Journal articles: 'Comprehensive proteomics'

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Beck, Martin, Manfred Claassen, and Ruedi Aebersold. "Comprehensive proteomics." Current Opinion in Biotechnology 22, no. 1 (February 2011): 3–8. http://dx.doi.org/10.1016/j.copbio.2010.09.002.

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Donato, P., F. Cacciola, L. Mondello, and P. Dugo. "Comprehensive chromatographic separations in proteomics." Journal of Chromatography A 1218, no. 49 (December 2011): 8777–90. http://dx.doi.org/10.1016/j.chroma.2011.05.070.

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Ji, Qing, Fangshi Zhu, Xuan Liu, Qi Li, and Shi-bing Su. "Recent Advance in Applications of Proteomics Technologies on Traditional Chinese Medicine Research." Evidence-Based Complementary and Alternative Medicine 2015 (2015): 1–13. http://dx.doi.org/10.1155/2015/983139.

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Proteomics technology, a major component of system biology, has gained comprehensive attention in the area of medical diagnosis, drug development, and mechanism research. On the holistic and systemic theory, proteomics has a convergence with traditional Chinese medicine (TCM). In this review, we discussed the applications of proteomic technologies in diseases-TCM syndrome combination researches. We also introduced the proteomic studies on thein vivoandin vitroeffects and underlying mechanisms of TCM treatments using Chinese herbal medicine (CHM), Chinese herbal formula (CHF), and acupuncture. Furthermore, the combined studies of proteomics with other “-omics” technologies in TCM were also discussed. In summary, this report presents an overview of the recent advances in the application of proteomic technologies in TCM studies and sheds a light on the future global and further research on TCM.

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Avram, Oren, Aya Kigel, Anna Vaisman-Mentesh, Sharon Kligsberg, Shai Rosenstein, Yael Dror, Tal Pupko, and Yariv Wine. "PASA: Proteomic analysis of serum antibodies web server." PLOS Computational Biology 17, no. 1 (January 25, 2021): e1008607. http://dx.doi.org/10.1371/journal.pcbi.1008607.

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Motivation A comprehensive characterization of the humoral response towards a specific antigen requires quantification of the B-cell receptor repertoire by next-generation sequencing (BCR-Seq), as well as the analysis of serum antibodies against this antigen, using proteomics. The proteomic analysis is challenging since it necessitates the mapping of antigen-specific peptides to individual B-cell clones. Results The PASA web server provides a robust computational platform for the analysis and integration of data obtained from proteomics of serum antibodies. PASA maps peptides derived from antibodies raised against a specific antigen to corresponding antibody sequences. It then analyzes and integrates proteomics and BCR-Seq data, thus providing a comprehensive characterization of the humoral response. The PASA web server is freely available at https://pasa.tau.ac.il and open to all users without a login requirement.

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Masood, Afshan, Hicham Benabdelkamel, and Assim Alfadda. "Obesity Proteomics: An Update on the Strategies and Tools Employed in the Study of Human Obesity." High-Throughput 7, no. 3 (September 12, 2018): 27. http://dx.doi.org/10.3390/ht7030027.

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Proteomics has become one of the most important disciplines for characterizing cellular protein composition, building functional linkages between protein molecules, and providing insight into the mechanisms of biological processes in a high-throughput manner. Mass spectrometry-based proteomic advances have made it possible to study human diseases, including obesity, through the identification and biochemical characterization of alterations in proteins that are associated with it and its comorbidities. A sizeable number of proteomic studies have used the combination of large-scale separation techniques, such as high-resolution two-dimensional gel electrophoresis or liquid chromatography in combination with mass spectrometry, for high-throughput protein identification. These studies have applied proteomics to comprehensive biochemical profiling and comparison studies while using different tissues and biological fluids from patients to demonstrate the physiological or pathological adaptations within their proteomes. Further investigations into these proteome-wide alterations will enable us to not only understand the disease pathophysiology, but also to determine signature proteins that can serve as biomarkers for obesity and related diseases. This review examines the different proteomic techniques used to study human obesity and discusses its successful applications along with its technical limitations.

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Jenkins, Conor, and Benjamin Orsburn. "The Cannabis Proteome Draft Map Project." International Journal of Molecular Sciences 21, no. 3 (January 31, 2020): 965. http://dx.doi.org/10.3390/ijms21030965.

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Recently we have seen a relaxation of the historic restrictions on the use and subsequent research on the Cannabis plants, generally classified as Cannabis sativa and Cannabis indica. What research has been performed to date has centered on chemical analysis of plant flower products, namely cannabinoids and various terpenes that directly contribute to phenotypic characteristics of the female flowers. In addition, we have seen many groups recently completing genetic profiles of various plants of commercial value. To date, no comprehensive attempt has been made to profile the proteomes of these plants. We report herein our progress on constructing a comprehensive draft map of the Cannabis proteome. To date we have identified over 17,000 potential protein sequences. Unfortunately, no annotated genome of Cannabis plants currently exists. We present a method by which “next generation” DNA sequencing output and shotgun proteomics data can be combined to produce annotated FASTA files, bypassing the need for annotated genetic information altogether in traditional proteomics workflows. The resulting material represents the first comprehensive annotated protein FASTA for any Cannabis plant. Using this annotated database as reference we can refine our protein identifications, resulting in the confident identification of 13,000 proteins with putative function. Furthermore, we demonstrate that post-translational modifications play an important role in the proteomes of Cannabis flower, particularly lysine acetylation and protein glycosylation. To facilitate the evolution of analytical investigations into these plant materials, we have created a portal to host resources developed from our proteomic and metabolomic analysis of Cannabis plant material as well as our results integrating these resources.

