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imaris filament tracer data  (Oxford Instruments)
99
Oxford Instruments imaris filament tracer data
a Image processing. Firstly, the images were non-linearly corrected (Supplementary Fig. ), then the images were linearly unmixed (Fig. and Supplementary Fig. ). If axial chromatic aberration correction was necessary, it was performed as described in Leiwe et al. . b Neurite detection with Neurolucida 360 (MBF Biosciences). Fluorescence images were loaded into Neurolucida 360, to automatically detect neurites using the directional kernels method. However, mistracing frequently occurred in densely labelled images, especially at branch and crossing points. Therefore, detected neurites are split into fragments at branch and crossing points (right). Note that somata were excluded in this step, as they are too bright, and their signals are beyond the linear range. Our QDyeFinder pipeline supports <t>data</t> in.swc format, which is commonly used for neurite reconstruction. To use <t>Imaris</t> <t>Filament</t> <t>Tracer</t> (Oxford Instrument) for automated neurite fragments, see Supplementary Note . c Once the fragments have been detected, the relevant voxels are identified, and the mean pixel intensity is calculated for each channel. After quality control (Supplementary Fig. ), fragments are represented in vector normalised space (colour vectors). d Colour vectors for the fragments are then clustered based on Th(d) with our clustering algorithm dCrawler (left and middle). Individual clusters can then be plotted to identify neurons from individual fragments (right).
Imaris Filament Tracer Data, supplied by Oxford Instruments, used in various techniques. Bioz Stars score: 99/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/tracer+data/pmc11199630-548-3-3?v=Oxford+Instruments
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imaris filament tracer data - by Bioz Stars, 2026-07
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isotope tracer data  (Mendeley Ltd)
90
Mendeley Ltd isotope tracer data
a Image processing. Firstly, the images were non-linearly corrected (Supplementary Fig. ), then the images were linearly unmixed (Fig. and Supplementary Fig. ). If axial chromatic aberration correction was necessary, it was performed as described in Leiwe et al. . b Neurite detection with Neurolucida 360 (MBF Biosciences). Fluorescence images were loaded into Neurolucida 360, to automatically detect neurites using the directional kernels method. However, mistracing frequently occurred in densely labelled images, especially at branch and crossing points. Therefore, detected neurites are split into fragments at branch and crossing points (right). Note that somata were excluded in this step, as they are too bright, and their signals are beyond the linear range. Our QDyeFinder pipeline supports <t>data</t> in.swc format, which is commonly used for neurite reconstruction. To use <t>Imaris</t> <t>Filament</t> <t>Tracer</t> (Oxford Instrument) for automated neurite fragments, see Supplementary Note . c Once the fragments have been detected, the relevant voxels are identified, and the mean pixel intensity is calculated for each channel. After quality control (Supplementary Fig. ), fragments are represented in vector normalised space (colour vectors). d Colour vectors for the fragments are then clustered based on Th(d) with our clustering algorithm dCrawler (left and middle). Individual clusters can then be plotted to identify neurons from individual fragments (right).
Isotope Tracer Data, supplied by Mendeley Ltd, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/tracer+data/pm40080501-242-0-7?v=Mendeley+Ltd
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isotope tracer data - by Bioz Stars, 2026-07
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filament tracer analysis lsfm data  (Oxford Instruments)
99
Oxford Instruments filament tracer analysis lsfm data
a Image processing. Firstly, the images were non-linearly corrected (Supplementary Fig. ), then the images were linearly unmixed (Fig. and Supplementary Fig. ). If axial chromatic aberration correction was necessary, it was performed as described in Leiwe et al. . b Neurite detection with Neurolucida 360 (MBF Biosciences). Fluorescence images were loaded into Neurolucida 360, to automatically detect neurites using the directional kernels method. However, mistracing frequently occurred in densely labelled images, especially at branch and crossing points. Therefore, detected neurites are split into fragments at branch and crossing points (right). Note that somata were excluded in this step, as they are too bright, and their signals are beyond the linear range. Our QDyeFinder pipeline supports <t>data</t> in.swc format, which is commonly used for neurite reconstruction. To use <t>Imaris</t> <t>Filament</t> <t>Tracer</t> (Oxford Instrument) for automated neurite fragments, see Supplementary Note . c Once the fragments have been detected, the relevant voxels are identified, and the mean pixel intensity is calculated for each channel. After quality control (Supplementary Fig. ), fragments are represented in vector normalised space (colour vectors). d Colour vectors for the fragments are then clustered based on Th(d) with our clustering algorithm dCrawler (left and middle). Individual clusters can then be plotted to identify neurons from individual fragments (right).
