Briefings in Functional Genomics and Proteomics

Publisher: Oxford University Press

Journal description

Briefings in Functional Genomics & Proteomics is an international forum for researchers and educators in the life sciences and reviews the techniques, protocols and approaches in genome and proteome research. The journal aims to provide a centralised resource for researchers in the fields of genomics and proteomics as well as give guidance to scientists new to these areas.

Current impact factor: 0.00

Impact Factor Rankings

Additional details

5-year impact 0.00
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Website Briefings in Functional Genomics and Proteomics website
Other titles Briefings in functional genomics & proteomics (Online), Briefings in functional genomics and proteomics
ISSN 1473-9550
OCLC 50167012
Material type Document, Periodical, Internet resource
Document type Internet Resource, Computer File, Journal / Magazine / Newspaper

Publisher details

Oxford University Press

  • Pre-print
    • Author can archive a pre-print version
  • Post-print
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  • Restrictions
    • 12 months embargo on science, technology, medicine articles
    • 2 years embargo on arts and humanities articles
    • Some titles may have different embargoes
  • Conditions
    • Pre-print can only be posted prior to acceptance
    • Pre-print must be accompanied by set statement (see link)
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    • Pre-print on author's personal website, employer website, free public server or pre-prints in subject area
    • Post-print in Institutional repositories or Central repositories
    • Publisher version cannot be used except for Nucleic Acids Research articles
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    • Must link to publisher version
    • Set phrase to accompany archived copy (see policy)
    • Articles in some journals can be made Open Access on payment of additional charge
    • Eligible UK authors may deposit in OpenDepot
    • Publisher will deposit on behalf of NIH funded authors to PubMed Central, Nucleic Acids Research authors must pay their fee first
    • Some titles may use different policies
  • Classification
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Publications in this journal