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Baker, M. S., P. Haynes, A. Len, M. Molloy, A. Lee, R. Saldanha, and J. Chick. "Desperately Seeking Comprehensive Mammalian Membrane Proteomics." Journal of Proteomics & Bioinformatics S2, no. 01 (July 2008): 108–9. http://dx.doi.org/10.4172/jpb.s1000088.

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Dunn, Michael J. "PROTEOMICS - Continued growth and comprehensive coverage." PROTEOMICS 6, no. 1 (January 2006): 1–3. http://dx.doi.org/10.1002/pmic.200690000.

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Hendriks, Ivo A., and Alfred C. O. Vertegaal. "A comprehensive compilation of SUMO proteomics." Nature Reviews Molecular Cell Biology 17, no. 9 (July 20, 2016): 581–95. http://dx.doi.org/10.1038/nrm.2016.81.

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Mirza, Shama P., and Michael Olivier. "Methods and approaches for the comprehensive characterization and quantification of cellular proteomes using mass spectrometry." Physiological Genomics 33, no. 1 (March 2008): 3–11. http://dx.doi.org/10.1152/physiolgenomics.00292.2007.

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Proteomics has been proposed as one of the key technologies in the postgenomic era. So far, however, the comprehensive analysis of cellular proteomes has been a challenge because of the dynamic nature and complexity of the multitude of proteins in cells and tissues. Various approaches have been established for the analyses of proteins in a cell at a given state, and mass spectrometry (MS) has proven to be an efficient and versatile tool. MS-based proteomics approaches have significantly improved beyond the initial identification of proteins to comprehensive characterization and quantification of proteomes and their posttranslational modifications (PTMs). Despite these advances, there is still ongoing development of new technologies to profile and analyze cellular proteomes more completely and efficiently. In this review, we focus on MS-based techniques, describe basic approaches for MS-based profiling of cellular proteomes and analysis methods to identify proteins in complex mixtures, and discuss the different approaches for quantitative proteome analysis. Finally, we briefly discuss novel developments for the analysis of PTMs. Altered levels of PTM, sometimes in the absence of protein expression changes, are often linked to cellular responses and disease states, and the comprehensive analysis of cellular proteome would not be complete without the identification and quantification of the extent of PTMs of proteins.

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Poetsch, Ansgar, and María Inés Marchesini. "Proteomics of Brucella." Proteomes 8, no. 2 (April 22, 2020): 8. http://dx.doi.org/10.3390/proteomes8020008.

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Brucella spp. are Gram negative intracellular bacteria responsible for brucellosis, a worldwide distributed zoonosis. A prominent aspect of the Brucella life cycle is its ability to invade, survive and multiply within host cells. Comprehensive approaches, such as proteomics, have aided in unravelling the molecular mechanisms underlying Brucella pathogenesis. Technological and methodological advancements such as increased instrument performance and multiplexed quantification have broadened the range of proteome studies, enabling new and improved analyses, providing deeper and more accurate proteome coverage. Indeed, proteomics has demonstrated its contribution to key research questions in Brucella biology, i.e., immunodominant proteins, host-cell interaction, stress response, antibiotic targets and resistance, protein secretion. Here, we review the proteomics of Brucella with a focus on more recent works and novel findings, ranging from reconfiguration of the intracellular bacterial proteome and studies on proteomic profiles of Brucella infected tissues, to the identification of Brucella extracellular proteins with putative roles in cell signaling and pathogenesis. In conclusion, proteomics has yielded copious new candidates and hypotheses that require future verification. It is expected that proteomics will continue to be an invaluable tool for Brucella and applications will further extend to the currently ill-explored aspects including, among others, protein processing and post-translational modification.

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Tracz, Joanna, and Magdalena Luczak. "Applying Proteomics and Integrative “Omics” Strategies to Decipher the Chronic Kidney Disease-Related Atherosclerosis." International Journal of Molecular Sciences 22, no. 14 (July 13, 2021): 7492. http://dx.doi.org/10.3390/ijms22147492.

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Patients with chronic kidney disease (CKD) are at increased risk of atherosclerosis and premature mortality, mainly due to cardiovascular events. However, well-known risk factors, which promote “classical” atherosclerosis are alone insufficient to explain the high prevalence of atherosclerosis-related to CKD (CKD-A). The complexity of the molecular mechanisms underlying the acceleration of CKD-A is still to be defied. To obtain a holistic picture of these changes, comprehensive proteomic approaches have been developed including global protein profiling followed by functional bioinformatics analyses of dysregulated pathways. Furthermore, proteomics surveys in combination with other “omics” techniques, i.e., transcriptomics and metabolomics as well as physiological assays provide a solid ground for interpretation of observed phenomena in the context of disease pathology. This review discusses the comprehensive application of various “omics” approaches, with emphasis on proteomics, to tackle the molecular mechanisms underlying CKD-A progression. We summarize here the recent findings derived from global proteomic approaches and underline the potential of utilizing integrative systems biology, to gain a deeper insight into the pathogenesis of CKD-A and other disorders.

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Jamdhade, Mahendra D., Harsh Pawar, Sandip Chavan, Gajanan Sathe, P. K. Umasankar, Kiran N. Mahale, Tanwi Dixit, et al. "Comprehensive Proteomics Analysis of Glycosomes fromLeishmania donovani." OMICS: A Journal of Integrative Biology 19, no. 3 (March 2015): 157–70. http://dx.doi.org/10.1089/omi.2014.0163.

