Bibliografie tematiche / Proteomics

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Letteratura scientifica selezionata sul tema "Proteomics"

Autore: Grafiati

Pubblicato: 4 giugno 2021

Ultima modifica: 25 luglio 2025

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Articoli di riviste sul tema "Proteomics"

Krieg, Rene C., Cloud P. Paweletz, Lance A. Liotta, and Emanuel F. Petricoin. "Clinical Proteomics for Cancer Biomarker Discovery and Therapeutic Targeting." Technology in Cancer Research & Treatment 1, no. 4 (2002): 263–72. http://dx.doi.org/10.1177/153303460200100407.

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As we emerge into the post-genome era, proteomics finds itself as the driving force field as we translate the nucleic acid information archive into understanding how the cell actually works and how disease processes operate. Even so, the traditionally held view of proteomics as simply cataloging and developing lists of the cellular protein repertoire of a cell are now changing, especially in the sub-discipline of clinical proteomics. The most relevant information archive to clinical applications and drug development involves the elucidation of the information flow of the cell; the “software” o

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Sukumaran, Pariveena, Ainun Aida Bahardin, Luqmanul Hakim Abdul Razak, and Mohd Harizal Senik. "Application of Proteomics in Alzheimer’s Disease: A Mini Review." SEPTEMBER 2023 19, no. 5 (2023): 317–30. http://dx.doi.org/10.47836/mjmhs.19.5.38.

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Alzheimer’s disease (AD) is classified as one of neurodegenerative disease caused by neuronal death. It is characterized as memory impairment, including the inability to produce new memories. Since AD has low treatment effectiveness, proteomics research opens possibilities for advancement. Proteomics is the study of proteomes produced by the disease-bearing host to identify and understand diseases. In this case, to investigate the use of protein as a reliable molecular entity and their involvement in AD. Therefore, this review focused on three main applications of proteomics; the potential use

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Mahajan, R., and P. Gupta. "Proteomics: taking over where genomics leaves off." Czech Journal of Genetics and Plant Breeding 46, No. 2 (2010): 47–53. http://dx.doi.org/10.17221/34/2009-cjgpb.

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The proteomic studies are simultaneously developed in several directions and significantly influence our notions on the capabilities of biological sciences. The need for proteomics research is necessary as there are certain genes in a cell that encode proteins with specific functions. Using a variety of techniques, proteomics can be used to study how proteins interact within a system or how the protein expression changes in different parts of the body, in different stages of its life cycle and in different environmental conditions as every individual has one genome and many proteomes. Besides

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Sadeesh, Nithin, Mauro Scaravilli, and Leena Latonen. "Proteomic Landscape of Prostate Cancer: The View Provided by Quantitative Proteomics, Integrative Analyses, and Protein Interactomes." Cancers 13, no. 19 (2021): 4829. http://dx.doi.org/10.3390/cancers13194829.

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Prostate cancer is the second most frequent cancer of men worldwide. While the genetic landscapes and heterogeneity of prostate cancer are relatively well-known already, methodological developments now allow for studying basic and dynamic proteomes on a large scale and in a quantitative fashion. This aids in revealing the functional output of cancer genomes. It has become evident that not all aberrations at the genetic and transcriptional level are translated to the proteome. In addition, the proteomic level contains heterogeneity, which increases as the cancer progresses from primary prostate

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Sokolowska, Izabela, Armand G. Ngounou Wetie, Alisa G. Woods, and Costel C. Darie. "Applications of Mass Spectrometry in Proteomics." Australian Journal of Chemistry 66, no. 7 (2013): 721. http://dx.doi.org/10.1071/ch13137.

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Characterisation of proteins and whole proteomes can provide a foundation to our understanding of physiological and pathological states and biological diseases or disorders. Constant development of more reliable and accurate mass spectrometry (MS) instruments and techniques has allowed for better identification and quantification of the thousands of proteins involved in basic physiological processes. Therefore, MS-based proteomics has been widely applied to the analysis of biological samples and has greatly contributed to our understanding of protein functions, interactions, and dynamics, adva

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Walther, Tobias C., and Matthias Mann. "Mass spectrometry–based proteomics in cell biology." Journal of Cell Biology 190, no. 4 (2010): 491–500. http://dx.doi.org/10.1083/jcb.201004052.

