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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. Data from discovery proteomic and phosphoproteomic experiments typically include missing values that correspond to proteins that have not been identified in the analyzed sample. Replacing the missing values wi...

    Authors: Matúš Medo, Daniel M. Aebersold and Michaela Medová

    Citation: BMC Bioinformatics 2019 20:563

    Content type: Methodology Article

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  2. Identifying differentially abundant features between different experimental groups is a common goal for many metabolomics and proteomics studies. However, analyzing data from mass spectrometry (MS) is difficul...

    Authors: Yuntong Li, Teresa W.M. Fan, Andrew N. Lane, Woo-Young Kang, Susanne M. Arnold, Arnold J. Stromberg, Chi Wang and Li Chen

    Citation: BMC Bioinformatics 2019 20:501

    Content type: Methodology Article

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  3. Utilization of quantitative proteomics data on the network level is still a challenge in proteomics data analysis. Currently existing models use sophisticated, sometimes hard to implement analysis techniques. ...

    Authors: Éva Csősz, Ferenc Tóth, Mohamed Mahdi, George Tsaprailis, Miklós Emri and József Tőzsér

    Citation: BMC Bioinformatics 2019 20:398

    Content type: Research article

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  4. Molecule identification is a crucial step in metabolomics and environmental sciences. Besides in silico fragmentation, as performed by MetFrag, also machine learning and statistical methods evolved, showing an...

    Authors: Christoph Ruttkies, Steffen Neumann and Stefan Posch

    Citation: BMC Bioinformatics 2019 20:376

    Content type: Research article

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  5. Mass Spectrometry (MS) is a widely used technique in biology research, and has become key in proteomics and metabolomics analyses. As a result, the amount of MS data has significantly increased in recent years...

    Authors: Ruochen Yang, Xi Chen and Idoia Ochoa

    Citation: BMC Bioinformatics 2019 20:368

    Content type: Methodology article

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  6. Essential proteins are distinctly important for an organism’s survival and development and crucial to disease analysis and drug design as well. Large-scale protein-protein interaction (PPI) data sets exist in Sac...

    Authors: Bihai Zhao, Yulin Zhao, Xiaoxia Zhang, Zhihong Zhang, Fan Zhang and Lei Wang

    Citation: BMC Bioinformatics 2019 20:355

    Content type: Research article

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  7. The advent of high-throughput experimental techniques paved the way to genome-wide computational analysis and predictive annotation studies. When considering the joint annotation of a large set of related enti...

    Authors: Stefano Teso, Luca Masera, Michelangelo Diligenti and Andrea Passerini

    Citation: BMC Bioinformatics 2019 20:338

    Content type: Software

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  8. Lipidomics, the comprehensive measurement of lipids within a biological system or substrate, is an emerging field with significant potential for improving clinical diagnosis and our understanding of health and...

    Authors: Jeremy P. Koelmel, Jason A. Cochran, Candice Z. Ulmer, Allison J. Levy, Rainey E. Patterson, Berkley C. Olsen, Richard A. Yost, John A. Bowden and Timothy J. Garrett

    Citation: BMC Bioinformatics 2019 20:217

    Content type: Software

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  9. Advances in high-resolution mass spectrometry facilitate the identification of hundreds of metabolites, thousands of proteins and their post-translational modifications. This remarkable progress poses a challe...

    Authors: Harald Marx and Joshua J. Coon

    Citation: BMC Bioinformatics 2019 20:21

    Content type: Software

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  10. Translational and post-translational control mechanisms in the cell result in widely observable differences between measured gene transcription and protein abundances. Herein, protein complexes are among the m...

    Authors: Morteza H. Chalabi, Vasileios Tsiamis, Lukas Käll, Fabio Vandin and Veit Schwämmle

    Citation: BMC Bioinformatics 2019 20:17

    Content type: Software

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  11. Long non-coding RNA (lncRNA) studies play an important role in the development, invasion, and metastasis of the tumor. The analysis and screening of the differential expression of lncRNAs in cancer and corresp...

    Authors: Rong Zhu, Guangshun Li, Jin-Xing Liu, Ling-Yun Dai and Ying Guo

    Citation: BMC Bioinformatics 2019 20:16

    Content type: Research article

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  12. Hypothetical proteins [HP] are those that are predicted to be expressed in an organism, but no evidence of their existence is known. In the recent past, annotation and curation efforts have helped overcome the...

    Authors: Johny Ijaq, Girik Malik, Anuj Kumar, Partha Sarathi Das, Narendra Meena, Neeraja Bethi, Vijayaraghava Seshadri Sundararajan and Prashanth Suravajhala

    Citation: BMC Bioinformatics 2019 20:14

    Content type: Methodology article

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  13. To further our understanding of immunopeptidomics, improved tools are needed to identify peptides presented by major histocompatibility complex class I (MHC-I). Many existing tools are limited by their relianc...

