Results 1 - 10 of 923

Correlation between protein and mRNA abundance in yeast

by Steven P. Gygi, Yvan Rochon, B. Robert Franza, Ruedi Aebersold, W. Zhou, J. Vogelstein, M. A. Basrai, D. E. Bassett, P. Hieter, B. Vogelstein, K. W. Kinzler - Mol Cell Biol , 1999
"... We have determined the relationship between mRNA and protein expression levels for selected genes expressed in the yeast Saccharomyces cerevisiae growing at mid-log phase. The proteins contained in total yeast cell lysate were separated by high-resolution two-dimensional (2D) gel electrophoresis. Ov ..."
Abstract - Cited by 193 (2 self) - Add to MetaCart
We have determined the relationship between mRNA and protein expression levels for selected genes expressed in the yeast Saccharomyces cerevisiae growing at mid-log phase. The proteins contained in total yeast cell lysate were separated by high-resolution two-dimensional (2D) gel electrophoresis. Over 150 protein spots were excised and identified by capillary liquid chromatography-tandem mass spectrometry (LC-MS/MS). Protein spots were quantified by metabolic labeling and scintillation counting. Corresponding mRNA levels were calculated from serial analysis of gene expression (SAGE) frequency tables (V. E. Velculescu, L. Zhang,
(Show Context)

A Dynamic Programming Approach to De Novo Peptide Sequencing via Tandem Mass Spectrometry

by Ting Chen, Ming-yang Kao, Matthew Tepel, John Rush, George M. Church - Journal of Computational Biology , 2001
"... Tandem mass spectrometry fragments a large number of molecules of the same peptide sequence into charged molecules of pre � x and suf � x peptide subsequences and then measures mass/charge ratios of these ions. The de novo peptide sequencing problem is to reconstruct the peptide sequence from a give ..."
Abstract - Cited by 92 (5 self) - Add to MetaCart
Tandem mass spectrometry fragments a large number of molecules of the same peptide sequence into charged molecules of pre � x and suf � x peptide subsequences and then measures mass/charge ratios of these ions. The de novo peptide sequencing problem is to reconstruct the peptide sequence from a given tandem mass spectral data of k ions. By implicitly transforming the spectral data into an NC-spectrum graph G (V, E) where V 2k 2, we can solve this problem in O ( V E) time and O ( V 2) space using dynamic programming. For an ideal noise-free spectrum with only b- and y-ions, we improve the algorithm to O ( V E) time and O ( V) space. Our approach can be further used to discover a modi � ed amino acid in O ( V E) time. The algorithms have been implemented and tested on experimental data. Key words: dynamic programming, peptide sequencing, mass spectrometry, computational proteomics, protein identi � cation, computational biology.
(Show Context)

Interpretation of Shotgun Proteomic Data: The Protein Inference Problem

by Alexey I. Nesvizhskii, Ruedi Aebersold - Mol. Cell. Proteomics , 2005
"... The shotgun proteomic strategy based on digesting proteins into peptides and sequencing them using tandem mass spectrometry and automated database searching has become the method of choice for identifying proteins in most large scale studies. However, the peptide-centric nature of shotgun proteomics ..."
Abstract - Cited by 84 (7 self) - Add to MetaCart
The shotgun proteomic strategy based on digesting proteins into peptides and sequencing them using tandem mass spectrometry and automated database searching has become the method of choice for identifying proteins in most large scale studies. However, the peptide-centric nature of shotgun proteomics complicates the analysis and biological interpretation of the data especially in the case of higher eukaryote organisms. The same peptide sequence can be present in multiple different proteins or protein isoforms. Such shared peptides therefore can lead to ambiguities in determining the identities of sample proteins. In this article we illustrate the difficulties of interpreting shotgun proteomic data and discuss the need for common nomenclature and transparent informatic approaches. We also discuss related issues such as the
(Show Context)

SCOPE: a probabilistic model for scoring tandem mass spectra against a peptide database

by Vineet Bafna, Nathan Edwards - Bioinformatics , 2001
"... Proteomics, or the direct analysis of the expressed protein components of a cell, is critical to our understanding of cellular biological processes in normal and diseased tissue. A key requirement for its success is the ability to identify proteins in complex mixtures. Recent technological advances ..."
Abstract - Cited by 81 (7 self) - Add to MetaCart
Proteomics, or the direct analysis of the expressed protein components of a cell, is critical to our understanding of cellular biological processes in normal and diseased tissue. A key requirement for its success is the ability to identify proteins in complex mixtures. Recent technological advances in tandem mass spectrometry has made it the method of choice for high-throughput identification of proteins. Unfortunately, the software for unambiguously identifying peptide sequences has not kept pace with the recent hardware improvements in mass spectrometry instruments. Critical for reliable high-throughput protein identification, scoring functions evaluate the quality of a match between experimental spectra and a database peptide. Current scoring function technology relies heavily on ad-hoc parameterization and manual curation by experienced mass spectrometrists. In this work, we propose a two-stage stochastic model for the observed MS/MS spectrum, given a peptide. Our model explicitly incorporates fragment ion probabilities, noisy spectra, and instrument measurement error. We describe how to compute this probability based score efficiently, using a dynamic programming technique. A prototype implementation demonstrates the effectiveness of the model. Contact:

Assigning significance to peptides identified by tandem mass spectrometry using decoy databases

by Lukas Käll, John D. Storey, Michael J. Maccoss, William Stafford Noble - J. Proteome Res , 2008
"... Automated methods for assigning peptides to observed tandem mass spectra typically return a list of peptide-spectrum matches, ranked according to an arbitrary score. In this article, we describe methods for converting these arbitrary scores into more useful statistical significance measures. These m ..."
Abstract - Cited by 64 (13 self) - Add to MetaCart
Automated methods for assigning peptides to observed tandem mass spectra typically return a list of peptide-spectrum matches, ranked according to an arbitrary score. In this article, we describe methods for converting these arbitrary scores into more useful statistical significance measures. These methods employ a decoy sequence database as a model of the null hypothesis, and use false discovery rate (FDR) analysis to correct for multiple testing. We first describe a simple FDR inference method and then describe how estimating and taking into account the percentage of incorrectly identified spectra in the entire data set can lead to increased statistical power.

