Search

Your search keyword '"Liu, J.S."' showing total 359 results
Start Over Author "Liu, J.S."
359 results on '"Liu, J.S."'

105. Genetics of rheumatoid arthritis contributes to biology and drug discovery

Author

Okada, Y., Wu, D., Trynka, G., Raj, T., Terao, C., Ikari, K., Kochi, Y., Ohmura, K., Suzuki, A., Yoshida, S., Graham, R.R., Manoharan, A., Ortmann, W., Bhangale, T., Denny, J.C., Carroll, R.J., Eyler, A.E., Greenberg, J.D., Kremer, J.M, Pappas, D.A., Jiang, L., Yin, J., Ye, L, Su, D.F., Yang, J., Xie, G., Keystone, E., Westra, H.J., Esko, T., Metspalu, A., Zhou, X., Gupta, N., Mirel, D., Stahl, E.A., Diogo, D., Cui, J., Liao, K., Guo, M.H., Myouzen, K., Kawaguchi, T., Coenen, M.J.H., Riel, P.L.C.M. van, Laar, M.A. van der, Guchelaar (LUMC), H.J., Huizinga, T.W.J., Dieude, P., Mariette, X., Bridges, S.L., Jr., Zhernakova, A., Toes, R.E., Tak, P.P., Miceli-Richard, C., Bang, S.Y., Lee, H.S., Martin, J., Gonzalez-Gay, M.A., Rodriguez-Rodriguez, L., Rantapaa-Dahlqvist, S., Arlestig, L., Choi, H.K., Kamatani, Y., Galan, P., Lathrop, M., Eyre, S., Bowes, J., Barton, A., Vries, N. de, Moreland, L.W., Criswell, L.A., Karlson, E.W., Taniguchi, A., Yamada, R., Kubo, M., Liu, J.S., Bae, S.C., Worthington, J., Padyukov, L., Klareskog, L., Gregersen, P.K., Raychaudhuri, S., Stranger, B.E., Jager, P.L. De, Franke, L., Visscher, P.M., Brown, M.A., Yamanaka, H., Mimori, T., Takahashi, A., Xu, H., Behrens, T.W., Siminovitch, K.A., Momohara, S., Matsuda, F., Yamamoto, K., Plenge, R.M., et al., Okada, Y., Wu, D., Trynka, G., Raj, T., Terao, C., Ikari, K., Kochi, Y., Ohmura, K., Suzuki, A., Yoshida, S., Graham, R.R., Manoharan, A., Ortmann, W., Bhangale, T., Denny, J.C., Carroll, R.J., Eyler, A.E., Greenberg, J.D., Kremer, J.M, Pappas, D.A., Jiang, L., Yin, J., Ye, L, Su, D.F., Yang, J., Xie, G., Keystone, E., Westra, H.J., Esko, T., Metspalu, A., Zhou, X., Gupta, N., Mirel, D., Stahl, E.A., Diogo, D., Cui, J., Liao, K., Guo, M.H., Myouzen, K., Kawaguchi, T., Coenen, M.J.H., Riel, P.L.C.M. van, Laar, M.A. van der, Guchelaar (LUMC), H.J., Huizinga, T.W.J., Dieude, P., Mariette, X., Bridges, S.L., Jr., Zhernakova, A., Toes, R.E., Tak, P.P., Miceli-Richard, C., Bang, S.Y., Lee, H.S., Martin, J., Gonzalez-Gay, M.A., Rodriguez-Rodriguez, L., Rantapaa-Dahlqvist, S., Arlestig, L., Choi, H.K., Kamatani, Y., Galan, P., Lathrop, M., Eyre, S., Bowes, J., Barton, A., Vries, N. de, Moreland, L.W., Criswell, L.A., Karlson, E.W., Taniguchi, A., Yamada, R., Kubo, M., Liu, J.S., Bae, S.C., Worthington, J., Padyukov, L., Klareskog, L., Gregersen, P.K., Raychaudhuri, S., Stranger, B.E., Jager, P.L. De, Franke, L., Visscher, P.M., Brown, M.A., Yamanaka, H., Mimori, T., Takahashi, A., Xu, H., Behrens, T.W., Siminovitch, K.A., Momohara, S., Matsuda, F., Yamamoto, K., Plenge, R.M., and et al.