    Authors: Kevin Michael Boehm, Bhavneet Bhinder, Vijay Joseph Raja, Noah Dephoure and Olivier Elemento

    Citation: BMC Bioinformatics 2019 20:7

    Content type: Methodology article

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  14. To address high-dimensional genomic data, most of the proposed prediction methods make use of genomic data alone without considering clinical data, which are often available and known to have predictive value....

    Authors: Caroline Bazzoli and Sophie Lambert-Lacroix

    Citation: BMC Bioinformatics 2018 19:314

    Content type: Methodology article

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  15. The oxidation of protein-bound methionine to form methionine sulfoxide, has traditionally been regarded as an oxidative damage. However, recent evidences support the view of this reversible reaction as a regul...

    Authors: Juan C. Aledo, Francisco R. Cantón and Francisco J. Veredas

    Citation: BMC Bioinformatics 2017 18:430

    Content type: Research Article

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  16. Lipids are ubiquitous and serve numerous biological functions; thus lipids have been shown to have great potential as candidates for elucidating biomarkers and pathway perturbations associated with disease. Me...

    Authors: Jeremy P. Koelmel, Nicholas M. Kroeger, Candice Z. Ulmer, John A. Bowden, Rainey E. Patterson, Jason A. Cochran, Christopher W. W. Beecher, Timothy J. Garrett and Richard A. Yost

    Citation: BMC Bioinformatics 2017 18:331

    Content type: Software

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  17. Identifying disease correlated features early before large number of molecules are impacted by disease progression with significant abundance change is very advantageous to biologists for developing early dise...

    Authors: Sirajul Salekin, Mehrab Ghanat Bari, Itay Raphael, Thomas G. Forsthuber and Jianqiu (Michelle) Zhang

    Citation: BMC Bioinformatics 2017 18:313

    Content type: Methodology Article

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  18. Characterization of mature protein N-termini by large scale proteomics is challenging. This is especially true for proteins undergoing cleavage of transit peptides when they are targeted to specific organelles...

    Authors: Willy Vincent Bienvenut, Jean-Pierre Scarpelli, Johan Dumestier, Thierry Meinnel and Carmela Giglione

    Citation: BMC Bioinformatics 2017 18:182

    Content type: Methodology article

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  19. Many plant pathogen secretory proteins are known to be elicitors or pathogenic factors,which play an important role in the host-pathogen interaction process. Bioinformatics approaches make possible the large s...

    Authors: Lan Jing, Dandan Guo, Wenjie Hu and Xiaofan Niu

    Citation: BMC Bioinformatics 2017 18:166

    Content type: Research article

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  20. High-throughput proteomics techniques, such as mass spectrometry (MS)-based approaches, produce very high-dimensional data-sets. In a clinical setting one is often interested in how mass spectra differ between...

    Authors: Tim O. F. Conrad, Martin Genzel, Nada Cvetkovic, Niklas Wulkow, Alexander Leichtle, Jan Vybiral, Gitta Kutyniok and Christof Schütte

    Citation: BMC Bioinformatics 2017 18:160

    Content type: Research Article

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  21. High-accuracy mass spectrometry enables near comprehensive quantification of the components of the cellular proteomes, increasingly including their chemically modified variants. Likewise, large-scale libraries...

    Authors: Paolo Cifani, Mojdeh Shakiba, Sagar Chhangawala and Alex Kentsis

    Citation: BMC Bioinformatics 2017 18:153

    Content type: Software

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  22. The classification of samples on a molecular level has manifold applications, from patient classification regarding cancer treatment to phylogenetics for identifying evolutionary relationships between species....

    Authors: Vera Rieder, Bernhard Blank-Landeshammer, Marleen Stuhr, Tilman Schell, Karsten Biß, Laxmikanth Kollipara, Achim Meyer, Markus Pfenninger, Hildegard Westphal, Albert Sickmann and Jörg Rahnenführer

    Citation: BMC Bioinformatics 2017 18:148

    Content type: Research Article

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  23. High throughput metabolomics makes it possible to measure the relative abundances of numerous metabolites in biological samples, which is useful to many areas of biomedical research. However, missing values (M...

    Authors: Jasmit S. Shah, Shesh N. Rai, Andrew P. DeFilippis, Bradford G. Hill, Aruni Bhatnagar and Guy N. Brock

    Citation: BMC Bioinformatics 2017 18:114

    Content type: Methodology article

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  24. Tandem mass spectrometry (MS/MS) followed by database search is a main approach to identify peptides/proteins in proteomic studies. A lot of effort has been devoted to improve the identification accuracy and s...

