cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.13145/bacdive127114.20241212.9.2
title: Streptomyces abikoensis

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive127114.20251217.10
title: Streptomyces abikoensis

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive127115.20241212.9.2
title: Streptomyces abikoensis

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive127115.20251217.10
title: Streptomyces abikoensis

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive127116.20241212.9.2
title: Streptomyces abikoensis

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive127116.20251217.10
title: Streptomyces abikoensis

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive127117.20241212.9.2
title: Streptomyces abikoensis

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.13145/bacdive127117.20251217.10
title: Streptomyces abikoensis

description: The range of data encompasses taxonomy, morphology, physiology, sampling and concomitant environmental conditions as well as molecular biology.
DOI: 10.15468/dl.b2w3s9
title: Occurrence Download

description: A dataset containing 1099 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Lepus callotis"
 ]
}

 The dataset includes 1099 records from 49 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0061498-250920141307145/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.kvb5pa
title: Occurrence Download

description: A dataset containing 15754 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Yucca brevifolia Engelm."
 ]
}

 The dataset includes 15754 records from 112 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0042198-241126133413365/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.25378/janelia.24260977
title: Manual organelle segmentations (crop292) in near-isotropic, reconstructed volume electron microscopy (FIB-SEM) of interphase COS-7 cell (jrc_cos7-1a)

description: <b>This acquisition is part of the CellMap 2024 Segmentation Challenge</b><b>Challenge DOI:</b> https://doi.org/10.25378/janelia.c.7456966<b>Challenge Website:</b> https://cellmapchallenge.janelia.org/<b>Annotation description</b>: Dense segmentations of mitochondrial membrane, mitochondrial lumen, endosome membrane, endoplasmic reticulum lumen, endoplasmic reticulum membrane, endosome lumen, heterochromatin, nuclear pore in, nuclear pore out, nuclear envelope lumen, nuclear envelope membrane, nucleoplasm, cytosol, nucleus, endosome, mitochondria, endoplasmic reticulum, nuclear envelope, nuclear pore, chromatin, cell, endoplasmic reticulum membrane collective, nuclear envelope membrane collective in jrc_cos7-1a using Amira 3D 2021.1, Classic Segmentation Workroom and the 'Using Amira to manually segment organelles in vEM for machine learning V.3' annotation protocol.<b>Annotation ID</b>: crop292<b>Primary Annotator</b>: Woohyun Park<b>Annotation protocol</b>: Using Amira to manually segment organelles in vEM for machine learning V.3 (http://dx.doi.org/10.17504/protocols.io.bp2l61rb5vqe/v3)<b>Software</b>: Amira 3D 2021.1, Classic Segmentation Workroom<b>Annotated voxel size (nm)</b>: 2 x 2 x 2 (x, y, z)<b>Annotated data dimensions (µm)</b>: 0.8 x 0.8 x 0.8 (x, y, z)<b>Annotated data offset (nm)</b>: 6702 x 5282 x 862 (x, y, z)<b>Classes annotated</b>: mitochondrial membrane, mitochondrial lumen, endosome membrane, endoplasmic reticulum lumen, endoplasmic reticulum membrane, endosome lumen, heterochromatin, nuclear pore in, nuclear pore out, nuclear envelope lumen, nuclear envelope membrane, nucleoplasm, cytosol, nucleus, endosome, mitochondria, endoplasmic reticulum, nuclear envelope, nuclear pore, chromatin, cell, endoplasmic reticulum membrane collective, nuclear envelope membrane collective<b>Dataset URL</b>: s3://janelia-cosem-datasets/jrc_cos7-1a/jrc_cos7-1a.zarr/recon-1/labels/groundtruth/crop292<b>Source (EM) dataset ID</b>: jrc_cos7-1a<b>Source (EM) voxel size (nm)</b>: 2 x 2 x 2 (x, y, z)<b>Source (EM) data dimensions (µm)</b>: 41.22 x 8.74 x 3.63 (x, y, z)<b>Source (EM) DOI</b>: https://doi.org/10.25378/janelia.24943716<b>Visualization website</b>: https://openorganelle.janelia.org/datasets/jrc_cos7-1a<b>Publication:</b> <i>CellMap Segmentation Challenge,</i> 2024.<b>The CellMap Project Team during this time consisted of:</b> David Ackerman, Davis Bennett, Marley Bryant, Hannah Nguyen, Grace Park, Alyson Petruncio, Alannah Post, Jacquelyn Price, Diana Ramirez, Jeff Rhoades, Rebecca Vorimo, Aubrey Weigel, Marwan Zouinkhi, Yurii Zubov.<b>The CellMap Project Team Steering Committee during this time consisted of:</b> Misha Ahrens, Christopher Beck, Teng-Leong Chew, Daniel Feliciano, Jan Funke, Harald Hess, Wyatt Korff, Jennifer Lippincott-Schwartz, Zhe J. Liu, Kayvon Pedram, Stephan Preibisch, Stephan Saalfeld, Ronald Vale, and Aubrey Weigel.
DOI: 10.25378/janelia.24260977.v1
title: Manual organelle segmentations (crop292) in near-isotropic, reconstructed volume electron microscopy (FIB-SEM) of interphase COS-7 cell (jrc_cos7-1a)