Filament Tracer Analysis Lsfm Data, supplied by Oxford Instruments, used in various techniques. Bioz Stars score: 99/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/tracer+data/pmc11303492-425-1-0?v=Oxford+Instruments
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filament tracer analysis lsfm data - by Bioz Stars, 2026-07
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data tracer v 3.0  (QuinTron Instrument Company Inc)
90
QuinTron Instrument Company Inc data tracer v 3.0
a Image processing. Firstly, the images were non-linearly corrected (Supplementary Fig. ), then the images were linearly unmixed (Fig. and Supplementary Fig. ). If axial chromatic aberration correction was necessary, it was performed as described in Leiwe et al. . b Neurite detection with Neurolucida 360 (MBF Biosciences). Fluorescence images were loaded into Neurolucida 360, to automatically detect neurites using the directional kernels method. However, mistracing frequently occurred in densely labelled images, especially at branch and crossing points. Therefore, detected neurites are split into fragments at branch and crossing points (right). Note that somata were excluded in this step, as they are too bright, and their signals are beyond the linear range. Our QDyeFinder pipeline supports <t>data</t> in.swc format, which is commonly used for neurite reconstruction. To use <t>Imaris</t> <t>Filament</t> <t>Tracer</t> (Oxford Instrument) for automated neurite fragments, see Supplementary Note . c Once the fragments have been detected, the relevant voxels are identified, and the mean pixel intensity is calculated for each channel. After quality control (Supplementary Fig. ), fragments are represented in vector normalised space (colour vectors). d Colour vectors for the fragments are then clustered based on Th(d) with our clustering algorithm dCrawler (left and middle). Individual clusters can then be plotted to identify neurons from individual fragments (right).
Data Tracer V 3.0, supplied by QuinTron Instrument Company Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/tracer+data/pm37764818-61-4-1?v=QuinTron+Instrument+Company+Inc
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data tracer v 3.0 - by Bioz Stars, 2026-07
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tracer data  (Meso Scale Diagnostics LLC)
90
Meso Scale Diagnostics LLC tracer data
a Image processing. Firstly, the images were non-linearly corrected (Supplementary Fig. ), then the images were linearly unmixed (Fig. and Supplementary Fig. ). If axial chromatic aberration correction was necessary, it was performed as described in Leiwe et al. . b Neurite detection with Neurolucida 360 (MBF Biosciences). Fluorescence images were loaded into Neurolucida 360, to automatically detect neurites using the directional kernels method. However, mistracing frequently occurred in densely labelled images, especially at branch and crossing points. Therefore, detected neurites are split into fragments at branch and crossing points (right). Note that somata were excluded in this step, as they are too bright, and their signals are beyond the linear range. Our QDyeFinder pipeline supports <t>data</t> in.swc format, which is commonly used for neurite reconstruction. To use <t>Imaris</t> <t>Filament</t> <t>Tracer</t> (Oxford Instrument) for automated neurite fragments, see Supplementary Note . c Once the fragments have been detected, the relevant voxels are identified, and the mean pixel intensity is calculated for each channel. After quality control (Supplementary Fig. ), fragments are represented in vector normalised space (colour vectors). d Colour vectors for the fragments are then clustered based on Th(d) with our clustering algorithm dCrawler (left and middle). Individual clusters can then be plotted to identify neurons from individual fragments (right).
Tracer Data, supplied by Meso Scale Diagnostics LLC, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/tracer+data/pm35182978-66-2-5?v=Meso+Scale+Diagnostics+LLC
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tracer data - by Bioz Stars, 2026-07
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mass spec data for lad (m6a-tracer +dd-dam-hcdt-lmnb1) bioid  (Biosite Inc)
90
Biosite Inc mass spec data for lad (m6a-tracer +dd-dam-hcdt-lmnb1) bioid
MeCP2 interacts with both LADs and lamin proteins (Zone2, interface between LADs and lamina). (A) Log 2 ratio plots from MEFs (mm9 build) chr 12 <t>of</t> <t>LmnB1</t> DamID (black), our LaminA (blue) and Lap2β DamID (green) ( Preprint ). (B) Venn diagram showing degree of overlap in percentage between Lamin A and Lap2β lamina associated domains (LADs). (C) Log 2 ratio plots from human fibroblasts (hg19 build) chr 8 of MeCP2 occupancy (ChIP) in red, LmnB1 DamID in black ( , ). (D) Venn diagrams showing the percentage (in terms of base coverage) of MeCP2 domains within LADs and the percentage (in base coverage) of LADs that are bound by MeCP2. (E) MeCP2 profile anchored at all boundaries of LADs of size 100 kb or greater and oriented from outside <t>LAD</t> (left) to inside LAD (right). Line graphs represent the average trend across all boundary profiles.
Mass Spec Data For Lad (M6a Tracer +Dd Dam Hcdt Lmnb1) Bioid, supplied by Biosite Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/tracer+data/pmc08008952-150-1-0?v=Biosite+Inc
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mass spec data for lad (m6a-tracer +dd-dam-hcdt-lmnb1) bioid - by Bioz Stars, 2026-07
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Image Search Results


