[jkh1]

For those interested, we did something similar a few years ago but for proteins in dividing cells where we could quantify how much of a protein is where in the cell over time during cell division [0]. Data [1], code [2] and web-based visualization [3] are available.

Although technology has improved, building the reagents and acquiring data remains labor-intensive. The value of such work would be in having an exhaustive resource (something like 500-600 relevant proteins for cell division) but once the proof of concept is published, you can't get funding for doing more.

[0] https://www.nature.com/articles/s41586-018-0518-z/

[1] https://idr.openmicroscopy.org/search/?query=Name:idr0041-ca...

[2] https://git.embl.de/grp-ellenberg/mitotic_cell_atlas

[3] https://www.mitocheck.org/mitotic_cell_atlas/index.html

[dd36]

Why can’t you get more funding?

Also, and I understand that we never really know the upside with fundamental research, but what’s the upside? Why wouldn’t pharma or biotech see advantages to the research?

[jkh1]

Once published, it's not new anymore. It would cost a few millions just to repeat the work on a few hundred proteins and unless something new or interesting surfaces, it won't be publishable in a high-visibility place. Also it might have to be done/repeated in different cell lines. I don't know much about what pharma/biotech is interested in but from what I see, getting basic quantitative data like this doesn't seem to be a prority though they would probably make use of it once available.

Edit to address the upside question: This is dynamic quantitative data with which you would eventually get at how much of a protein interacts with how much of another, where and when during cell division. Basically, this is getting at the dynamics of protein interactions in live cells. The goal would be to build an dynamic molecular interaction network of cell division.