Abigail Green-Saxena
Abigail Green-Saxena
Geverifieerd e-mailadres voor alumni.caltech.edu
Geciteerd door
Geciteerd door
Extensive exchange of fungal cultivars between sympatric species of fungus‐growing ants
AM Green, UG Mueller, RMM Adams
Molecular Ecology 11 (2), 191-195, 2002
Garden sharing and garden stealing in fungus-growing ants
RMM Adams, UG Mueller, AK Holloway, AM Green, J Narozniak
Naturwissenschaften 87 (11), 491-493, 2000
Patterns of 15N assimilation and growth of methanotrophic ANME‐2 archaea and sulfate‐reducing bacteria within structured syntrophic consortia revealed by FISH …
VJ Orphan, KA Turk, AM Green, CH House
Environmental microbiology 11 (7), 1777-1791, 2009
Heavy water and 15N labelling with NanoSIMS analysis reveals growth rate‐dependent metabolic heterogeneity in chemostats
SH Kopf, SE McGlynn, A Green‐Saxena, Y Guan, DK Newman, ...
Environmental microbiology 17 (7), 2542-2556, 2015
Global molecular analyses of methane metabolism in methanotrophic Alphaproteobacterium, Methylosinus trichosporium OB3b. Part II. Metabolomics and 13C-labeling study
MG Kalyuzhanaya, S Yang, JB Matsen, M Konopka, A Green-Saxena, ...
Frontiers in microbiology 4, 70, 2013
Nitrate-based niche differentiation by distinct sulfate-reducing bacteria involved in the anaerobic oxidation of methane
A Green-Saxena, AE Dekas, NF Dalleska, VJ Orphan
The ISME journal 8 (1), 150-163, 2014
Pseudofossils in relict methane seep carbonates resemble endemic microbial consortia
JV Bailey, TD Raub, AN Meckler, BK Harrison, TMD Raub, AM Green, ...
Palaeogeography, Palaeoclimatology, Palaeoecology 285 (1-2), 131-142, 2010
Neural crest and cancer: Divergent travelers on similar paths
KL Gallik, RW Treffy, LM Nacke, K Ahsan, M Rocha, A Green-Saxena, ...
Mechanisms of development 148, 89-99, 2017
Active sulfur cycling by diverse mesophilic and thermophilic microorganisms in terrestrial mud volcanoes of A zerbaijan
A Green‐Saxena, A Feyzullayev, CRJ Hubert, J Kallmeyer, M Krüger, ...
Environmental Microbiology 14 (12), 3271-3286, 2012
Widespread nitrogen fixation in sediments from diverse deep‐sea sites of elevated carbon loading
AE Dekas, DA Fike, GL Chadwick, A Green‐Saxena, J Fortney, ...
Environmental microbiology 20 (12), 4281-4296, 2018
Multicenter validation of a machine-learning algorithm for 48-h all-cause mortality prediction
H Mohamadlou, S Panchavati, J Calvert, A Lynn-Palevsky, S Le, A Allen, ...
Health informatics journal 26 (3), 1912-1925, 2020
Prediction of respiratory decompensation in Covid-19 patients using machine learning: The READY trial
H Burdick, C Lam, S Mataraso, A Siefkas, G Braden, RP Dellinger, ...
Computers in biology and medicine 124, 103949, 2020
Effect of a sepsis prediction algorithm on patient mortality, length of stay and readmission: a prospective multicentre clinical outcomes evaluation of real-world patient data …
H Burdick, E Pino, D Gabel-Comeau, A McCoy, C Gu, J Roberts, S Le, ...
BMJ Health & Care Informatics 27 (1), e100109, 2020
Chapter two—whole cell immunomagnetic enrichment of environmental microbial consortia using rRNATargeted Magneto-FISH
E Trembath-Reichert, A Green-Saxena, VJ Orphan, FD Edward
Microbial metagenomics, metatranscriptomics, and metaproteomics, 21-44, 2013
Whole cell immunomagnetic enrichment of environmental microbial consortia using rRNA-targeted Magneto-FISH
E Trembath-Reichert, A Green-Saxena, VJ Orphan
Methods in Enzymology 531, 21-44, 2013
Supervised Machine Learning for the Early Prediction of Acute Respiratory Distress Syndrome (ARDS)
S Le, E Pellegrini, A Green-Saxena, C Summers, J Hoffman, J Calvert, ...
medRxiv, 2020
Mortality prediction model for the triage of COVID-19, pneumonia, and mechanically ventilated ICU patients: a retrospective study
L Ryan, C Lam, S Mataraso, A Allen, A Green-Saxena, E Pellegrini, ...
Annals of Medicine and Surgery 59, 207-216, 2020
Is Machine Learning a Better Way to Identify COVID-19 Patients Who Might Benefit from Hydroxychloroquine Treatment?—The IDENTIFY Trial
H Burdick, C Lam, S Mataraso, A Siefkas, G Braden, RP Dellinger, ...
Journal of clinical medicine 9 (12), 3834, 2020
Validation of a machine learning algorithm for early severe sepsis prediction: a retrospective study predicting severe sepsis up to 48 h in advance using a diverse dataset from …
H Burdick, E Pino, D Gabel-Comeau, C Gu, J Roberts, S Le, J Slote, ...
BMC medical informatics and decision making 20 (1), 1-10, 2020
Predicting Ventilator-Associated Pneumonia with Machine Learning
C Giang, J Calvert, G Barnes, A Siefkas, A Green-Saxena, J Hoffman, ...
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Artikelen 1–20