Manages proteomic mass spectrometry workflows and data analysis. Multiplierz provides a toolset of multiple methods for peptide identification, quantitation, reporting, as well as tools for easily manipulating standard data formats. This software is a Python library compatible with new reporting formats and high-level tools to achieve post-perform proteomic analyses. The architecture of the software environment has seamless integration with native data files via mzAPI.
Facilitates visualization, statistical analysis, and high-quality image and data export. MALDIViz is a comprehensive informatics application for MALDI HTS data. This package provides a theme on top of Shiny, allowing the creation of visually attractive dashboards. It also offers user selectable options for generating a 3D PCA plot, for classification and identification of major sources of variation in the data.
Provides intuitive, yet powerful, instrument control, data acquisition, qualitative and quantitative data analysis, and reporting for Agilent time-of-flight (TOF), quadrupole time-of-flight (Q-TOF), ICP-MS, and triple quadrupole systems. Designed from the ground up to make MS analyses easier from tuning to final report MassHunter Workstation software can be complemented by application-specific MassHunter software packages that provide even more power and stream-lined operation for specialized analytical tasks such as expression profiling.
Offers a platform giving access to Clinical Proteomics Tumor Analysis Consortium (CPTAC) datasets. P-MartCancer is a web application that evaluates peptides to identify the most abundant or reproducible ones and gives a median signal. The program allows users to perform four main functions: (i) quality control processing; (ii) gene or protein quantiﬁcation; (iii) statistics; and (iv) exploratory data analysis.
Allows to analyse shotgun proteomics data. CPFP is a data analysis pipeline that aims to provide a simple interface for core facility staff and clients, and to fully automate the analysis of tandem mass spectrometry (MS/MS) data with multiple search engines. The software consists of a web application, relational database and collection of pipeline scripts. It can be installed locally or started in the Amazon Web Services (AWS) cloud.
Analyzes metabolomics data generated from the 2D gas chromatography time-of-flight mass spectrometry (GCxGC-TOF MS) instrument. MetPP is able to recognize the concentration difference of the spiked-in metabolite standards between sample groups. It is composed of different modules for: retention index matching, peak filtering and merging, peak list alignment, quant mass conversion, normalization, statistical significance tests and pattern recognition.
Identifies peptides from a sequence database with tandem mass spectrometry data. PEAKS employs de novo sequencing as a subroutine and exploits the de novo sequencing results to improve both the speed and accuracy of the database search. Each protein obtains a score by adding its three highest peptide CAA scores, and the protein feature of a peptide is the maximum score of the proteins containing this peptide. PEAKS also provides a user-friendly interface to show each resultant peptide spectrum match from de novo sequencing.
Provides an interface for basic analysis of mass spectrometry data. mzDesktop gives access to the proteomic analysis algorithms from the library of the Multiplierz software. This software offers several functions existing in Multiplierz but through a graphical user interface. Users can visualize the degree of protein sequence coverage supported by given set of peptide-spectrum match (PSM). It is compatible with mzReports and mzIdentML files.
Manages and combines both identifications and semiquantitative data related to multiple liquid chromatography-mass spectrometry (LC−MS)/MS analyses. hEIDI can be used to compile analyses and retrieve lists of nonredundant protein groups. It allows direct comparison of series of analyses, on the basis of protein groups, while ensuring consistent protein inference and also computing spectral counts. The tool was able to compare pools of analyses in projects for which up to 1500 search results had been combined.
Handles the computational complexity of pairwise comparisons of spectra in the context of large volumes. SpecOMS can compare a whole set of experimental spectra generated by a discovery proteomics experiment to a whole set of theoretical spectra deduced from a protein database. It contains SpecXtract, which computes the number of common (or shared) fragment masses for any pair of spectra, SpecTrees, a data structure to store all the input spectra without any filtering, and SpecFit to analyse the pairs provided by SpecXtract.
Identifies monoisotopic masses of precursors for tandem mass spectrometry (MS/MS) spectra. pParse proposes a method for determining candidate clusters and classifying them according the sum of the intensity, the similarity of the experimental and the theoretical isotopic distribution, and the similarity of elution profiles. The application was developed to be utilized with Thermo FT/Orbitrap RAW files.
A Java-based proteomics cloud computing pipeline system for peptide and protein identifications. The ProteoCloud pipeline consists of three types of units: (i) a single client-side controller unit, that constitutes the master control for the pipeline; (ii) any number of worker units that will perform the actual identifications; and (iii) a single database unit running the MySQL database instance where all results will be stored.
