| 1. |
- Adler, Jeremy, et al.
(författare)
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Quantifying Colocalization by Correlation : The Pearson Correlation Coefficient is Superior to the Mander's Overlap Coefficient
- 2010
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Ingår i: CYTOMETRY PART A. - : Wiley. - 1552-4922 .- 1552-4930. ; 77A:8, s. 733-742
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Tidskriftsartikel (refereegranskat)abstract
- The Pearson correlation coefficient (PCC) and the Mander's overlap coefficient (MOC) are used to quantify the degree of colocalization between fluorophores. The MOC was introduced to overcome perceived problems with the PCC. The two coefficients are mathematically similar, differing in the use of either the absolute intensities (MOC) or of the deviation from the mean (PCC). A range of correlated datasets, which extend to the limits of the PCC, only evoked a limited response from the MOC. The PCC is unaffected by changes to the offset while the MOC increases when the offset is positive. Both coefficients are independent of gain. The MOC is a confusing hybrid measurement, that combines correlation with a heavily weighted form of co-occurrence, favors high intensity combinations, downplays combinations in which either or both intensities are low and ignores blank pixels. The PCC only measures correlation. A surprising finding was that the addition of a second uncorrelated population can substantially increase the measured correlation, demonstrating the importance of excluding background pixels. Overall, since the MOC is unresponsive to substantial changes in the data and is hard to interpret, it is neither an alternative to nor a useful substitute for the PCC. The MOC is not suitable for making measurements of colocalization either by correlation or co-occurrence.
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| 2. |
- Adler, Jeremy, et al.
(författare)
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Quantifying Colocalization: the Case for Discarding the Manders Overlap Coefficient.
- 2021
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Ingår i: Cytometry. Part A : the journal of the International Society for Analytical Cytology. - : Wiley. - 1552-4930. ; 99:9, s. 910-920
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Tidskriftsartikel (refereegranskat)abstract
- Colocalization measurements aim to characterize the relative distribution of two molecules within a biologically relevant area. It is efficient to measure two distinct features, co-occurrence, the extent to which the molecules appear together, and correlation, how well variations in concentration of the two molecules match. The Manders overlap coefficient (MOC) appears in most colocalization software but the literature contains three interpretations of its measurements: a) co-occurrence, b) correlation or c) a combination of both. This is surprising given the simplicity of the underlying equation. Testing shows that the MOC responds both to changes in co-occurrence and to changes in correlation. Further testing reveals that different distributions of intensity (Gaussian, gamma, uniform, exponential) dramatically alter the balance between the contribution from co-occurrence and correlation. It follows that the MOC's ability to differentiate between different patterns of colocalization is very limited, since any value is compatible with widely differing combinations of co-occurrence, correlation and intensity distribution. To characterize colocalization we recommend reporting both co-occurrence and correlation, using coefficients specific for each attribute. Since the MOC has no clear role in the measurement of colocalization and causes considerable confusion, we conclude that it should be discarded. This article is protected by copyright. All rights reserved.
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| 3. |
- Allalou, Amin, et al.
(författare)
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Robust signal detection in 3D fluorescence microscopy
- 2010
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Ingår i: Cytometry. Part A. - : Wiley. - 1552-4922 .- 1552-4930. ; 77A:1, s. 86-96
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Tidskriftsartikel (refereegranskat)abstract
- Robust detection and localization of biomolecules inside cells is of great importance to better understand the functions related to them. Fluorescence microscopy and specific staining methods make biomolecules appear as point-like signals on image data, often acquired in 3D. Visual detection of such point-like signals can be time consuming and problematic if the 3D images are large, containing many, sometimes overlapping, signals. This sets a demand for robust automated methods for accurate detection of signals in 3D fluorescence microscopy. We propose a new 3D point-source signal detection method that is based on Fourier series. The method consists of two parts, a detector, which is a cosine filter to enhance the point-like signals, and a verifier, which is a sine filter to validate the result from the detector. Compared to conventional methods, our method shows better robustness to noise and good ability to resolve signals that are spatially close. Tests on image data show that the method has equivalent accuracy in signal detection in comparison to Visual detection by experts. The proposed method can be used as an efficient point-like signal detection tool for various types of biological 3D image data.
