Zeitschriftenartikel zum Thema „Multiomics analysis“
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Lee, Jeongwoo, Do Young Hyeon und Daehee Hwang. „Single-cell multiomics: technologies and data analysis methods“. Experimental & Molecular Medicine 52, Nr. 9 (September 2020): 1428–42. http://dx.doi.org/10.1038/s12276-020-0420-2.
Dai, Ling-Yun, Rong Zhu und Juan Wang. „Joint Nonnegative Matrix Factorization Based on Sparse and Graph Laplacian Regularization for Clustering and Co-Differential Expression Genes Analysis“. Complexity 2020 (16.11.2020): 1–10. http://dx.doi.org/10.1155/2020/3917812.
Wang, Tzu-Hao, Cheng-Yang Lee, Tzong-Yi Lee, Hsien-Da Huang, Justin Bo-Kai Hsu und Tzu-Hao Chang. „Biomarker Identification through Multiomics Data Analysis of Prostate Cancer Prognostication Using a Deep Learning Model and Similarity Network Fusion“. Cancers 13, Nr. 11 (21.05.2021): 2528. http://dx.doi.org/10.3390/cancers13112528.
Boroń, Dariusz, Nikola Zmarzły, Magdalena Wierzbik-Strońska, Joanna Rosińczuk, Paweł Mieszczański und Beniamin Oskar Grabarek. „Recent Multiomics Approaches in Endometrial Cancer“. International Journal of Molecular Sciences 23, Nr. 3 (22.01.2022): 1237. http://dx.doi.org/10.3390/ijms23031237.
Rotroff, Daniel M., und Alison A. Motsinger-Reif. „Embracing Integrative Multiomics Approaches“. International Journal of Genomics 2016 (2016): 1–5. http://dx.doi.org/10.1155/2016/1715985.
Nassar, Sam F., Khadir Raddassi und Terence Wu. „Single-Cell Multiomics Analysis for Drug Discovery“. Metabolites 11, Nr. 11 (25.10.2021): 729. http://dx.doi.org/10.3390/metabo11110729.
Perkel, Jeffrey M. „Single-cell analysis enters the multiomics age“. Nature 595, Nr. 7868 (19.07.2021): 614–16. http://dx.doi.org/10.1038/d41586-021-01994-w.
Marshall, John L., Beth N. Peshkin, Takayuki Yoshino, Jakob Vowinckel, Håvard E. Danielsen, Gerry Melino, Ioannis Tsamardinos et al. „The Essentials of Multiomics“. Oncologist 27, Nr. 4 (22.02.2022): 272–84. http://dx.doi.org/10.1093/oncolo/oyab048.
Campuzano, Susana, Rodrigo Barderas, Paloma Yáñez-Sedeño und José M. Pingarrón. „Electrochemical biosensing to assist multiomics analysis in precision medicine“. Current Opinion in Electrochemistry 28 (August 2021): 100703. http://dx.doi.org/10.1016/j.coelec.2021.100703.
Xing, Lu, Tao Wu, Li Yu, Nian Zhou, Zhao Zhang, Yunjing Pu, Jinnan Wu und Hong Shu. „Exploration of Biomarkers of Psoriasis through Combined Multiomics Analysis“. Mediators of Inflammation 2022 (23.09.2022): 1–25. http://dx.doi.org/10.1155/2022/7731082.
Li, Lin, Long Bai, Huan Lin, Lin Dong, Rumeng Zhang, Xiao Cheng, Zexian Liu, Yi Ouyang und Keshuo Ding. „Multiomics analysis of tumor mutational burden across cancer types“. Computational and Structural Biotechnology Journal 19 (2021): 5637–46. http://dx.doi.org/10.1016/j.csbj.2021.10.013.
He, Yong, Hao Chen, Hao Sun, Jiadong Ji, Yufeng Shi, Xinsheng Zhang und Lei Liu. „High‐dimensional integrative copula discriminant analysis for multiomics data“. Statistics in Medicine 39, Nr. 30 (15.10.2020): 4869–84. http://dx.doi.org/10.1002/sim.8758.
