{"EMPIAR-11370":{"imagesets":[{"segmentations":[],"name":"Unaligned tilt series of mouse embrionic fibroblasts with mitochondrial targeted GFP treated with vehicle or thapsigargin","directory":"data/Tilt_Series","category":"tilt series","header_format":"MRC","data_format":"MRC","num_images_or_tilt_series":34,"frames_per_image":10,"frame_range_min":null,"frame_range_max":null,"voxel_type":"UNSIGNED 16 BIT INTEGER","pixel_width":null,"pixel_height":null,"micrographs_file_pattern":"","picked_particles_file_pattern":"","picked_particles_directory":"","details":"Single tilt axis tilt series. Tilt range is variable. For tilt series where frames were acquired the number of frames is 10 and the motioncorrected tilt series is given. Tilt series are from multiple data sets and have either a pixel spacing of 3.345 or 3.11, please refer to associated .mdoc file.","image_width":"3710","image_height":"3838"},{"segmentations":[{"file":"data/Voxel_Segmentations","description":"The voxel segmentations from AMIRA of membranes from mitochondria and ER in mouse embrionic fibroblasts treated with vehicle or thapsigargin","original_files":null,"original_format":"REC","entry":null},{"file":"data/Membrane_surface_mesh","description":"Polygon Surface meshes generated from voxel segmentations using 'Surface_Morphometrics' for all membranes from mitochondria and ER.","original_files":null,"original_format":"STL","entry":null}],"name":"Reconstructed tomograms used for segmentation of mitochondria and endoplasmic reticulum membranes","directory":"data/Tomograms","category":"reconstructed volumes","header_format":"MRC","data_format":"MRC","num_images_or_tilt_series":34,"frames_per_image":1,"frame_range_min":null,"frame_range_max":null,"voxel_type":"UNSIGNED 16 BIT INTEGER","pixel_width":null,"pixel_height":null,"micrographs_file_pattern":"","picked_particles_file_pattern":"","picked_particles_directory":"","details":"Bin 4 reconstructed volumes from tilt series.","image_width":"960","image_height":"928"}],"workflow_file":null,"grant_references":[],"version_history":[],"title":"A surface morphometrics toolkit to quantify organellar membrane ultrastructure using cryo-electron tomography","principal_investigator":[{"author_orcid":"0000-0001-6346-5137","middle_name":null,"organization":"Department of Integrative Structural and Computational Biology, The Scripps Research Institute","street":"10550 N Torrey Pines Rd","town_or_city":"La Jolla","state_or_province":"California","post_or_zip":"92037","telephone":"(858) 784-8761","fax":null,"first_name":"Michaela","last_name":"Medina","email":"mmedina300kv [at] gmail.com","country":"United States","entry":"EMPIAR-11370"}],"status":"REL","deposition_date":"2023-01-06","release_date":"2023-02-10","obsolete_date":null,"update_date":"2023-02-10","corresponding_author":{"author":{"author_orcid":"0000-0001-6346-5137","middle_name":null,"organization":"Department of Integrative Structural and Computational Biology, The Scripps Research Institute","street":"10550 N Torrey Pines Rd","town_or_city":"La Jolla","state_or_province":"California","post_or_zip":"92037","first_name":"Michaela","last_name":"Medina","country":"United States"}},"authors":[{"author":{"name":"Barad BA","author_orcid":"0000-0002-1016-862X"}},{"author":{"name":"Medina M","author_orcid":"0000-0001-6346-5137"}},{"author":{"name":"Fuentes D","author_orcid":"0000-0002-9687-0902"}},{"author":{"name":"Wiseman RL","author_orcid":"0000-0001-9287-6840"}},{"author":{"name":"Grotjahn DA","author_orcid":"0000-0001-5908-7882"}}],"cross_references":[],"biostudies_references":[],"idr_references":[],"empiar_references":[],"citation":[{"authors":[{"name":"Barad BA","author_orcid":"0000-0002-1016-862X"},{"name":"Medina M","author_orcid":"0000-0001-6346-5137"},{"name":"Fuentes D","author_orcid":"0000-0002-9687-0902"},{"name":"Wiseman RL","author_orcid":"0000-0001-9287-6840"},{"name":"Grotjahn DA","author_orcid":"0000-0001-5908-7882"}],"editors":[],"published":true,"j_or_nj_citation":true,"title":"A surface morphometrics toolkit to quantify organellar membrane ultrastructure using cryo-electron tomography","volume":null,"country":"","first_page":null,"last_page":null,"year":"2022","language":null,"doi":"10.1101/2022.01.23.477440","pubmedid":null,"details":null,"book_chapter_title":null,"publisher":null,"publication_location":null,"journal":"bioRxiv","journal_abbreviation":"","issue":null,"preprint":true}],"dataset_size":"126.9 GB","experiment_type":"Exception","scale":"cell","entry_doi":"10.6019/EMPIAR-11370"}}