At the Kusterlab, we have developed a statistical analysis tool (CurveCurator) to mine these proteome-wide dose-response curves. You may want to give it a try. github.com/kusterlab/cu...
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If your time pattern specifically looks like a sigmoidal dose-response curve and that’s the only thing you are looking for, you can also try CurveCurator. I know some folks who have done this already. Then you get statistics and FDR estimation for free.. doi.org/10.1038/s414...

Love y'all at @kusterlab.bsky.social! I bonded with Bernard over the shock that, before CurveCurator, there wasn't even a unified equation to fit DRC for proteomics. Great idea to do a larger curve, I think we also have a time course queued up that we might be able to hack CurveCurator to fit

A very nice implementation of magnetic beads based competition pull-downs with DIA readout. This workflow is well suited for real throughput …

CurveCurator is the perfect match for fast and reliable statistical analysis of these dose-response data sets.

🧬🖥️So excited to show you the outcome of @pascivers.bsky.social and my latest project: "From Hype to Health Check: Critical Evaluation of Drug Response Prediction Models with DrEval" doi.org/10.1101/2025.05.26.655288, published with M. Picciani, M. Wilhelm, K. Baum & @itisalist.bsky.social.
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Thanks @NatureComms for featuring CurveCurator on the Editors' Highlights for "Biotechnology and Methods": https://t.co/k520oNBUNm 🎉. We are honored! Nice to see that people like the package. 😊
Stay tuned for more dose-response content...

I am looking forward to discuss with with you:

• (phospho)proteome-wide dose-response profiling

• statistical analysis of 180 million curves with CurveCurator

• mapping kinase-resolved activities changes due to all target engagements

• (re-)evaluating the kinase substrate space in humans

What makes it even better: All experiments were performed in a dose-resolved manner—so you can dive into dose-response curves in our interactive dashboards! #CurveCurator #BeautifulCurves (3/4)

Out today in @NatureComms: CurveCurator, a software to support the analysis of dose-dependent data sets.
Congrats to Flo and Co.! 🍾🥳 (1/3) https://t.co/Q4Fk0ol95q

Dose-response curves help to identify real biological signal in omics data sets because one has a clear expectation about how they should look like. Our CurveCurator software has automated this “gold digging” for everyone.

We are happy to see CurveCurator and its "relevance score" highlighted in the bigger picture of omics data analysis. https://t.co/LxN7ZvvQ4q.

Original Article: https://t.co/PURcSXB1e0 https://t.co/dXE4BtyrTh

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5. Missing ablation studies make it hard to identify the benefits of model parts (e.g., multi-omics).

6. Due to inconsistent preprocessing, metrics and resulting error scores are incomparable.
The drug response prediction field needs a robust, shared benchmark with uniformly processed data.

CurveCurator fits log-logistic models to data from any kind of dose-dependent assay and provides characteristics such as effect potency, effect size, and statistical significance. (2/3) https://t.co/88toeadUwn