer, G. Smulian, M.T. Cushion and J. Arnold. 2003. Mapping by sequencing the pneumocystis genome using the ordering DNA sequences V3 tool. Genetics 163: 1299-1313.
  • Battogtokh D., D.K. Asch, M.E. Case, J. Arnold and H.-B. Schuttler. 2002. An ensemble method for identifying regulatory circuits with special reference to the qa gene cluster of Neurospora crassa. Proc. Natl. Acad. Sci. USA 99: 16904-16909.
  • Hall, R. D., J. Miller, J. Arnold, K. Kochut, A. Sheth and M.J. Weise. 2002. Using workflow to build an information management system for a geographically distributed genome sequencing initiative. In: Genomics of Plants and Fungi. R.A. Prade and H.J. Bohnert (eds). Marcel Dekker, NY.
  • Fang, X., J.A. Miller and J. Arnold. 2002. J3DV: a Java-based 3D database visualization tool. Software – Practice and Experience 32: 443-463.
  • Kochut, K.J., J. Arnold, A. Sheth, J. Miller, E. Kraemer, B. Arpinar and J. Cordoso. 2002. INTELLIGEN: a distributed workflow system for discovering protein-protein interactions. Parallel and Distributed Databases 13: 43-72.
  • Fundyga, R., T.J. Lott and J. Arnold. 2002. Population structure of Candida albicans, a member of the human flora, as determined by microsatellite loci. Infection, Genetics, and Evolution 2: 57-68.
  • Kelkar, H.S., J. Griffith, M.E. Case, S. Covert, R.D. Hall, C. Keith, J.S. Oliver, M.J. Orbach, M.S. Sachs, J. Wagner, M.J. Weise, J. Wunderlich and J. Arnold. 2001. The Neurospora crassa genome: cosmid libraries sorted by chromosome. Genetics 157: 979-990.
  • Hoyer, L.L., R. Fundyga, J.E. Hecht, J.C. Kapetyn, F.M. Klis and J. Arnold. 2001. Characterization of ALS genes from non-albicans Candida and phylogenetic analysis of the ALS family. Genetics 157: 1555-1567.
  • Hall, R.D., S.M. Bhandarkar, J. Arnold and T. Jiang. 2001. Physical mapping with automatic capture of hybridization data. Bioinformatics 17: 205-213.
  • Kraemer, E., J. Wang, J. Guo, S. Hopkins and J. Arnold. 2001. An analysis of gene-finding approaches for Neurospora crassa. Bioinformatics 17: 901-912.
  • Sanchez, M.S., J. Arnold and M.A. Asmussen. 2000. Symbiont survival and host-symbiont disequilibria under differential vertical transmission. Genetics 154: 1347-1365.
Articles Featuring Jonathan Arnold

An interdisciplinary team of researchers at the University of Georgia has developed a new technology that may help scientists better understand how an individual cell synchronizes its biological clock with other cells. See full article…

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