description: <b>This acquisition is part of the CellMap 2024 Segmentation Challenge</b><b>Challenge DOI:</b> https://doi.org/10.25378/janelia.c.7456966<b>Challenge Website:</b> https://cellmapchallenge.janelia.org/<b>Annotation description</b>: Dense segmentations of mitochondrial membrane, mitochondrial lumen, endosome membrane, endoplasmic reticulum lumen, endoplasmic reticulum membrane, endosome lumen, heterochromatin, nuclear pore in, nuclear pore out, nuclear envelope lumen, nuclear envelope membrane, nucleoplasm, cytosol, nucleus, endosome, mitochondria, endoplasmic reticulum, nuclear envelope, nuclear pore, chromatin, cell, endoplasmic reticulum membrane collective, nuclear envelope membrane collective in jrc_cos7-1a using Amira 3D 2021.1, Classic Segmentation Workroom and the 'Using Amira to manually segment organelles in vEM for machine learning V.3' annotation protocol.<b>Annotation ID</b>: crop292<b>Primary Annotator</b>: Woohyun Park<b>Annotation protocol</b>: Using Amira to manually segment organelles in vEM for machine learning V.3 (http://dx.doi.org/10.17504/protocols.io.bp2l61rb5vqe/v3)<b>Software</b>: Amira 3D 2021.1, Classic Segmentation Workroom<b>Annotated voxel size (nm)</b>: 2 x 2 x 2 (x, y, z)<b>Annotated data dimensions (µm)</b>: 0.8 x 0.8 x 0.8 (x, y, z)<b>Annotated data offset (nm)</b>: 6702 x 5282 x 862 (x, y, z)<b>Classes annotated</b>: mitochondrial membrane, mitochondrial lumen, endosome membrane, endoplasmic reticulum lumen, endoplasmic reticulum membrane, endosome lumen, heterochromatin, nuclear pore in, nuclear pore out, nuclear envelope lumen, nuclear envelope membrane, nucleoplasm, cytosol, nucleus, endosome, mitochondria, endoplasmic reticulum, nuclear envelope, nuclear pore, chromatin, cell, endoplasmic reticulum membrane collective, nuclear envelope membrane collective<b>Dataset URL</b>: s3://janelia-cosem-datasets/jrc_cos7-1a/jrc_cos7-1a.zarr/recon-1/labels/groundtruth/crop292<b>Source (EM) dataset ID</b>: jrc_cos7-1a<b>Source (EM) voxel size (nm)</b>: 2 x 2 x 2 (x, y, z)<b>Source (EM) data dimensions (µm)</b>: 41.22 x 8.74 x 3.63 (x, y, z)<b>Source (EM) DOI</b>: https://doi.org/10.25378/janelia.24943716<b>Visualization website</b>: https://openorganelle.janelia.org/datasets/jrc_cos7-1a<b>Publication:</b> <i>CellMap Segmentation Challenge,</i> 2024.<b>The CellMap Project Team during this time consisted of:</b> David Ackerman, Davis Bennett, Marley Bryant, Hannah Nguyen, Grace Park, Alyson Petruncio, Alannah Post, Jacquelyn Price, Diana Ramirez, Jeff Rhoades, Rebecca Vorimo, Aubrey Weigel, Marwan Zouinkhi, Yurii Zubov.<b>The CellMap Project Team Steering Committee during this time consisted of:</b> Misha Ahrens, Christopher Beck, Teng-Leong Chew, Daniel Feliciano, Jan Funke, Harald Hess, Wyatt Korff, Jennifer Lippincott-Schwartz, Zhe J. Liu, Kayvon Pedram, Stephan Preibisch, Stephan Saalfeld, Ronald Vale, and Aubrey Weigel.
DOI: 10.25378/janelia.24256204
title: Manual organelle segmentations (crop257) in near-isotropic, reconstructed volume electron microscopy (FIB-SEM) of interphase COS-7 cell (jrc_cos7-1a)