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The global analysis of protein composition, modifications, and dynamics are important goals in cell biology. Mass spectrometry (MS)–based proteomics has matured into an attractive technology for this purpose. Particularly, high resolution MS methods have been extremely successful for quantitative analysis of cellular and organellar proteomes. Rapid advances in all areas of the proteomic workflow, including sample preparation, MS, and computational analysis, should make the technology more easily available to a broad community and turn it into a staple methodology for cell biologists.

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Oikonomou, Panos, Roberto Salatino, and Saeed Tavazoie. "In vivo mRNA display enables large-scale proteomics by next generation sequencing." Proceedings of the National Academy of Sciences 117, no. 43 (2020): 26710–18. http://dx.doi.org/10.1073/pnas.2002650117.

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Large-scale proteomic methods are essential for the functional characterization of proteins in their native cellular context. However, proteomics has lagged far behind genomic approaches in scalability, standardization, and cost. Here, we introduce in vivo mRNA display, a technology that converts a variety of proteomics applications into a DNA sequencing problem. In vivo-expressed proteins are coupled with their encoding messenger RNAs (mRNAs) via a high-affinity stem-loop RNA binding domain interaction, enabling high-throughput identification of proteins with high sensitivity and specificity

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Soleymani, Nooshinmehr, Soheil Sadr, Cinzia Santucciu, et al. "Unveiling Novel Insights in Helminth Proteomics: Advancements, Applications, and Implications for Parasitology and Beyond." Biologics 4, no. 3 (2024): 314–44. http://dx.doi.org/10.3390/biologics4030020.

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Helminths have developed intricate mechanisms to survive and evade the host’s immune responses. Hence, understanding the excretory-secretory products (ESPs) by helminths is crucial for developing control tools, including drug targets, vaccines, and potential therapies for inflammatory and metabolic disorders caused by them. Proteomics, the large-scale analysis of proteins, offers a powerful approach to unravel the complex proteomes of helminths and gain insights into their biology. Proteomics, as a science that delves into the functions of proteins, has the potential to revolutionize clinical

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Stubbs, Keith A., and David J. Vocadlo. "Affinity-Based Proteomics Probes; Tools for Studying Carbohydrate-Processing Enzymes." Australian Journal of Chemistry 62, no. 6 (2009): 521. http://dx.doi.org/10.1071/ch09140.

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As more information becomes available through the efforts of high-throughput screens, there is increasing pressure on the three main ‘omic’ fields, genomics, proteomics, and metabolomics, to organize this material into useful libraries that enable further understanding of biological systems. Proteomics especially is faced with two highly challenging tasks. The first is assigning the activity of thousands of putative proteins, the existence of which has been suggested by genomics studies. The second is to serve as a link between genomics and metabolomics by demonstrating which enzymes play role

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Duong, Van-An, and Hookeun Lee. "Bottom-Up Proteomics: Advancements in Sample Preparation." International Journal of Molecular Sciences 24, no. 6 (2023): 5350. http://dx.doi.org/10.3390/ijms24065350.

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Liquid chromatography–tandem mass spectrometry (LC–MS/MS)-based proteomics is a powerful technique for profiling proteomes of cells, tissues, and body fluids. Typical bottom-up proteomic workflows consist of the following three major steps: sample preparation, LC–MS/MS analysis, and data analysis. LC–MS/MS and data analysis techniques have been intensively developed, whereas sample preparation, a laborious process, remains a difficult task and the main challenge in different applications. Sample preparation is a crucial stage that affects the overall efficiency of a proteomic study; however, i

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Tesi sul tema "Proteomics"

Miller, V. F. "Neuroretinal proteomics." Thesis, Queen's University Belfast, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.411748.

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Franchin, Cinzia. "Mass Spectrometry-Based Quantitative Proteomics to Study Proteomes, Phosphoproteomes and Interactomes." Doctoral thesis, Università degli studi di Padova, 2012. http://hdl.handle.net/11577/3422169.

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Over the past few years, mass spectrometry-based proteomics has been widely applied to the most diverse fields of biochemistry, biomedicine and biology, and several approaches have been developed to allow absolute and relative quantification of proteins in very complex mixtures. During my PhD, I have conducted three main studies, taking advantage of different quantitative proteomics techniques. In particular SILAC and iTRAQ approaches have been exploited to investigate the calcification process induced by endotoxin in clonal interstitial aortic valve cells, while SILAC and label-free quantitat

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Walther, Dirk Martin. "Analysis of aging by quantitative proteomics and mitochondrial organellar proteomics." Diss., Ludwig-Maximilians-Universität München, 2012. http://nbn-resolving.de/urn:nbn:de:bvb:19-174637.

