Academic literature on the topic 'Proteomic pattern'
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Journal articles on the topic "Proteomic pattern"
Mischak, Harald, Eric Schiffer, Petra Zürbig, Mohammed Dakna, and Jochen Metzger. "Urinary Proteome Analysis using Capillary Electrophoresis Coupled to Mass Spectrometry: A Powerful Tool in Clinical Diagnosis, Prognosis and Therapy Evaluation." Journal of Medical Biochemistry 28, no. 4 (October 1, 2009): 223–34. http://dx.doi.org/10.2478/v10011-009-0020-0.
Full textBaumann, Sven, Uta Ceglarek, Georg Martin Fiedler, Jan Lembcke, Alexander Leichtle, and Joachim Thiery. "Standardized Approach to Proteome Profiling of Human Serum Based on Magnetic Bead Separation and Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry." Clinical Chemistry 51, no. 6 (June 1, 2005): 973–80. http://dx.doi.org/10.1373/clinchem.2004.047308.
Full textYu, Li-Rong, Ming Zhou, Thomas P. Conrads, and Timothy D. Veenstra. "Diagnostic Proteomics: Serum Proteomic Patterns for the Detection of Early Stage Cancers." Disease Markers 19, no. 4-5 (2004): 209–18. http://dx.doi.org/10.1155/2004/612071.
Full textZhan, Xianquan, Biao Li, Xiaohan Zhan, Hartmut Schlüter, Peter R. Jungblut, and Jens R. Coorssen. "Innovating the Concept and Practice of Two-Dimensional Gel Electrophoresis in the Analysis of Proteomes at the Proteoform Level." Proteomes 7, no. 4 (October 30, 2019): 36. http://dx.doi.org/10.3390/proteomes7040036.
Full textWalker, Maura E., Rebecca J. Song, Xiang Xu, Robert E. Gerszten, Debby Ngo, Clary B. Clish, Laura Corlin, et al. "Proteomic and Metabolomic Correlates of Healthy Dietary Patterns: The Framingham Heart Study." Nutrients 12, no. 5 (May 19, 2020): 1476. http://dx.doi.org/10.3390/nu12051476.
Full textMischak-Weissinger, Eva M., Jochen Metzger, Annika Krons, Julia Kontsendorn, Jürgen Krauter, Michael Stadler, Harald Mischak, and Arnold Ganser. "Prospective Evaluation of Proteomic Screening with An Agvhd-Specific Proteomic Pattern MS-17." Blood 114, no. 22 (November 20, 2009): 2246. http://dx.doi.org/10.1182/blood.v114.22.2246.2246.
Full textGillette, Michael A., D. R. Mani, and Steven A. Carr. "Place of Pattern in Proteomic Biomarker Discovery†." Journal of Proteome Research 4, no. 4 (August 2005): 1143–54. http://dx.doi.org/10.1021/pr0500962.
Full textMüller, Ute, Günther Ernst, Christian Melle, Reinhard Guthke, and Ferdinand von Eggeling. "Convergence of the proteomic pattern in cancer." Bioinformatics 22, no. 11 (March 7, 2006): 1293–96. http://dx.doi.org/10.1093/bioinformatics/btl077.
Full textConrads, T. P., V. A. Fusaro, S. Ross, D. Johann, V. Rajapakse, B. A. Hitt, S. M. Steinberg, et al. "High-resolution serum proteomic features for ovarian cancer detection." Endocrine-related cancer 11, no. 2 (June 2004): 163–78. http://dx.doi.org/10.1677/erc.0.0110163.
Full textPouliquen, Daniel L., Alice Boissard, Cécile Henry, Stéphanie Blandin, Olivier Coqueret, and Catherine Guette. "Lymphoid Organ Proteomes Identify Therapeutic Efficacy Biomarkers following the Intracavitary Administration of Curcumin in a Highly Invasive Rat Model of Peritoneal Mesothelioma." International Journal of Molecular Sciences 22, no. 16 (August 9, 2021): 8566. http://dx.doi.org/10.3390/ijms22168566.
Full textDissertations / Theses on the topic "Proteomic pattern"
Komori, Mika. "Proteomic pattern analysis discriminates among multiple sclerosis-related disorders." Kyoto University, 2012. http://hdl.handle.net/2433/152501.
Full textLiu, Yiding. "Technologies for Proteomic and Genomic Biomarker Analysis." Cleveland State University / OhioLINK, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=csu1229461302.
Full textAgatea, Lisa. "An integrated proteomic and genomic approach to study FAP patients without APC and MutHY mutations." Doctoral thesis, Università degli studi di Padova, 2016. http://hdl.handle.net/11577/3424509.
