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Unknown
(14)
Transcriptomics
(1)
Repository
biostudies-arrayexpress
(1)
Instrument Platform
Anaerobic workstation with airlock
(1)
Publication Date
2008
(1)
Study type
Transcription profiling by array
(1)
Release Date
2023
(5)
2024
(3)
2022
(3)
2021
(3)
2008
(1)
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Transcription profiling of C. difficile following environmental stress
Data is also available from http://bugs.sgul.ac.uk/E-BUGS-55
ORGANISM(S):
Clostridium difficile
2008-11-18
|
E-BUGS-55
|
biostudies-arrayexpress
Cite
Chronic use of renin-angiotensin-aldosterone system blockers and mortality in COVID-19: A multicenter prospective cohort and literature review.
Not available
S-EPMC8250758
|
biostudies-literature
Cite
Sex differences in post-acute neurological sequelae of SARS-CoV-2 and symptom resolution in adults after coronavirus disease 2019 hospitalization: an international multi-centre prospective observational study.
Not available
S-EPMC10914448
|
biostudies-literature
Cite
Long Covid: a global health issue - a prospective, cohort study set in four continents.
Not available
S-EPMC11552006
|
biostudies-literature
Cite
Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries.
Not available
S-EPMC10364528
|
biostudies-literature
Cite
Implementation of Recommendations on the Use of Corticosteroids in Severe COVID-19.
Not available
S-EPMC10751594
|
biostudies-literature
Cite
Ten months of temporal variation in the clinical journey of hospitalised patients with COVID-19: An observational cohort.
Not available
S-EPMC8791638
|
biostudies-literature
Cite
Respiratory support in patients with severe COVID-19 in the International Severe Acute Respiratory and Emerging Infection (ISARIC) COVID-19 study: a prospective, multinational, observational study.
Not available
S-EPMC9469080
|
biostudies-literature
Cite
Paediatric COVID-19 mortality: a database analysis of the impact of health resource disparity.
Not available
S-EPMC9621167
|
biostudies-literature
Cite
At-admission prediction of mortality and pulmonary embolism in an international cohort of hospitalised patients with COVID-19 using statistical and machine learning methods.
Not available
S-EPMC11252333
|
biostudies-literature
Cite
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