Bibliografías temáticas / Cancer bioinformatics

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Literatura académica sobre el tema "Cancer bioinformatics"

Autor: Grafiati
Publicado: 4 de junio de 2021
Última modificación: 13 de febrero de 2022

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Artículos de revistas sobre el tema "Cancer bioinformatics"

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Desany, Brian, and Zemin Zhang. "Bioinformatics and cancer target discovery." Drug Discovery Today 9, no. 18 (September 2004): 795–802. http://dx.doi.org/10.1016/s1359-6446(04)03224-6.

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Brenner, Chad. "Applications of Bioinformatics in Cancer." Cancers 11, no. 11 (October 24, 2019): 1630. http://dx.doi.org/10.3390/cancers11111630.

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Blekherman, Grigoriy, Reinhard Laubenbacher, Diego F. Cortes, Pedro Mendes, Frank M. Torti, Steven Akman, Suzy V. Torti, and Vladimir Shulaev. "Bioinformatics tools for cancer metabolomics." Metabolomics 7, no. 3 (January 12, 2011): 329–43. http://dx.doi.org/10.1007/s11306-010-0270-3.

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Puig, Oscar, Eugene Joseph, Malgorzata Jaremko, Gregory Kellogg, Robert Wisotzkey, Roman Shraga, Bonny Patel, et al. "Comprehensive next generation sequencing assay and bioinformatic pipeline for identifying pathogenic variants associated with hereditary cancers." Journal of Clinical Oncology 35, no. 15_suppl (May 20, 2017): e13105-e13105. http://dx.doi.org/10.1200/jco.2017.35.15_suppl.e13105.

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e13105 Background: Diagnosis of hereditary cancer syndromes involves time-consuming comprehensive clinical and laboratory work-up, however, timely and accurate diagnosis is pivotal to the clinical management of cancer patients. Germline genetic testing has shown to facilitate the diagnostic process, allowing for identification and management of individuals at risk for inherited cancers. However, the laboratory diagnostics process requires not only development and validation of comprehensive gene panels to improve diagnostic yields, but a quality driven workflow including an end-to-end bioinfor
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UMAR, ASAD. "Applications of Bioinformatics in Cancer Detection: A Lexicon of Bioinformatics Terms." Annals of the New York Academy of Sciences 1020, no. 1 (May 2004): 263–76. http://dx.doi.org/10.1196/annals.1310.021.

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Fenstermacher, David A. "Book Review: Bioinformatics in Cancer and Cancer Therapy." Cancer Control 16, no. 4 (October 2009): 349. http://dx.doi.org/10.1177/107327480901600411.

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Xu, Chaobo, and Ming Liu. "Integrative bioinformatics analysis of KPNA2 in six major human cancers." Open Medicine 16, no. 1 (January 1, 2021): 498–511. http://dx.doi.org/10.1515/med-2021-0257.

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Abstract Background Malignant tumors were considered as the leading causes of cancer-related mortality globally. More and more studies found that dysregulated genes played an important role in carcinogenesis. The aim of this study was to explore the significance of KPNA2 in human six major cancers including non-small cell lung cancer (NSCLC), gastric cancer, colorectal cancer, breast cancer, hepatocellular carcinoma, and bladder cancer based on bioinformatics analysis. Methods The data were collected and comprehensively analyzed based on multiple databases. KPNA2 mRNA expression in six major c
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Van Neste, Leander, James G. Herman, Kornel E. Schuebel, Leslie Cope, Stephen B. Baylin, Wim Van Criekinge, and Nita Ahuja. "A Bioinformatics Pipeline for Cancer Epigenetics." Current Bioinformatics 5, no. 3 (September 1, 2010): 153–63. http://dx.doi.org/10.2174/157489310792006710.

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YANG, HOWARD H., and MAXWELL P. LEE. "Application of Bioinformatics in Cancer Epigenetics." Annals of the New York Academy of Sciences 1020, no. 1 (May 2004): 67–76. http://dx.doi.org/10.1196/annals.1310.008.