description: <b>This acquisition is part of the CellMap 2024 Segmentation Challenge</b><b>Challenge DOI:</b> https://doi.org/10.25378/janelia.c.7456966<b>Challenge Website:</b> https://cellmapchallenge.janelia.org/<b>Annotation description</b>: Dense segmentations of nucleus in jrc_cos7-1a using Amira 3D 2021.1, Classic Segmentation Workroom and the 'Using Amira to manually segment organelles in vEM for machine learning V.3' annotation protocol.<b>Annotation ID</b>: crop257<b>Primary Annotator</b>: Alyson Petruncio<b>Annotation protocol</b>: Using Amira to manually segment organelles in vEM for machine learning V.3 (http://dx.doi.org/10.17504/protocols.io.bp2l61rb5vqe/v3)<b>Software</b>: Amira 3D 2021.1, Classic Segmentation Workroom<b>Annotated voxel size (nm)</b>: 8 x 8 x 8 (x, y, z)<b>Annotated data dimensions (µm)</b>: 8.8 x 4.8 x 3.6 (x, y, z)<b>Annotated data offset (nm)</b>: 803 x 2403 x 3 (x, y, z)<b>Classes annotated</b>: nucleus<b>Dataset URL</b>: s3://janelia-cosem-datasets/jrc_cos7-1a/jrc_cos7-1a.zarr/recon-1/labels/groundtruth/crop257<b>Source (EM) dataset ID</b>: jrc_cos7-1a<b>Source (EM) voxel size (nm)</b>: 2 x 2 x 2 (x, y, z)<b>Source (EM) data dimensions (µm)</b>: 41.22 x 8.74 x 3.63 (x, y, z)<b>Source (EM) DOI</b>: https://doi.org/10.25378/janelia.24943716<b>Visualization website</b>: https://openorganelle.janelia.org/datasets/jrc_cos7-1a<b>Publication:</b> <i>CellMap Segmentation Challenge,</i> 2024.<b>The CellMap Project Team during this time consisted of:</b> David Ackerman, Davis Bennett, Marley Bryant, Hannah Nguyen, Grace Park, Alyson Petruncio, Alannah Post, Jacquelyn Price, Diana Ramirez, Jeff Rhoades, Rebecca Vorimo, Aubrey Weigel, Marwan Zouinkhi, Yurii Zubov.<b>The CellMap Project Team Steering Committee during this time consisted of:</b> Misha Ahrens, Christopher Beck, Teng-Leong Chew, Daniel Feliciano, Jan Funke, Harald Hess, Wyatt Korff, Jennifer Lippincott-Schwartz, Zhe J. Liu, Kayvon Pedram, Stephan Preibisch, Stephan Saalfeld, Ronald Vale, and Aubrey Weigel.
DOI: 10.25378/janelia.24256204.v1
title: Manual organelle segmentations (crop257) in near-isotropic, reconstructed volume electron microscopy (FIB-SEM) of interphase COS-7 cell (jrc_cos7-1a)