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Ismail, Marcus. "Blodplasmahantering för proteomics." Thesis, Mälardalen University, School of Sustainable Development of Society and Technology, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-5485.

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Stone, Helen Marie. "Proteomics in COPD." Thesis, University of Birmingham, 2017. http://etheses.bham.ac.uk//id/eprint/7565/.

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In alpha-1-antitrypsin deficiency (A1ATD) there is excess neutrophil elastase activity, resulting in proteolytic destruction of the lung parenchyma. I hypothesised that the peptide fragments of proteins present in the lung might be detectable in plasma by mass spectrometry and that they might be useful biomarkers of disease activity and treatment efficacy. Calcium ionophore, neutrophil elastase and proteinase 3 were added to plasma from patients with A1ATD to create an in vitro model of the destructive processes. MALDI-based peptide profiling of plasma from patients pre and post treatment with

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Le, Thao Thi. "Aptamers for proteomics." Thesis, Imperial College London, 2008. http://hdl.handle.net/10044/1/1385.

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Changes in post-translation modifications are very important in the regulation of biological processes. Many modifications occur at very low levels, resulting in a low-abundance of the modified proteins in cells, and therefore assessing those modifications is not an easy task. Modern proteomics needs improved methods for identifying such changes. In this thesis, we focus on generating aptamers that can bind phosphoproteins with high affinities and therefore would be able to detect even low-abundance proteins. Aptamers are short sequences of nucleic acids that can be selected from libraries thr

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Lang, Alastair Michael. "Developing tissue proteomics : differential in gel electrophoresis in biomarker discovery and proteomic degradation." Thesis, University of Glasgow, 2013. http://theses.gla.ac.uk/4642/.

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The field of proteomics and functional genomics has developed steadily since the completion of the human genome project. The wealth of genomic information and the pace at which it was compiled was astounding. Proteomics, despite considerable effort, on the other hand has not seen quite the same pace of development. The progress being considerably hindered by the lack of an amplification process and the relative complexity of the proteome in comparison to the genome. These intrinsic difficulties have led to the sensitivity of proteomic techniques being pushed closer to physical limits. There is

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Culwell, Thomas Franklin. "Study of the reproducibility of proteomics methods and variability of fruit fly proteomes /." Diss., CLICK HERE for online access, 2008. http://contentdm.lib.byu.edu/ETD/image/etd2252.pdf.

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Culwell, Thomas Franklin. "Study of the Reproducibility of Proteomics Methods and Variability of Fruit Fly Proteomes." BYU ScholarsArchive, 2007. https://scholarsarchive.byu.edu/etd/1232.

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The reliability of biomarker discovery by means of proteomics has been called into question. It was speculated that "background noise" variation resulting from differences in preparation and handling of samples and proteome dynamics may mask subtle, yet important, differences due to the biological condition. Little is understood about complex proteomes and their variability. A critical aspect of proteomic biomarker research that is largely unexplored is the comparative reproducibility of certain methods such as two-dimensional gel electrophoresis and liquid chromatography/mass spectrometry. I

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Svensson, Marcus. "Neuropeptidomics expanding proteomics downwards /." Doctoral thesis, Uppsala : Uppsala universitet, Fakultetsövergripande enheter, Acta Universitatis Upsaliensis, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-7465.

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Più fonti

Libri sul tema "Proteomics"

Comai, Lucio, Jonathan E. Katz, and Parag Mallick, eds. Proteomics. Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4939-6747-6.

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Reinders, Jörg, and Albert Sickmann, eds. Proteomics. Humana Press, 2009. http://dx.doi.org/10.1007/978-1-60761-157-8.

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Seppo, Meri, and Baumann Marc, eds. Proteomics. Elsevier, 2001.

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Fernando, Vivanco. Cardiovascular Proteomics. Humana Press, 2006. http://dx.doi.org/10.1385/1597452149.

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Valerie, Mechin, Damerval Catherine, Zivy Michel, and Thiellement Hervé. Plant Proteomics. Humana Press, 2006. http://dx.doi.org/10.1385/1597452270.

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Carrera, Mónica, and Jesús Mateos, eds. Shotgun Proteomics. Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-1178-4.

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Owens, Raymond J., ed. Structural Proteomics. Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-1406-8.

