Gotowa bibliografia na temat „Epigenomic regulators”
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Artykuły w czasopismach na temat "Epigenomic regulators"
Al-Janabi, Ismail. "Therapeutic Targeting of the Regulators of Cancer Epigenomes". Al-Rafidain Journal of Medical Sciences ( ISSN 2789-3219 ) 5 (1.07.2023): 1–13. http://dx.doi.org/10.54133/ajms.v5i.128.
Pełny tekst źródłaPaul, Aswathy Mary, Madhavan Radhakrishna Pillai i Rakesh Kumar. "Prognostic Significance of Dysregulated Epigenomic and Chromatin Modifiers in Cervical Cancer". Cells 10, nr 10 (5.10.2021): 2665. http://dx.doi.org/10.3390/cells10102665.
Pełny tekst źródłaSchmitz, Ulf, Jaynish S. Shah, Bijay P. Dhungel, Geoffray Monteuuis, Phuc-Loi Luu, Veronika Petrova, Cynthia Metierre i in. "Widespread Aberrant Alternative Splicing despite Molecular Remission in Chronic Myeloid Leukaemia Patients". Cancers 12, nr 12 (11.12.2020): 3738. http://dx.doi.org/10.3390/cancers12123738.
Pełny tekst źródłaZhou, Huaijun. "97 Dissection of Evolution of Cis-Regulatory Elements and Its Application on Genetic Control of Complex Traits in Farm Animals". Journal of Animal Science 101, Supplement_3 (6.11.2023): 51–52. http://dx.doi.org/10.1093/jas/skad281.063.
Pełny tekst źródłaTseng, Yen-Tzu, Hung-Fu Liao, Chih-Yun Yu, Chu-Fan Mo i Shau-Ping Lin. "Epigenetic factors in the regulation of prospermatogonia and spermatogonial stem cells". REPRODUCTION 150, nr 3 (wrzesień 2015): R77—R91. http://dx.doi.org/10.1530/rep-14-0679.
Pełny tekst źródłaDeng, Xian, Xianwei Song, Liya Wei, Chunyan Liu i Xiaofeng Cao. "Epigenetic regulation and epigenomic landscape in rice". National Science Review 3, nr 3 (1.09.2016): 309–27. http://dx.doi.org/10.1093/nsr/nww042.
Pełny tekst źródłaRada-Iglesias, Alvaro, Ruchi Bajpai, Sara Prescott, Samantha A. Brugmann, Tomek Swigut i Joanna Wysocka. "Epigenomic Annotation of Enhancers Predicts Transcriptional Regulators of Human Neural Crest". Cell Stem Cell 11, nr 5 (listopad 2012): 633–48. http://dx.doi.org/10.1016/j.stem.2012.07.006.
Pełny tekst źródłaSmetanina, Mariya A., Valeria A. Korolenya, Alexander E. Kel, Ksenia S. Sevostyanova, Konstantin A. Gavrilov, Andrey I. Shevela i Maxim L. Filipenko. "Epigenome-Wide Changes in the Cell Layers of the Vein Wall When Exposing the Venous Endothelium to Oscillatory Shear Stress". Epigenomes 7, nr 1 (20.03.2023): 8. http://dx.doi.org/10.3390/epigenomes7010008.
Pełny tekst źródłaBoix, Carles A., Benjamin T. James, Yongjin P. Park, Wouter Meuleman i Manolis Kellis. "Regulatory genomic circuitry of human disease loci by integrative epigenomics". Nature 590, nr 7845 (3.02.2021): 300–307. http://dx.doi.org/10.1038/s41586-020-03145-z.
Pełny tekst źródłakong, ranran, Ayushi S. Patel, Takashi Sato, Seungyeul Yoo, Abhilasha Sinha, Yang Tian, Feng Jiang i in. "Abstract 5709: Transcriptional circuitry of NKX2-1 and SOX1 defines a previously unrecognized lineage subtype of small cell lung cancer". Cancer Research 82, nr 12_Supplement (15.06.2022): 5709. http://dx.doi.org/10.1158/1538-7445.am2022-5709.
