IDEAL-Q 1.065 – Mass Spectrometry Protein Quantitation

IDEAL-Q 1.063

:: DESCRIPTION

IDEAL-Q is an automated analysis tool for label-free quantitative proteomics. It accepts mzXML raw data format and Mascot xml and ProtXML/PepXML for identification result. IDEAL-Q uses an elution time prediction and peak alignment algorithms to quantify peptides across different LC-MS runs and increase quantitation coverage. Furthermore, the tool adopts an stringent validation step on Signal-to-noise ratio, Charge state, Isotopic distribution (SCI validation) to ensure quantitation accuracy. IDEAL-Q provides variously optional normalization tools for flexible workflow design such as addition of fractionation strategies and multiple spiked internal standards

::DEVELOPER

Computational Omics Labortary, Academia Sinica

:: SCREENSHOTS

:: REQUIREMENTS

  •  Windows

:: DOWNLOAD

 IDEAL-Q

:: MORE INFORMATION

Citation

Chih-Chiang Tsou et al. ,
IDEAL-Q: An automated tool for label-free quantitation analysis using an efficient peptide alignment approach and spectral data validation”,
Molecular & Cellular Proteomics, Vol. 9, pp. 131-144, 2010.

ProtMAX – Analyzing Large Shotgun Proteomics Mass Spectrometry data sets

ProtMAX

:: DESCRIPTION

ProtMAX is a fast and robust software tool for analyzing large shotgun proteomics mass spectrometry data sets.

::DEVELOPER

Molecular Systems Biology, University of Vienna

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows

:: DOWNLOAD

 ProtMAX

:: MORE INFORMATION

Citation:

Nat Protoc. 2013 Mar;8(3):595-601. doi: 10.1038/nprot.2013.013. Epub 2013 Feb 28.
Using ProtMAX to create high-mass-accuracy precursor alignments from label-free quantitative mass spectrometry data generated in shotgun proteomics experiments.
Egelhofer V1, Hoehenwarter W, Lyon D, Weckwerth W, Wienkoop S.

LC-IMS-MS Feature Finder v2.2.6487 – Detecting Multidimensional Liquid Chromatography, Ion Mobility and Mass Spectrometry features

LC-IMS-MS Feature Finder v2.2.6487

:: DESCRIPTION

LC-IMS-MS Feature Finder is a command line software application that searches for molecular ion signatures in multidimensional liquid chromatography-ion mobility spectrometry-mass spectrometry (LC-IMS-MS) data by clustering deisotoped peaks with similar monoisotopic mass, charge state, LC elution time, and ion mobility drift time values.

::DEVELOPER

Biological MS Data and Software Distribution Center , Pacific Northwest National Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Windows
  • Microsoft NET Framework 2.0

:: DOWNLOAD

 LC-IMS-MS Feature Finder

:: MORE INFORMATION

Citation

Bioinformatics. 2013 Nov 1;29(21):2804-5. doi: 10.1093/bioinformatics/btt465. Epub 2013 Sep 5.
LC-IMS-MS Feature Finder: detecting multidimensional liquid chromatography, ion mobility and mass spectrometry features in complex datasets.
Crowell KL1, Slysz GW, Baker ES, LaMarche BL, Monroe ME, Ibrahim YM, Payne SH, Anderson GA, Smith RD.

LFQuant 20120114 – Label-free Quantitative Analysis Tool for LC-MS/MS Proteomics Data

LFQuant 20120114

:: DESCRIPTION

LFQuant is a new analysis tool for label-free LC-MS/MS quantitative proteomics data. It is compatible with high-resolution mass spectrometers (Thermo RAW data) and two popular database search engines (SEQUEST and MASCOT) with target-decoy search strategy.

::DEVELOPER

LFQuant team

:: SCREENSHOTS

LFQuant

:: REQUIREMENTS

  • Windows

:: DOWNLOAD

 LFQuant

:: MORE INFORMATION

Citation

Proteomics. 2012 Dec;12(23-24):3475-84. doi: 10.1002/pmic.201200017.
LFQuant: a label-free fast quantitative analysis tool for high-resolution LC-MS/MS proteomics data.
Zhang W1, Zhang J, Xu C, Li N, Liu H, Ma J, Zhu Y, Xie H.

NITPICK 2.0 – Peak Identification for Mass Spectrometry Data

NITPICK 2.0

:: DESCRIPTION

NITPICK is a Non-greedy, Iterative Template-based peak PICKer that deconvolves complex overlapping isotope distributions in multicomponent mass spectra.