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Chen, Yue, and Luke Erber. Functional Proteomics. American Chemical Society, 2022. http://dx.doi.org/10.1021/acsinfocus.7e5010.

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Corrales, Fernando J., Alberto Paradela, and Miguel Marcilla, eds. Clinical Proteomics. Springer US, 2022. http://dx.doi.org/10.1007/978-1-0716-1936-0.

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Bertrand, Eric, and Michel Faupel, eds. Subcellular Proteomics. Springer Netherlands, 2007. http://dx.doi.org/10.1007/978-1-4020-5943-8.

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Capitoli di libri sul tema "Proteomics"

Schork, Karin, Katharina Podwojski, Michael Turewicz, Christian Stephan, and Martin Eisenacher. "Important Issues in : Statistical Considerations of Quantitative Proteomic Data." In Methods in Molecular Biology. Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-1024-4_1.

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AbstractMass spectrometry is frequently used in quantitative proteomics to detect differentially regulated proteins. A very important but unfortunately oftentimes neglected part in detecting differential proteins is the statistical analysis. Data from proteomics experiments are usually high-dimensional and hence require profound statistical methods. It is especially important to already correctly design a proteomic experiment before it is conducted in the laboratory. Only this can ensure that the statistical analysis is capable of detecting truly differential proteins afterward. This chapter t

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Duan, Dayue Darrel. "Proteomics and Functional Proteomics." In Textbook of Pulmonary Vascular Disease. Springer US, 2010. http://dx.doi.org/10.1007/978-0-387-87429-6_41.

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Budzinski, Ilara Gabriela F., Thaís Regiani, Mônica T. Veneziano Labate, et al. "Proteomics." In Omics in Plant Breeding. John Wiley & Sons, Inc, 2014. http://dx.doi.org/10.1002/9781118820971.ch4.

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Ramsden, Jeremy. "Proteomics." In Computational Biology. Springer London, 2015. http://dx.doi.org/10.1007/978-1-4471-6702-0_14.

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Ravi, Indu. "Proteomics." In Advances in Biotechnology. Springer India, 2013. http://dx.doi.org/10.1007/978-81-322-1554-7_8.

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McAllister-Williams, R. Hamish, Daniel Bertrand, Hans Rollema, et al. "Proteomics." In Encyclopedia of Psychopharmacology. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-540-68706-1_308.

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Bertolla, Ricardo P. "Proteomics." In Proteomics in Human Reproduction. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-48418-1_2.

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Turner, J. Rick. "Proteomics." In Encyclopedia of Behavioral Medicine. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-39903-0_1689.

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Turner, J. Rick. "Proteomics." In Encyclopedia of Behavioral Medicine. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-1005-9_1689.

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Nahler, Gerhard. "proteomics." In Dictionary of Pharmaceutical Medicine. Springer Vienna, 2009. http://dx.doi.org/10.1007/978-3-211-89836-9_1152.

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Atti di convegni sul tema "Proteomics"

Palermo, Marcelo Benedeti, Cristiano André da Costa, and Rodrigo da Rosa Righi. "Uncovering Potential Proteomic Biomarkers for Cancer Patients with COVID-19 Infection using Multilabel Deep Learning Model." In Simpósio Brasileiro de Computação Aplicada à Saúde. Sociedade Brasileira de Computação - SBC, 2025. https://doi.org/10.5753/sbcas.2025.7181.

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The effects of COVID-19 on cancer patients are concerning. This work proposes a framework that employs a multilabel classifier processing longitudinal proteomics patients’ data to identify potential proteomic biomarkers that correlate cancer and COVID-19. The framework uses Olink NPX data from 305 COVID-19-positive cancer patients. Stratified k-fold cross-validation addresses data imbalance. The overall average results show a Jaccard index of 88.79%, a hamming loss of 0.32%, a Wasserstein distance of 0.64%, and an area under the curve of 94.47%, across 312 labels, with four proteins presenting

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Lesley, Scott A., Marc Nasoff, Andreas Kreusch, and Glen Spraggon. "High-throughput proteomics." In BiOS 2001 The International Symposium on Biomedical Optics, edited by Ramesh Raghavachari and Weihong Tan. SPIE, 2001. http://dx.doi.org/10.1117/12.424595.

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"Computational proteomics and genomics." In 2011 24th International Symposium on Computer-Based Medical Systems (CBMS). IEEE, 2011. http://dx.doi.org/10.1109/cbms.2011.5999043.