  • [Show abstract] [Hide abstract]
    ABSTRACT: While genome sequencing efforts reveal the basic building blocks of life, a genome sequence alone is insufficient for elucidating biological function. Genome annotation--the process of identifying genes and assigning function to each gene in a genome sequence--provides the means to elucidate biological function from sequence. Current state-of-the-art high-throughput genome annotation uses a combination of comparative (sequence similarity data) and non-comparative (ab initio gene prediction algorithms) methods to identify protein-coding genes in genome sequences. Because approaches used to validate the presence of predicted protein-coding genes are typically based on expressed RNA sequences, they cannot independently and unequivocally determine whether a predicted protein-coding gene is translated into a protein. With the ability to directly measure peptides arising from expressed proteins, high-throughput liquid chromatography-tandem mass spectrometry-based proteomics approaches can be used to verify coding regions of a genomic sequence. Here, we highlight several ways in which high-throughput tandem mass spectrometry-based proteomics can improve the quality of genome annotations and suggest that it could be efficiently applied during the gene calling process so that the improvements are propagated through the subsequent functional annotation process.
    Briefings in Functional Genomics and Proteomics 02/2008; 7(1):50-62. DOI:10.1093/bfgp/eln010
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    ABSTRACT: Acquired or innate resistance to chemotherapy is a major drawback of cancer therapeutics, which is frequently seen in epithelial cancers. However, the molecular mechanisms underlying chemotherapy resistance remain poorly understood. The mitochondrial pathway is a critical death pathway common to many different types of chemotherapy. Aberrations in this pathway can result in resistance to chemotherapy. The Bcl-2 family of proteins control commitment to programmed cell death by mitochondrial apoptosis. In this review, we will summarize the strategies in determining the components of apoptotic defects responsible for chemotherapy resistance, mainly focused on Bcl-2 protein network.
    Briefings in Functional Genomics and Proteomics 02/2008; 7(1):27-34. DOI:10.1093/bfgp/eln002
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    ABSTRACT: Biomarker discovery in clinical proteomics is being performed on relatively large patient cohorts by utilizing the high throughput of laser desorption/ionization mass spectrometry (MALDI- and SELDI-TOF-MS). Dealing directly with patient samples as opposed to working in cell or animal systems requires a host of considerations both before and after mass spectrometric analysis to obtain robust biomarker candidates. The challenges associated with the heterogeneity of typical samples are amplified by the ability to detect hundreds to thousands of proteins simultaneously. Adherence to protocols and consistency, however, can ensure optimal results. A study starts necessarily with a relevant clinical question and proceeds to a planning phase where sample availability, statistical test selection, logistics and bias reduction are key points. The physical analysis requires consistency and standardized protocols that are helped significantly through automation. Data analysis is broken into two stages, screening and final testing, which can detect either single candidates or a pattern of proteins. Biomarker identification can be performed at this point and will help significantly in the last stage, interpretation. Replication should be performed in an independent sample set in a separate study. The candidate biomarkers from an initial study give a wealth of information that can help to pinpoint patient subpopulations for a more exhaustive proteomic study using complementary platforms with limited capacity but extremely high information content. A clinical proteomics pilot project can also lead to better selection of model systems by providing a direct link with patient samples.
    Briefings in Functional Genomics and Proteomics 02/2008; 7(1):74-83. DOI:10.1093/bfgp/eln005
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    ABSTRACT: Natural killer (NK) cells are lymphocytes with an innate ability to recognize and kill infected cells and tumour cells. Unlike B and T cells, NK cells do not express an antigen receptor. Instead, NK cells detect changes in the phenotype of the target cell surface; malignant transformation or infection resulting in the loss or gain of particular molecules that are detected by inhibitory or activating receptors on the NK cell surface. The identification and characterization of NK cells and their receptors was made possible by monoclonal antibody technology. The ease with which genes and gene products can now be identified and manipulated has accelerated our understanding of NK cell function. Furthermore, gene and protein profiling studies are beginning to refine our understanding of NK cells, their interactions with other cells and their effector mechanisms. This review illustrates some of the basic features of NK cell biology and highlights the contribution made by post-genomic technology in defining the molecular mechanisms by which NK cells identify and kill susceptible targets.
    Briefings in Functional Genomics and Proteomics 02/2008; 7(1):8-16. DOI:10.1093/bfgp/elm037
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    ABSTRACT: Conventional molecular and genetic methods for studying cancer are limited to the analysis of one locus at a time. A cluster of genes that are regulated together can be identified by DNA microarray, and the functional relationships can uncover new aspects of cancer biology. Breast cancer can be used to provide a model to demonstrate the current approaches to the molecular analysis of cancer. Meta-analysis is an important tool for the identification and validation of differentially expressed genes to increase power in clinical and biological studies across different sets of data. Recently, meta-analysis approaches have been applied to large collections of microarray datasets to investigate molecular commonalities of multiple cancer types not only to find the common molecular pathways in tumour development but also to compare the individual datasets to other cancer datasets to identify new sets of genes. Several investigators agree that microarray results should be validated. One commonly used method is quantitative reverse transcription PCR (qRT-PCR) to validate the expression profiles of the target genes obtained through microarray experiments. qRT-PCR is attractive for clinical use, since it can be automated and performed on fresh or archived formalin-fixed, paraffin-embedded tissue samples. The outcome of these analyses might accelerate the application of basic research findings into daily clinical practice through translational research and may have an impact on foreseeing the clinical outcome, predicting tumour response to specific therapy, identification of new prognostic biomarkers, discovering targets for the development of novel therapies and providing further insights into tumour biology.
    Briefings in Functional Genomics and Proteomics 02/2008; 7(1):1-7. DOI:10.1093/bfgp/eln009
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    ABSTRACT: Directionality in protein signalling networks is due to modulated protein-protein interactions and is fundamental for proper signal progression and response to external and internal cues. This property is in part enabled by linear motifs embedding post-translational modification sites. These serve as recognition sites, guiding phosphorylation by kinases and subsequent binding of modular domains (e.g. SH2 and BRCT). Characterization of such modification-modulated interactions on a proteome-wide scale requires extensive computational and experimental analysis. Here, we review the latest advances in methods for unravelling phosphorylation-mediated cellular interaction networks. In particular, we will discuss how the combination of new quantitative mass-spectrometric technologies and computational algorithms together are enhancing mapping of these largely uncharted dynamic networks. By combining quantitative measurements of phosphorylation events with computational approaches, we argue that systems level models will help to decipher complex diseases through the ability to predict cellular systems trajectories.