description: <b>This acquisition is part of the CellMap 2024 Segmentation Challenge</b><b>Challenge DOI:</b> https://doi.org/10.25378/janelia.c.7456966<b>Challenge Website:</b> https://cellmapchallenge.janelia.org/<b>Annotation description</b>: Dense segmentations of nucleus in jrc_cos7-1a using Amira 3D 2021.1, Classic Segmentation Workroom and the 'Using Amira to manually segment organelles in vEM for machine learning V.3' annotation protocol.<b>Annotation ID</b>: crop257<b>Primary Annotator</b>: Alyson Petruncio<b>Annotation protocol</b>: Using Amira to manually segment organelles in vEM for machine learning V.3 (http://dx.doi.org/10.17504/protocols.io.bp2l61rb5vqe/v3)<b>Software</b>: Amira 3D 2021.1, Classic Segmentation Workroom<b>Annotated voxel size (nm)</b>: 8 x 8 x 8 (x, y, z)<b>Annotated data dimensions (µm)</b>: 8.8 x 4.8 x 3.6 (x, y, z)<b>Annotated data offset (nm)</b>: 803 x 2403 x 3 (x, y, z)<b>Classes annotated</b>: nucleus<b>Dataset URL</b>: s3://janelia-cosem-datasets/jrc_cos7-1a/jrc_cos7-1a.zarr/recon-1/labels/groundtruth/crop257<b>Source (EM) dataset ID</b>: jrc_cos7-1a<b>Source (EM) voxel size (nm)</b>: 2 x 2 x 2 (x, y, z)<b>Source (EM) data dimensions (µm)</b>: 41.22 x 8.74 x 3.63 (x, y, z)<b>Source (EM) DOI</b>: https://doi.org/10.25378/janelia.24943716<b>Visualization website</b>: https://openorganelle.janelia.org/datasets/jrc_cos7-1a<b>Publication:</b> <i>CellMap Segmentation Challenge,</i> 2024.<b>The CellMap Project Team during this time consisted of:</b> David Ackerman, Davis Bennett, Marley Bryant, Hannah Nguyen, Grace Park, Alyson Petruncio, Alannah Post, Jacquelyn Price, Diana Ramirez, Jeff Rhoades, Rebecca Vorimo, Aubrey Weigel, Marwan Zouinkhi, Yurii Zubov.<b>The CellMap Project Team Steering Committee during this time consisted of:</b> Misha Ahrens, Christopher Beck, Teng-Leong Chew, Daniel Feliciano, Jan Funke, Harald Hess, Wyatt Korff, Jennifer Lippincott-Schwartz, Zhe J. Liu, Kayvon Pedram, Stephan Preibisch, Stephan Saalfeld, Ronald Vale, and Aubrey Weigel.
DOI: 10.6084/m9.figshare.28063481
title: <b>The Genetic Link Between ACTN3 Variations and Physical Performance in Resistance Training Practitioners</b>

description: This study aimed to investigate the relationship between <i>ACTN3</i> polymorphisms and key physical performance parameters, including phase angle, one-repetition maximum (1RM) for bench press and back squat, and relative strength, in Brazilian strength training practitioners. 72 strength training practitioners (49 men, 23 women) and 450 age-matched male non-athletes were included in this study. Genomic DNA was extracted from buccal cells, and the <i>ACTN3</i> polymorphism (rs1815739) was genotyped using qPCR. Anthropometric measurements, phase angle (via bioimpedance analysis), and 1RM for bench press and back squat were assessed. Genotype and allelic frequencies were compared using Chi-square tests, and performance metrics were analyzed across genotypes using ANOVA and t-tests.
DOI: 10.6084/m9.figshare.28063481.v1
title: <b>The Genetic Link Between ACTN3 Variations and Physical Performance in Resistance Training Practitioners</b>

