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Metabolomics data normalization with EigenMS. [PDF]
PLoS ONE, 2014 Liquid chromatography mass spectrometry has become one of the analytical platforms of choice for metabolomics studies. However, LC-MS metabolomics data can suffer from the effects of various systematic biases.
Yuliya V Karpievitch +4 more
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Group normalization for genomic data. [PDF]
PLoS ONE, 2012 Data normalization is a crucial preliminary step in analyzing genomic datasets. The goal of normalization is to remove global variation to make readings across different experiments comparable.
Mahmoud Ghandi, Michael A Beer
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Comparison of Data Normalization Strategies for Array-Based MicroRNA Profiling Experiments and Identification and Validation of Circulating MicroRNAs as Endogenous Controls in Hypertension [PDF]
Frontiers in Genetics, 2022 Introduction: MicroRNAs are small noncoding RNAs with potential regulatory roles in hypertension and drug response. The presence of many of these RNAs in biofluids has spurred investigation into their role as possible biomarkers for use in precision ...
Lakshmi Manasa S. Chekka +3 more
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Loan classification using logistic regression
Informatika, 2023 Objectives. The studied problem of loan classification is particularly important for financial institutions, which must efficiently allocate monetary assets between entities as part of the provision of financial services.
U. I. Behunkou, M. Y. Kovalyov
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Data & Policy, 2021 The quality of service in healthcare is constantly challenged by outlier events such as pandemics (i.e., Covid-19) and natural disasters (such as hurricanes and earthquakes).
Chih-Hao Huang +5 more
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Optimum “Eye Location” Problem for Spectral Clustering With Cosine Distance
IEEE Access, 2023 It has recently been reported that Spectral Clustering gives state-of-the art clustering performance for many real-life benchmark datasets. When building the dissimilarity (distance) matrix for the Laplacian matrix, cosine distance is also reported to ...
Zekeriya Uykan
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Системный анализ и прикладная информатика, 2022 Quality assessment is an integral stage in the processing and analysis of digital images in various automated systems. With the increase in the number and variety of devices that allow receiving data in various digital formats, as well as the expansion ...
Y. I. Golub
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Crowdsourced-Data Normalization with Python and Pandas
The Programming Historian, 2021 Pandas is a popular and powerful package used in Python communities for data handling and analysis. This lesson describes crowdsourcing as a form of data creation as well as how pandas can be used to prepare a crowdsourced dataset for analysis.
Halle Burns
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Data normalization in machine learning
Informatika, 2021 In machine learning, the input data is often given in different dimensions. As a result of the scientific papers review, it is shown that the initial data described in different types of scales and units of measurement should be converted into a single ...
V. V. Starovoitov, Yu. I. Golub
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Statistical Analysis of NMR Metabolic Fingerprints: Established Methods and Recent Advances
Metabolites, 2018 In this review, we summarize established and recent bioinformatic and statistical methods for the analysis of NMR-based metabolomics. Data analysis of NMR metabolic fingerprints exhibits several challenges, including unwanted biases, high dimensionality,
Helena U. Zacharias +2 more
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