Evaluation SIHUMI dataset: A sectioning and database enrichment approach for improved peptide spectrum matching in large, genome-guided protein sequence databases

Dataset for evaluation of database sectioning method for generating an enriched database for mass-spectrometry-based proteomic approaches using large databases. Our evaluation demonstrates that this method helps to increase the sensitivity of PSMs while maintaining acceptable FDR statistics. This dataset was acquired from the protein samples containing proteins from eight microorganisms (<em>Anaerostipes caccae, Bacteroides thetaiotaomicron, Bifidobacterium longum, Blautia producta, Clostridium butyricum, Clostridium ramosum, Escherichia coli, Lactobacillus plantarum</em>) that were grown in a bioreactor. The MS-data for this dataset was acquired by Dr. Hettich's group at Oak Ridge National Laboratory, and it was made available by Dr. Nico Jehmlich from Helmholtz Center for Environmental Research through the 3rd International Metaproteome Symposium (https://www.ufz.de/index.php?en=44639).