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Goh, Wilson Wen Bin, and Limsoon Wong. "Computational proteomics: designing a comprehensive analytical strategy." Drug Discovery Today 19, no. 3 (March 2014): 266–74. http://dx.doi.org/10.1016/j.drudis.2013.07.008.

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Yao, Tingting, Xiaowei Xu, and Rong Huang. "Recent Advances about the Applications of Click Reaction in Chemical Proteomics." Molecules 26, no. 17 (September 3, 2021): 5368. http://dx.doi.org/10.3390/molecules26175368.

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Despite significant advances in biological and analytical approaches, a comprehensive portrait of the proteome and its dynamic interactions and modifications remains a challenging goal. Chemical proteomics is a growing area of chemical biology that seeks to design small molecule probes to elucidate protein composition, distribution, and relevant physiological and pharmacological functions. Click chemistry focuses on the development of new combinatorial chemical methods for carbon heteroatom bond (C-X-C) synthesis, which have been utilized extensively in the field of chemical proteomics. Click reactions have various advantages including high yield, harmless by-products, and simple reaction conditions, upon which the molecular diversity can be easily and effectively obtained. This paper reviews the application of click chemistry in proteomics from four aspects: (1) activity-based protein profiling, (2) enzyme-inhibitors screening, (3) protein labeling and modifications, and (4) hybrid monolithic column in proteomic analysis.

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Szeto, Christopher, Kevin Kazmierczak, Andrew Chambers, Yeoun Jin Kim, Andrew Nguyen, Iain B. Tan, Stephen Charles Benz, and Charles Joseph Vaske. "Comprehensive -omic analysis of 152 CRC patients allows greater subclassification than CMS or sidedness alone." Journal of Clinical Oncology 37, no. 4_suppl (February 1, 2019): 601. http://dx.doi.org/10.1200/jco.2019.37.4_suppl.601.

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601 Background: Despite relatively high TMB in CRC, immune checkpoint inhibition (ICI) response is lower than in similarly mutated tissues such as melanoma (ORR 10-20% vs. 20-50%). MSI-status can be used to pre-select likely-responders, however MSI is rare. There is a need to guide ICI candidacy in CRC. Four transcriptomic-based CRC consensus molecular subtypes (CMS) have been described with ad hocclinical associations. We sought to confirm these subtypes in proteomic assays and their clinical associations. Methods: 152 CRC tumors from the National Cancer Centre Singapore were available for analysis. Tumor/normal-paired DNAseq (WGS or WES) and deep RNAseq was performed. Mass-spec based global proteomics was successfully performed on 143/152 samples. Consensus between RNAseq and global proteomics was confirmed by correlation significance analysis. MSI-status was determined by both PCR and WGS/WES profiles. CMS types, checkpoint expression, and immune-infiltration deconvolution were calculated upon RNAseq data. A CMS-like clustering of proteomic data was identified by analyzing homogeneity of candidate clusterings with CMS types. Significant enrichment for MSI, immune status, CMS types, and clinical covariates was analyzed. Results: DNAseq-based MSI and PCR-based MSI were statistically equivalent (adj. p < 1.4E-14). 3075/5135 genes were significantly correlated between RNAseq and global proteomic assays. The most correlated genes within COSMIC cancer-related genes were enriched for MHC binding processes. Clustering of immune-expression deconvolution bifurcated into hot and cold tumors. Significant association was found between CMS1, MSI, transverse sides, and being immune hot. Conversely, CMS2 was found to be significantly MSS, left-sided, and immune cold. A semi-supervised clustering of global proteomic data significantly recapitulated some CMS subtypes, but grouped CMS1 (MSI enriched) and CMS3 (Ras mt enriched) subtypes. Genes driving this association were significantly enriched for ECM organization. Conclusions: CMS1 tumors are the best candidates for ICI therapy. CMS3 co-clusters with CMS1 in ECM genes within proteomic data, warranting further research of CMS3 ICI outcomes.

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Matsumoto, Naomi, Junji Ezaki, Masaaki Komatsu, Katsuyuki Takahashi, Reiko Mineki, Hikari Taka, Mika Kikkawa, et al. "Comprehensive proteomics analysis of autophagy-deficient mouse liver." Biochemical and Biophysical Research Communications 368, no. 3 (April 2008): 643–49. http://dx.doi.org/10.1016/j.bbrc.2008.01.112.

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Fossati, Andrea, Alicia L. Richards, Kuei-Ho Chen, Devan Jaganath, Adithya Cattamanchi, Joel D. Ernst, and Danielle L. Swaney. "Toward Comprehensive Plasma Proteomics by Orthogonal Protease Digestion." Journal of Proteome Research 20, no. 8 (July 28, 2021): 4031–40. http://dx.doi.org/10.1021/acs.jproteome.1c00357.

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Pruess, Manuela, and Rolf Apweiler. "Bioinformatics Resources for In Silico Proteome Analysis." Journal of Biomedicine and Biotechnology 2003, no. 4 (2003): 231–36. http://dx.doi.org/10.1155/s1110724303209219.

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In the growing field of proteomics, tools for the in silico analysis of proteins and even of whole proteomes are of crucial importance to make best use of the accumulating amount of data. To utilise this data for healthcare and drug development, first the characteristics of proteomes of entire species—mainly the human—have to be understood, before secondly differentiation between individuals can be surveyed. Specialised databases about nucleic acid sequences, protein sequences, protein tertiary structure, genome analysis, and proteome analysis represent useful resources for analysis, characterisation, and classification of protein sequences. Different from most proteomics tools focusing on similarity searches, structure analysis and prediction, detection of specific regions, alignments, data mining, 2D PAGE analysis, or protein modelling, respectively, comprehensive databases like the proteome analysis database benefit from the information stored in different databases and make use of different protein analysis tools to provide computational analysis of whole proteomes.

