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11441 |
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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11442 |
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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11443 |
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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11444 |
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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11445 |
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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11446 |
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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11447 |
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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11448 |
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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11449 |
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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11450 |
Revelation of microcracks as tooth structural element by X-ray tomography and machine learning Enthalten in Scientific reports Bd. 12, 28.12.2022, Nr. 1, date:12.2022: 1-14
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