Publications

Displaying 41 - 50 of 110 total publications

Fundamental Biological Features of Spaceflight: Advancing the Field to Enable Deep-Space Exploration

Afshinnekoo, E., Scott, R. T., MacKay, M. J., Pariset, E., Cekanaviciute, E., Barker, R., Gilroy, S., et al., (2020). Fundamental Biological Features of Spaceflight: Advancing the Field to Enable Deep-Space Exploration, Cell. doi.org/10.1016/j.cell.2020.10.050

Evaluating the effect of spaceflight on the host–pathogen interaction between human intestinal epithelial cells and Salmonella Typhimurium

Barrila, J., Sarker, S. F., Hansmeier, N., Yang, S., Buss, K., Briones, N., Park, J., Davis, R. R., Forsyth, R. J., Ott, C. M., Sato, K., Kosnik, C., Yang, A., Shimoda, C., Rayl, N., Ly, D., Landenberger, A., Wilson, S. D., Yamazaki, N., Steel, J., Montano, C., Halden, R.U., Cannon, T., Castro-Wallace, S. L. and Nickerson, C. A., (2021).  Evaluating the effect of spaceflight on the host–pathogen interaction between human intestinal epithelial cells and Salmonella Typhimurium, Microgravity.  doi.org/10.1038/s41526-021-00136-w

Dataset: GLDS-323

Network Analysis of Gene Transcriptions of Arabidopsis thaliana in Spaceflight Microgravity

Manian, V., Orozco, J., Gangapuram, H., Janwa, H., and Agrinsoni, C., (2021). Network Analysis of Gene Transcriptions of Arabidopsis thaliana in Spaceflight Microgravity, Genes. doi.org/10.3390/genes12030337

Datasets: GLDS-7 and GLDS-120

Knowledge Network Embedding of Transcriptomic Data from Spaceflown Mice Uncovers Signs and Symptoms Associated with Terrestrial Diseases

Nelson, C.A., Acuna, A.U., Paul, A.M., Scott, R.T., Butte, A.J., Cekanaviciute, E, Baranzini, S.E., and Costes, S.V., (2021). Knowledge Network Embedding of Transcriptomic Data from Spaceflown Mice Uncovers Signs and Symptoms Associated with Terrestrial Diseases, Life. doi.org/10.3390/life11010042

Datasets: GLDS-4, GLDS-244, GLDS-245, GLDS-246, GLDS-288, and GLDS-289.

Comparisons of Transcriptome Profiles from Bacillus subtilis Cells Grown in Space versus High Aspect Ratio Vessel (HARV) Clinostats Reveal a Low Degree of Concordance

Morrison, Michael D., Nicholson, Wayne L. "Comparisons of Transcriptome Profiles from Bacillus subtilis Cells Grown in Space versus High Aspect Ratio Vessel (HARV) Clinostats Reveal a Low Degree of Concordance. Astrobiology 2020, doi.org/10.1089/ast.2020.2235

Datasets: GLDS-31, GLDS-39, GLDS-14, GLDS-15

Approaches for Surveying Cosmic Radiation Damage in Large Populations of Arabidopsis thaliana Seeds – Antarctic Balloons and Particle Beams

Califar, B., Tucker, R., Cromie, J., Sng, N., Schmitz, R. A., Callaham, J. A., Barbazuk, B., Paul, A-L, Ferl, R. J. (2020). Approaches for Surveying Cosmic Radiation Damage in Large Populations of Arabidopsis thaliana Seeds – Antarctic Balloons and Particle Beams, Gravitational and Space Research 6:2, doi.org/10.2478/gsr-2018-0010

Dataset: GLDS-210

Sierra Nevada Sweep: Metagenomic Measurements of Bioaerosols Vertically Distributed Across the Troposphere

Jaing, C., Thissen, J., Morrison, M. et al. (2020) Sierra Nevada Sweep: Metagenomic Measurements of Bioaerosols Vertically Distributed Across the Troposphere. Sci Rep 10, 12399. doi.org/10.1038/s41598-020-69188-4

Dataset: GLDS-256

Draft Genome Sequences of Sphingomonas Species Associated with the International Space Station

Bijlani, S., Singh, N.K., Mason, C.E., Wang, C.C.C., Venkateswaran, K., (2020). Draft genome sequences of Sphingomonas species associated with the International Space Station. Microbiology Resource Announcement, 9:e00578-20. doi.org/10.1128/MRA.00578-20.

Dataset: GLDS-298

Draft Genome Sequences of Enterobacteriales Strains Isolated from the International Space Station

Bharadwaj, A.R., Daudu. R., Singh, N.K., Wood, J.M., Debieu, M., O’Hara, N.B., Karouia, F., Mason, C.E., Venkateswaran, K. (2020) Draft Genome Sequences of Enterobacteriales Strains Isolated from the International Space Station. Microbiology Resource Announcement - 9:e00817-20. doi.org/10.1128/MRA.00817-20.

Datasets: GLDS-302, GLDS-311

 

Integrated RNA-seq Analysis Indicates Asynchrony in Clock Genes between Tissues under Spaceflight

Fujita, S-I, Rutter, L., Ong, Q., Muratani, M. (2020). Integrated RNA-seq Analysis Indicates Asynchrony in Clock Genes between Tissues under Spaceflight. Life 2020, 10(9), 196; doi.org/10.3390/life10090196

Datasets: GLDS-98, GLDS-99, GLDS-101, GLDS-102, GLDS-103, GLDS-104, GLDS-105, GLDS-168, GLDS-48