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Moghieb, Ahmed, Geremy Clair, Hugh D. Mitchell, Joseph Kitzmiller, Erika M. Zink, Young-Mo Kim, Vladislav Petyuk, et al. "Time-resolved proteome profiling of normal lung development." American Journal of Physiology-Lung Cellular and Molecular Physiology 315, no. 1 (July 1, 2018): L11—L24. http://dx.doi.org/10.1152/ajplung.00316.2017.

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Biochemical networks mediating normal lung morphogenesis and function have important implications for ameliorating morbidity and mortality in premature infants. Although several transcript-level studies have examined normal lung development, corresponding protein-level analyses are lacking. Here we performed proteomics analysis of murine lungs from embryonic to early adult ages to identify the molecular networks mediating normal lung development. We identified 8,932 proteins, providing a deep and comprehensive view of the lung proteome. Analysis of the proteomics data revealed discrete modules and the underlying regulatory and signaling network modulating their expression during development. Our data support the cell proliferation that characterizes early lung development and highlight responses of the lung to exposure to a nonsterile oxygen-rich ambient environment and the important role of lipid (surfactant) metabolism in lung development. Comparison of dynamic regulation of proteomic and recent transcriptomic analyses identified biological processes under posttranscriptional control. Our study provides a unique proteomic resource for understanding normal lung formation and function and can be freely accessed at Lungmap.net.

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Zhang, Qing, Ayumu Taguchi, Mark Schliekelman, Chee-Hong Wong, Alice Chin, Rork Kuick, David E. Misek, and Samir Hanash. "Comprehensive Proteomic Profiling of Aldehyde Dehydrogenases in Lung Adenocarcinoma Cell Lines." International Journal of Proteomics 2011 (October 29, 2011): 1–8. http://dx.doi.org/10.1155/2011/145010.

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We have explored the potential of proteomic profiling to contribute to the delineation of the range of expression and subcellular localization of aldehyde dehydrogenases (ALDHs) in lung adenocarcinoma. In-depth quantitative proteomics was applied to 40 lung adenocarcinoma cell lines resulting in the identification of the known members of the ALDH family. Substantial heterogeneity in the level and occurrence of ALDHs in total lysates and on the cell surface and in their release into the culture media was observed based on mass spectrometry counts. A distinct pattern of expression of ALDHs was observed in cells exhibiting epithelial features relative to cells exhibiting mesenchymal features. Strikingly elevated levels of ALDH1A1 were observed in two cell lines. We also report on the occurrence of an immune response to ALDH1A1 in lung cancer.

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Maxwell, Karen L., and Lori Frappier. "Viral Proteomics." Microbiology and Molecular Biology Reviews 71, no. 2 (June 2007): 398–411. http://dx.doi.org/10.1128/mmbr.00042-06.

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SUMMARY Viruses have long been studied not only for their pathology and associated disease but also as model systems for molecular processes and as tools for identifying important cellular regulatory proteins and pathways. Recent advances in mass spectrometry methods coupled with the development of proteomic approaches have greatly facilitated the detection of virion components, protein interactions in infected cells, and virally induced changes in the cellular proteome, resulting in a more comprehensive understanding of viral infection. In addition, a rapidly increasing number of high-resolution structures for viral proteins have provided valuable information on the mechanism of action of these proteins as well as aided in the design and understanding of specific inhibitors that could be used in antiviral therapies. In this paper, we discuss proteomic studies conducted on all eukaryotic viruses and bacteriophages, covering virion composition, viral protein structures, virus-virus and virus-host protein interactions, and changes in the cellular proteome upon viral infection.

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Wareth, Gamal, Mathias W. Pletz, Heinrich Neubauer, and Jayaseelan Murugaiyan. "Proteomics of Brucella: Technologies and Their Applications for Basic Research and Medical Microbiology." Microorganisms 8, no. 5 (May 20, 2020): 766. http://dx.doi.org/10.3390/microorganisms8050766.

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Brucellosis is a global zoonosis caused by Gram-negative, facultative intracellular bacteria of the genus Brucella (B.). Proteomics has been used to investigate a few B. melitensis and B. abortus strains, but data for other species and biovars are limited. Hence, a comprehensive analysis of proteomes will significantly contribute to understanding the enigmatic biology of brucellae. For direct identification and typing of Brucella, matrix-assisted laser desorption ionization—time of flight mass spectrometry (MALDI—TOF MS) has become a reliable tool for routine diagnosis due to its ease of handling, price and sensitivity highlighting the potential of proteome-based techniques. Proteome analysis will also help to overcome the historic but still notorious Brucella obstacles of infection medicine, the lack of safe and protective vaccines and sensitive serologic diagnostic tools by identifying the most efficient protein antigens. This perspective summarizes past and recent developments in Brucella proteomics with a focus on species identification and serodiagnosis. Future applications of proteomics in these fields are discussed.

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Reddy, Panga Jaipal, Sandipan Ray, Gajanan J. Sathe, Akshada Gajbhiye, T. S. Keshava Prasad, Srikanth Rapole, Dulal Panda, and Sanjeeva Srivastava. "A comprehensive proteomic analysis of totarol induced alterations in Bacillus subtilis by multipronged quantitative proteomics." Journal of Proteomics 114 (January 2015): 247–62. http://dx.doi.org/10.1016/j.jprot.2014.10.025.

