Published August 14, 2023 | Version v1.0
Dataset Open

NanoPyx - Figures' Data

  • 1. Instituto Gulbenkian de Ciência, Oeiras, Portugal
  • 2. Instituto Gulbenkian de Ciência, Oeiras, Portugal; Instituto Superior Técnico, Lisboa, Portugal
  • 3. Instituto Gulbenkian de Ciência, Oeiras, Portugal; Instituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa, Oeiras, Portugal
  • 4. Turku Bioscience Centre, University of Turku and Åbo Akademi University, Turku, Finland
  • 5. Instituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa, Oeiras, Portugal
  • 6. DFG Cluster of Excellence "Physics of Life", TU Dresden, Dresden Germany
  • 7. Turku Bioscience Centre, University of Turku and Åbo Akademi University, Turku, Finland; Turku Bioimaging, University of Turku and Åbo Akademi University, FI- 20520 Turku, FI; Faculty of Science and Engineering, Cell Biology, Åbo Akademi University, Turku, Finland; InFLAMES Research Flagship Center, Åbo Akademi University, FI- 20520, Turku, FI
  • 8. Instituto Gulbenkian de Ciência, Oeiras, Portugal; MRC-Laboratory for Molecular Cell Biology, University College London, London, UK

Description

a549_mt.tif

  • Data used in Figure "Microscopy image processing workflow using NanoPyx methods".
  • Fixed A549 cells immunolabelled against ß-tubulin with Alexa Fluor™ 647.
  • Acquired using a Nanoimager microscope (Oxford Nanoimaging; ONI) equipped with a 100 × oil-immersion objective (Olympus 100x NA 1.45)
  • Image size 10000x283x283 (pixel size 117 nm)
  • .tif 16-bit

huvec_nuclei.tif

  • Data used in Figure "Comparative run times of multiple implementations of an algorithm, ran on a consumer-grade laptop and a professional workstation".
  • Human Umbilical Vein Endothelial Cells (HUVEC) stained with DAPI
  • Acquired in a Marianas spinning-disk confocal microscope. The objective used was a 63x oil (NA 1.4 oil, Plan-Apochromat, M27).
  • Image size 100x512x512
  • .tif 16-bit

Notes

Funding Bodies: R.H., P.M.P and R.P. acknowledge support from LS4FUTURE Associated Laboratory (LA/P/0087/2020). R.H., B.M.S. and I.C. acknowledge the support of the Gulbenkian Foundation (Fundação Calouste Gulbenkian), the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No. 101001332), the European Commission through the Horizon Europe program (AI4LIFE project with grant agreement 101057970-AI4LIFE, and RT-SuperES project with grant agreement 101099654-RT-SuperES), the European Molecular Biology Organization (EMBO) Installation Grant (EMBO-2020-IG-4734) and the Chan Zuckerberg Initiative Visual Proteomics Grant (vpi-0000000044 with DOI:10.37921/743590vtudfp In addition, A.D.B acknowledges the FCT 2021.06849.BD fellowship. R.H. and B.M.S. also acknowledge that this project has been made possible in part by a grant from the Chan Zuckerberg Initiative DAF, an advised fund of Silicon Valley Community Foundations (Chan Zuckerberg Initiative Napari Plugin Foundations Grants Cycle 2, NP2-0000000085). P.M.P and R.P. acknowledge support from Fundação para a Ciência e Tecnologia (Portugal) project grant (PTDC/BIA-MIC/2422/2020) and the MOSTMICRO-ITQB R&D Unit (UIDB/04612/2020, UIDP/04612/2020), P.M.P acknowledges support from La Caixa Junior Leader Fellowship (LCF/BQ/PI20/11760012) financed by "la Caixa" Foundation (ID 100010434) and by European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 847648, and a from a Maratona da Saúde award. This study was supported by the Academy of Finland (338537 to G.J.), the Sigrid Juselius Foundation (to G.J.), the Cancer Society of Finland (Syöpäjärjestöt; to G.J.), and the Solutions for Health strategic funding to Åbo Akademi University (to G.J.). This research was supported by InFLAMES Flagship Programme of the Academy of Finland (decision number: 337531).

Files

a549_mt.tif

Files (1.7 GB)

Name Size Download all
md5:6f81f85be5cf16691fb080c4123cd8d8
1.6 GB Preview Download
md5:ff03c54913110134959a6d6c7eb60cdd
52.5 MB Preview Download

Additional details

Related works

Is referenced by
Preprint: 10.1101/2023.08.13.553080 (DOI)