    Authors: Chunwei Ma, Shaohang Xu, Geng Liu, Xin Liu, Xun Xu, Bo Wen and Siqi Liu

    Citation: BMC Bioinformatics 2017 18:109

    Content type: Methodology article

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  25. Metabolomics offers a unique integrative perspective for health research, reflecting genetic and environmental contributions to disease-related phenotypes. Identifying robust associations in population-based o...

    Authors: Anna C. Reisetter, Michael J. Muehlbauer, James R. Bain, Michael Nodzenski, Robert D. Stevens, Olga Ilkayeva, Boyd E. Metzger, Christopher B. Newgard, William L. Lowe Jr. and Denise M. Scholtens

    Citation: BMC Bioinformatics 2017 18:84

    Content type: Methodology article

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  26. In recent years, successful contact prediction methods and contact-guided ab initio protein structure prediction methods have highlighted the importance of incorporating contact information into protein struct...

    Authors: Badri Adhikari, Jackson Nowotny, Debswapna Bhattacharya, Jie Hou and Jianlin Cheng

    Citation: BMC Bioinformatics 2016 17:517

    Content type: Software

    Published on:

  27. When combined with a clinical outcome variable, the size, complexity and nature of mass-spectrometry proteomics data impose great statistical challenges in the discovery of potential disease-associated biomark...

    Authors: Eleanor Stanley, Eleni Ioanna Delatola, Esther Nkuipou-Kenfack, William Spooner, Walter Kolch, Joost P. Schanstra, Harald Mischak and Thomas Koeck

    Citation: BMC Bioinformatics 2016 17:496

    Content type: Research article

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  28. Proteomics of bacterial pathogens is a developing field exploring microbial physiology, gene expression and the complex interactions between bacteria and their hosts. One of the complications in proteomic appr...

    Authors: Dmitry Ischenko, Dmitry Alexeev, Egor Shitikov, Alexandra Kanygina, Maja Malakhova, Elena Kostryukova, Andrey Larin, Sergey Kovalchuk, Olga Pobeguts, Ivan Butenko, Nikolay Anikanov, Ilya Altukhov, Elena Ilina and Vadim Govorun

    Citation: BMC Bioinformatics 2016 17:450

    Content type: Research Article

    Published on:

  29. Genome-scale models of metabolism and macromolecular expression (ME) significantly expand the scope and predictive capabilities of constraint-based modeling. ME models present considerable computational challe...

    Authors: Laurence Yang, Ding Ma, Ali Ebrahim, Colton J. Lloyd, Michael A. Saunders and Bernhard O. Palsson

    Citation: BMC Bioinformatics 2016 17:391

    Content type: Methodology Article

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  30. Peptide identification based upon mass spectrometry (MS) is generally achieved by comparison of the experimental mass spectra with the theoretically digested peptides derived from a reference protein database....

    Authors: Bo Wen, Shaohang Xu, Ruo Zhou, Bing Zhang, Xiaojing Wang, Xin Liu, Xun Xu and Siqi Liu

    Citation: BMC Bioinformatics 2016 17:244

    Content type: Software

    Published on:

  31. Aptamer-protein interacting pairs play a variety of physiological functions and therapeutic potentials in organisms. Rapidly and effectively predicting aptamer-protein interacting pairs is significant to desig...

    Authors: Lina Zhang, Chengjin Zhang, Rui Gao, Runtao Yang and Qing Song

    Citation: BMC Bioinformatics 2016 17:225

    Content type: Research Article

    Published on:

  32. Proteins are the important molecules which participate in virtually every aspect of cellular function within an organism in pairs. Although high-throughput technologies have generated considerable protein-prot...

    Authors: Yu-An Huang, Zhu-Hong You, Xing Chen, Keith Chan and Xin Luo

    Citation: BMC Bioinformatics 2016 17:184

    Content type: Research article

    Published on:

  33. Understanding the interactions between antibodies and the linear epitopes that they recognize is an important task in the study of immunological diseases. We present a novel computational method for the design...

    Authors: Rob Patro, Raquel Norel, Robert J. Prill, Julio Saez-Rodriguez, Peter Lorenz, Felix Steinbeck, Bjoern Ziems, Mitja Luštrek, Nicola Barbarini, Alessandra Tiengo, Riccardo Bellazzi, Hans-Jürgen Thiesen, Gustavo Stolovitzky and Carl Kingsford

    Citation: BMC Bioinformatics 2016 17:155

    Content type: Research Article

    Published on:

2018 Journal Metrics

  • Citation Impact
    2.511 - 2-year Impact Factor
    2.970 - 5-year Impact Factor
    0.855 - Source Normalized Impact per Paper (SNIP)
    1.374 - SCImago Journal Rank (SJR)

    Usage 
    4,129,368 downloads

    Social Media Impact
    4446 mentions

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