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Hall, Drew, Xiahan Zhou, and Chih-Cheng Huang. "Magnetoresistive biosensors for quantitative proteomics." In Biosensing and Nanomedicine X, edited by Hooman Mohseni, Massoud H. Agahi, and Manijeh Razeghi. SPIE, 2017. http://dx.doi.org/10.1117/12.2276933.

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Lennox, Mark, Neil Robertson, and Barry Devereux. "Deep Metric Learning for Proteomics." In 2020 19th IEEE International Conference on Machine Learning and Applications (ICMLA). IEEE, 2020. http://dx.doi.org/10.1109/icmla51294.2020.00057.

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Hashim, O. "Proteomics Approach To Cancer Studies." In 2nd International University of Malaya Research Imaging Symposium (UMRIS) 2005: Fundamentals of Molecular Imaging. Department of Biomedical Imaging, University of Malaya, 2005. http://dx.doi.org/10.2349/biij.1.1.e7-41.

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Enzer, N. A., S. Mason, B. Choi, et al. "Prediction of Sarcopenia Using Proteomics." In American Thoracic Society 2022 International Conference, May 13-18, 2022 - San Francisco, CA. American Thoracic Society, 2022. http://dx.doi.org/10.1164/ajrccm-conference.2022.205.1_meetingabstracts.a3787.

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Costessi, Mr Adalberto, Mr Carlo Vascotto, Dr Alex Pines, et al. "Bone Proteomics experiment (BOP): the first proteomic analysis of mammalian cells cultured in weightlessness conditions." In 57th International Astronautical Congress. American Institute of Aeronautics and Astronautics, 2006. http://dx.doi.org/10.2514/6.iac-06-a1.4.08.

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Giannopoulou, Eugenia G., George Lepouras, and Elias S. Manolakos. "VIP: Visualization of integrated proteomics data." In 2008 8th IEEE International Conference on Bioinformatics and BioEngineering (BIBE). IEEE, 2008. http://dx.doi.org/10.1109/bibe.2008.4696670.

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Henao, Ricardo, J. Will Thompson, M. Arthur Moseley, Geoffrey S. Ginsburg, Lawrence Carin, and Joseph E. Lucas. "Hierarchical factor modeling of proteomics data." In 2012 IEEE 2nd International Conference on Computational Advances in Bio and Medical Sciences (ICCABS). IEEE, 2012. http://dx.doi.org/10.1109/iccabs.2012.6182638.

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Rapporti di organizzazioni sul tema "Proteomics"

Aebersold, Ruedi. Proteomics: Technology and Applications. Office of Scientific and Technical Information (OSTI), 2003. http://dx.doi.org/10.2172/840129.

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Klein, Jon B. Pediatric Clinical Proteomics Center. Office of Scientific and Technical Information (OSTI), 2013. http://dx.doi.org/10.2172/1063767.

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McCarty, Niko. How to Scale Proteomics. Asimov Press, 2025. https://doi.org/10.62211/29ur-44hf.

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Davidson, George S. High-throughput proteomics : optical approaches. Office of Scientific and Technical Information (OSTI), 2008. http://dx.doi.org/10.2172/945920.

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Stemke-Hale, Katherine, Nevine Eltonsy, and Zhenlin Ju. Functional Proteomics-Based Ovarian Cancer Biomarkers. Defense Technical Information Center, 2010. http://dx.doi.org/10.21236/ada586794.

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Chu, Fanny, Andy Lin, Daniel Lewis, et al. Proteomics Analysis of Human Contaminant Proteins. Office of Scientific and Technical Information (OSTI), 2024. http://dx.doi.org/10.2172/2476858.

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Fodor, I., and D. Nelson. Leveraging Genomics Software to Improve Proteomics Results. Office of Scientific and Technical Information (OSTI), 2005. http://dx.doi.org/10.2172/883739.

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Vaidyanathan, P. P. Genomics and Proteomics: A Signal Processor's Tour. Defense Technical Information Center, 2004. http://dx.doi.org/10.21236/ada427792.

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Benner, William. CRADA Final Report: Mass Spectrometry for Proteomics. Office of Scientific and Technical Information (OSTI), 2001. http://dx.doi.org/10.2172/1157027.

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Moita, Brenda, and Vikram Sharma. Applications of Prostate Cancer Proteomics: A Review. Journal of Young Investigators, 2021. http://dx.doi.org/10.22186/jyi.39.4.45-53.

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