About Imaging and Multiomics Data Stories

This collection is now closed to submissions.

Data scientists and computational biologists draw from several sources to perform analytics and construct data stories. Purpose-specific data analysis is distinct to data pipelines, it is an iterative process that heavily relies on data scientists’ skills in modelling, interpretation, and communication to produce scientific storytelling. Collaborative learning facilitates the development of such skills by sharing the thinking process around the creation of data stories.

This collection aims to bring together illustrations of analysis techniques for addressing questions in biomedical fields utilising imaging and/or multiomics technologies. We welcome works related to simultaneous examination of multiple modalities including but not limited to sequencing, spatial omics, proteomics, and imaging, with particular focus in generating data stories.

Keywords: living workshop; collaborative learning; molecular biology; data science; analytics; computational biology; data stories

This collection is part of the Cell & Molecular Biology and Bioinformatics Gateways.

Any questions about this collection? Please get in contact directly with research@f1000.com.