Full textLa poliposi adenomatosa familiare (FAP) è una delle più importanti forme cliniche di cancro colo-rettale ereditario ed è caratterizzata dallo sviluppo di centinaia/migliaia di polipi adenomatosi nel colon e nel retto durante la seconda decade di vita. La FAP è causata da una mutazione germinale del gene APC o da varianti bialleliche del gene MutYH. Quasi tutti i pazienti FAP sviluppano il cancro se la patologia non viene precocemente identificata e trattata chirurgicamente. Lo scopo di questo lavoro è stato caratterizzare 4 pazienti in cui, nonostante l’esame colonscopico presentasse una poliposi conclamata, non risultavano mutazioni nei gene APC e MutYH (in questa tesi definiti pazienti FAP irrisolti) utilizzando un approccio integrato di peptidomica e genomica. Riguardo la peptidomica, il MALDI-TOF è stato utilizzato per studiare il profilo peptidico plasmatico di pazienti FAP mutati ed irrisolti comparando i dati ottenuti con quelli derivanti dallo studio di pazienti con adenoma, cancro colo-rettale e soggetti sani di controllo. Dopo analisi statistica è stato ottenuto il fingerprint peptidico dei pazienti FAP mutati. Sono state ottenute 45 specie ioniche differentemente espresse nei quattro gruppi considerati, 12 delle quali peculiari per i pazienti FAP. L’intensità di segnale di quattro di queste specie ioniche è stata trovata statisticamente alterata nello switch tra adenoma e carcinoma maligno. I peptidi potenzialmente prognostici identificati in questo studio derivano principalmente da proteine circolanti, alcune delle quali implicate nella risposta infiammatoria. In particolare è noto dalla letteratura che proteine del sistema del complemento come C3 e C4 vengono tagliate da esoproteasi che sembrano essere patologia correlate. Riguardo ai pazienti FAP irrisolti, per definirne un pattern specifico, i dati derivanti dall’analisi con il MALDI-TOF sono stati combinati con quelli ottenuti dal sequenzia-mento dell’esoma. I dati di peptidomica hanno chiaramente evidenziato le differenze tra pazienti FAP mutati e FAP irrisolti. Infatti i pazienti FAP irrisolti presentano caratteristiche simili a quelle dei soggetti di controllo, dei pazienti con adenoma e cancro colo rettale ma non a quelle dei pazienti FAP mutati. Allo scopo di capire la via di trasduzione del segnale implicata, è stato quindi eseguito il sequenziamento dell'esoma dei pazienti FAP irrisolti. Da questa analisi sono stati selezionati 285 geni variati in tutti i pazienti e tra questi la via di trasduzione del segnale della O-glicosilazione delle mucine è risultata la più rappresentata. In conclusione, in questo studio è stato definito per la prima volta un set peptidico specifico per i pazienti FAP mutati che potrebbe essere utilizzato per monitorare e predire l’evoluzione patologica della malattia. Inoltre è stato possibile caratterizzare un pattern preliminare per i pazienti FAP irrisolti in cui i geni delle mucine potrebbero rappresentare la chiave della via di trasduzione del segnale implicata. Ulteriori studi saranno necessari per correlare i geni delle mucine con la poliposi e costruire l'interatoma (network biologico definito come l’insieme di tutte le interazioni molecolari dirette e indirette che ci sono all'interno di una cellula e di un organismo) di questi pazienti FAP irrisolti.
Wibom, Carl. "Multivariate analyses of proteomic and metabolomic patterns in brain tumors." Doctoral thesis, Umeå universitet, Onkologi, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-25670.
Full textCerjan, Dijana. "INTRACELLULAR DISTRIBUTION PATTERNS OF ORGANELL SPECIFIC PROTEINS USING IMMUNOHISTOCHEMICAL STAINING OF TISSUE MICRO ARRAYS." Thesis, Uppsala University, Department of Medical Biochemistry and Microbiology, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-6154.
Full textThe knowledge of the human genome sequence, as revealed in the HUGO project, has created exciting new possibilities for biomedical research. The Swedish Human Proteome Resource (HPR) program aims to make use of this information to gain further insight into the human proteome. Recombinant proteins are generated from coding sequences identified from the human genome sequence and used to produce specific antibodies to target proteins. Antibodies are subsequently utilized for functional analysis of the corresponding proteins using tissue micro arrays. The aim of my project was to investigate the possibility of distinguishing characteristic distribution patterns of intracellular proteins in the resolution capacity offered by light microscopy. A map of representative distribution patterns was created using immunohistological staining with commercially available antibodies toward well-characterised proteins in the cell. Such a map could then aid in interpreting the results of immunohistological staining of intracellular proteins using antibodies produced within the Human Proteome Resource program. Proteins manifested in nucleus, nuclear membrane and plasma membrane were clearly visible at the expected location. Proteins manifested in different organelles in the cytoplasm however, showed all a similar staining pattern, making determination of exact protein location uncertain. A possible explanation is the resolution of the light microscope not being sufficient to visualize certain proteins specific to organelles in the cytoplasm. Results may also have been influenced by the choice of secondary antibody, where the strenghtened signal generated by an enzyme labelled polymer may have a negative effect on depiction of details in the image generated.