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Charoentong, Pornpimol, Mihaela Angelova, Mirjana Efremova, Ralf Gallasch, Hubert Hackl, Jerome Galon, and Zlatko Trajanoski. "Bioinformatics for cancer immunology and immunotherapy." Cancer Immunology, Immunotherapy 61, no. 11 (September 18, 2012): 1885–903. http://dx.doi.org/10.1007/s00262-012-1354-x.

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Tesis sobre el tema "Cancer bioinformatics"

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Webber, James Trubek. "Cancer Bioinformatics for Biomarker Discovery." Thesis, University of California, San Francisco, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10604636.

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<p> Cancer is a complex and multifaceted disease, and a vast amount of time and effort has been spent on characterizing its behaviors, identifying its weaknesses, and discovering effective treatments. Two major obstacles stand in the way of progress toward effective precision treatment for the majority of patients.</p><p> First, cancer's extraordinary heterogeneity&mdash;both between and even within patients&mdash;means that most patients present with a disease slightly different from every previously recorded case. New methods are necessary to analyze the growing body of patient data so tha
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Wang, Leying. "Noncoding RNA-Involved Interactions for Cancer Prognosis: A Prostate Cancer Study." The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1586651927830285.

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Wu, Tsung-Jung. "Integration of Cancer-Related Mutations for Pan-Cancer Analysis." Thesis, The George Washington University, 2014. http://pqdtopen.proquest.com/#viewpdf?dispub=1556905.

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<p> Years of sequence feature curation by UniProtKB/Swiss-Prot, PIR-PSD, NCBI-CDD, RefSeq and other database biocurators has led to a rich repository of information on functional sites of genes and proteins. This information along with variation-related annotation can be used to scan human short sequence reads from next-generation sequencing (NGS) pipelines for presence of non-synonymous single-nucleotide variations (nsSNVs) that affect functional sites. This and similar workflows are becoming more important because thousands of NGS data sets are being made available through projects such as T
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Pepin, Francois. "Bioinformatics approaches to understanding the breast cancer microenvironment." Thesis, McGill University, 2010. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=92240.

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Breast cancer is a complex disease that requires the acquisition of several traits in order to proliferate and spread to nearby and distant tissues. However, many combinations are possible, making it harder to determine their significance. Genome-wide approaches such as gene expression profiling have provided an unbiased and global tool to investigate those traits, allowing investigators to both separate tumors into biologically meaningful categories and then to investigate their features in that context. A well-organized effort is required in order to collect and analyze the large number of s
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Liao, Peter Lee Ming Liao. "Bioinformatics approaches to cancer biomarker discovery and characterization." Case Western Reserve University School of Graduate Studies / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=case1525694252170957.

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Zacharouli, Markella-Achilleia. "Characterization of immune infiltrate in early breast cancer based on a multiplex imaging method." Thesis, Uppsala universitet, Institutionen för biologisk grundutbildning, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-417716.

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Breast cancer is the most common type of cancer among women worldwide. Multiple studies have reported the role of tumor-immune interactions and mechanisms that the immune system uses to combat tumor cells. Therapies based on the immune response are evolving by time, but more research is required to understand and identify the patterns and relationships within the tumor microenvironment. This study aims to characterize immune cell expression patterns using a multiplex method and to investigate the way different subpopulations in breast cancer patients’ tissue samples are correlated with clinico
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Hillerton, Thomas. "Predicting adverse drug reactions in cancer treatment using a neural network based approach." Thesis, Högskolan i Skövde, Institutionen för biovetenskap, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-15659.

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Pestana, Valeria. "Modeling drug response in cancer cell linesusing genotype and high-throughput“omics” data." Thesis, KTH, Skolan för datavetenskap och kommunikation (CSC), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-166744.

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Stetson, Lindsay C. "Computational Approaches for Cancer Precision Medicine." Case Western Reserve University School of Graduate Studies / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=case1428050439.

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Bebek, Gurkan. "Functional Characteristics of Cancer Driver Genes in Colorectal Cancer." Case Western Reserve University School of Graduate Studies / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=case1495012693440067.

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Libros sobre el tema "Cancer bioinformatics"

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Nagl, Sylvia, ed. Cancer Bioinformatics. Chichester, UK: John Wiley & Sons, Ltd, 2006. http://dx.doi.org/10.1002/0470032898.

