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Recent Research Papers of Note in Proteomics: Apr 12, 2007

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Journal: Journal of Proteome Research, March 31 [Epub ahead of print]
Title: Estimating the statistical significance of peptide identifications from shotgun proteomics experiments
Authors: RE Higgs; MD Knierman; AB Freeman; LM Gelbert; ST Patil; JE Hale
 
Authors use a wrapper-based approach “to estimate and control the false discovery rate for peptide identifications using the outputs from multiple commercially available MS/MS search engines,” according to the abstract. The authors say their approach is flexible enough to combine output from multiple search engines with sequence and spectral derived features in a flexible classification model.
 

 
Journal: Journal of Proteome Research, April 3 [Epub ahead of print]
Title: Mining phosphopeptide signal in liquid chromatography-mass spectrometry data for protein phosphorylation analysis
Authors: HY Wu; VS Tsen; PC Liao
 
Authors propose a method of mining phosphopeptide signals generated from a mixture of proteins from LC-MS/MS analysis. Their approach combines dephosphorylation reaction, measurements from Q-TOF MS, and a computing algorithm to differentiate possible phosphopeptide signals from LC-MS analysis.
 

 
Journal: Proceedings of the National Academy of Sciences of the United States of America, April 3
Title: Multiple reaction monitoring for robust quantitative proteomic analysis of cellular signaling networks
Authors: A Wolf-Yadlin; S Hautaniemi; DA Lauffenburger; FM White
 
Authors have developed an MS-based strategy, based on multiple reaction monitoring of stable isotope-labeled peptides, that enables highly reproducible quantification of hundreds of nodes within a signaling network and across multiple conditions. Using their approach, authors quantified temporal phosphorylation profiles of 222 tyrosine phosphorylated peptides across seven time points following EGF treatment. According to the authors, 88 percent of the signaling nodes were reproducibly quantified in four analyses.
 

 
Journal: The Journal of Histochemistry and Cytochemistry: Official Journal of the Histochemistry Society, April 4 [Epub ahead of print]
Title: Proteome analysis of microdissected formalin-fixed and paraffin-embedded tissue specimens
Authors: T Guo; W Wang; PA Rudnick; T Song; J Li; Z Zhuang; RJ Weil; DL Devoe; CS Lee; BM Balgley
 
Authors used combined capillary isoelectric focusing/nano-reversed-phase LC separations, equipped with nano-electrospray ionization-tandem MS, to study proteins extracted from microdissected formalin-fixed and paraffin-embedded blioblastoma tissues using a heat-induced antigen retrieval technique. They identified 14,478 distinct peptides, leading to the identification of 2,733 non-redundant SwissProt protein entries.
 

 
Journal: Journal of chromatography. B, Analytical technologies in the biomedical and life sciences, April 15
Title: Higher dimensional (Hi-D) separation strategies dramatically improve the potential for cancer biomarker detection in serum and plasma
Authors: SA Hoffman; WA Joo; LA Echan; DW Speicher
 
Authors describe methods using more than two dimensions of fraction to profile the low abundance proteome in plasma.
 

 
Journal: Journal of chromatography. B, Analytical technologies in the biomedical and life sciences, April 15
Title: Improvements in the search for potential biomarkers by proteomics: Application of principal component and discriminant analyses for two-dimensional maps evaluation
Authors: AM Rodriguez-Pineiro; FJ Rodriguez-Berrocal; M Paez de la Cadena
 
Authors evaluate the application of multivariate analysis on data obtained from two-dimensional protein maps as a possible improvement in the search for protein markers. They first did a proteomic study of the differential expression of serum N-glycoproteins in colorectal cancer patients. Then they applied principal component analysis to assess the utility of the 2D protein pattern and certain subsets of spots to distinguish control and case samples, and tested the accuracy of the classification model by linear discriminant analysis. 
 

 
Journal: Journal of Computational Chemistry, April 30
Title: Computational chemistry approach to protein kinase recognition using 3D stochastic van der Waals spectral moments
Authors: H Gonzalez-Diaz; L Saiz-Urra; R Molina; Y Gonzalez-Diaz; A Sanchez-Gonzalez
 
Authors present a new class of 3D structure molecular descriptors for folded proteins named the stochastic van der Waals spectral moments. They chose kinase recognition because of the lack of computational chemistry studies in the area.
 

 
Journal: Biostatistics, April
Title: A statistical method for chromatographic alignment of LC-MS data
Authors: P Wang; H Tang; MP Fitzgibbon; M McIntosh; M Coram; H Zhang; E Yi; R Aebersold
 
Authors propose a new method called Peptide Element Alignment, or PETAL, that uses raw spectrum data and detected peak to simultaneously align features from multiple LC-MS experiments. PETAL creates spectrum elements, with each element representing the mass spectrum of a single peptide in a single scan. Peptides in different LC-MS data are aligned if they can be represented by the same elements.
 

 
Journal: Computers in Biology and Medicine, April
Title: A wavelet-based data pre-processing analysis approach in mass spectrometry
Authors: X Li; J Li; X Yao
 
The approach described by the authors applies wavelet-based transforms to MS data to reduce or eliminate noise from data that are potentially contaminated in acquisition.
 

 
Journal: Proteomics, April
Title: Biomarker clustering to address correlations in proteomic data
Authors: SM Carlson; A Najmi; HJ Cohen
 
Authors propose a preprocessing algorithm that clusters highly correlated features as a way of solving correlated variables that can complicate statistical analyses of proteomics experiments, especially those that use MS for parallel measurements. The approach described in the paper uses Bayes information criterion to select an optimal number of clusters. Statistical analysis of clusters, according to the abstract, benefits from lower noise and reduces the difficulties associated with strongly correlated data.
 

 
Journal: Proteomics, April
Title: Yeast proteome map (update 2006)
Authors: M Perrot; AL Guieysse-Peugeot; A Massoni; C Espagne; S Claverol; RM Silva; P Jeno; M Santos; M Bonneu; H Boucherie
 
Authors systematically identified Saccharomyces cerevisiae proteins separated on 2D gels and report 187 novel protein spots. Authors used mass spectrometry and gene inactivation to perform the identification. The identifications extend the number of protein spots identified on their yeast 2D proteome map to 602, almost half of the detectable spots of the proteome map and correspond to 417 different proteins.
 

 
Journal: Proteins, May 1
Title: PIER: protein interface recognition for structural proteomics
Authors: I Kufareva; L Budagyan; E Raush; M Totrov; R Abagyan
 
Authors describe a method they developed for predicting interfaces from a single protein structure. Their method, called Protein Interface Recognition, is based on local statistical properties of the protein surface derived at the level of atomic groups.
 

 
Journal: Proteins, May 1
Title: Walking through the protein sequence space: towards new generation of the homology modeling
Authors: ZM Frenkel; EN Trifonov
 
Authors propose a new approach “to reveal apparent evolutionary relationships between fragments with similar 3D structures by finding ‘intermediate’ sequences in the proteomic database,” according to the abstract. Instead of looking for homologies and intermediates for a whole protein domain, the authors built a chain of intermediate short sequences, allowing them to link similar structural modules of proteins belonging to the same or different families.

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