Sabounchi, Schütt Fariba. "Bronchoalveolar lavage and serum protein patterns in healthy individuals and sarcoidosis patients : a proteomics approach /." Stockholm, 2004. http://diss.kib.ki.se/2004/91-7349-790-8/.
Full textÖztürk, Özgür. "Feature extraction and similarity-based analysis for proteome and genome databases." Columbus, Ohio : Ohio State University, 2007. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1190138805.
Full textLindskog, Bergström Cecilia. "Tissue Microarrays for Analysis of Expression Patterns." Doctoral thesis, Uppsala universitet, Molekylär och morfologisk patologi, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-186272.
Full textGöbel, Thomas. "Identifizierung von Proteom Pattern und Proteinmarkern durch SELDI-TOF MS bei Patienten mit chronischer Hepatitis C." Düsseldorf, 2008. http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&doc_number=016540450&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA.
Full textPajak, Maciej. "Evolutionary conservation and diversification of complex synaptic function in human proteome." Thesis, University of Edinburgh, 2018. http://hdl.handle.net/1842/31108.
Full textBooks on the topic "Proteomic pattern"
Grant, Seth G. N. Synaptic Mechanisms of Psychotic Disorders. Edited by Dennis S. Charney, Eric J. Nestler, Pamela Sklar, and Joseph D. Buxbaum. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190681425.003.0017.
Full textSuffredini, Anthony F., and J. Perren Cobb. Genetic and molecular expression patterns in critical illness. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199600830.003.0031.
Full textBook chapters on the topic "Proteomic pattern"
Taguchi, Y. h., and Akira Okamoto. "Principal Component Analysis for Bacterial Proteomic Analysis." In Pattern Recognition in Bioinformatics, 141–52. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-34123-6_13.
Full textHarris, Keith, Mark Girolami, and Harald Mischak. "Definition of Valid Proteomic Biomarkers: A Bayesian Solution." In Pattern Recognition in Bioinformatics, 137–49. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-04031-3_13.
Full textDeusdado, Sérgio, and Paulo Carvalho. "Efficient Exact Pattern-Matching in Proteomic Sequences." In Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living, 1178–86. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02481-8_178.
Full textJong, Kees, Elena Marchiori, and Aad van der Vaart. "Analysis of Proteomic Pattern Data for Cancer Detection." In Lecture Notes in Computer Science, 41–51. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-24653-4_5.
Full textArnau, Vicente, and Ignacio Marín. "A Hierarchical Clustering Strategy and Its Application to Proteomic Interaction Data." In Pattern Recognition and Image Analysis, 62–69. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-44871-6_8.
Full textKim, Jung-Ja, Young-Ho Kim, and Yonggwan Won. "Proteomic Pattern Classification Using Bio-markers for Prostate Cancer Diagnosis." In Computational and Information Science, 631–38. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30497-5_99.
Full textSomorjai, Ray L. "Pattern Recognition Approaches for Classifying Proteomic Mass Spectra of Biofluids." In Methods in Molecular Biology™, 383–95. Totowa, NJ: Humana Press, 2008. http://dx.doi.org/10.1007/978-1-59745-117-8_20.
Full textCarpentier, Sebastien C. "Multiple Testing and Pattern Recognition in 2-DE Proteomics." In Methods in Molecular Biology, 215–35. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4939-3255-9_13.
Full textNg, Julio, Amihood Amir, and Pavel A. Pevzner. "Blocked Pattern Matching Problem and Its Applications in Proteomics." In Lecture Notes in Computer Science, 298–319. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20036-6_27.
Full textLuo, Zhiyuan, Tony Bellotti, and Alex Gammerman. "Qualified Predictions for Proteomics Pattern Diagnostics with Confidence Machines." In Lecture Notes in Computer Science, 46–51. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-28651-6_7.
Full textConference papers on the topic "Proteomic pattern"
LIU, YING. "SERUM PROTEOMIC PATTERN ANALYSIS FOR EARLY CANCER DETECTION." In Proceedings of the International Conference. WORLD SCIENTIFIC, 2005. http://dx.doi.org/10.1142/9789812702098_0015.
