Publications

  1. Chen, K., Liao, H., Arnold, A.E., Korotkin, H.B., Wu, S.H., Matheny, P.B., Lutzoni, F., 2022. Comparative transcriptomics of fungal endophytes in co‐culture with their moss host Dicranum scoparium reveals fungal trophic lability and moss unchanged to slightly increased growth rates. New Phytologist nph.18078. https://doi.org/10.1111/nph.18078
  2. Liao, H.-L., Bonito, G., Hameed, K., Wu, S.H., Chen, K.-H., Labbé, J., Schadt, C.W., Tuskan, G.A., Martin, F., Kuo, A., Barry, K., Grigoriev, I.V., Vilgalys, R., 2021. Heterospecific Neighbor Plants Impact Root Microbiome Diversity and Molecular Function of Root Fungi. Frontiers in Microbiology 12, 3355. https://doi.org/10.3389/fmicb.2021.680267
  3. Wong, T.K.F., Li, T., Ranjard, L., Wu, S.H., Sukumaran, J., Rodrigo, A.G., 2021. An assembly-free method of phylogeny reconstruction using short-read sequences from pooled samples without barcodes. PLOS Computational Biology 17, e1008949. https://doi.org/10.1371/journal.pcbi.1008949
  4. Liao, H.-L., Bonito, G., Rojas, J.A., Hameed, K., Wu, S., Schadt, C.W., Labbé, J., Tuskan, G.A., Martin, F., Grigoriev, I.V., Vilgalys, R., 2019. Fungal Endophytes of Populus trichocarpa Alter Host Phenotype, Gene Expression, and Rhizobiome Composition. MPMI 32, 853–864. https://doi.org/10.1094/MPMI-05-18-0133-R
  5. Garcia-Pichel, F., Lombard, J., Soule, T., Dunaj, S., Wu, S.H., Wojciechowski, M.F., 2019. Timing the Evolutionary Advent of Cyanobacteria and the Later Great Oxidation Event Using Gene Phylogenies of a Sunscreen. mBio 10. https://doi.org/10.1128/mBio.00561-19
  6. Winter, D.J., Wu, S.H., Howell, A.A., Azevedo, R.B.R., Zufall, R.A., Cartwright, R.A., 2018. accuMUlate: a mutation caller designed for mutation accumulation experiments. Bioinformatics 34, 2659–2660. https://doi.org/10.1093/bioinformatics/bty165
  7. Martinez, G., McCord, S., Driscoll, C., Todorova, S., Wu, S., Araújo, J., Vega, C., Fernandez, L., 2018. Mercury Contamination in Riverine Sediments and Fish Associated with Artisanal and Small-Scale Gold Mining in Madre de Dios, Peru. IJERPH 15, 1584. https://doi.org/10.3390/ijerph15081584
  8. Zeng, Q., Wu, S., Sukumaran, J., Rodrigo, A., 2017. Models of microbiome evolution incorporating host and microbial selection. Microbiome 5, 127. https://doi.org/10.1186/s40168-017-0343-x
  9. Wu, S.H., Schwartz, R.S., Winter, D.J., Conrad, D.F., Cartwright, R.A., 2017. Estimating error models for whole genome sequencing using mixtures of Dirichlet-multinomial distributions. Bioinformatics 33, 2322–2329. https://doi.org/10.1093/bioinformatics/btx133
  10. Uehling, J., Gryganskyi, A., Hameed, K., Tschaplinski, T., Misztal, P.K., Wu, S., Desirò, A., Vande Pol, N., Du, Z., Zienkiewicz, A., Zienkiewicz, K., Morin, E., Tisserant, E., Splivallo, R., Hainaut, M., Henrissat, B., Ohm, R., Kuo, A., Yan, J., Lipzen, A., Nolan, M., LaButti, K., Barry, K., Goldstein, A.H., Labbé, J., Schadt, C., Tuskan, G., Grigoriev, I., Martin, F., Vilgalys, R., Bonito, G., 2017. Comparative genomics of Mortierella elongata and its bacterial endosymbiont Mycoavidus cysteinexigens. Environ Microbiol 19, 2964–2983. https://doi.org/10.1111/1462-2920.13669
