Www.biorxiv.org (6)#

Bridging Imaging Users to Imaging Analysis - A community survey#

Suganya Sivagurunathan, Stefania Marcotti, Carl J Nelson, Martin L Jones, David J Barry, Thomas J A Slater, Kevin W Eliceiri, Beth A Cimini

Published 2023

Licensed BSD-3-CLAUSE

Tags: Bioimage Analysis

Content type: Publication, Preprint

https://www.biorxiv.org/content/10.1101/2023.06.05.543701v1

COBA-NIH/2023_ImageAnalysisSurvey


CellTrackColab#

Guillaume Jacquemet

Licensed MIT

Content type: Notebook, Collection

https://www.biorxiv.org/content/10.1101/2023.10.20.563252v2

guijacquemet/CellTracksColab


SpatialData: an open and universal data framework for spatial omics#

Luca Marconato, Giovanni Palla, Kevin A Yamauchi, Isaac Virshup, Elyas Heidari, Tim Treis, Marcella Toth, Rahul Shrestha, Harald Vöhringer, Wolfgang Huber, Moritz Gerstung, Josh Moore, Fabian J Theis, Oliver Stegle

Licensed CC-BY-4.0

Tags: Python

Content type: Publication, Preprint

https://www.biorxiv.org/content/10.1101/2023.05.05.539647v1.abstract


Studentsourcing - aggregating and re-using data from a practical cell biology course#

Joachim Goedhart

Tags: Sharing

Content type: Preprint

https://www.biorxiv.org/content/10.1101/2023.10.09.561479v1


Using Glittr.org to find, compare and re-use online training materials#

Geert van Geest, Yann Haefliger, Monique Zahn-Zabal, Patricia M. Palagi

Licensed CC-BY-4.0

Glittr.org is a platform that aggregates and indexes training materials on computational life sciences from public git repositories, making it easier for users to find, compare, and analyze these resources based on various metrics. By providing insights into the availability of materials, collaboration patterns, and licensing practices, Glittr.org supports adherence to the FAIR principles, benefiting the broader life sciences community.

Tags: Bioimage Analysis, Research Data Management

Content type: Publication, Preprint

https://www.biorxiv.org/content/10.1101/2024.08.20.608021v1


WebAtlas pipeline for integrated single cell and spatial transcriptomic data#

Tong Li, David Horsfall, Daniela Basurto-Lozada

Published 2023-04-28

Licensed None

Single cell and spatial transcriptomics illuminate complementary features of tissues. However, the online dissemination and exploration of multi-modal datasets is challenging. We introduce the WebAtlas pipeline for user-friendly sharing and interactive navigation of integrated datasets. WebAtlas unifies commonly used atlassing technologies into the cloud-optimised Zarr format and builds on Vitessce to enable remote data navigation. We showcase WebAtlas on the developing human lower limb to cross-query cell types and genes across single cell, sequencing- and imaging-based spatial transcriptomic data.

Tags: Spatial Transcriptomics, Single Cell, Bioimage Analysis

Content type: Collection, Atlas

https://developmental.cellatlas.io/webatlas

https://www.biorxiv.org/content/10.1101/2023.05.19.541329v1