Recovering Sparse Low-Rank Blocks in Mass Spectrometry
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2013
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Working Paper
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Abstract
We develop a novel sparse low-rank block (SLoB) signal recovery framework that simultaneously exploits sparsity and low-rankness to accurately identify peptides (fragments of proteins) from biological samples via tandem mass spectrometry (TMS). To efficiently perform SLoB-based peptide identification, we propose two novel recovery algorithms, an exact iterative method and an approximate greedy algorithm, and provide analytical recovery guarantees. Using experiments with synthetic and real-world TMS data, we demonstrate that the proposed framework and algorithms are capable of substantially outperforming existing sparse signal recovery techniques.
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ETH Zurich
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Sparse signal recovery; nuclear norm; convex optimization; recovery guarantees.
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09695 - Studer, Christoph / Studer, Christoph
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