  11. Long, H., Winter, D.J., Chang, A.Y.-C., Sung, W., Wu, S.H., Balboa, M., Azevedo, R.B.R., Cartwright, R.A., Lynch, M., Zufall, R.A., 2016. Low Base-Substitution Mutation Rate in the Germline Genome of the Ciliate Tetrahymena thermophil. Genome Biol Evol evw223. https://doi.org/10.1093/gbe/evw223
  12. Zeng, Q., Sukumaran, J., Wu, S., Rodrigo, A., 2015. Neutral Models of Microbiome Evolution. PLoS Comput Biol 11, e1004365. https://doi.org/10.1371/journal.pcbi.1004365
  13. Wu, S.H., Rodrigo, A.G., 2015. Estimation of evolutionary parameters using short, random and partial sequences from mixed samples of anonymous individuals. BMC Bioinformatics 16, 357. https://doi.org/10.1186/s12859-015-0810-y
  14. Wu, S., Koelle, K., Rodrigo, A., 2013. Coalescent Entanglement and the Conditional Dependence of the Times to Common Ancestry of Mutually Exclusive Pairs of Individuals. Journal of Heredity 104, 86–91. https://doi.org/10.1093/jhered/ess074
  15. Ho, C., Wu, S., Amos, J.D., Colvin, L., Smith, S.D., Wilks, A.B., DeMarco, C.T., Brinkley, C., Denny, T.N., Schmitz, J.E., Rodrigo, A.G., Permar, S.R., 2013. Transient Compartmentalization of Simian Immunodeficiency Virus Variants in the Breast Milk of African Green Monkeys. J Virol 87, 11292–11299. https://doi.org/10.1128/JVI.01643-13
  16. Wu, S.H., Black, M.A., North, R.A., Rodrigo, A.G., 2012. A Bayesian model for classifying all differentially expressed proteins simultaneously in 2D PAGE gels. BMC Bioinformatics 13, 137. https://doi.org/10.1186/1471-2105-13-137
  17. Gryganskyi, A.P., Humber, R.A., Smith, M.E., Miadlikovska, J., Wu, S., Voigt, K., Walther, G., Anishchenko, I.M., Vilgalys, R., 2012. Molecular phylogeny of the Entomophthoromycota. Molecular Phylogenetics and Evolution 65, 682–694. https://doi.org/10.1016/j.ympev.2012.07.026
  18. Blumenstein, M., McCowan, L.M.E., Wu, S., Cooper, G.J.S., North, R.A., 2012. Plasma Clusterin Increased Prior to Small for Gestational Age (SGA) Associated With Preeclampsia and Decreased Prior to SGA in Normotensive Pregnancies. Reprod Sci 19, 650–657. https://doi.org/10.1177/1933719111430999
  19. Seed, P.T., Chappell, L.C., Black, M.A., Poppe, K.K., Hwang, Y.-C., Kasabov, N., McCowan, L., Shennan, A.H., Wu, S.H., Poston, L., North, R.A., 2011. Prediction of Preeclampsia and Delivery of Small for Gestational Age Babies Based on a Combination of Clinical Risk Factors in High-Risk Women. Hypertension in Pregnancy 30, 58–73. https://doi.org/10.3109/10641955.2010.486460
  20. Wu, S.H., Black, M.A., North, R.A., Atkinson, K.R., Rodrigo, A.G., 2009. A Statistical Model to Identify Differentially Expressed Proteins in 2D PAGE Gels. PLoS Comput Biol 5, e1000509. https://doi.org/10.1371/journal.pcbi.1000509
  21. Blumenstein, M., McMaster, M.T., Black, M.A., Wu, S., Prakash, R., Cooney, J., McCowan, L.M.E., Cooper, G.J.S., North, R.A., 2009. A proteomic approach identifies early pregnancy biomarkers for preeclampsia: Novel linkages between a predisposition to preeclampsia and cardiovascular disease. Proteomics 9, 2929–2945. https://doi.org/10.1002/pmic.200800625
  22. Atkinson, K.R., Blumenstein, M., Black, M.A., Wu, S.H., Kasabov, N., Taylor, R.S., Cooper, G.J.S., North, R.A., 2009. An altered pattern of circulating apolipoprotein E3 isoforms is implicated in preeclampsia. Journal of Lipid Research 50, 71–80. https://doi.org/10.1194/jlr.M800296-JLR200