Nygren, Petra Johanna, Aino Häkkinen, Daehong Kim, Timo Jarvinen, Fumihiro Ishida, Stefania Bortoluzzi, Andrea Binatti et al. „A Comprehensive, Multiomics Analysis of Natural Killer-Cell Malignancies“. Blood 140, Supplement 1 (15.11.2022): 6390–91. http://dx.doi.org/10.1182/blood-2022-162285.
Sherrod, Stacy D., und John A. McLean. „Systems-Wide High-Dimensional Data Acquisition and Informatics Using Structural Mass Spectrometry Strategies“. Clinical Chemistry 62, Nr. 1 (01.01.2016): 77–83. http://dx.doi.org/10.1373/clinchem.2015.238261.
Taguchi, Y.-h., und Turki Turki. „Tensor-Decomposition-Based Unsupervised Feature Extraction in Single-Cell Multiomics Data Analysis“. Genes 12, Nr. 9 (18.09.2021): 1442. http://dx.doi.org/10.3390/genes12091442.
Kaur, Harpreet, Rajesh Kumar, Anjali Lathwal und Gajendra P. S. Raghava. „Computational resources for identification of cancer biomarkers from omics data“. Briefings in Functional Genomics 20, Nr. 4 (01.04.2021): 213–22. http://dx.doi.org/10.1093/bfgp/elab021.
Pak, Kyoungjune, Sae-Ock Oh, Tae Sik Goh, Hye Jin Heo, Myoung-Eun Han, Dae Cheon Jeong, Chi-Seung Lee et al. „A User-Friendly, Web-Based Integrative Tool (ESurv) for Survival Analysis: Development and Validation Study“. Journal of Medical Internet Research 22, Nr. 5 (05.05.2020): e16084. http://dx.doi.org/10.2196/16084.
Jiang, Aimin, Yewei Bao, Anbang Wang, Wenliang Gong, Xinxin Gan, Jie Wang, Yi Bao et al. „Establishment of a Prognostic Prediction and Drug Selection Model for Patients with Clear Cell Renal Cell Carcinoma by Multiomics Data Analysis“. Oxidative Medicine and Cellular Longevity 2022 (04.01.2022): 1–30. http://dx.doi.org/10.1155/2022/3617775.
Gao, Junpeng, Yuxuan Zheng, Lin Li, Minjie Lu, Xiangjian Chen, Yu Wang, Yanna Li et al. „Integrated transcriptomics and epigenomics reveal chamber-specific and species-specific characteristics of human and mouse hearts“. PLOS Biology 19, Nr. 5 (18.05.2021): e3001229. http://dx.doi.org/10.1371/journal.pbio.3001229.
Ugidos, Manuel, Sonia Tarazona, José M. Prats-Montalbán, Alberto Ferrer und Ana Conesa. „MultiBaC: A strategy to remove batch effects between different omic data types“. Statistical Methods in Medical Research 29, Nr. 10 (04.03.2020): 2851–64. http://dx.doi.org/10.1177/0962280220907365.
Lin, Jimmy, Eric Ariazi, Michael Dzamba, Teng-Kuei Hsu, Steven Kothen-Hill, Kang Li, Tzu-Yu Liu et al. „Evaluation of a sensitive blood test for the detection of colorectal advanced adenomas in a prospective cohort using a multiomics approach.“ Journal of Clinical Oncology 39, Nr. 3_suppl (20.01.2021): 43. http://dx.doi.org/10.1200/jco.2021.39.3_suppl.43.
Cancemi, Patrizia, Miriam Buttacavoli, Gianluca Di Cara, Nadia Ninfa Albanese, Serena Bivona, Ida Pucci-Minafra und Salvatore Feo. „A multiomics analysis of S100 protein family in breast cancer“. Oncotarget 9, Nr. 49 (26.06.2018): 29064–81. http://dx.doi.org/10.18632/oncotarget.25561.
Lin, Dan‐Yu, Donglin Zeng und David Couper. „A general framework for integrative analysis of incomplete multiomics data“. Genetic Epidemiology 44, Nr. 7 (21.07.2020): 646–64. http://dx.doi.org/10.1002/gepi.22328.