A software tool for the analysis of MALDI data. This is an application that covers the whole process of MALDI data analysis, from data preprocessing to complex data analyses. Mass-Up incorporates the most common analyses, aside from protein identification and focusing in biomarker discovery, such as statistical tests-based biomarker discovery, clustering, PCA, and classification. In addition, other less common analyses such as quality control and biclustering are also included. Therefore, Mass-Up provides users with a wide range of tools to analyze and explore their MALDI data.
Aligns multiple liquid chromatography-mass spectrometry (LC-MS) datasets to one another by clustering mass and chromatographic elution features across datasets. The MultiAlign application provides advanced visualization and manipulation capabilities for LC-MS datasets acquired on high resolution mass spectrometers. Functionalities include overlaid 2D plots, alignment plots, normalizations, and basic statistical comparisons. MultiAlign uses the LCMSWARP algorithm to align LC-MS datasets to a master list (mass tag database or a single LC-MS dataset) and then consolidate features into a consensus map. These features can be matched to an accurate mass and time (AMT) tag database to identify the LC-MS features.
Calculates proteome-wide distances directly from MS/MS data. DISMS2 allows for the choice of the spectrum distance measure and includes different spectra preprocessing and filtering steps that can be tailored to specific situations by parameter optimization. It can be applied to samples from species without database annotation, as on the fresh water snail Radix species and on the foraminifera Amphistegina lessonii and gibbosa.
Enables peptide-level processing of phosphoproteomic data generated by multiple protein identification search algorithms, including Mascot, Sequest, and Paragon, as well as cross-comparison of their identification results. The software supports both qualitative and quantitative phosphoproteomics studies, as well as multiple between-group comparisons.
Provides a complete data analysis solution for the users of MALDI-TOF MS proteomics raw data especially biomedical researchers with no statistics background. pkDACLASS classifies the samples based on the peaks using the randomForest R package classifier in addition to considering equal numbers of cases and controls for the classification process. It offers flexibility to the users to accomplish the complete and integrated analysis in one step or conduct analysis as a flexible platform and reveal the results at each and every step of the analysis.
Allows users to perform qualitative analysis of mass spectrometric data. MSGRAPH provides access to information contained in a liquid chromatography–mass spectrometry (LC/MS) analysis run. To facilitate information exchange or archiving, the program can read and write on any virtual (network) and physical drive. Moreover, data of mass spectra or mass chromatograms can be exported.
Quantifies thorough statistics and inspects graphical data for any kind of high-throughput stable isotope labelling (SIL) experiment on routine basis. QuiXoT allows practically quantification of any kind of isotopic or isobaric labelling. It can perform a retention time alignment of labelled and unlabelled peaks for the cases the chromatography system separates slightly in elution time labelled peptides from their unlabelled pairs.
Allows users to investigate databases. Open-pFind consists of a two-steps search algorithm that first preprocesses mass-spectrometry (MS) data, and calibrates and extracts multiple precursor ions corresponding to each tandem mass spectrum. Secondly, the MS/MS data is searched against the indexed database. It can be used for key factors that affect the identification rate, including unexpected modifications, amino acid mutations, semi-/non-specific digestion and co-eluting peptides.
A package for protein identification and quantification in biologic complex samples. It covers a wide range of possible proteomic analyses from proteins and peptides identification to post-translational modification. It searches in many databases (SEQUEST, Z-Core, Mascot, …) and several dissociation technics (CID, HCD, ETD) for complete analyses. Proteome Discover automatizes data analyse and allows to easily represent results thanks to modules like GO enrichment.
Serves for proteomics data visualization. PDV is designed to support different kinds of tandem mass spectrometry (MS/MS) identification results visualization. It contains several functions, such as: (1) database searching; (2) Denovo sequencing, whose results can be visualized by PDV; (3) MaxQuant; (4) Proteogenomics; or (5) single PSM.
Finds peaks in raw mass spectra. ICR-2LS is a PC-based software package that supports advanced experimental techniques and automated data analysis. Capabilities include full waveform generation, automated mass spectra interpretation, and database searching integration of FASTA or GenBank files.
A Java library of algorithms for processing mass spectrometry data. The goals of MSDK are to provide a flexible data model with Java interfaces for mass-spectrometry related objects (including raw spectra, processed data sets, identification results etc.) and to integrate the existing algorithms that are currently scattered around various Java-based graphical tools
Consists of a proteomics data processing pipeline. Proteomatic allows users to evaluate mass spectrometric proteomics experiments. Different functionalities are provided via scripts that can be chained together into this high-throughput data processing pipeline.
A platform for mass spectrometry data processing, protein identification, quantification and unexpected post-translational modification characterization. EasyProt provides a fully integrated graphical experience to perform a large part of the proteomic data analysis workflow. Our goal was to develop a software platform that would fulfill the needs of scientists in the field, while emphasizing ease-of-use for non-bioinformatician users.