Pełny tekst źródłaRozprawy doktorskie na temat "Epigenomic regulators"
Ferré, Quentin. "Leveraging combinations of epigenomic regulators". Electronic Thesis or Diss., Aix-Marseille, 2021. http://www.theses.fr/2021AIXM0151.
Pełny tekst źródłaGenetic cis-regulation in humans is effected through chromatin regulators, such as histone marks and Transcriptional Regulators (TRs). Those regulators seldom act alone, instead forming complexes. The development of NGS provides experimental methods to study this regulation, which includes ChIP-seq. The goal of this thesis is to leverage such combinations through the use of machine learning methods, which are effective at learning regularities in the data. We propose to represent the regions where regulators bind as lists of intervals, converted into matrix and tensor representations. ChIP-seq and other experimental assays can suffer from errors and false positives, poor quality control, and several other biases that are difficult to correct. Furthermore, the use of larger volumes of data increases the probability of errors. We assume that noise peaks will not respect the usual combinations between sources, and propose atyPeak which exploits combinations of TRs, and redundant experiments from the ReMap database. We propose to use a multi-view convolutional autoencoder to perform a “Goldilocks” compression. We developed approaches to evaluate autoencoders based on their respect of existing correlations. Finally, the enrichment of given n-wise combinations of elements (how often they are found compared to expected by chance) needs to be precisely quantified. We propose the OLOGRAM-MODL approach, demonstrating a Monte Carlo based method to fit a Negative Binomial model on the number of base pairs on which a given combination is observed. We also propose an itemset mining algorithm to based on which combinations best rebuild the original data
DAS, VIVEK. "LEVERAGING TRANSCRIPTOMIC ANALYSIS TO IDENTIFY TRANSCRIPTION FACTORS ORCHESTRATING CANCER PROGRESSION". Doctoral thesis, Università degli Studi di Milano, 2018. http://hdl.handle.net/2434/559711.
Pełny tekst źródłaJhanwar, Shalu 1986. "Computational analysis of epigenomic variability and its effect on regulatory activity". Doctoral thesis, Universitat Pompeu Fabra, 2017. http://hdl.handle.net/10803/580601.
Pełny tekst źródłaLa epigenética proporciona un enlace plausible entre el medio ambiente y los cambios en la expresión de genes que podrían contribuir a fenotipo de las enfermedades. El objetivo principal de la tesis es el estudio de la variabilidad epigenómica y su efecto sobre la actividad reguladora subyacente a la dinámica de la cromatina. Con un objetivo último de identificar variantes de regulación que contribuyen al cáncer, así como patrones epigenómicos específicos en enfermedades neurológicas, las tesis se enfoca en el desarrollo y posterior aplicación de un nuevo método supervisado para predecir potenciadores basado en aprendizaje automático (GEP). Además, para abordar el papel de la metilación del ADN en la configuración de dos formas larvarias distintas de un solo huevo en una avispa poliembriónica parasitaria, hemos desarrollado un nuevo método computacional (dMeth-X) para identificar los genes diferencialmente metilados que podrían contribuir distinguiendo formas larvarias contrastantes. Adicionalmente, la tesis incorporó el estudio del efecto de factores externos sobre la variabilidad epigenómica de la corteza del cerebro de ratón. En general, creemos que mi tesis doctoral es un esfuerzo exitoso para estudiar la variabilidad epigenética y la actividad reguladora utilizando enfoques de secuenciación de próxima generación.
Jené, i. Sanz Alba 1984. "Integrative study of the regulatory and epigenomic programs involved in cancer development". Doctoral thesis, Universitat Pompeu Fabra, 2013. http://hdl.handle.net/10803/113380.
