Pockmarks Offshore Big Sur, California Provide Evidence for Recurrent, Regional, and Unconfined Sediment Gravity Flows.

Autor: Lundsten, E.¹ (AUTHOR) eve@mbari.org, Paull, C. K.¹ (AUTHOR), Gwiazda, R.¹ (AUTHOR), Dobbs, S.² (AUTHOR), Caress, D. W.¹ (AUTHOR), Kuhnz, L. A.^1,3 (AUTHOR), Walton, M.^4,5 (AUTHOR), Nieminski, N.^4,6 (AUTHOR), McGann, M.⁷ (AUTHOR), Lorenson, T.⁴ (AUTHOR), Cochrane, G.⁴ (AUTHOR), Addison, J.⁷ (AUTHOR)

Publikováno v: Journal of Geophysical Research. Earth Surface. May2024, Vol. 129 Issue 5, p1-22. 22p.

The FAANG Data Portal: Global, Open-Access, 'FAIR', and Richly Validated Genotype to Phenotype Data for High-Quality Functional Annotation of Animal Genomes

Autor: Harrison PW, Sokolov A, Nayak A, Fan J, Zerbino D, Cochrane G and Flicek P

The Functional Annotation of ANimal Genomes (FAANG) project is a worldwide coordinated action creating high-quality functional annotation of farmed and companion animal genomes. The generation of a rich genome-to-phenome resource and supporting infor

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od______2659::c12cae73c837d094b7957111137192fd
https://zenodo.org/record/7688870

Vegetation Studies in Forest-fire Areas of the Mount Lofty Ranges, South Australia

Autor: Cochrane, G. Ross

Publikováno v: Ecology, 1963 Jan 01. 44(1), 41-52.

Externí odkaz: https://www.jstor.org/stable/1933179

Effect of Sex of Fetus on Asthma during Pregnancy: Blind Prospective Study

Autor: Beecroft, N., Cochrane, G. M., Milburn, Heather J.

Publikováno v: BMJ: British Medical Journal, 1998 Sep . 317(7162), 856-857.

Externí odkaz: https://www.jstor.org/stable/25180493

Understanding and predicting ciprofloxacin minimum inhibitory concentration in Escherichia coli with machine learning

Autor: Pataki B. A., Matamoros S., van der Putten B. C. L., Remondini D., Giampieri E., Aytan-Aktug D., Hendriksen R. S., Lund O., Csabai I., Schultsz C., Janes V., Clausen P., Aarestrup F. M., Koopmans M., Pataki B., Visontai D., Steger J., Szalai-Gindl J. M., Pakseresht N., Rossello M., Silvester N., Amid C., Cochrane G., Pradel F., Westeel E., Fuchs S., Kumar S. M., Xavier B. B., Ngoc M. N., Pasquali F., Petrovska L., Ajayi D., Nielsen E. M., Trung N. V., Hoa N. T., Ishii Y., Aoki K., McDermott P.

Publikováno v: Scientific Reports
Scientific Reports, Vol 10, Iss 1, Pp 1-9 (2020)
Scientific Reports, 10(1):15026. Nature Publishing Group
Pataki, B Á, Matamoros, S, van der Putten, B C L, Remondini, D, Giampieri, E, Aytan-Aktug, D, Hendriksen, R S, Lund, O, Csabai, I, Schultsz, C & COMPARE ML-AMR group, SPS 2020, ' Understanding and predicting ciprofloxacin minimum inhibitory concentration in Escherichia coli with machine learning ', Scientific Reports, vol. 10, no. 1, 15026 . https://doi.org/10.1038/s41598-020-71693-5
Scientific reports, 10(1):15026. Nature Publishing Group

2.AbstractA possible way to tackle the crisis of antimicrobial resistance development is a strict policy when prescribing antibiotics. Thus, it is important that prescriptions are based on antimicrobial susceptibility data to ensure effective treatme

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1bed87c02836305405fd4127aea01351