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Junyan Lu

Heidelberg / DE

Heidelberg University

Speaker

Tue, Oct 22
Poster presentation
P-II-0476
MsBayesImpute: a versatile framework for handling missing values in mass-spectrometry data through a combined Bayesian factorization and probabilistic dropout model
New Technology: AI and Bioinformatics in Mass Spectrometry

Further involvements

Mon, Oct 21
Poster presentation
P-I-0016
Exploring EGFR and MET cross-talk in NSCLC: a pathway to improved therapy efficacy
Defining Signaling Networks - Functional PTMs
Mon, Oct 21
Poster presentation
P-I-0277
Identifying mass spectrometry-based biomarkers for predicting tumor recurrence in lung cancer
Clinical Proteomics
Tue, Oct 22
Poster presentation
P-II-0476
MsBayesImpute: a versatile framework for handling missing values in mass-spectrometry data through a combined Bayesian factorization and probabilistic dropout model
New Technology: AI and Bioinformatics in Mass Spectrometry
Wed, Oct 23
Poster presentation
P-III-0792
Exploring dynamic behavior with SmartPhos: an integrated pipeline for low-input, high-throughput Phosphoproteomics in clinical samples
Data Integration: With Bioinformatics to Biological Knowledge