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Bhawal, Ruchika, Ann L. Oberg, Sheng Zhang, and Manish Kohli. "Challenges and Opportunities in Clinical Applications of Blood-Based Proteomics in Cancer." Cancers 12, no. 9 (August 27, 2020): 2428. http://dx.doi.org/10.3390/cancers12092428.

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Blood is a readily accessible biofluid containing a plethora of important proteins, nucleic acids, and metabolites that can be used as clinical diagnostic tools in diseases, including cancer. Like the on-going efforts for cancer biomarker discovery using the liquid biopsy detection of circulating cell-free and cell-based tumor nucleic acids, the circulatory proteome has been underexplored for clinical cancer biomarker applications. A comprehensive proteome analysis of human serum/plasma with high-quality data and compelling interpretation can potentially provide opportunities for understanding disease mechanisms, although several challenges will have to be met. Serum/plasma proteome biomarkers are present in very low abundance, and there is high complexity involved due to the heterogeneity of cancers, for which there is a compelling need to develop sensitive and specific proteomic technologies and analytical platforms. To date, liquid chromatography mass spectrometry (LC-MS)-based quantitative proteomics has been a dominant analytical workflow to discover new potential cancer biomarkers in serum/plasma. This review will summarize the opportunities of serum proteomics for clinical applications; the challenges in the discovery of novel biomarkers in serum/plasma; and current proteomic strategies in cancer research for the application of serum/plasma proteomics for clinical prognostic, predictive, and diagnostic applications, as well as for monitoring minimal residual disease after treatments. We will highlight some of the recent advances in MS-based proteomics technologies with appropriate sample collection, processing uniformity, study design, and data analysis, focusing on how these integrated workflows can identify novel potential cancer biomarkers for clinical applications.

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Guo, Xiaofeng, David C. Trudgian, Andrew Lemoff, Sivaramakrishna Yadavalli, and Hamid Mirzaei. "Confetti: A Multiprotease Map of theHeLaProteome for Comprehensive Proteomics." Molecular & Cellular Proteomics 13, no. 6 (April 2, 2014): 1573–84. http://dx.doi.org/10.1074/mcp.m113.035170.

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Subong, Bryan John J., Arturo O. Lluisma, Rhodora V. Azanza, and Lilibeth A. Salvador-Reyes. "Differentiating Two Closely Related Alexandrium Species Using Comparative Quantitative Proteomics." Toxins 13, no. 1 (December 23, 2020): 7. http://dx.doi.org/10.3390/toxins13010007.

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Alexandrium minutum and Alexandrium tamutum are two closely related harmful algal bloom (HAB)-causing species with different toxicity. Using isobaric tags for relative and absolute quantitation (iTRAQ)-based quantitative proteomics and two-dimensional differential gel electrophoresis (2D-DIGE), a comprehensive characterization of the proteomes of A. minutum and A. tamutum was performed to identify the cellular and molecular underpinnings for the dissimilarity between these two species. A total of 1436 proteins and 420 protein spots were identified using iTRAQ-based proteomics and 2D-DIGE, respectively. Both methods revealed little difference (10–12%) between the proteomes of A. minutum and A. tamutum, highlighting that these organisms follow similar cellular and biological processes at the exponential stage. Toxin biosynthetic enzymes were present in both organisms. However, the gonyautoxin-producing A. minutum showed higher levels of osmotic growth proteins, Zn-dependent alcohol dehydrogenase and type-I polyketide synthase compared to the non-toxic A. tamutum. Further, A. tamutum had increased S-adenosylmethionine transferase that may potentially have a negative feedback mechanism to toxin biosynthesis. The complementary proteomics approach provided insights into the biochemistry of these two closely related HAB-causing organisms. The identified proteins are potential biomarkers for organismal toxicity and could be explored for environmental monitoring.

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Choi, Woonyoung, Sonya W. Song, and Wei Zhang. "Understanding Cancer through Proteomics." Technology in Cancer Research & Treatment 1, no. 4 (August 2002): 221–30. http://dx.doi.org/10.1177/153303460200100402.

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Proteomics is a rapidly expanding discipline that aims to gain a comprehensive understanding of the expressions, modification, interactions, and regulation of proteins in cells. New high-throughput technologies, such as protein chips and isotope-coded affinity tag peptide labeling, coupled with classic technologies such as two-dimensional gel electrophoresis and mass spectrometry, complement genomic technologies, providing cancer researchers with powerful tools for cancer diagnosis and prognosis and for the identification of targets for therapy.

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Smythers, Amanda L., and Leslie M. Hicks. "Mapping the plant proteome: tools for surveying coordinating pathways." Emerging Topics in Life Sciences 5, no. 2 (February 23, 2021): 203–20. http://dx.doi.org/10.1042/etls20200270.

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Plants rapidly respond to environmental fluctuations through coordinated, multi-scalar regulation, enabling complex reactions despite their inherently sessile nature. In particular, protein post-translational signaling and protein–protein interactions combine to manipulate cellular responses and regulate plant homeostasis with precise temporal and spatial control. Understanding these proteomic networks are essential to addressing ongoing global crises, including those of food security, rising global temperatures, and the need for renewable materials and fuels. Technological advances in mass spectrometry-based proteomics are enabling investigations of unprecedented depth, and are increasingly being optimized for and applied to plant systems. This review highlights recent advances in plant proteomics, with an emphasis on spatially and temporally resolved analysis of post-translational modifications and protein interactions. It also details the necessity for generation of a comprehensive plant cell atlas while highlighting recent accomplishments within the field.

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Chen, Yanyu, Wenyun Hou, Miner Zhong, and Bin Wu. "Comprehensive Proteomic Analysis of Colon Cancer Tissue Revealed the Reason for the Worse Prognosis of Right-Sided Colon Cancer and Mucinous Colon Cancer at the Protein Level." Current Oncology 28, no. 5 (September 15, 2021): 3554–72. http://dx.doi.org/10.3390/curroncol28050305.