Pełny tekst źródłaCancer has traditionally been regarded as a genetic disease, but recently it is becoming apparent that the deregulation of epigenetic mechanisms greatly contributes to tumour development. At the crossing of genetics and epigenetics lie chromatin regulatory factors (CRFs), which are the focus of intense research due to their potential usefulness in anticancer therapy. In this thesis, I determine the transcriptomic state of normal and tumour cells based on epigenetic and regulatory information, and describe the existence of a global synchronisation of gene expression in which Polycomb regulation arises as one of the two main components. I present an analysis on how the under-expression of Polycomb regulated genes contributes to breast cancer progression and epithelial to mesenchymal transition. Furthermore, I identify this under-expression as a valuable independent prognostic factor. Taking advantage on the wealth of cancer genomics data made available recently, I also evaluate the mutational status of CRFs across many human tumours from different tissues and cancer cell lines, and find that 39 CRFs are potential cancer drivers in at least one tissue, even though most of them are mutated at relatively low frequencies. Finally, I present a resource to visualise and analyse genomic alterations across cancer cell lines in the context of drug sensitivity/resistance and the information on somatic tumour alterations.
Purcaro, Michael J. "Analysis, Visualization, and Machine Learning of Epigenomic Data". eScholarship@UMMS, 2017. https://escholarship.umassmed.edu/gsbs_diss/938.
Pełny tekst źródłaZhu, Yan. "Microfluidic Technology for Low-Input Epigenomic Analysis". Diss., Virginia Tech, 2018. http://hdl.handle.net/10919/83402.
Pełny tekst źródłaPh. D.
Batra, Rajbir Nath. "Decoding the regulatory role and epiclonal dynamics of DNA methylation in 1482 breast tumours". Thesis, University of Cambridge, 2018. https://www.repository.cam.ac.uk/handle/1810/274923.
Pełny tekst źródłaBogatyrova, Olga [Verfasser], i Christoph [Akademischer Betreuer] Plass. "Mutations in regulators of the epigenome and their effects on the DNA methylome / Olga Bogatyrova ; Betreuer: Christoph Plass". Heidelberg : Universitätsbibliothek Heidelberg, 2016. http://d-nb.info/1180617304/34.
Pełny tekst źródłaMorikawa, Hiromasa. "Differential roles of epigenetic changes and Foxp3 expression in regulatory T cell-specific transcriptional regulation". Kyoto University, 2013. http://hdl.handle.net/2433/180610.
Pełny tekst źródłaFloc'hlay, Swann. "Computational analysis and modelling of regulatory networks controlling embryonic development". Electronic Thesis or Diss., Université Paris sciences et lettres, 2020. http://www.theses.fr/2020UPSLE036.
Pełny tekst źródłaThe development of an embryo derives from the DNA sequence of this organism. Genetic variability gives rise to great morphological diversity, while maintaining a robust general organisation. Mutations present within cis-regulatory regions impact transcription via epigenomic mechanisms. The resulting variability in gene expression can be buffered by tran feedback mechanisms within the regulatory network. The precise organisation of these cis and trans interactions remains difficult to decipher. In order to better grasp the effect of mutations on transcription, I analysed genetic, epigenomic and transcriptomic data in collaboration with the Furlong laboratory (EMBL, Heidelberg). The use of allele-specific data from Drosophila F1 lines enabled to infer direct cis-interactions between the regulatory layers, suggesting a difference in the action of the epigenomic markers H3K27ac and H3K4me3 on gene expression. To better understand the trans impact of the structure of regulatory networks on gene expression, I have built a logical model of the dorsal-ventral axis specification in sea urchin embryo, in collaboration with the Lepage laboratory (iBV, Nice). Multicellular and stochastic analyses permitted to detect key components of the network, including the cross-repression dynamic between Nodal and BMP. To conclude, allele-specific data analysis and logical modelling allowed me to study the mechanisms of transcription regulation from two complementary perspectives
Książki na temat "Epigenomic regulators"
Lusardi, Theresa A., i Detlev Boison. Ketogenic Diet, Adenosine, Epigenetics, and Antiepileptogenesis. Redaktor Detlev Boison. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780190497996.003.0023.
Pełny tekst źródłaCzęści książek na temat "Epigenomic regulators"
Zhu, Yan, i Chang Lu. "Microfluidic Chromatin Immunoprecipitation for Analysis of Epigenomic Regulations". W Microfluidic Methods for Molecular Biology, 349–63. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-30019-1_16.
