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15601 |
Revealing Alzheimer’s disease genes spectrum in the whole-genome by machine learning
Enthalten in BMC neurology Bd. 18, 10.1.2018, Nr. 1, date:12.2018: 1-8
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15602 |
Revealing effective regional decarbonisation measures to limit global temperature increase in uncertain transition scenarios with machine learning techniques
Enthalten in Climatic change Bd. 176, 16.6.2023, Nr. 7, date:7.2023: 1-23
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15603 |
Revealing low-temperature plasma efficacy through a dose-rate assessment by DNA damage detection combined with machine learning models
Enthalten in Scientific reports Bd. 12, 1.11.2022, Nr. 1, date:12.2022: 1-10
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15604 |
Revealing novel pyroptosis-related therapeutic targets for sepsis based on machine learning
Enthalten in BMC medical genomics Bd. 16, 10.2.2023, Nr. 1, date:12.2023: 1-15
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15605 |
Revealing potential diagnostic gene biomarkers of septic shock based on machine learning analysis
Enthalten in BMC infectious diseases Bd. 22, 19.1.2022, Nr. 1, date:12.2022: 1-16
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15606 |
Revealing Prdx4 as a potential diagnostic and therapeutic target for acute pancreatitis based on machine learning analysis
Enthalten in BMC medical genomics Bd. 17, 19.4.2024, Nr. 1, date:12.2024: 1-15
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15607 |
Revealing sequence variation patterns in rice with machine learning methods
Enthalten in BMC bioinformatics Bd. 9, 30.10.2008, Nr. 10, date:10.2008: 1-3
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15608 |
Revealing sleep and pain reciprocity with wearables and machine learning
Enthalten in Communications medicine Bd. 5, 7.5.2025, Nr. 1, date:12.2025: 1-6
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15609 |
Revealing the nature of soil liquefaction using machine learning
Enthalten in Earth science informatics Bd. 18, 21.1.2025, Nr. 2, date:2.2025: 1-27
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15610 |
Revealing third-order interactions through the integration of machine learning and entropy methods in genomic studies
Enthalten in BioData Mining Bd. 17, 30.1.2024, Nr. 1, date:12.2024: 1-17
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Administration