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To clarify the molecular mechanisms underlying the poor prognosis of right-sided and mucinous colon cancer at the proteomic level. A tandem mass tag-proteomics approach was used to identify differentially expressed proteins (DEPs) in colon carcinoma tissues from different locations and with different histological types to reveal the underlying mechanisms of these differences at the protein level. In additional, the DEPs were analyzed using bioinformatics methods. The proteomics profiles among colon cancers with different tumor locations and histological types were dramatically distinguished. In terms of tumor locations, the right-sided carcinoma specific DEPs may promote the tumor progression via activating inflammation, metastasis associated pathways. When referring to histological types, the mucinous colon cancers perhaps increased the invasion and metastasis through distinct mechanisms in different tumor locations. For mucinous cancer located in right-sided colon, the mucinous specific DEPs were mainly associated with ECM-related remodeling and the IL-17 signal pathway. For mucinous cancer located in left-sided colon, the mucinous specific DEPs showed a strong relationship with ACE2/Ang-(1–7)/MasR axis. The proteomics profiles of colon cancers showed distinct differences related to locations and histological types. These results suggested a distinct mechanism underlying the diverse subtypes of colon cancers.

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Liu, Yan, Tianbao Lin, Maria Valderrama Valencia, Cankui Zhang, and Zhiqiang Lv. "Unraveling the Roles of Vascular Proteins Using Proteomics." Molecules 26, no. 3 (January 27, 2021): 667. http://dx.doi.org/10.3390/molecules26030667.

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Vascular bundles play important roles in transporting nutrients, growth signals, amino acids, and proteins between aerial and underground tissues. In order to understand these sophisticated processes, a comprehensive analysis of the roles of the components located in the vascular tissues is required. A great deal of data has been obtained from proteomic analyses of vascular tissues in plants, which mainly aim to identify the proteins moving through the vascular tissues. Here, different aspects of the phloem and xylem proteins are reviewed, including their collection methods, and their main biological roles in growth, and biotic and abiotic stress responses. The study of vascular proteomics shows great potential to contribute to our understanding of the biological mechanisms related to development and defense in plants.

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Xu, Senhan, Fangxu Sun, Ming Tong, and Ronghu Wu. "MS-based proteomics for comprehensive investigation of protein O-GlcNAcylation." Molecular Omics 17, no. 2 (2021): 186–96. http://dx.doi.org/10.1039/d1mo00025j.

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Protein O-GlcNAcylation plays critical roles in mammalian cells, and here we review MS-based proteomics methods for comprehensive and site-specific analysis of protein O-GlcNAcylation, ranging from enrichment, fragmentation, to quantification.

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Wu, Jinlu, Qingsong Lin, Teck Kwang Lim, Tiefei Liu, and Choy-Leong Hew. "White Spot Syndrome Virus Proteins and Differentially Expressed Host Proteins Identified in Shrimp Epithelium by Shotgun Proteomics and Cleavable Isotope-Coded Affinity Tag." Journal of Virology 81, no. 21 (August 22, 2007): 11681–89. http://dx.doi.org/10.1128/jvi.01006-07.

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ABSTRACT Shrimp subcuticular epithelial cells are the initial and major targets of white spot syndrome virus (WSSV) infection. Proteomic studies of WSSV-infected subcuticular epithelium of Penaeus monodon were performed through two approaches, namely, subcellular fractionation coupled with shotgun proteomics to identify viral and host proteins and a quantitative time course proteomic analysis using cleavable isotope-coded affinity tags (cICATs) to identify differentially expressed cellular proteins. Peptides were analyzed by offline coupling of two-dimensional liquid chromatography with matrix-assisted laser desorption ionization-tandem time of flight mass spectrometry. We identified 27, 20, and 4 WSSV proteins from cytosolic, nuclear, and membrane fractions, respectively. Twenty-eight unique WSSV proteins with high confidence (total ion confidence interval percentage [CI%], >95%) were observed, 11 of which are reported here for the first time, and 3 of these novel proteins were shown to be viral nonstructural proteins by Western blotting analysis. A first shrimp protein data set containing 1,999 peptides (ion score, ≥20) and 429 proteins (total ion score CI%, >95%) was constructed via shotgun proteomics. We also identified 10 down-regulated proteins and 2 up-regulated proteins from the shrimp epithelial lysate via cICAT analysis. This is the first comprehensive study of WSSV-infected epithelia by proteomics. The 11 novel viral proteins represent the latest addition to our knowledge of the WSSV proteome. Three proteomic data sets consisting of WSSV proteins, epithelial cellular proteins, and differentially expressed cellular proteins generated in the course of WSSV infection provide a new resource for further study of WSSV-shrimp interactions.

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Tsai, Chia-Feng, Rui Zhao, Sarah M. Williams, Ronald J. Moore, Kendall Schultz, William B. Chrisler, Ljiljana Pasa-Tolic, et al. "An Improved Boosting to Amplify Signal with Isobaric Labeling (iBASIL) Strategy for Precise Quantitative Single-cell Proteomics." Molecular & Cellular Proteomics 19, no. 5 (March 3, 2020): 828–38. http://dx.doi.org/10.1074/mcp.ra119.001857.