Full textKim, Young Bun, Jean Gao, Ying Dong, and Chin-Rang Yang. "Functional Proteomic Pattern Identification under Low Dose Ionizing Radiation." In 2008 IEEE International Conference on Bioinformatics and Biomedicine. IEEE, 2008. http://dx.doi.org/10.1109/bibm.2008.50.
Full textSzasz, A., A. Szasz, A. Szasz, M. Micsinai, A. Tokes, A. Tokes, L. Madaras, T. Krenacs, and J. Kulka. "Proteomic Profiling of Breast Carcinomas Based on Claudin Expression Pattern." In Abstracts: Thirty-Second Annual CTRC‐AACR San Antonio Breast Cancer Symposium‐‐ Dec 10‐13, 2009; San Antonio, TX. American Association for Cancer Research, 2009. http://dx.doi.org/10.1158/0008-5472.sabcs-09-6123.
Full textMeng, Yan. "A Swarm Intelligence Based Algorithm for Proteomic Pattern Detection of Ovarian Cancer." In 2006 IEEE Symposium on Computational Intelligence and Bioinformatics and Computational Biology. IEEE, 2006. http://dx.doi.org/10.1109/cibcb.2006.331010.
Full textXu, Q., S. S. Mohamed, M. M. A. Salama, M. Kamel, and K. Rizkalla. "Mass spectrometry-based proteomic pattern analysis for prostate cancer detection using neural networks with statistical significance test-based feature selection." In 2009 IEEE Toronto International Conference - Science and Technology for Humanity (TIC-STH 2009). IEEE, 2009. http://dx.doi.org/10.1109/tic-sth.2009.5444384.
Full textMartens, William L., Philip Poronnik, and Darren Saunders. "Hypothesis-Driven Sonification of Proteomic Data Distributions Indicating Neurodegredation in Amyotrophic Lateral Sclerosis." In The 22nd International Conference on Auditory Display. Arlington, Virginia: The International Community for Auditory Display, 2016. http://dx.doi.org/10.21785/icad2016.024.
Full textManole, Sagi, Amit Golander, and Shlomo Weiss. "Workload optimization of proteomics pattern matching using embedded accelerator." In Electronics Engineers in Israel (IEEEI 2010). IEEE, 2010. http://dx.doi.org/10.1109/eeei.2010.5662102.
Full textNolasco Jauregui, Oralia. "A Machine Learning approach to Neural Information Decoding of Spike Train Distances in the Peripheral Nervous System." In LatinX in AI at Neural Information Processing Systems Conference 2019. Journal of LatinX in AI Research, 2019. http://dx.doi.org/10.52591/lxai2019120817.
Full textKordy, Hussain Montazery. "A hybrid wavelet based feature extraction approach to analysis of high dimensional proteomic patterns." In 2011 International Conference on Electrical and Control Engineering (ICECE). IEEE, 2011. http://dx.doi.org/10.1109/iceceng.2011.6057914.
Full textZhang, Xuegong. "Pattern Recognition in Mining High-Throughput Genomics/Proteomics Data: The New Challenges in Old Questions." In 2007 International Conference on Computing: Theory and Applications (ICCTA'07). IEEE, 2007. http://dx.doi.org/10.1109/iccta.2007.103.
Full textReports on the topic "Proteomic pattern"
Avni, Adi, and Gitta L. Coaker. Proteomic investigation of a tomato receptor like protein recognizing fungal pathogens. United States Department of Agriculture, January 2015. http://dx.doi.org/10.32747/2015.7600030.bard.
Full textHeifetz, Yael, and Michael Bender. Success and failure in insect fertilization and reproduction - the role of the female accessory glands. United States Department of Agriculture, December 2006. http://dx.doi.org/10.32747/2006.7695586.bard.
Full textHarman, Gary E., and Ilan Chet. Enhancement of plant disease resistance and productivity through use of root symbiotic fungi. United States Department of Agriculture, July 2008. http://dx.doi.org/10.32747/2008.7695588.bard.
Full textManulis, Shulamit, Christine D. Smart, Isaac Barash, Guido Sessa, and Harvey C. Hoch. Molecular Interactions of Clavibacter michiganensis subsp. michiganensis with Tomato. United States Department of Agriculture, January 2011. http://dx.doi.org/10.32747/2011.7697113.bard.
Full textEpel, Bernard, and Roger Beachy. Mechanisms of intra- and intercellular targeting and movement of tobacco mosaic virus. United States Department of Agriculture, November 2005. http://dx.doi.org/10.32747/2005.7695874.bard.
Full textBlumwald, Eduardo, and Avi Sadka. Citric acid metabolism and mobilization in citrus fruit. United States Department of Agriculture, October 2007. http://dx.doi.org/10.32747/2007.7587732.bard.
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