    Briefings in Functional Genomics and Proteomics 02/2008; 7(1):17-26. DOI:10.1093/bfgp/eln001
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    ABSTRACT: Cyanobacteria, which are considered to be the chloroplast precursors, are significant contributors to global photosynthetic productivity. The ample variety of membrane and soluble proteins containing different metals (mainly, iron and copper) has made these organisms develop a complex homeostasis with different mechanisms and tight regulation processes to fulfil their metal requirements in a changing environment. Cell metabolism is so adapted as to synthesize alternative proteins depending on the relative metal availabilities. In particular, plastocyanin, a copper protein, and cytochrome c(6), a haem protein, can replace each other to play the same physiological role as electron carriers in photosynthesis and respiration, with the synthesis of one protein or another being regulated by copper concentration in the medium. The unicellular cyanobacterium Synechocystis sp. PCC 6803 has been widely used as a model system because of completion of its genome sequence and the ease of its genetic manipulation, with a lot of proteomic work being done. In this review article, we focus on the functional characterization of knockout Synechocystis mutants for plastocyanin and cytochrome c(6), and discuss the ongoing proteomic analyses performed at varying copper concentrations to investigate the cyanobacterial metal homeostasis and cell response to changing environmental conditions.
    Briefings in Functional Genomics and Proteomics 01/2008; 6(4):322-9. DOI:10.1093/bfgp/elm030
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    ABSTRACT: The immunoglobulin superfamily (IgSF) comprises the immunoglobulins (IG), T cell receptors (TR) and proteins that have the common feature of having at least one Ig-like domain. The major histocompatibility complex (MHC) superfamily (MhcSF) comprises, in addition to the MHC, proteins which share the common feature of having Mhc-like domains. IMGT, the international ImMunoGeneTics information system ( has set up a unique numbering system and standardized 2D graphical representations, or IMGT Colliers de Perles, which take into account the structural features of the Ig-like and Mhc-like domains. In this article, we review the IMGT Scientific chart rules for the description of the IgSF (V and C types) and of the MhcSF (G type) domains. These rules are based on the IMGT-ONTOLOGY axioms and concepts and are applicable for the sequence and structure analysis, whatever the species, the IgSF or MhcSF protein, or the chain type. These IMGT Colliers de Perles are particularly useful for antibody engineering, sequence-structure analysis, visualization and comparison of positions for mutations, polymorphisms and contact analysis.
    Briefings in Functional Genomics and Proteomics 01/2008; 6(4):253-64. DOI:10.1093/bfgp/elm032
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    ABSTRACT: Microarray based transcription profiling is now a consolidated methodology and has widespread use in areas such as pharmacogenomics, diagnostics and drug target identification. Large-scale microarray studies are also becoming crucial to a new way of conceiving experimental biology. A main issue in microarray transcription profiling is data analysis and mining. When microarrays became a methodology of general use, considerable effort was made to produce algorithms and methods for the identification of differentially expressed genes. More recently, the focus has switched to algorithms and database development for microarray data mining. Furthermore, the evolution of microarray technology is allowing researchers to grasp the regulative nature of transcription, integrating basic expression analysis with mRNA characteristics, i.e. exon-based arrays, and with DNA characteristics, i.e. comparative genomic hybridization, single nucleotide polymorphism, tiling and promoter structure. In this article, we will review approaches used to detect differentially expressed genes and to link differential expression to specific biological functions.
    Briefings in Functional Genomics and Proteomics 01/2008; 6(4):265-81. DOI:10.1093/bfgp/elm034
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    ABSTRACT: Yeast two-hybrid (Y2H) screening methods are an effective means for the detection of protein-protein interactions. Optimisation and automation has increased the throughput of the method to an extent that allows the systematic mapping of protein-protein interactions on a proteome-wide scale. Since two-hybrid screens fail to detect a great number of interactions, parallel high-throughput approaches are needed for proteome-wide interaction screens. In this review, we discuss and compare different approaches for adaptation of Y2H screening to high-throughput, the limits of the method and possible alternative approaches to complement the mapping of organism-wide protein-protein interactions.
    Briefings in Functional Genomics and Proteomics 01/2008; 6(4):302-12. DOI:10.1093/bfgp/elm035
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    ABSTRACT: A number of fundamental technical developments like the evolvement of oligonucleotide microarrays, new sequencing technologies and gene synthesis have considerably changed the character of genomic biological resource centres in recent years. While genomic biological resource centres traditionally served mainly as providers of sparsely characterized cDNA clones and clone sets, there is nowadays a clear tendency towards well-characterized, high-quality clones. In addition, major new service units like microarray services have developed, which are completely independent of clone collections, reflecting the co-evolution of data generation and technology development. The new technologies require an increasingly higher degree of specialization, data integration and quality standards. Altogether, these developments result in spin-offs of highly specialized biotech companies, some of which will take a prominent position in translational medicine.
    Briefings in Functional Genomics and Proteomics 10/2007; 6(3):163-70. DOI:10.1093/bfgp/elm026
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    ABSTRACT: Modelling and simulation techniques are valuable tools for the understanding of complex biological systems. The design of a computer model necessarily has many diverse inputs, such as information on the model topology, reaction kinetics and experimental data, derived either from the literature, databases or direct experimental investigation. In this review, we describe different data resources, standards and modelling and simulation tools that are relevant to integrative systems biology.
    Briefings in Functional Genomics and Proteomics 10/2007; 6(3):240-51. DOI:10.1093/bfgp/elm027
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    ABSTRACT: The rapidly increasing amount of information on three-dimensional (3D) structures of biological macro-molecules has still an insufficient impact on genome analysis, functional genomics and proteomics as well as on many other fields in biomedicine including disease-related research. There are, however, attempts to make structural data more easily accessible to the bench biologist. As members of the world-wide Protein Data Bank (wwPDB), the RCSB Protein Data Bank (PDB), the Protein Data Bank Japan and the Macromolecular Structure Database are the primary information resources for 3D structures of proteins, nucleic acids, carbohydrates and complexes thereof. In addition, a number of secondary resources have been set up that also provide information on all currently known structures in a relatively comprehensive manner and not focusing on specific features only. They include PDBsum, the OCA browser-database for protein structure/function, the Molecular Modeling Database and the Jena Library of Biological Macromolecules--JenaLib. Both the primary and secondary resources often merge the information in the PDB files with data from other resources and offer additional analysis tools thereby adding value to the original PDB data. Here, we briefly describe these resources from a user's point of view and from a comparative perspective. It is our aim to guide researchers outside the structure biology field in getting the most out of the 3D structure resources.
    Briefings in Functional Genomics and Proteomics 10/2007; 6(3):220-39. DOI:10.1093/bfgp/elm020