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Mass spectrometry (MS)-based proteomics has great potential for overcoming the limitations of antibody-based immunoassays for antibody-independent, comprehensive, and quantitative proteomic analysis of single cells. Indeed, recent advances in nanoscale sample preparation have enabled effective processing of single cells. In particular, the concept of using boosting/carrier channels in isobaric labeling to increase the sensitivity in MS detection has also been increasingly used for quantitative proteomic analysis of small-sized samples including single cells. However, the full potential of such boosting/carrier approaches has not been significantly explored, nor has the resulting quantitation quality been carefully evaluated. Herein, we have further evaluated and optimized our recent boosting to amplify signal with isobaric labeling (BASIL) approach, originally developed for quantifying phosphorylation in small number of cells, for highly effective analysis of proteins in single cells. This improved BASIL (iBASIL) approach enables reliable quantitative single-cell proteomics analysis with greater proteome coverage by carefully controlling the boosting-to-sample ratio (e.g. in general <100×) and optimizing MS automatic gain control (AGC) and ion injection time settings in MS/MS analysis (e.g. 5E5 and 300 ms, respectively, which is significantly higher than that used in typical bulk analysis). By coupling with a nanodroplet-based single cell preparation (nanoPOTS) platform, iBASIL enabled identification of ∼2500 proteins and precise quantification of ∼1500 proteins in the analysis of 104 FACS-isolated single cells, with the resulting protein profiles robustly clustering the cells from three different acute myeloid leukemia cell lines. This study highlights the importance of carefully evaluating and optimizing the boosting ratios and MS data acquisition conditions for achieving robust, comprehensive proteomic analysis of single cells.

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Schrattenholz, André, Martina Klemm, and Michael Cahill. "Potential of Comprehensive Toxico-proteomics: Quantitative and Differential Mining of Functional Proteomes from Native Samples." Alternatives to Laboratory Animals 32, no. 1_suppl (January 2004): 123–31. http://dx.doi.org/10.1177/026119290403201s19.

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Arnold, Georg J., and T. Frohlich. "Dynamic proteome signatures in gametes, embryos and their maternal environment." Reproduction, Fertility and Development 23, no. 1 (2011): 81. http://dx.doi.org/10.1071/rd10223.

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Comprehensive molecular analysis at the level of proteins represents a technically demanding, but indispensable, task since several post-transcriptional regulation mechanisms disable a valid prediction of quantitative protein expression profiles from transcriptome analysis. In crucial steps of gamete and early embryo development, de novo transcription is silenced, meaning that almost all macromolecular events take place at the level of proteins. In this review, we describe selected examples of dynamic proteome signatures addressing capacitation of spermatozoa, in vitro maturation of oocytes, effect of oestrous cycle on oviduct epithelial cells and embryo-induced alterations to the maternal environment. We also present details of the experimental strategies applied and the experiments performed to verify quantitative proteomic data. Far from being comprehensive, examples were selected to cover several mammalian species as well as the most powerful proteomic techniques currently applied. To enable non-experts in the field of proteomics to appraise published proteomic data, our examples are preceded by a customised description of quantitative proteomic methods, covering 2D difference gel electrophoresis (2D-DIGE), nano-liquid chromatography combined with tandem mass spectrometry, and label-free as well as stable-isotope labelling strategies for mass spectrometry-based quantifications.

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Lacombe, Maud, Michel Jaquinod, Lucid Belmudes, Yohann Couté, Claire Ramus, Florence Combes, Thomas Burger, et al. "Comprehensive and comparative exploration of the Atp7b−/− mouse plasma proteome." Metallomics 12, no. 2 (2020): 249–58. http://dx.doi.org/10.1039/c9mt00225a.

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Wilson's disease (WD) is a rare genetic disease caused by mutations in the ATP7B gene. In this study, we used MS-based proteomics to explore the plasma proteome of the Atp7b^−/− mouse, a genetic and phenotypic model for WD.

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Pattnaik, Lolly, and Laxmikanta Acharya. "A comprehensive review on vernal keratoconjunctivitis with emphasis on proteomics." Life Sciences 128 (May 2015): 47–54. http://dx.doi.org/10.1016/j.lfs.2015.01.040.

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Chervet, J. P., G. Mitulovic, E. Varesio, and R. Locher. "Comprehensive 2-D capillary/nano LC/MS for complex proteomics." Pathology - Research and Practice 200, no. 4 (January 2004): 281–82. http://dx.doi.org/10.1016/s0344-0338(04)80505-3.

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Yang, C., W. b. Guo, W. s. Zhang, J. Bian, J. k. Yang, Q. z. Zhou, M. k. Chen, et al. "Comprehensive proteomics analysis of exosomes derived from human seminal plasma." Andrology 5, no. 5 (September 2017): 1007–15. http://dx.doi.org/10.1111/andr.12412.

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Li, Jing, Juan Li, Wei-Gang Zhao, Hai-Dan Sun, Zheng-Guang Guo, Xiao-Yan Liu, Xiao-Yue Tang, et al. "Comprehensive proteomics and functional annotation of mouse brown adipose tissue." PLOS ONE 15, no. 5 (May 6, 2020): e0232084. http://dx.doi.org/10.1371/journal.pone.0232084.

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Sonsare, Pravinkumar M., and C. Gunavathi. "Investigation of machine learning techniques on proteomics: A comprehensive survey." Progress in Biophysics and Molecular Biology 149 (December 2019): 54–69. http://dx.doi.org/10.1016/j.pbiomolbio.2019.09.004.

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Hecker, Michael, and Uwe Völker. "Towards a comprehensive understanding ofBacillus subtiliscell physiology by physiological proteomics." PROTEOMICS 4, no. 12 (November 12, 2004): 3727–50. http://dx.doi.org/10.1002/pmic.200401017.

