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Proteomics

Section edited by John Garavelli

This section incorporates all aspects of proteomic analysis including but not limited to: methods and applications for the analysis of post-translational modifications, proteomic, mass spectroscopic, and chemoinformatic data.

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  1. Content type: Methodology article

    Studies of functional modules in a Protein-Protein Interaction (PPI) network contribute greatly to the understanding of biological mechanisms. With the development of computing science, computational approache...

    Authors: Jun Zhong Ji, Lang Jiao, Cui Cui Yang, Jia Wei Lv and Ai Dong Zhang

    Citation: BMC Bioinformatics 2014 15:325

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  2. Content type: Research article

    DNA-binding proteins are vital for the study of cellular processes. In recent genome engineering studies, the identification of proteins with certain functions has become increasingly important and needs to be...

    Authors: Li Song, Dapeng Li, Xiangxiang Zeng, Yunfeng Wu, Li Guo and Quan Zou

    Citation: BMC Bioinformatics 2014 15:298

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  3. Content type: Software

    In quantitative proteomics, peptide mapping is a valuable approach to combine positional quantitative information with topographical and domain information of proteins. Quantitative proteomic analysis of cell ...

    Authors: Pavankumar Videm, Deepika Gunasekaran, Bernd Schröder, Bettina Mayer, Martin L Biniossek and Oliver Schilling

    Citation: BMC Bioinformatics 2014 15:207

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  4. Content type: Research article

    Over the last 20 years in biotechnology, the production of recombinant proteins has been a crucial bioprocess in both biopharmaceutical and research arena in terms of human health, scientific impact and econom...

    Authors: Narjeskhatoon Habibi, Siti Z Mohd Hashim, Alireza Norouzi and Mohammed Razip Samian

    Citation: BMC Bioinformatics 2014 15:134

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  5. Content type: Methodology article

    Principal component analysis (PCA) has been widely used to visualize high-dimensional metabolomic data in a two- or three-dimensional subspace. In metabolomics, some metabolites (e.g., the top 10 metabolites) ...

    Authors: Hiroyuki Yamamoto, Tamaki Fujimori, Hajime Sato, Gen Ishikawa, Kenjiro Kami and Yoshiaki Ohashi

    Citation: BMC Bioinformatics 2014 15:51

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  6. Content type: Methodology article

    An ion mobility (IM) spectrometer coupled with a multi-capillary column (MCC) measures volatile organic compounds (VOCs) in the air or in exhaled breath. This technique is utilized in several biotechnological ...

    Authors: Marianna D’Addario, Dominik Kopczynski, Jörg Ingo Baumbach and Sven Rahmann

    Citation: BMC Bioinformatics 2014 15:25

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  7. Content type: Methodology article

    The goal of many proteomics experiments is to determine the abundance of proteins in biological samples, and the variation thereof in various physiological conditions. High-throughput quantitative proteomics, ...

    Authors: Ashlee M Benjamin, J Will Thompson, Erik J Soderblom, Scott J Geromanos, Ricardo Henao, Virginia B Kraus, M Arthur Moseley and Joseph E Lucas

    Citation: BMC Bioinformatics 2013 14:364

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  8. Content type: Research article

    Determining sample sizes for metabolomic experiments is important but due to the complexity of these experiments, there are currently no standard methods for sample size estimation in metabolomics. Since pilot...

    Authors: Gift Nyamundanda, Isobel Claire Gormley, Yue Fan, William M Gallagher and Lorraine Brennan

    Citation: BMC Bioinformatics 2013 14:338

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  9. Content type: Methodology article

    Comprehensive protein-protein interaction (PPI) maps are a powerful resource for uncovering the molecular basis of genetic interactions and providing mechanistic insights. Over the past decade, high-throughput...

    Authors: George Tucker, Po-Ru Loh and Bonnie Berger

    Citation: BMC Bioinformatics 2013 14:299

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  10. Content type: Software

    Cheminformaticians have to routinely process and analyse libraries of small molecules. Among other things, that includes the standardization of molecules, calculation of various descriptors, visualisation of m...

    Authors: Stephan Beisken, Thorsten Meinl, Bernd Wiswedel, Luis F de Figueiredo, Michael Berthold and Christoph Steinbeck

    Citation: BMC Bioinformatics 2013 14:257

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  11. Content type: Methodology article

    Dynamic protein phosphorylation is an essential regulatory mechanism in various organisms. In this capacity, it is involved in a multitude of signal transduction pathways. Kinase-specific phosphorylation data ...

    Authors: Liang Zou, Mang Wang, Yi Shen, Jie Liao, Ao Li and Minghui Wang

    Citation: BMC Bioinformatics 2013 14:247

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  12. Content type: Methodology article

    Subunit vaccines based on recombinant proteins have been effective in preventing infectious diseases and are expected to meet the demands of future vaccine development. Computational approach, especially rever...

    Authors: Varun Jaiswal, Sree Krishna Chanumolu, Ankit Gupta, Rajinder S Chauhan and Chittaranjan Rout

    Citation: BMC Bioinformatics 2013 14:211

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  13. Content type: Methodology article

    Many content-based statistical features of secondary structural elements (CBF-PSSEs) have been proposed and achieved promising results in protein structural class prediction, but until now position distributio...

    Authors: Qi Dai, Yan Li, Xiaoqing Liu, Yuhua Yao, Yunjie Cao and Pingan He

    Citation: BMC Bioinformatics 2013 14:152

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  14. Content type: Software

    Despite progress in conventional cancer therapies, cancer is still one of the leading causes of death in industrial nations. Therefore, an urgent need of progress in fighting cancer remains. A promising altern...

    Authors: Joachim von Eichborn, Anna Lena Woelke, Filippo Castiglione and Robert Preissner

    Citation: BMC Bioinformatics 2013 14:127

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  15. Content type: Research article

    Since peak alignment in metabolomics has a huge effect on the subsequent statistical analysis, it is considered a key preprocessing step and many peak alignment methods have been developed. However, existing p...

    Authors: Jaesik Jeong, Xiang Zhang, Xue Shi, Seongho Kim and Changyu Shen

    Citation: BMC Bioinformatics 2013 14:123

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2016 Journal Metrics

  • Citation Impact
    2.448 - 2-year Impact Factor
    3.450 - 5-year Impact Factor
    0.946 - Source Normalized Impact per Paper (SNIP)
    1.467 - SCImago Journal Rank (SJR)

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