Archive for January, 2011

Data processing pipelines for comprehensive profiling of proteomics samples by label-free LC-MS for biomarker discovery.

Authors: Christin C, Bischoff R, Horvatovich P
Label-free quantitative LC-MS profiling of complex body fluids has become an important analytical tool for biomarker and biological knowledge discovery in the past decade. Accurate processing, statistical analysis and validation of acquired data diversified by the different types of mass spectrometers, mass spectrometer parameter settings and applied sample preparation steps are essential to answer complex life science research questions and understand the molecular mechanism of disease onset and developments. This review provides insight into the main modules of label-free data processing pipelines with statistical analysis and validation and discusses recent developments. Special emphasis is devoted to quality control methods, performanc…

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Transcriptome profile analysis of flowering molecular processes of early flowering trifoliate orange mutant and the wild-type [Poncirus trifoliata (L.) Raf.] by massively parallel signature sequencing

Conclusion:
Our results provide a foundation for comparative gene expression studies between WT and precocious trifoliate orange. Additionally, a number of candidate genes required for the early flowering process of precocious trifoliate orange were identified. These results provide new insight into the molecular processes regulating flowering time in citrus. (Source: BMC Genomics – Latest articles)

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Initial characterization of the human central proteome

Conclusions:
Our data and analysis provide a new and deeper description of the human central proteome compared to previous results thereby extending and complementing our knowledge of commonly expressed human proteins. All the data are made publicly available to help other researchers who, for instance, need to compare or link focused data sets to a common background. (Source: BMC Systems Biology – Latest articles)

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Gepoclu: a software tool for identifying and analyzing gene positional clusters in large-scale gene expression analysis.

Conclusions:
Gepoclu is a useful data-mining tool for exploring relationships among transcriptional data deriving form different sources. It provides an easy interactive environment for analyzing positional clustering behavior of co-expressed genes, and at the same time it is fully programmable, so that it can be customized and extended to support specific analysis needs. (Source: BMC Bioinformatics – Latest articles)

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A genetic algorithm-Bayesian network approach for the analysis of metabolomics and spectroscopic data: application to the rapid detection of Bacillus spores and identification of Bacillus species

Conclusions:
This final compact Bayesian network classification model is parsimonious, computationally fast to run and its graphical visualization allows easy interpretation of the probabilistic relationships among selected biomarkers. In addition, we compare the features selected by the genetic algorithm-Bayesian network approach with the features selected by partial least squares-discriminant analysis (PLS-DA). The classification accuracy results show that the set of features selected by the GA-BN is far superior to PLS-DA. (Source: BMC Bioinformatics – Latest articles)

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New publication describes creation of a worm Phenotype Ontology

WormBase curators have published a new paper describing a controlled vocabulary for worm phenotypes. The paper is now available at BMC Bioinformatics in provisional form. (Source: WormBase)

MedWorm Message: Watch the new MedWorm demo and find out how to get all the very latest, relevant, organized information daily!

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Log-Linear Modelling of Protein Dipeptide Structure Reveals Interesting Patterns of Side-Chain–Backbone Interactions

It has long been known that the amino-acid sequence of a protein determines its 3-dimensional structure, but accurate ab initio prediction of structure from sequence remains elusive. We gain insight into local protein structure conformation by studying the relationship of dihedral angles in pairs of residues in protein sequences (dipeptides). We adopt a contingency table approach, exploring a targeted set of hypotheses through log-linear modelling to detect patterns of association of these dihedral angles in all dipeptides considered. Our models indicate a substantial association of the side-chain conformation of the first residue with the backbone conformation of the second residue (side-to-back interaction) as well as a weaker but still significant association of the backbone conformatio…

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BioGrid Australia facilitates collaborative medical and bioinformatics research across hospitals and medical research institutes by linking data from diverse disease and data types

This article reviews BioGrid’s first seven years and how it has overcome 9 of its top 10 challenges. © 2011 Wiley‐Liss, Inc. (Source: Human Mutation)

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Deep RNA sequencing analysis of readthrough gene fusions in human prostate adenocarcinoma and reference samples

Conclusions:
Deep transcriptional sequencing and analysis with targeted and spliced alignment methods can effectively identify TIC events across the genome in individual tissues. Prostate and reference samples exhibit a wide range of TIC events, involving more genes than estimated previously using ESTs. Tissue specificity of TIC events is correlated with expression patterns of the upstream gene. Some TIC events, such as MSMB-NCOA4, may play functional roles in cancer. (Source: BioMed Central)

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Worm Phenotype Ontology: integrating phenotype data within and beyond the C. elegans community

Conclusions:
We provide a phenotype ontology (WPO) that will help to facilitate data retrieval, and cross-species comparisons within the nematode community. In the larger scientific community, the WPO will permit data integration, and interoperability across the different Model Organism Databases (MODs) and other biological databases. This standardized phenotype ontology will therefore allow for more complex data queries and enhance bioinformatic analyses. (Source: BMC Bioinformatics – Latest articles)

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