description: This study aimed to investigate the relationship between <i>ACTN3</i> polymorphisms and key physical performance parameters, including phase angle, one-repetition maximum (1RM) for bench press and back squat, and relative strength, in Brazilian strength training practitioners. 72 strength training practitioners (49 men, 23 women) and 450 age-matched male non-athletes were included in this study. Genomic DNA was extracted from buccal cells, and the <i>ACTN3</i> polymorphism (rs1815739) was genotyped using qPCR. Anthropometric measurements, phase angle (via bioimpedance analysis), and 1RM for bench press and back squat were assessed. Genotype and allelic frequencies were compared using Chi-square tests, and performance metrics were analyzed across genotypes using ANOVA and t-tests.
DOI: 10.25378/janelia.24256201
title: Manual organelle segmentations (crop256) in near-isotropic, reconstructed volume electron microscopy (FIB-SEM) of interphase COS-7 cell (jrc_cos7-1a)

description: <b>This acquisition is part of the CellMap 2024 Segmentation Challenge</b><b>Challenge DOI:</b> https://doi.org/10.25378/janelia.c.7456966<b>Challenge Website:</b> https://cellmapchallenge.janelia.org/<b>Annotation description</b>: Dense segmentations of mitochondrial membrane, mitochondrial lumen, vesicle membrane, vesicle lumen, mitochondrial ribosome, endoplasmic reticulum lumen, endoplasmic reticulum membrane, microtubule out, microtubule in, cytosol, vesicle, mitochondria, endoplasmic reticulum, microtubule, cell, endoplasmic reticulum membrane collective in jrc_cos7-1a using Amira 3D 2021.1, Classic Segmentation Workroom and the 'Using Amira to manually segment organelles in vEM for machine learning V.3' annotation protocol.<b>Annotation ID</b>: crop256<b>Primary Annotator</b>: Diana Ramirez<b>Annotation protocol</b>: Using Amira to manually segment organelles in vEM for machine learning V.3 (http://dx.doi.org/10.17504/protocols.io.bp2l61rb5vqe/v3)<b>Software</b>: Amira 3D 2021.1, Classic Segmentation Workroom<b>Annotated voxel size (nm)</b>: 2 x 2 x 2 (x, y, z)<b>Annotated data dimensions (µm)</b>: 0.8 x 0.8 x 0.8 (x, y, z)<b>Annotated data offset (nm)</b>: 8574 x 6158 x 1582 (x, y, z)<b>Classes annotated</b>: mitochondrial membrane, mitochondrial lumen, vesicle membrane, vesicle lumen, mitochondrial ribosome, endoplasmic reticulum lumen, endoplasmic reticulum membrane, microtubule out, microtubule in, cytosol, vesicle, mitochondria, endoplasmic reticulum, microtubule, cell, endoplasmic reticulum membrane collective<b>Dataset URL</b>: s3://janelia-cosem-datasets/jrc_cos7-1a/jrc_cos7-1a.zarr/recon-1/labels/groundtruth/crop256<b>Source (EM) dataset ID</b>: jrc_cos7-1a<b>Source (EM) voxel size (nm)</b>: 2 x 2 x 2 (x, y, z)<b>Source (EM) data dimensions (µm)</b>: 41.22 x 8.74 x 3.63 (x, y, z)<b>Source (EM) DOI</b>: https://doi.org/10.25378/janelia.24943716<b>Visualization website</b>: https://openorganelle.janelia.org/datasets/jrc_cos7-1a<b>Publication:</b> <i>CellMap Segmentation Challenge,</i> 2024.<b>The CellMap Project Team during this time consisted of:</b> David Ackerman, Davis Bennett, Marley Bryant, Hannah Nguyen, Grace Park, Alyson Petruncio, Alannah Post, Jacquelyn Price, Diana Ramirez, Jeff Rhoades, Rebecca Vorimo, Aubrey Weigel, Marwan Zouinkhi, Yurii Zubov.<b>The CellMap Project Team Steering Committee during this time consisted of:</b> Misha Ahrens, Christopher Beck, Teng-Leong Chew, Daniel Feliciano, Jan Funke, Harald Hess, Wyatt Korff, Jennifer Lippincott-Schwartz, Zhe J. Liu, Kayvon Pedram, Stephan Preibisch, Stephan Saalfeld, Ronald Vale, and Aubrey Weigel.
DOI: 10.25378/janelia.24256201.v1
title: Manual organelle segmentations (crop256) in near-isotropic, reconstructed volume electron microscopy (FIB-SEM) of interphase COS-7 cell (jrc_cos7-1a)