a Image processing. Firstly, the images were non-linearly corrected (Supplementary Fig. ), then the images were linearly unmixed (Fig. and Supplementary Fig. ). If axial chromatic aberration correction was necessary, it was performed as described in Leiwe et al. . b Neurite detection with Neurolucida 360 (MBF Biosciences). Fluorescence images were loaded into Neurolucida 360, to automatically detect neurites using the directional kernels method. However, mistracing frequently occurred in densely labelled images, especially at branch and crossing points. Therefore, detected neurites are split into fragments at branch and crossing points (right). Note that somata were excluded in this step, as they are too bright, and their signals are beyond the linear range. Our QDyeFinder pipeline supports data in.swc format, which is commonly used for neurite reconstruction. To use Imaris Filament Tracer (Oxford Instrument) for automated neurite fragments, see Supplementary Note . c Once the fragments have been detected, the relevant voxels are identified, and the mean pixel intensity is calculated for each channel. After quality control (Supplementary Fig. ), fragments are represented in vector normalised space (colour vectors). d Colour vectors for the fragments are then clustered based on Th(d) with our clustering algorithm dCrawler (left and middle). Individual clusters can then be plotted to identify neurons from individual fragments (right).

Journal: Nature Communications

Article Title: Automated neuronal reconstruction with super-multicolour Tetbow labelling and threshold-based clustering of colour hues

doi: 10.1038/s41467-024-49455-y

Figure Lengend Snippet: a Image processing. Firstly, the images were non-linearly corrected (Supplementary Fig. ), then the images were linearly unmixed (Fig. and Supplementary Fig. ). If axial chromatic aberration correction was necessary, it was performed as described in Leiwe et al. . b Neurite detection with Neurolucida 360 (MBF Biosciences). Fluorescence images were loaded into Neurolucida 360, to automatically detect neurites using the directional kernels method. However, mistracing frequently occurred in densely labelled images, especially at branch and crossing points. Therefore, detected neurites are split into fragments at branch and crossing points (right). Note that somata were excluded in this step, as they are too bright, and their signals are beyond the linear range. Our QDyeFinder pipeline supports data in.swc format, which is commonly used for neurite reconstruction. To use Imaris Filament Tracer (Oxford Instrument) for automated neurite fragments, see Supplementary Note . c Once the fragments have been detected, the relevant voxels are identified, and the mean pixel intensity is calculated for each channel. After quality control (Supplementary Fig. ), fragments are represented in vector normalised space (colour vectors). d Colour vectors for the fragments are then clustered based on Th(d) with our clustering algorithm dCrawler (left and middle). Individual clusters can then be plotted to identify neurons from individual fragments (right).

Article Snippet: SWC exporter for Imaris Filament Tracer data written in Phython is available at GitHub ( https://github.com/Elsword016/Swc-plugins-for-Imaris-10 , 10.5281/zenodo.11232963).

Techniques: Fluorescence, Control, Plasmid Preparation

MeCP2 interacts with both LADs and lamin proteins (Zone2, interface between LADs and lamina). (A) Log 2 ratio plots from MEFs (mm9 build) chr 12 of LmnB1 DamID (black), our LaminA (blue) and Lap2β DamID (green) ( Preprint ). (B) Venn diagram showing degree of overlap in percentage between Lamin A and Lap2β lamina associated domains (LADs). (C) Log 2 ratio plots from human fibroblasts (hg19 build) chr 8 of MeCP2 occupancy (ChIP) in red, LmnB1 DamID in black ( , ). (D) Venn diagrams showing the percentage (in terms of base coverage) of MeCP2 domains within LADs and the percentage (in base coverage) of LADs that are bound by MeCP2. (E) MeCP2 profile anchored at all boundaries of LADs of size 100 kb or greater and oriented from outside LAD (left) to inside LAD (right). Line graphs represent the average trend across all boundary profiles.

Journal: Life Science Alliance

Article Title: Mapping the micro-proteome of the nuclear lamina and lamina-associated domains

doi: 10.26508/lsa.202000774

Figure Lengend Snippet: MeCP2 interacts with both LADs and lamin proteins (Zone2, interface between LADs and lamina). (A) Log 2 ratio plots from MEFs (mm9 build) chr 12 of LmnB1 DamID (black), our LaminA (blue) and Lap2β DamID (green) ( Preprint ). (B) Venn diagram showing degree of overlap in percentage between Lamin A and Lap2β lamina associated domains (LADs). (C) Log 2 ratio plots from human fibroblasts (hg19 build) chr 8 of MeCP2 occupancy (ChIP) in red, LmnB1 DamID in black ( , ). (D) Venn diagrams showing the percentage (in terms of base coverage) of MeCP2 domains within LADs and the percentage (in base coverage) of LADs that are bound by MeCP2. (E) MeCP2 profile anchored at all boundaries of LADs of size 100 kb or greater and oriented from outside LAD (left) to inside LAD (right). Line graphs represent the average trend across all boundary profiles.

