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Peptide Calculator

Calculates chemical formula and molecular weight of peptides. Peptide Calculator gives calculated values for isoelectric point (pI) and molar extinction coefficient as well as a plot of calculated b-strand propensity for a sequence. It provides a pie chart summarizing proportions of acidic, basic and uncharged residues in the sequence submitted. The tool is able to determine the molecular weights for all peptide/deletion/modification combinations incorporating single or double deletions and single or double modifications.


Provides identification of natural organic matter (NOM) species using high-resolution mass spectra (HR MS). Formularity is a software that couples a two algorithmic searches functions through a graphical interface as well as a least squares regression based internal calibration function. Formulas can be assigned for high-resolution mass spectra collected in positive or negative ionization mode, with proton or electron ion physics, charge states, and different molecular adducts.


Calculates the statistical significance of the top pair of peptides matched from the database to a given mixture spectrum. MixGF determines the probability that a random pair of peptides will match a given mixture spectrum with a score at least as high as that of the top-scoring Peptide–Peptide Spectrum Match (PPSM). Analysis of multiple datasets with this application reveals that in complex biological samples the number of identified mixture spectra can be as high as 20% of all the identified spectra.

IPPD / Isotopic Peak Pattern Deconvolution

Provides functionality to extract isotopic peak patterns from raw mass spectra. IPPD offers a flexible function which tries to estimate model parameters in a way tailored to the peak shapes in the data. This is done by fitting a large set of template basis functions to the raw spectrum using either nonnegative least squares or least absolute deviation fitting. The package also provides functionality to process liquid chromatography-mass spectrometry (LCMS) runs.


An algorithm to reduce the number of incorrect peptide matches and maximize the number of correct peptides at a fixed false discovery rate using a minimal number of scoring outputs from the SEQUEST search engine. De-Noise uses a three-step process: data cleaning, data refining through a SVM-based decision function, and a final data refining step based on proteolytic peptide patterns. Because De-Noise uses a limited number of scoring attributes, it can be easily implemented with other search engines.