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Junyan Lu

@junyanlu.bsky.social
97 followers 53 following 8 posts

Group leader at University Hospital Heidelberg Former Postdoc at EMBL Bioinformatician, Data scientists Computational mass-spectrometry, multi-omics, and precision oncology. He/Him lu-group-ukhd.github.io

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Junyan Lu @junyanlu.bsky.social · 07/10/2025
Across synthetic, semi-synthetic, and experimental serial dilution datasets, msBayesImpute consistently: ✅ Achieved the lowest imputation error ✅ Improved sample-wise normalization ✅ Delivered the highest accuracy in DE analysis across 9 methods
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Junyan Lu @junyanlu.bsky.social · 07/10/2025
Missing values in proteomics are often not missing at random (MNAR). Existing methods either assume MAR or oversimplify MNAR. 💡 msBayesImpute learns protein-specific dropout curves directly from the data using Bayesian matrix factorization + probabilistic dropout models.
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