Article Snippet: BioSIte mass spec data for LAD (m6A-tracer +DD-Dam-hCdt-LMNB1) BioID.

Techniques:

(A) Plot of replicate runs of MS1 level quantitation ratios of mass spectrometry identities of BirA*-m6A-tracer/DD-Dam-LMNB1 plus shield over minus shield ligand. (B) Gene set enrichment analysis of m6A-tracer BioID LAD proteome. (C) Integrative venn diagram of published nuclear lamina proteomic analyses, our current LAP2β BioID interactome analysis and the LAD-ome analysis. Proteins marked * have been validated by various groups, including ours. The experiments and results are summarized in . Proteins marked ** have been bioinformatically validated in-house. Note: not all proteins in these overlaps are shown for display purposes. Please see Table S3 for a full list of proteins. Data from C57BL/6 3T3-derived WT MEFs.

Journal: Life Science Alliance

Article Title: Mapping the micro-proteome of the nuclear lamina and lamina-associated domains

doi: 10.26508/lsa.202000774

Figure Lengend Snippet: (A) Plot of replicate runs of MS1 level quantitation ratios of mass spectrometry identities of BirA*-m6A-tracer/DD-Dam-LMNB1 plus shield over minus shield ligand. (B) Gene set enrichment analysis of m6A-tracer BioID LAD proteome. (C) Integrative venn diagram of published nuclear lamina proteomic analyses, our current LAP2β BioID interactome analysis and the LAD-ome analysis. Proteins marked * have been validated by various groups, including ours. The experiments and results are summarized in . Proteins marked ** have been bioinformatically validated in-house. Note: not all proteins in these overlaps are shown for display purposes. Please see Table S3 for a full list of proteins. Data from C57BL/6 3T3-derived WT MEFs.

Article Snippet: BioSIte mass spec data for LAD (m6A-tracer +DD-Dam-hCdt-LMNB1) BioID.

Techniques: Quantitation Assay, Mass Spectrometry, Derivative Assay

Table detailing experiments and results from published work directly validating protein hits from our BioID study.

Journal: Life Science Alliance

Article Title: Mapping the micro-proteome of the nuclear lamina and lamina-associated domains

doi: 10.26508/lsa.202000774

Figure Lengend Snippet: Table detailing experiments and results from published work directly validating protein hits from our BioID study.

Article Snippet: BioSIte mass spec data for LAD (m6A-tracer +DD-Dam-hCdt-LMNB1) BioID.

Techniques: Functional Assay, Double Knockout, Expressing, Knockdown, Immunofluorescence, Electron Microscopy, Knock-Out, Fractionation, Fluorescence, Binding Assay, Mutagenesis, Inhibition, Control, Over Expression

Nup153 interacts with lamins, but not LADs (Zone 1). (A) Log 2 ratio plots from human fibroblasts (hg19 build) chr 8 of LmnB1 DamID (blue) and Nup153 DamID peaks in green ( , ). (B) Inset shows a magnified view of a lamina-associated domain (LAD) that appears to be highly dense with Nup153 binding sites. (C) Venn diagram showing the percentage (in base coverage) of Nup153 distribution relative to LADs. (D) LmnB1 profile anchored at all LAD-Nup153 peaks (the 13.7% that are found within LADs) centers. Line graphs represent the average trend across all such Nup153 peaks.

Journal: Life Science Alliance

Article Title: Mapping the micro-proteome of the nuclear lamina and lamina-associated domains

doi: 10.26508/lsa.202000774

Figure Lengend Snippet: Nup153 interacts with lamins, but not LADs (Zone 1). (A) Log 2 ratio plots from human fibroblasts (hg19 build) chr 8 of LmnB1 DamID (blue) and Nup153 DamID peaks in green ( , ). (B) Inset shows a magnified view of a lamina-associated domain (LAD) that appears to be highly dense with Nup153 binding sites. (C) Venn diagram showing the percentage (in base coverage) of Nup153 distribution relative to LADs. (D) LmnB1 profile anchored at all LAD-Nup153 peaks (the 13.7% that are found within LADs) centers. Line graphs represent the average trend across all such Nup153 peaks.

Article Snippet: BioSIte mass spec data for LAD (m6A-tracer +DD-Dam-hCdt-LMNB1) BioID.

Techniques: Binding Assay