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Krasnitz, Alexander, ed. Cancer Bioinformatics. New York, NY: Springer New York, 2019. http://dx.doi.org/10.1007/978-1-4939-8868-6.

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Xu, Ying, Juan Cui, and David Puett. Cancer Bioinformatics. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-1381-7.

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Gordon, Gavin J., ed. Bioinformatics in Cancer and Cancer Therapy. Totowa, NJ: Humana Press, 2009. http://dx.doi.org/10.1007/978-1-59745-576-3.

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Boegel, Sebastian, ed. Bioinformatics for Cancer Immunotherapy. New York, NY: Springer US, 2020. http://dx.doi.org/10.1007/978-1-0716-0327-7.

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Cesario, Alfredo, and Frederick Marcus, eds. Cancer Systems Biology, Bioinformatics and Medicine. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-1567-7.

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Schmitz, Ulf. MicroRNA Cancer Regulation: Advanced Concepts, Bioinformatics and Systems Biology Tools. Dordrecht: Springer Netherlands, 2013.

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Cesario, Alfredo. Cancer Systems Biology, Bioinformatics and Medicine: Research and Clinical Applications. Dordrecht: Springer Science+Business Media B.V., 2011.

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Computational systems biology of cancer. Boca Raton, FL: Taylor & Francis, 2013.

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Kashyap, Amita, D. Bujamma, and Naresh Babu M. Bioinformatics of Non Small Cell Lung Cancer and the Ras Proto-Oncogene. Singapore: Springer Singapore, 2015. http://dx.doi.org/10.1007/978-981-4585-08-8.

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Capítulos de libros sobre el tema "Cancer bioinformatics"

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He, Mingyan, Li Feng, and Jinglin Xia. "Cancer Bioinformatics." In Single Cell Sequencing and Systems Immunology, 175–77. Dordrecht: Springer Netherlands, 2015. http://dx.doi.org/10.1007/978-94-017-9753-5_13.

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Meetz, Kirsten, Hans-Peter Meinzer, Sândor Suhai, and Martina Kieninger. "Bioinformatics." In Current Cancer Research 1992, 183–200. Heidelberg: Steinkopff, 1992. http://dx.doi.org/10.1007/978-3-662-11384-4_10.

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Reczko, Martin, Sándor Suhai, Annemarie Poustka, Uwe Engelmann, Manuela Schäfer, and Hans-Peter Meinzer. "Bioinformatics." In Current Cancer Research 1995, 147–66. Heidelberg: Steinkopff, 1995. http://dx.doi.org/10.1007/978-3-642-48687-6_11.

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Neidle, Stephen. "Structural Bioinformatics in Cancer." In Cancer Bioinformatics, 127–40. Chichester, UK: John Wiley & Sons, Ltd, 2006. http://dx.doi.org/10.1002/0470032898.ch7.

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Xu, Ying, Juan Cui, and David Puett. "Basic Cancer Biology." In Cancer Bioinformatics, 1–39. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-1381-7_1.

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Nagl, Sylvia. "A Path to Knowledge: from Data to Complex Systems Models of Cancer." In Cancer Bioinformatics, 1–27. Chichester, UK: John Wiley & Sons, Ltd, 2006. http://dx.doi.org/10.1002/0470032898.ch1.

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Brentani, Ricardo, Anamaria A. Camargo, Helena Brentani, and Sandro J. De Souza. "The FAPESP/LICR Human Cancer Genome Project: Perspectives on Integration." In Cancer Bioinformatics, 169–84. Chichester, UK: John Wiley & Sons, Ltd, 2006. http://dx.doi.org/10.1002/0470032898.ch10.

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Knox, Kirstine, Amanda Taylor, and David J. Kerr. "Today's Science, Tomorrow's Patient: the Pivotal Role of Tissue, Clinical Data and Informatics in Modern Drug Development." In Cancer Bioinformatics, 185–209. Chichester, UK: John Wiley & Sons, Ltd, 2006. http://dx.doi.org/10.1002/0470032898.ch11.