Abstract

Item does not contain fulltext, A major challenge in human genetics is to devise a systematic strategy to integrate disease-associated variants with diverse genomic and biological data sets to provide insight into disease pathogenesis and guide drug discovery for complex traits such as rheumatoid arthritis (RA). Here we performed a genome-wide association study meta-analysis in a total of >100,000 subjects of European and Asian ancestries (29,880 RA cases and 73,758 controls), by evaluating approximately 10 million single-nucleotide polymorphisms. We discovered 42 novel RA risk loci at a genome-wide level of significance, bringing the total to 101 (refs 2 - 4). We devised an in silico pipeline using established bioinformatics methods based on functional annotation, cis-acting expression quantitative trait loci and pathway analyses--as well as novel methods based on genetic overlap with human primary immunodeficiency, haematological cancer somatic mutations and knockout mouse phenotypes--to identify 98 biological candidate genes at these 101 risk loci. We demonstrate that these genes are the targets of approved therapies for RA, and further suggest that drugs approved for other indications may be repurposed for the treatment of RA. Together, this comprehensive genetic study sheds light on fundamental genes, pathways and cell types that contribute to RA pathogenesis, and provides empirical evidence that the genetics of RA can provide important information for drug discovery.

Published
2014

113. A recessive gene for revolute cotyledons in cucumber

Author

Wehner, T.C., Staub, J.E., and Liu, J.S.

Subjects
Cucumbers -- Genetic aspects, Plant genetics -- Research, Biological sciences
Abstract

The genetics of the revolute cotyledons trait in the cucumber inbred NCG-093 was investigated in an experiment. NCG-093 was crossed with inbred WI 2757 to produce F1, F2, and BC1 generations for evaluation. The BC1A(F1xWI 2757) progeny had normal cotyledons and the segregation of the BCB(f1xNCG-093) fit a ratio of 1 normal:1 revolute cotyledons. Likewise, the F1 progeny expressed normal cotyledons and the segregation of the F2 progeny fit a ratio of 3 normal:1 revolute cotyledons. These suggested that revolute cotyledons in NCG-093 was conferred by revolute cotyledons-2.

Published
1998

114. SASGENE: a SAS computer program for genetic analysis of gene segregation and linkage

Author

Liu, J.S., Wehner, T.C., and Donaghy, S.B.

Subjects
Linkage (Genetics) -- Research, Genetic research, Biological sciences
Abstract

A SASGENE computer program was developed for genetic analysis of gene segregation and linkage. It consists of two SAS macros namely, SGENE and Linkage. The SGENE performs single gene goodness-of-fit tests of observed frequency data while, LINKAGE performs analysis of gene linkage relationships. The program is being distributed for free. Files can be obtained from the World Wide Web or from T.C. Wehner.

Published
1997

116. A comparison of various Gibbs energy dissipation correlations for predicting microbial growth yields

Author

Liu, J.S., Vojinovic, V., Patiño, R., Maskow, Thomas, von Stockar, U., Liu, J.S., Vojinovic, V., Patiño, R., Maskow, Thomas, and von Stockar, U.

Abstract

Thermodynamic analysis may be applied in order to predict microbial growth yields roughly, based on an empirical correlation of the Gibbs energy of the overall growth reaction or Gibbs energy dissipation. Due to the well-known trade-off between high biomass yield and high Gibbs energy dissipation necessary for fast growth, an optimal range of Gibbs energy dissipation exists and it can be correlated to physical characteristics of the growth substrates. A database previously available in the literature has been extended significantly in order to test such correlations. An analysis of the relationship between biomass yield and Gibbs energy dissipation reveals that one does not need a very precise estimation of the latter to predict the former roughly. Approximating the Gibbs energy dissipation with a constant universal value of -500 kJ C-mol-1 of dry biomass grown predicts many experimental growth yields nearly as well as a carefully designed, complex correlation available from the literature, even though a number of predictions are grossly out of range. A new correlation for Gibbs energy dissipation is proposed which is just as accurate as the complex literature correlation despite its dramatically simpler structure.

Published
2007

Catalog

Books, media, physical & digital resources
See catalog results