description: <b>This acquisition is part of the CellMap 2024 Segmentation Challenge</b><b>Challenge DOI:</b> https://doi.org/10.25378/janelia.c.7456966<b>Challenge Website:</b> https://cellmapchallenge.janelia.org/<b>Annotation description</b>: Dense segmentations of mitochondrial membrane, mitochondrial lumen, vesicle membrane, vesicle lumen, mitochondrial ribosome, endoplasmic reticulum lumen, endoplasmic reticulum membrane, microtubule out, microtubule in, cytosol, vesicle, mitochondria, endoplasmic reticulum, microtubule, cell, endoplasmic reticulum membrane collective in jrc_cos7-1a using Amira 3D 2021.1, Classic Segmentation Workroom and the 'Using Amira to manually segment organelles in vEM for machine learning V.3' annotation protocol.<b>Annotation ID</b>: crop256<b>Primary Annotator</b>: Diana Ramirez<b>Annotation protocol</b>: Using Amira to manually segment organelles in vEM for machine learning V.3 (http://dx.doi.org/10.17504/protocols.io.bp2l61rb5vqe/v3)<b>Software</b>: Amira 3D 2021.1, Classic Segmentation Workroom<b>Annotated voxel size (nm)</b>: 2 x 2 x 2 (x, y, z)<b>Annotated data dimensions (µm)</b>: 0.8 x 0.8 x 0.8 (x, y, z)<b>Annotated data offset (nm)</b>: 8574 x 6158 x 1582 (x, y, z)<b>Classes annotated</b>: mitochondrial membrane, mitochondrial lumen, vesicle membrane, vesicle lumen, mitochondrial ribosome, endoplasmic reticulum lumen, endoplasmic reticulum membrane, microtubule out, microtubule in, cytosol, vesicle, mitochondria, endoplasmic reticulum, microtubule, cell, endoplasmic reticulum membrane collective<b>Dataset URL</b>: s3://janelia-cosem-datasets/jrc_cos7-1a/jrc_cos7-1a.zarr/recon-1/labels/groundtruth/crop256<b>Source (EM) dataset ID</b>: jrc_cos7-1a<b>Source (EM) voxel size (nm)</b>: 2 x 2 x 2 (x, y, z)<b>Source (EM) data dimensions (µm)</b>: 41.22 x 8.74 x 3.63 (x, y, z)<b>Source (EM) DOI</b>: https://doi.org/10.25378/janelia.24943716<b>Visualization website</b>: https://openorganelle.janelia.org/datasets/jrc_cos7-1a<b>Publication:</b> <i>CellMap Segmentation Challenge,</i> 2024.<b>The CellMap Project Team during this time consisted of:</b> David Ackerman, Davis Bennett, Marley Bryant, Hannah Nguyen, Grace Park, Alyson Petruncio, Alannah Post, Jacquelyn Price, Diana Ramirez, Jeff Rhoades, Rebecca Vorimo, Aubrey Weigel, Marwan Zouinkhi, Yurii Zubov.<b>The CellMap Project Team Steering Committee during this time consisted of:</b> Misha Ahrens, Christopher Beck, Teng-Leong Chew, Daniel Feliciano, Jan Funke, Harald Hess, Wyatt Korff, Jennifer Lippincott-Schwartz, Zhe J. Liu, Kayvon Pedram, Stephan Preibisch, Stephan Saalfeld, Ronald Vale, and Aubrey Weigel.
DOI: 10.25378/janelia.24256165
title: Manual organelle segmentations (crop248) in near-isotropic, reconstructed volume electron microscopy (FIB-SEM) of Interphase COS-7 cell (jrc_cos7-1a)