::DEVELOPER

Image Analysis and Learning Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows/ MacOsX
  • R

:: DOWNLOAD

  NITPICK

:: MORE INFORMATION

Citation

BMC Bioinformatics. 2008 Aug 28;9:355. doi: 10.1186/1471-2105-9-355.
NITPICK: peak identification for mass spectrometry data.
Renard BY1, Kirchner M, Steen H, Steen JA, Hamprecht FA.

pLSA – Probabilistic Latent Semantic Analysis of Imaging Mass Spectrometry Data

pLSA

:: DESCRIPTION

pLSA contains MATLAB code to perform a probabilistic Latent Semantic Analysis of Imaging Mass Spectrometry Data. In contrast to other unsupervised methods like Principal Component Analysis or Independent Component Analysis this method accounts for the non-negativity of mass spectra.

::DEVELOPER

Image Analysis and Learning Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux / Windows/ MacOsX
  • MatLab

:: DOWNLOAD

 pLSA

:: MORE INFORMATION

Citation

Anal Chem. 2008 Dec 15;80(24):9649-58. doi: 10.1021/ac801303x.
Concise representation of mass spectrometry images by probabilistic latent semantic analysis.
Hanselmann M1, Kirchner M, Renard BY, Amstalden ER, Glunde K, Heeren RM, Hamprecht FA.

BICEPS 1.0.3 – Novel Error Tolerant Search Strategy for Cross-Species Proteomics

BICEPS 1.0.3

:: DESCRIPTION

BICEPS (Bayesian information criterion-driven error-tolerant peptide search) offer an open source implementation based on this statistical criterion to automatically balance the information of each single spectrum and the database, while limiting the run time.

::DEVELOPER

Hamprecht lab ,Steen Laboratory

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/ Windows

:: DOWNLOAD

 BICEPS

:: MORE INFORMATION

Citation

Overcoming species boundaries in peptide identification with Bayesian information criterion-driven error-tolerant peptide search (BICEPS).
Renard BY, Xu B, Kirchner M, Zickmann F, Winter D, Korten S, Brattig NW, Tzur A, Hamprecht FA, Steen H.
Mol Cell Proteomics. 2012 Jul;11(7):M111.014167. doi: 10.1074/mcp.M111.014167.

ProteinDecision 1.0 – Protein Identification using Peptide-Mass Fingerprinting Data

ProteinDecision 1.0

:: DESCRIPTION

ProteinDecision is a computer software for identifying protein by serching against protein database with the input Peptide-Mass Fingerprinting Data. It can handle the issues of selecting peaks from mass spectrum, transforming database format, displaying the top ranks of identification result, and detailed information for each ranking.

::DEVELOPER

Digital Biology Laboratory, University Of Missouri-Columbia

:: SCREENSHOTS

ProteinDecision

:: REQUIREMENTS

  • Windows/Linux/MacOsX
  • Java

:: DOWNLOAD

 ProteinDecision

:: MORE INFORMATION

Citation

Methods Mol Biol. 2010;604:7-22. doi: 10.1007/978-1-60761-444-9_2.
Bioinformatics methods for protein identification using Peptide mass fingerprinting.
Song Z1, Chen L, Xu D.

MixDB 1.0r – Identify Mixture MS/MS Spectra from more than one Peptide

MixDB 1.0r

:: DESCRIPTION

MixDB is a database search tool that able to identify mixture MS/MS spectra from more than one peptide.

::DEVELOPER

CCMS The Center for Computational Mass Spectrometry

:: SCREENSHOTS

N/A

:: REQUIREMENTS

  • Linux/windows
  • Java
  • Perl

:: DOWNLOAD

   MixDB

:: MORE INFORMATION

Citation:

Peptide identification by database search of mixture tandem mass spectra.
Wang, J., Bourne, P. E., Bandeira, N.
Mol. Cell. Proteomics, 2011

GenoMS 20120110 – Sequencing Whole Proteins using a Template Databases

GenoMS 20120110

:: DESCRIPTION

GenoMS is a tool for sequencing a small set of proteins using an imperfect database and tandem mass spectra. The database need not contain full protein sequence, but instead can contain exons or partial sequences. The database can also be a small region of the genome. Tandem mass spectra should be from overlapping peptides produced from digestion by multiple proteases.

::DEVELOPER

Natalie Castellana  ,CCMS The Center for Computational Mass Spectrometry

:: SCREENSHOTS

N/A

:: REQUIREMENTS

:: DOWNLOAD

   GenoMS

:: MORE INFORMATION

Citation:

Template Proteogenomics: sequencing whole proteins using an imperfect database.
NE Castellana, V Pham, D Arnott, JR Lill, V Bafna. (2010).
Mol. Cell. Proteomics, 9, 6:1260-70.