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Gotterbarn, Don, and Simon Rogerson. "Software Design Ethics for Biomedicine." In Cancer Bioinformatics, 211–31. Chichester, UK: John Wiley & Sons, Ltd, 2006. http://dx.doi.org/10.1002/0470032898.ch12.

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Kalra, Dipak, and David Ingram. "Ethical Issues of Electronic Patient Data and Informatics in Clinical Trial Settings." In Cancer Bioinformatics, 233–56. Chichester, UK: John Wiley & Sons, Ltd, 2006. http://dx.doi.org/10.1002/0470032898.ch13.

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Actas de conferencias sobre el tema "Cancer bioinformatics"

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Giakos, George C., Stefanie Marotta, Suman Shrestha, Aditi Deshpande, Tannaz Farrahi, Lin Zhang, Thomas Cambria, et al. "Bioinformatics of Lung Cancer." In 2015 IEEE International Conference on Imaging Systems and Techniques (IST). IEEE, 2015. http://dx.doi.org/10.1109/ist.2015.7294524.

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Zhang, Jingshu, Hao Sun, Xuyao An, Kun Yu, Penglin Li, and Hao Sun. "Bioinformatics analysis of colorectal cancer related gene." In 2019 6th International Conference on Systems and Informatics (ICSAI). IEEE, 2019. http://dx.doi.org/10.1109/icsai48974.2019.9010480.

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Hashem, Hasan, and Iyad Sultan. "Immune Dysregulation Disorders in the Bioinformatics Paradigm." In 2018 1st International Conference on Cancer Care Informatics (CCI). IEEE, 2018. http://dx.doi.org/10.1109/cancercare.2018.8618246.

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Goldin, Leah. "Bioinformatics Integration for Cancer Research-Goal Question analysis." In 2006 International Conference on Information Technology: Research and Education. IEEE, 2006. http://dx.doi.org/10.1109/itre.2006.381575.

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Liu, Wenjia, Nanjiao Ying, Qiusi Mo, and Lei Zhu. "Screening Potential Biomarkers of Breast Cancer Based on Bioinformatics." In ICBBS '20: 2020 9th International Conference on Bioinformatics and Biomedical Science. New York, NY, USA: ACM, 2020. http://dx.doi.org/10.1145/3431943.3432282.

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Alsmadi, Osama, Mohammed Odeh, Iyad Sultan, Anas Al-okaily, and Abdelghani Tbakhi. "Bridging Arabian Mendelian and Complex Diseases Necessitates Utilizing Modern Bioinformatics." In 2018 1st International Conference on Cancer Care Informatics (CCI). IEEE, 2018. http://dx.doi.org/10.1109/cancercare.2018.8618237.

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Phan, J. H., Qiqin Yin-Goen, A. N. Young, and M. D. Wang. "Emerging translational bioinformatics: Knowledge-guided biomarker identification for cancer diagnostics." In 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2009. http://dx.doi.org/10.1109/iembs.2009.5333937.

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Rodríguez-Segura, M. A., J. J. Godina-Nava, and S. Villa-Treviño. "The bioinformatics of microarrays to study cancer: Advantages and disadvantages." In MEDICAL PHYSICS: Twelfth Mexican Symposium on Medical Physics. AIP, 2012. http://dx.doi.org/10.1063/1.4764632.

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Wasti, Afshan Zeeshan. "ERBB2 - A Potential Breast Cancer Marker: An Integrated Bioinformatics Strategy." In IBRAS 2021 INTERNATIONAL CONFERENCE ON BIOLOGICAL RESEARCH AND APPLIED SCIENCE. Juw, 2021. http://dx.doi.org/10.37962/ibras/2021/1-2.

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"PROGNOSIS OF BREAST CANCER BASED ON A FUZZY CLASSIFICATION METHOD." In International Conference on Bioinformatics. SciTePress - Science and and Technology Publications, 2010. http://dx.doi.org/10.5220/0002716601230130.

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Informes sobre el tema "Cancer bioinformatics"

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Brueggemeier, Robert W. Drug Discovery and Structural Bioinformatics in Breast Cancer. Fort Belvoir, VA: Defense Technical Information Center, December 1999. http://dx.doi.org/10.21236/ada384146.

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