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Kirshner A, Eddins D, French R, Helmcke K, Page GP, Linney E, Lnenicka G, Berger K, Welsh-Bohmer KA, Corl AB, Levin ED, Hirsch HV, Aschner M, Bartlett S, Possidente B, Hayden KM, Chen L, Possidente D, Ruden D, Heberlein U
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Neurotoxicology,
2009]
Considerable progress has been made over the past couple of decades concerning the molecular bases of neurobehavioral function and dysfunction. The field of neurobehavioral genetics is becoming mature. Genetic factors contributing to neurologic diseases such as Alzheimer's disease have been found and evidence for genetic factors contributing to other diseases such as schizophrenia and autism are likely. This genetic approach can also benefit the field of behavioral neurotoxicology. It is clear that there is substantial heterogeneity of response with behavioral impairments resulting from neurotoxicants. Many factors contribute to differential sensitivity, but it is likely that genetic variability plays a prominent role. Important discoveries concerning genetics and behavioral neurotoxicity are being made on a broad front from work with invertebrate and piscine mutant models to classic mouse knockout models and human epidemiologic studies of polymorphisms. Discovering genetic factors of susceptibility to neurobehavioral toxicity not only helps identify those at special risk, it also advances our understanding of the mechanisms by which toxicants impair neurobehavioral function in the larger population. This symposium organized by Edward Levin and Annette Kirshner, brought together researchers from the laboratories of Michael Aschner, Douglas Ruden, Ulrike Heberlein, Edward Levin and Kathleen Welsh-Bohmer conducting studies with Caenorhabditis elegans, Drosophila, fish, rodents and humans studies to determine the role of genetic factors in susceptibility to behavioral impairment from neurotoxic exposure.
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[
Genetics,
2016]
The Genetics Society of America's Edward Novitski Prize recognizes an extraordinary level of creativity and intellectual ingenuity in the solution of significant problems in genetics research. The 2016 winner, Leonid Kruglyak, has made innovative contributions to the fields of linkage analysis, population genetics, and genomics, while drawing on a combination of mathematical, computational, and experimental approaches. Among other achievements, his work on statistical standards for genome-wide linkage studies has transformed their experimental design, and the linkage analysis program GENEHUNTER has been used to identify hundreds of human disease loci. Kruglyak's group also pioneered expression quantitative trait locus studies, which enabled variation in global gene expression to shed light on the genetics of complex human diseases. In recent years, his laboratory has focused on using genomic technology to establish Saccharomyces cerevisiae and Caenorhabditis elegans as model organisms for studies of complex genetic variation.
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[
Genetics,
2017]
The Genetics Society of America's Edward Novitski Prize recognizes a single experimental accomplishment or a body of work in which an exceptional level of creativity and intellectual ingenuity has been used to design and execute scientific experiments to solve a difficult problem in genetics. The 2017 winner, Jonathan Hodgkin, used elegant genetic studies to unravel the sex determination pathway in Caenorhabditis elegans He inferred the order of genes in the pathway and their modes of regulation using epistasis analyses-a powerful tool that was quickly adopted by other researchers. He expanded the number and use of informational suppressor mutants in C. elegans that are able to act on many genes. He also introduced the use of collections of wild C. elegans to study naturally occurring genetic variation, paving the way for SNP mapping and QTL analysis, as well as studies of hybrid incompatibilities between worm species. His current work focuses on nematode-bacterial interactions and innate immunity.
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[
Plant Disease Reporter,
1975]
Twenty-five genera of nematodes were identified in six vegetable crops (carrot, pea, broccoli, rutabaga, Brussels sprouts, cauliflower) at fifty-six locations in Prince Edward Island (P.E.I.). Root lesion nematodes, Pratylenchus penetrans, were found in the soil at all locations and accounted for about 19% of the total nematode fauna. Meloidogyne hapla were recovered in only a few samples in low numbers, as were nematodes in the order Dorylaimida which accounted for about 5% of the total population. Non-stylet bearing nematodes made up 55% of the total and most of these were in two genera, Caenorhabditis spp. and Cephalobus spp. Carrot soils harbored the highest number of root lesion nematodes and pea soils had the least; 4726 and 547/kg of dry soil, respectively. Pea roots, however, had 2647/g dry root of these nematodes. No root lesion or other endoparasitic nematodes were recovered from the tap roots of carrots or from rutabagas. Some carrot and pea fields appeared to have lower than average yields where root lesion nematodes were recovered from soil and roots in very high numbers.
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[
Mol Cell Probes,
2014]
Based on the study of Ramanujan sum and Ramanujan coefficient, this paper suggests the concepts of discrete Ramanujan transform and spectrum. Using Voss numerical representation, one maps a symbolic DNA strand as a numerical DNA sequence, and deduces the discrete Ramanujan spectrum of the numerical DNA sequence. It is well known that of discrete Fourier power spectrum of protein coding sequence has an important feature of 3-base periodicity, which is widely used for DNA sequence analysis by the technique of discrete Fourier transform. It is performed by testing the signal-to-noise ratio at frequency N/3 as a criterion for the analysis, where N is the length of the sequence. The results presented in this paper show that the property of 3-base periodicity can be only identified as a prominent spike of the discrete Ramanujan spectrum at period 3 for the protein coding regions. The signal-to-noise ratio for discrete Ramanujan spectrum is defined for numerical measurement. Therefore, the discrete Ramanujan spectrum and the signal-to-noise ratio of a DNA sequence can be used for distinguishing the protein coding regions from the noncoding regions. All the exon and intron sequences in whole chromosomes 1, 2, 3 and 4 of Caenorhabditis elegans have been tested and the histograms and tables from the computational results illustrate the reliability of our method. In addition, we have analyzed theoretically and gotten the conclusion that the algorithm for calculating discrete Ramanujan spectrum owns the lower computational complexity and higher computational accuracy. The computational experiments show that the technique by using discrete Ramanujan spectrum for classifying different DNA sequences is a fast and effective method.