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Tsou, Chih-Chiang, Dmitry Avtonomov, Brett Larsen, Monika Tucholska, Hyungwon Choi, Anne-Claude Gingras, and Alexey I. Nesvizhskii. "DIA-Umpire: comprehensive computational framework for data-independent acquisition proteomics." Nature Methods 12, no. 3 (January 19, 2015): 258–64. http://dx.doi.org/10.1038/nmeth.3255.

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Imran, Muhammad, George Katselis, and Mary Buhr. "Fertility-associated comprehensive proteomics of bovine sperm head plasma membrane." Animal Reproduction Science 220 (September 2020): 106453. http://dx.doi.org/10.1016/j.anireprosci.2020.106453.

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Jain, Manavi, Paramveer Yadav, and Priyadarshini. "Proteomics Study in Urolithiasis." Current Proteomics 17, no. 2 (January 30, 2020): 88–94. http://dx.doi.org/10.2174/1570164616666190722161823.

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Urolithiasis, which is the presence of stones in the urinary tract, has long been linked with a higher risk of causing chronic kidney diseases and associated illnesses, such as diabetes-affecting 12% of the world population. This clinical condition arises due to the supersaturation of urine and alterations in the expression of cellular and urinary proteins. The renal stone mineral composition has been well understood and incorporated as a routine part of stone removal, however, the protein composition, an essential fraction of the stone matrix has been inadequately understood and not adeptly established. Stone proteomics consists of a number of techniques including crystal analysis using X-ray diffractometry and IR spectroscopy, sample purification, identification and characterization of proteins using high throughput mass spectrometric methods. However, not many studies have utilized the data obtained from these experiments to assign functional significance to associated identified proteins. Protein network analysis using bioinformatic tools such as STRING to study protein-protein interactions will enable researchers to get better insight into stone formation mechanics. Hence, a comprehensive proteomic study of kidney stone matrix will help in deciphering protein-crystal pathways generating novel information useful for clinical application.

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Kremer, Andreas, Reinhard Schneider, and Georg C. Terstappen. "A Bioinformatics Perspective on Proteomics: Data Storage, Analysis, and Integration." Bioscience Reports 25, no. 1-2 (February 4, 2005): 95–106. http://dx.doi.org/10.1007/s10540-005-2850-4.

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The field of proteomics is advancing rapidly as a result of powerful new technologies and proteomics experiments yield a vast and increasing amount of information. Data regarding protein occurrence, abundance, identity, sequence, structure, properties, and interactions need to be stored. Currently, a common standard has not yet been established and open access to results is needed for further development of robust analysis algorithms. Databases for proteomics will evolve from pure storage into knowledge resources, providing a repository for information (meta-data) which is mainly not stored in simple flat files. This review will shed light on recent steps towards the generation of a common standard in proteomics data storage and integration, but is not meant to be a comprehensive overview of all available databases and tools in the proteomics community.

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Yang, Lei, Dapeng Hao, Jizhe Wang, Xudong Xing, Yingli Lv, Yongchun Zuo, and Wei Jiang. "Characterization of proteins in S. cerevisiae with subcellular localizations." Molecular BioSystems 11, no. 5 (2015): 1360–69. http://dx.doi.org/10.1039/c5mb00124b.

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Jimenez, Connie R., and Henk M. W. Verheul. "Mass Spectrometry-Based Proteomics: From Cancer Biology to Protein Biomarkers, Drug Targets, and Clinical Applications." American Society of Clinical Oncology Educational Book, no. 34 (May 2014): e504-e510. http://dx.doi.org/10.14694/edbook_am.2014.34.e504.

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Proteomics is optimally suited to bridge the gap between genomic information on the one hand and biologic functions and disease phenotypes at the other, since it studies the expression and/or post-translational modification (especially phosphorylation) of proteins—the major cellular players bringing about cellular functions—at a global level in biologic specimens. Mass spectrometry technology and (bio)informatic tools have matured to the extent that they can provide high-throughput, comprehensive, and quantitative protein inventories of cells, tissues, and biofluids in clinical samples at low level. In this article, we focus on next-generation proteomics employing nanoliquid chromatography coupled to high-resolution tandem mass spectrometry for in-depth (phospho)protein profiling of tumor tissues and (proximal) biofluids, with a focus on studies employing clinical material. In addition, we highlight emerging proteogenomic approaches for the identification of tumor-specific protein variants, and targeted multiplex mass spectrometry strategies for large-scale biomarker validation. Below we provide a discussion of recent progress, some research highlights, and challenges that remain for clinical translation of proteomic discoveries.

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Chen, Chen, Jie Hou, John J. Tanner, and Jianlin Cheng. "Bioinformatics Methods for Mass Spectrometry-Based Proteomics Data Analysis." International Journal of Molecular Sciences 21, no. 8 (April 20, 2020): 2873. http://dx.doi.org/10.3390/ijms21082873.

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Recent advances in mass spectrometry (MS)-based proteomics have enabled tremendous progress in the understanding of cellular mechanisms, disease progression, and the relationship between genotype and phenotype. Though many popular bioinformatics methods in proteomics are derived from other omics studies, novel analysis strategies are required to deal with the unique characteristics of proteomics data. In this review, we discuss the current developments in the bioinformatics methods used in proteomics and how they facilitate the mechanistic understanding of biological processes. We first introduce bioinformatics software and tools designed for mass spectrometry-based protein identification and quantification, and then we review the different statistical and machine learning methods that have been developed to perform comprehensive analysis in proteomics studies. We conclude with a discussion of how quantitative protein data can be used to reconstruct protein interactions and signaling networks.

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Journal articles on the topic 'Comprehensive proteomics'

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