Pełny tekst źródłaJhanwar, Shalu. "Computational Epigenomics and Its Application in Regulatory Genomics". W Bioinformatics: Sequences, Structures, Phylogeny, 115–39. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1562-6_6.
Pełny tekst źródłaHu, Yongfeng, i Dao-Xiu Zhou. "Rice Epigenomes: Characteristics, Regulatory Functions, and Reprogramming Mechanisms". W Rice Genomics, Genetics and Breeding, 453–71. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-7461-5_23.
Pełny tekst źródłaRoy Choudhury, Samrat, i Brian A. Walker. "Aberrant Epigenomic Regulatory Networks in Multiple Myeloma and Strategies for Their Targeted Reversal". W RNA Technologies, 543–72. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-14792-1_22.
Pełny tekst źródłaKlann, Tyler S., Gregory E. Crawford, Timothy E. Reddy i Charles A. Gersbach. "Screening Regulatory Element Function with CRISPR/Cas9-based Epigenome Editing". W Methods in Molecular Biology, 447–80. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4939-7774-1_25.
Pełny tekst źródłaHalene, Tobias B., Gregor Hasler, Amanda Mitchell i Schahram Akbarian. "Epigenomic Exploration of the Human Brain". W Psychiatric Genetics, 144–64. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190221973.003.0010.
Pełny tekst źródłaZhou, Tong. "Small non-coding RNAs as epigenetic regulators". W Nutritional Epigenomics, 37–47. Elsevier, 2019. http://dx.doi.org/10.1016/b978-0-12-816843-1.00003-5.
Pełny tekst źródłaBeetch, Megan, Sadaf Harandi-Zadeh, Kate Shen i Barbara Stefanska. "Stilbenoids as dietary regulators of the cancer epigenome". W Nutritional Epigenomics, 353–70. Elsevier, 2019. http://dx.doi.org/10.1016/b978-0-12-816843-1.00021-7.
Pełny tekst źródłaMihaylova, Maria M., i Matthew S. Stratton. "Short chain fatty acids as epigenetic and metabolic regulators of neurocognitive health and disease". W Nutritional Epigenomics, 381–97. Elsevier, 2019. http://dx.doi.org/10.1016/b978-0-12-816843-1.00023-0.
Pełny tekst źródłaYan, Menghong. "The paternal diet regulates the offspring epigenome and health". W Nutritional Epigenomics, 191–200. Elsevier, 2019. http://dx.doi.org/10.1016/b978-0-12-816843-1.00012-6.
Pełny tekst źródłaStreszczenia konferencji na temat "Epigenomic regulators"
Takamatsu, Hironori, Naoko Hattori, Naofumi Asano, Naoko Iida, Akihiko Yoshida, Eisuke Kobayashi, Robert Nakayama i in. "Abstract 843: Epigenomic disruption of adipogenic regulators in dedifferentiated liposarcoma". W Proceedings: AACR Annual Meeting 2019; March 29-April 3, 2019; Atlanta, GA. American Association for Cancer Research, 2019. http://dx.doi.org/10.1158/1538-7445.sabcs18-843.
Pełny tekst źródłaTakamatsu, Hironori, Naoko Hattori, Naofumi Asano, Naoko Iida, Akihiko Yoshida, Eisuke Kobayashi, Robert Nakayama i in. "Abstract 843: Epigenomic disruption of adipogenic regulators in dedifferentiated liposarcoma". W Proceedings: AACR Annual Meeting 2019; March 29-April 3, 2019; Atlanta, GA. American Association for Cancer Research, 2019. http://dx.doi.org/10.1158/1538-7445.am2019-843.
Pełny tekst źródłaGEVAERT, OLIVIER, i SYLVIA PLEVRITIS. "IDENTIFYING MASTER REGULATORS OF CANCER AND THEIR DOWNSTREAM TARGETS BY INTEGRATING GENOMIC AND EPIGENOMIC FEATURES". W Proceedings of the Pacific Symposium. WORLD SCIENTIFIC, 2012. http://dx.doi.org/10.1142/9789814447973_0013.