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| 4. |
- Antoniadi, Ioanna, et al.
(författare)
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Best practices in plant cytometry
- 2021
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Ingår i: Cytometry Part A. - : Wiley. - 1552-4922 .- 1552-4930. ; 99, s. 311-317
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Tidskriftsartikel (refereegranskat)
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| 5. |
- Antoniadi, Ioanna, et al.
(författare)
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Fluorescence activated cell sorting-A selective tool for plant cell isolation and analysis
- 2022
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Ingår i: Cytometry Part A. - : Wiley. - 1552-4922 .- 1552-4930. ; 101, s. 725-736
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Tidskriftsartikel (refereegranskat)abstract
- Instrumentation for flow cytometry and sorting is designed around the assumption that samples are single-cell suspensions. However, with few exceptions, higher plants comprise complex multicellular tissues and organs, in which the individual cells are held together by shared cell walls. Single-cell suspensions can be obtained through digestion of the cells walls and release of the so-called protoplasts (plants without their cell wall). Here we describe best practices for protoplast preparation, and for analysis through flow cytometry and cell sorting. Finally, the numerous downstream applications involving sorted protoplasts are discussed.
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| 6. |
- Apweiler, Rolf, et al.
(författare)
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Approaching clinical proteomics : current state and future fields of application in cellular proteomics
- 2009
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Ingår i: Cytometry. Part A : the journal of the International Society for Analytical Cytology. - : Wiley. - 1552-4922. ; 75A:10, s. 816-832
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Forskningsöversikt (refereegranskat)abstract
- Recent developments in proteomics technology offer new opportunities for clinical applications in hospital or specialized laboratories including the identification of novel biomarkers, monitoring of disease, detecting adverse effects of drugs, and environmental hazards. Advanced spectrometry technologies and the development of new protein array formats have brought these analyses to a standard, which now has the potential to be used in clinical diagnostics. Besides standardization of methodologies and distribution of proteomic data into public databases, the nature of the human body fluid proteome with its high dynamic range in protein concentrations, its quantitation problems, and its extreme complexity present enormous challenges. Molecular cell biology (cytomics) with its link to proteomics is a new fast moving scientific field, which addresses functional cell analysis and bioinformatic approaches to search for novel cellular proteomic biomarkers or their release products into body fluids that provide better insight into the enormous biocomplexity of disease processes and are suitable for patient stratification, therapeutic monitoring, and prediction of prognosis. Experience from studies of in vitro diagnostics and especially in clinical chemistry showed that the majority of errors occurs in the preanalytical phase and the setup of the diagnostic strategy. This is also true for clinical proteomics where similar preanalytical variables such as inter- and intra-assay variability due to biological variations or proteolytical activities in the sample will most likely also influence the results of proteomics studies. However, before complex proteomic analysis can be introduced at a broader level into the clinic, standardization of the preanalytical phase including patient preparation, sample collection, sample preparation, sample storage, measurement, and data analysis is another issue which has to be improved. In this report, we discuss the recent advances and applications that fulfill the criteria for clinical proteomics with the focus on cellular proteomics (cytoproteomics) as related to preanalytical and analytical standardization and to quality control measures required for effective implementation of these technologies and analytes into routine laboratory testing to generate novel actionable health information. It will then be crucial to design and carry out clinical studies that can eventually identify novel clinical diagnostic strategies based on these techniques and validate their impact on clinical decision making.
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| 7. |
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| 8. |
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| 9. |
- Bengtsson, Ewert, et al.
(författare)
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Special Section on Image Cytometry
- 2019
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Ingår i: Cytometry Part A. - : Wiley. - 1552-4922 .- 1552-4930. ; 95A:4, s. 363-365
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)
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| 10. |
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