description: <b>This acquisition is part of the CellMap 2024 Segmentation Challenge</b><b>Challenge DOI:</b> https://doi.org/10.25378/janelia.c.7456966<b>Challenge Website:</b> https://cellmapchallenge.janelia.org/<b>Annotation description</b>: Dense segmentations of extracellular space, plasma membrane, mitochondrial membrane, mitochondrial lumen, vesicle membrane, endosome membrane, vesicle lumen, mitochondrial ribosome, endoplasmic reticulum lumen, endoplasmic reticulum membrane, endosome lumen, microtubule out, microtubule in, cytosol, endosome, vesicle, mitochondria, endoplasmic reticulum, microtubule, cell, endoplasmic reticulum membrane collective in jrc_cos7-1a using Amira 3D 2021.1, Classic Segmentation Workroom and the 'Using Amira to manually segment organelles in vEM for machine learning V.3' annotation protocol.<b>Annotation ID</b>: crop248<b>Primary Annotator</b>: Woohyun Park<b>Annotation protocol</b>: Using Amira to manually segment organelles in vEM for machine learning V.3 (http://dx.doi.org/10.17504/protocols.io.bp2l61rb5vqe/v3)<b>Software</b>: Amira 3D 2021.1, Classic Segmentation Workroom<b>Annotated voxel size (nm)</b>: 2 x 2 x 2 (x, y, z)<b>Annotated data dimensions (µm)</b>: 0.8 x 0.8 x 0.8 (x, y, z)<b>Annotated data offset (nm)</b>: 7922 x 4300 x 90 (x, y, z)<b>Classes annotated</b>: extracellular space, plasma membrane, mitochondrial membrane, mitochondrial lumen, vesicle membrane, endosome membrane, vesicle lumen, mitochondrial ribosome, endoplasmic reticulum lumen, endoplasmic reticulum membrane, endosome lumen, microtubule out, microtubule in, cytosol, endosome, vesicle, mitochondria, endoplasmic reticulum, microtubule, cell, endoplasmic reticulum membrane collective<b>Dataset URL</b>: s3://janelia-cosem-datasets/jrc_cos7-1a/jrc_cos7-1a.zarr/recon-1/labels/groundtruth/crop248<b>Source (EM) dataset ID</b>: jrc_cos7-1a<b>Source (EM) voxel size (nm)</b>: 2 x 2 x 2 (x, y, z)<b>Source (EM) data dimensions (µm)</b>: 41.22 x 8.74 x 3.63 (x, y, z)<b>Source (EM) DOI</b>: https://doi.org/10.25378/janelia.24943716<b>Visualization website</b>: https://openorganelle.janelia.org/datasets/jrc_cos7-1a<b>Publication:</b> <i>CellMap Segmentation Challenge,</i> 2024.<b>The CellMap Project Team during this time consisted of:</b> David Ackerman, Davis Bennett, Marley Bryant, Hannah Nguyen, Grace Park, Alyson Petruncio, Alannah Post, Jacquelyn Price, Diana Ramirez, Jeff Rhoades, Rebecca Vorimo, Aubrey Weigel, Marwan Zouinkhi, Yurii Zubov.<b>The CellMap Project Team Steering Committee during this time consisted of:</b> Misha Ahrens, Christopher Beck, Teng-Leong Chew, Daniel Feliciano, Jan Funke, Harald Hess, Wyatt Korff, Jennifer Lippincott-Schwartz, Zhe J. Liu, Kayvon Pedram, Stephan Preibisch, Stephan Saalfeld, Ronald Vale, and Aubrey Weigel.