Pełny tekst źródłaWorsham, MJ, KM Chen, I. Datta, JK Stephen, D. Chitale i G. Divine. "Abstract P1-04-06: Network integration of epigenomic data: Leveraging the concept of master regulators in ER negative breast cancer". W Abstracts: 2016 San Antonio Breast Cancer Symposium; December 6-10, 2016; San Antonio, Texas. American Association for Cancer Research, 2017. http://dx.doi.org/10.1158/1538-7445.sabcs16-p1-04-06.
Pełny tekst źródłaBattle, Stephanie L., Antti Larjo, Joling Liao, Harri Lähdesmäki, Andre Lieber i R. David Hawkins. "Abstract AS04: Epigenomic characterization of gene regulatory networks in human ovarian cancer stem cells". W Abstracts: 10th Biennial Ovarian Cancer Research Symposium; September 8-9, 2014; Seattle, WA. American Association for Cancer Research, 2015. http://dx.doi.org/10.1158/1557-3265.ovcasymp14-as04.
Pełny tekst źródłaLaFave, Lindsay M., Vinay Kartha, Sai Ma, Kevin Meli, Isabella Del Priore, Caleb Lareau, Venkat Sanker i in. "Abstract PR08: Leveraging single-cell epigenomics to uncover regulatory programs in lung adenocarcinoma". W Abstracts: AACR Special Conference on the Evolving Landscape of Cancer Modeling; March 2-5, 2020; San Diego, CA. American Association for Cancer Research, 2020. http://dx.doi.org/10.1158/1538-7445.camodels2020-pr08.
Pełny tekst źródłaTricarico, Rossella, Pietro Mancuso, Vikram Bhattacharjee, Neil Beeharry, Emmanuelle Nicolas, Margret Einarson, Laura Cosentino i in. "Abstract LB-249: TDG, a dual genomic and epigenomic regulator, as a novel antimelanoma target". W Proceedings: AACR 106th Annual Meeting 2015; April 18-22, 2015; Philadelphia, PA. American Association for Cancer Research, 2015. http://dx.doi.org/10.1158/1538-7445.am2015-lb-249.
Pełny tekst źródłaXU, Liangliang, Feng WU, Otto K. W. CHEUNG, Lemuel L. M. SZETO, Myth T. S. MOK, Kevin Y. L. Yip, Ka F. To i Alfred S. L. CHENG. "Abstract 868: Epigenomic profiling of primary hepatocellular carcinoma reveals super-enhancer-associated chromatin regulator network". W Proceedings: AACR Annual Meeting 2019; March 29-April 3, 2019; Atlanta, GA. American Association for Cancer Research, 2019. http://dx.doi.org/10.1158/1538-7445.sabcs18-868.
Pełny tekst źródłaXU, Liangliang, Feng WU, Otto K. W. CHEUNG, Lemuel L. M. SZETO, Myth T. S. MOK, Kevin Y. L. Yip, Ka F. To i Alfred S. L. CHENG. "Abstract 868: Epigenomic profiling of primary hepatocellular carcinoma reveals super-enhancer-associated chromatin regulator network". W Proceedings: AACR Annual Meeting 2019; March 29-April 3, 2019; Atlanta, GA. American Association for Cancer Research, 2019. http://dx.doi.org/10.1158/1538-7445.am2019-868.
Pełny tekst źródłaZacharias, W., M. Morley, D. T. Swarr, P. Senthamarai Kannan, M. C. Basil i E. E. Morrisey. "Integrated Epigenomic Analysis of the Gene Regulatory Networks Underlying Regenerative Capacity in Alveolar Epithelial Progenitor Cells". W American Thoracic Society 2019 International Conference, May 17-22, 2019 - Dallas, TX. American Thoracic Society, 2019. http://dx.doi.org/10.1164/ajrccm-conference.2019.199.1_meetingabstracts.a4012.
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