IQMMA: Efficient MS1 Intensity Extraction Pipeline Using Multiple Feature Detection Algorithms for DDA Proteomics.

One of the key steps in data dependent acquisition (DDA) proteomics is detection of peptide isotopic clusters, also called "features", in MS1 spectra and matching them to MS/MS-based peptide identifications. A number of peptide feature detection tools became available in recent years, each relying on its own matching algorithm. Here, we provide an integrated solution, the intensity-based Quantitative Mix and Match Approach (IQMMA), which integrates a number of untargeted peptide feature detection algorithms and returns the most probable intensity values for the MS/MS-based identifications.

On the excessive use of coefficient of variation as a metric of quantitation quality in proteomics.

The coefficient of variation (CV) is often used in proteomics as a proxy to characterize the performance of a quantitation method and/or the related software. In this note, we question the excessive reliance on this metric in quantitative proteomics that may result in erroneous conclusions. We support this note using a ground-truth Human-Yeast-E.

[Activity of Lentinus edodes intracellular lectins at various developmental stages of the fungus].

We studied changes of the hemagglutinating activity of intracellular lectins of the basidiomycete Lentinus edodes (shiitake) at various stages of its morphogenetic development depending on erythrocyte type, growth medium, and lectin purification degree. Under certain experimental conditions, the specific lectin activity at the brown mycelium film stage exceeded the corresponding value for nonpigmented mycelium. The sensitivity of the lectins towards trypsin-treated rabbit erythrocytes was no less than a hundredfold higher than towards any other erythrocyte type studied.