The Paragon Algorithm, a Next Generation Search Engine That Uses Sequence Temperature Values and Feature Probabilities to Identify Peptides from Tandem Mass Spectra * □S

by Ignat V. Shilov, Sean L. Seymour, Alpesh A. Patel, Alex Loboda, Wilfred H. Tang, Sean P. Keating, Christie L. Hunter, Lydia M. Nuwaysir, Daniel A. Schaeffer
"... The Paragon TM Algorithm, a novel database search engine for the identification of peptides from tandem mass spectrometry data, is presented. Sequence Temperature Values are computed using a sequence tag algorithm, allowing the degree of implication by an MS/MS spectrum of each region of a database ..."
Abstract - Cited by 62 (0 self) - Add to MetaCart
The Paragon TM Algorithm, a novel database search engine for the identification of peptides from tandem mass spectrometry data, is presented. Sequence Temperature Values are computed using a sequence tag algorithm, allowing the degree of implication by an MS/MS spectrum of each region of a database to be determined on a continuum. Counter to conventional approaches, features such as modifications, substitutions, and cleavage events are modeled with probabilities rather than by discrete user-controlled settings to consider or not consider a feature. The use of feature probabilities in conjunction with Sequence Temperature Values allows for a very large increase in the effective search space with only a very small increase in the actual number of hypotheses that must be scored. The algorithm has a new kind of user
(Show Context)

Toward a human blood serum proteome: analysis by multidimensional separation coupled with mass spectrometry

by Joshua N. Adkins, Susan M. Varnum, Kenneth J. Auberry, Ronald J. Moore, Nicolas H. Angell, Richard D. Smith, David L. Springer, Joel G. Pounds - Mol. Cell. Proteomics , 2002
"... Blood serum is a complex body fluid that contains various proteins ranging in concentration over at least 9 orders of magnitude. Using a combination of mass spectrometry technologies with improvements in sample preparation, we have performed a proteomic analysis with submilliliter quantities of seru ..."
Abstract - Cited by 56 (4 self) - Add to MetaCart
Blood serum is a complex body fluid that contains various proteins ranging in concentration over at least 9 orders of magnitude. Using a combination of mass spectrometry technologies with improvements in sample preparation, we have performed a proteomic analysis with submilliliter quantities of serum and increased the measurable concentration range for proteins in blood serum beyond previous reports. We have detected 490 proteins in serum by on-line reversed-phase microcapillary liquid chromatography coupled with ion trap mass spectrometry. To perform this analysis, immunoglobulins were removed from serum using protein A/G, and the remaining proteins were digested with trypsin. Resulting peptides were separated by strong cation exchange chromatography into distinct fractions prior to analysis. This separation resulted in a
(Show Context)

Characterization of the low molecular weight human serum proteome

by Radhakrishna S. Tirumalai, King C. Chan, Darue A. Prieto, Haleem J. Issaq, Thomas P, Timothy D. Veenstra - Mol. Cell. Proteomics , 2003
"... chromatography; ESI, electrospray ionization; MS/MS, tandem mass spectrometry; IT- ..."
Abstract - Cited by 49 (3 self) - Add to MetaCart
chromatography; ESI, electrospray ionization; MS/MS, tandem mass spectrometry; IT-
(Show Context)

Mutation-Tolerant Protein Identification by Mass Spectrometry

by Pavel A. Pevzner, Vlado Dancík, Chris L. Tang , 2000
"... Database search in tandem mass spectrometry is a powerful tool for protein identification. High-throughput spectral acquisition raises the problem of dealing with genetic variation and peptide modifications within a population of related proteins. A method that cross-correlates and clusters related ..."
Abstract - Cited by 48 (5 self) - Add to MetaCart
Database search in tandem mass spectrometry is a powerful tool for protein identification. High-throughput spectral acquisition raises the problem of dealing with genetic variation and peptide modifications within a population of related proteins. A method that cross-correlates and clusters related spectra in large collections of uncharacterized spectra (i.e., from normal and diseased individuals) would be very valuable in functional proteomics. This problem is far from being simple since very similar peptides may have very different spectra. We introduce a new notion of spectral similarity that allows one to identify related spectra even if the corresponding peptides have multiple modifications/mutations. Based on this notion, we developed a new algorithm for mutation-tolerant database search as well as a method for cross-correlating related uncharacterized spectra.
(Show Context)

The peptideatlas project

by Frank Desiere, Eric W. Deutsch, Nichole L. King, Alexey I. Nesvizhskii, Parag Mallick, Jimmy Eng, Sharon Chen, James Eddes, Ra N. Loevenich, Ruedi Aebersold - Nucleic Acids Res, 34(Database issue):D655–8 , 2006
"... The completion of the sequencing of the human genome and the concurrent, rapid development of high-throughput proteomic methods have resulted in an increasing need for automated approaches to archive proteomic data in a repository that enables the exchange of data among researchers and also accurate ..."
Abstract - Cited by 47 (2 self) - Add to MetaCart
The completion of the sequencing of the human genome and the concurrent, rapid development of high-throughput proteomic methods have resulted in an increasing need for automated approaches to archive proteomic data in a repository that enables the exchange of data among researchers and also accurate integration with genomic data. Peptide-Atlas
(Show Context)