Project description:Serum of LCMV infected mice. Data was generated on a Thermo Q Exactive and C18 RP UHPLC. Positive polarity acquisition on LC-MS/MS.
Project description:To explore the protein components for scallop byssus, the soluble fractions of scallop byssus was extract. For mass spectrometric analysis, proteins were extracted from byssal adhesive plaques, and the whole protein smple was treated with trypsin and analyzed using Thermo Fisher Q Exactive Mass Spectrometer (Thermo Fisher Scientific, USA). The mass spectrometry raw data were searched against the full set of predicted proteins from the C. farreri genome and Transcriptome using Mascot v2.3.0 (Matrix Science, London, UK).
Project description:Metabolomics analysis of Fecal samples from a Dietary interventions in Crohn's patients. Fecal samples were extracted with 50:50 (MeOH:H2O) and analyzed using the LC-MS/MS method on the Thermo Orbitrap Q Exactive.
Project description:Serum of LCMV infected mice. Data was generated on a Thermo Q Exactive and C18 RP UHPLC. Positive polarity acquisition on LC-MS/MS.
Project description:Metabolite analysis of DDW fecal samples, standard methanol extraction. Data were acquired using a Bruker Daltonics maXis Impact and C18 RP-UHPLC. Positive polarity acquisition of LC-MS/MS.
Project description:q exactive hf, 28 min method, comparison between IBD patients and ctrl methanol extraction, human serum and feces methanol extraction
Project description:Logistic regression classification models were fit to manually classified quality control (QC) LC-MS/MS datasets to develop a model that can predict whether a dataset is in or out of control. Model parameters were optimized by minimizing a loss function that accounts for the tradeoff between false positive and false negative errors. In addition to the 1152 training/testing datasets, we are including 2662 additional datasets, all of the same QC sample (whole cell lysate of Shewanella oneidensis). Datasets originate from 6 Thermo instrument platforms: Exactive, LTQ, VelosPro, Orbitrap, Q-Exactive, and Velos Orbitrap.
Project description:Logistic regression classification models were fit to manually classified quality control (QC) LC-MS/MS datasets to develop a model that can predict whether a dataset is in or out of control. Model parameters were optimized by minimizing a loss function that accounts for the tradeoff between false positive and false negative errors. In addition to the 1152 training/testing datasets, we are including 2662 additional datasets, all of the same QC sample (whole cell lysate of Shewanella oneidensis). Datasets originate from 6 Thermo instrument platforms: Exactive, LTQ, VelosPro, Orbitrap, Q-Exactive, and Velos Orbitrap.
Project description:Logistic regression classification models were fit to manually classified quality control (QC) LC-MS/MS datasets to develop a model that can predict whether a dataset is in or out of control. Model parameters were optimized by minimizing a loss function that accounts for the tradeoff between false positive and false negative errors. In addition to the 1152 training/testing datasets, we are including 2662 additional datasets, all of the same QC sample (whole cell lysate of Shewanella oneidensis). Datasets originate from 6 Thermo instrument platforms: Exactive, LTQ, VelosPro, Orbitrap, Q-Exactive, and Velos Orbitrap.