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An open-source protein assembly tool that derives a minimum protein list from peptide identifications filtered to a specified false discovery rate. By segregating peptide identifications for thresholding using both the precursor charge state and the number of tryptic termini, IDPicker retrieves more peptides for protein assembly. The new version is more robust against false positive proteins, especially in searches using multispecies databases, by requiring additional novel peptides in the parsimony process.
NeXtProt peptide uniqueness checker
Offers a web app and a corresponding application programming interface (API) service to define which peptide can be used to validate the existence of human proteins. NeXtProt peptide uniqueness checker is a comprehensive human-centric discovery platform, offering its users a seamless integration of and navigation through protein-related data. It validates the existence of human proteins based on several criteria, including peptide identification data from mass spectrometry (MS)-based proteomics experiments. This resource is designed to help researchers make sense of what all human proteins do.
Matches de novo sequences to homologous proteins and overcomes many of the limitations of other sequence homology search algorithms. OpenSea was designed to align de novo sequences from all MS/MS spectra for a given experiment to database protein sequences, even in situations when de novo sequencing algorithms cannot account for an entire peptide sequence. The implementation of this algorithm can rapidly identify proteins from complex mixtures of peptides using de novo sequences derived via high mass accuracy tandem mass spectrometry.
iTop-Q / intelligent Top-down Proteomics Quantitation
Allows protein quantitation in mass spectrometry (MS) level. iTop-Q is an automated graphical tool that constructs extracted ion chromatograms (XICs) across multiple MS spectra for proteoform quantitation. The software also aligns the detected putative proteoforms across different replicates/samples for direct abundance comparison. It is implemented with a quantitation wizard that guides users to process the imported data step by step.
Aims users to treat problems in protein inference for large data sets. IsoformResolver is a peptide-centric protein grouping methods allowing an analyze of results from many protein profiling experiments. This tool presents several advantages: (1) its method that allows concise display of proteins including all possible candidates; (2) its ability to display related proteins adjacently in a protein profile and compare proteomics data sets; or (3) its integration of label-free quantification by spectral counting into protein sets.
PIA / Protein Inference Algorithms
A flexible software suite for combining peptide spectrum matches (PSMs) from different search engine runs and turning these into consistent results. PIA can be integrated into proteomics data analysis workflows in several ways. A user-friendly graphical user interface can be run either locally or (e.g., for larger core facilities) from a central server. For automated data processing, stand-alone tools are available. PIA implements several established protein inference algorithms and can combine results from different search engines seamlessly. PIA supports the majority of established search engines and data in the mzIdentML standard format.
Allows the launching of database search engine, the interactive validation of assignments and the automatic management of sequence redundancy for protein inference and phosphosite identification. X!TandemPipeline uses the de novo technique to perform identification on data collected from ion trap mass spectrometers. It performs automated analysis by connection of two applications: (i) pepNovo for automating interpretation of tandem mass spectrometry spectra in a possible peptide sequence; (ii) Fasts to identify proteins from peptides sequences.
A Java-based platform for visualization and parsimony analysis of single and comparative LC-MS/MS database search engine results. The success of mass spectrometric peptide sequence assignment algorithms has led to the need for a tool to merge and evaluate the increasing data set sizes that result from LC-MS/MS-based shotgun proteomic experiments. MassSieve supports reports from multiple search engines with differing search characteristics, which can increase peptide sequence coverage and/or identify conflicting or ambiguous spectral assignments.
An algorithm for peptide identification using tandem mass spectrometry and protein sequence databases. ProLuCID uses a three tier scoring scheme. First, a binomial probability is used as a preliminary scoring scheme to select candidate peptides. The binomial probability scores generated by ProLuCID minimize molecular weight bias and are independent of database size. A modified cross-correlation score is calculated for each candidate peptide identified by the binomial probability. This cross-correlation scoring function models the isotopic distributions of fragment ions of candidate peptides which ultimately results in higher sensitivity and specificity than that obtained with the SEQUEST XCorr. Finally, ProLuCID uses the distribution of XCorr values for all of the selected candidate peptides to compute a Z score for the peptide hit with the highest XCorr.
A protein identification algorithm that combines two different tasks–peptide-spectrum match (PSM) verification and protein inference–into a single learning algorithm. Barista requires three inputs: a set of MS2 spectra, a protein database, and the results of searching the spectra against the database. Barista produces as output three ranked lists of proteins, peptides and PSMs, based on how likely the proteins and peptides are to be present in the sample and how likely the PSMs are to be correct. Barista can jointly analyze the results of multiple shotgun proteomics experiments, corresponding to different experiments or replicate runs.
Assists mass spectrometry-based bioinorganic studies via top-down and bottom-up approaches in positive and negative ion modes. PolyCut is designed to cope with metalloproteins, metallo-polymers and biomolecules with heavy element(s) as one (or more) of the charging agents at defined but different oxidation states. It does automatic assignment by considering the entire experimental and simulated isotopic patterns of an ion rather than reading only the mono-isotopic and average m/z values (and/or mass values).
INKA / Integrative Inferred Kinase Activity
Serves for phosphoproteomic inference of active phosphokinases. INKA utilizes label-free quantification of phosphopeptides derived from: kinases, kinase activation loops, kinase substrates deduced from prior experimental knowledge, and kinase substrates predicted from sequence motifs. This tool is able to identify active kinases, with potential clinical significance. It combines direct observations on phosphokinases, with observations on phosphoproteins that are known or predicted substrates for the pertinent kinase.
Spectrum Mill
Identifies proteins and peptides through fast database searches with automatic or manual match validation and unique algorithms that minimize false positives. Spectrum Mill software can identify relative abundance differences of twofold or greater without complicated isotope labelling and the system will summarize and correlate results in formats that provide maximum insight and convenience. It also offers de novo spectral interpretation for proteins not found in databases.
Classifies shotgun proteomics data from any organism. PeptideClassifier carries out several steps: first, it analyzes protein sequence redundancies and generates an identifiable proteome index; second, it parses the database search result files; third, it classifies the experimentally identified peptides into six evidence classes with different information contents (see below); fourth, it infers a minimal list of protein identifications per evidence class; and finally, it can report a minimal set of protein identifications that would explain the remaining ambiguous peptides, following the Occam's Razor approach.
Identifies modified proteoforms using top-down tandem mass spectra, which is based on algorithms for the mass graph alignment problem. TopMG is a mass graph-based software tool for proteoform identification. It was tested on three top-down MS/MS data sets. Experimental results showed that TopMG was efficient in identifying proteoforms with variable Post-Translational Modifications (PTMs) and outperformed MS-Align-E and ProSightPC in identifying complex proteoforms, especially those with terminal truncations.
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