Allows scientists to deposit mass spectrometry (MS) raw files, perform proteome identification and quantification online, carry out bioinformatics analyses, and extract knowledge. Firmiana offers a way to easy visualize results without the need for programming expertise. It aims to facilitate for users the entire process of bioinformatics analysis from raw MS data to generate biological knowledge. The tool permits to automate large-scale data processing by using streamlined data computing workflows.
Processes large-scale mass spectrometry-based proteomics data. STEM is a stand-alone computational tool that evaluates, integrates, and compares large datasets produced by Mascot. STEM is compatible with quantitative proteomics studies that utilize various stable isotope tags. This software is designed to execute high-speed processing/organization of experimental data from a large-scale proteomics study. The STEM V-mode removes unreliable candidates from the large amount of Mascot search data, removes redundant peptide assignments for individual proteins, and efficiently extracts and integrates valuable information relevant to peptide/protein identification. The STEM C-mode compares lists of identified proteins, and proteins found in common between the lists and/or unique to a list from a specific analysis can be pulled out rapidly, enabling easy comparison of very complex proteomics results.
Incorporates and compares protein identification results from Mascot and Paragon. Compid can build summaries from database search results. It assists users in the investigation of the peptide and protein identification results. This tool imports data sets into an internal database, and then construct reports from the imported data. It is not able to find new probabilities regarding peptide identifications.
Determines peptide sequences with unspecified modifications. PeaksPTM is a standalone software based on an algorithm that exploits both peptide pair and post-translational modifications (PTM) rareness to improve unrestricted PTM search. The application takes into account the totality of the PTMs contained in the Unimod database as variable PTMs and provides several searching strategies.
Provides a comprehensive proteomics data analysis method. Visualize is a workstation application with an intuitive graphical user interface (GUI). It brings together different approaches to examine complex proteomics data sets at both the low level of Mass Spectrometry (MS) spectra and the identification details as well as the high levels of quantitation, analysis, and annotation to produce the output and figures required to communicate the results in presentations, publications, and applications.
Dr. Yashwanth Subbannayya obtained his M.Sc. degree in Medical Biochemistry from Manipal University. He qualified the competitive CSIR-UGC National Eligibility Test and joined the Institute of Bioinformatics, Bangalore as a UGC Junior Research Fellow. As part of his Ph.D. work, he studied the molecular mechanisms of gastric cancer in clinical specimens using quantitative proteomic technologies. This study, the results of which were published in Cancer Biology and Therapy, yielded a novel therapeutic target for gastric cancer- CAMKK2. Further, he also studied the serum proteome of gastric cancer patients and developed assays for potential markers using the revolutionary multiple reaction monitoring approach. The results of this study were published in Journal of Proteomics. In addition to his research work, he also trained extensively in sample preparation for mass spectrometry, fractionation techniques and gained expertise in quantitative proteomic techniques and data analysis. In addition, he also trained extensively in various validation platforms including immunohistochemsitry, multiple reaction monitoring and Western blot. He has also worked as a curator for several biological databases including NetPath, Human Protein Reference Database (HPRD) and Breast cancer database. His work in various research projects have yielded him 23 publications either as lead author or co-author in peer reviewed journals. He is a reviewer for the journal Proteomics.
Dr. Yashwanth Subbannayya joined the YU-IOB Center for Systems Biology and Molecular Medicine in June, 2015. During the initial period, his job consisted of assisting other personnel of the university in the establishment of YU-IOB Center for Systems Biology and Molecular Medicine. He was also involved in training of Ph.D. students in biological aspects. After the establishment of the center, he trained in cell culture techniques and metabolomics analysis. At YU-IOB CSBMM, he is studying the molecular mechanisms in various cancers including oral cancer. In addition, he is studying the molecular mechanisms as well as the metabolic constituents of traditional medicine formulations using mass spectrometry technologies. In June 2016, he convened the national symposium “Genomics in clinical practice: Future of precision medicine” held at Yenepoya University on June 1 and 2, 2016. The resource persons included 16 individuals from various academic organizations as well as industry. The symposium was attended by 218 participants from 24 institutions around India. He is a member of the Scientific Review Board of Yenepoya Research Centre where he facilitates timely scientific review of research projects.
Kishore KJ PhD | Experienced in Mass spectrometry, Proteomics & Informatics tools | Looking for new opportunities
Highly motivated, enthusiastic researcher with 6 years’ experience in analytical method development and project management. Broad range of technical and project management skills in the development of new approaches to discover bio-materials and its interactions.
Proficient in performing analysis using MALDI-MS/MS, ESI-MS/MS, Potentiostat / Galvanostat, FTIR, UV-Vis Spectrophotometer, microplate reader, robotic liquid handling & Wet chemistry analysis.