Taguchi, Y.-h., und Turki Turki. „Tensor-Decomposition-Based Unsupervised Feature Extraction Applied to Prostate Cancer Multiomics Data“. Genes 11, Nr. 12 (11.12.2020): 1493. http://dx.doi.org/10.3390/genes11121493.
Carapito, Raphael, Christine Carapito, Aurore Morlon, Nicodème Paul, Alvaro Sebastian Vaca Jacome, Ghada Alsaleh, Véronique Rolli et al. „Multi-OMICS analyses unveil STAT1 as a potential modifier gene in mevalonate kinase deficiency“. Annals of the Rheumatic Diseases 77, Nr. 11 (20.07.2018): 1675–87. http://dx.doi.org/10.1136/annrheumdis-2018-213524.
Kalari, Krishna R., Jason P. Sinnwell, Kevin J. Thompson, Xiaojia Tang, Erin E. Carlson, Jia Yu, Peter T. Vedell et al. „PANOPLY: Omics-Guided Drug Prioritization Method Tailored to an Individual Patient“. JCO Clinical Cancer Informatics, Nr. 2 (Dezember 2018): 1–11. http://dx.doi.org/10.1200/cci.18.00012.
Sugawara, Junichi, Daisuke Ochi, Riu Yamashita, Takafumi Yamauchi, Daisuke Saigusa, Maiko Wagata, Taku Obara et al. „Maternity Log study: a longitudinal lifelog monitoring and multiomics analysis for the early prediction of complicated pregnancy“. BMJ Open 9, Nr. 2 (Februar 2019): e025939. http://dx.doi.org/10.1136/bmjopen-2018-025939.
Lianqun, Jia, Ju Xing, Ma Yixin, Chen Si, Lv Xiaoming, Song Nan, Sui Guoyuan et al. „Comprehensive multiomics analysis of the effect of ginsenoside Rb1 on hyperlipidemia“. Aging 13, Nr. 7 (19.03.2021): 9732–47. http://dx.doi.org/10.18632/aging.202728.
Han, Leshan, Xiaomeng Liu, Chongchuan Wang, Jianhang Liu, Qinglong Wang, Shuo Peng, Xidong Ren, Deqiang Zhu und Xinli Liu. „Breeding of a High-Nisin-Yielding Bacterial Strain and Multiomics Analysis“. Fermentation 8, Nr. 6 (27.05.2022): 255. http://dx.doi.org/10.3390/fermentation8060255.
Alam, Md Morshedul, Kanchan Chakma, Shahriar Mahmud, Mohammad Nazir Hossain, M. Rezaul Karim und Md Ariful Amin. „Multiomics analysis of altered NRF3 expression reveals poor prognosis in cancer“. Informatics in Medicine Unlocked 29 (2022): 100892. http://dx.doi.org/10.1016/j.imu.2022.100892.
Surowiec, Izabella, Tomas Skotare, Rickard Sjögren, Sandra Gouveia-Figueira, Judy Orikiiriza, Sven Bergström, Johan Normark und Johan Trygg. „Joint and unique multiblock analysis of biological data – multiomics malaria study“. Faraday Discussions 218 (2019): 268–83. http://dx.doi.org/10.1039/c8fd00243f.
Li, Xiunan, Jiayi Li, Leizuo Zhao, Zicheng Wang, Peizhi Zhang, Yingkun Xu und Guangzhen Wu. „Comprehensive Multiomics Analysis Reveals Potential Diagnostic and Prognostic Biomarkers in Adrenal Cortical Carcinoma“. Computational and Mathematical Methods in Medicine 2022 (09.08.2022): 1–33. http://dx.doi.org/10.1155/2022/2465598.
Quirós, Pedro M., Miguel A. Prado, Nicola Zamboni, Davide D’Amico, Robert W. Williams, Daniel Finley, Steven P. Gygi und Johan Auwerx. „Multi-omics analysis identifies ATF4 as a key regulator of the mitochondrial stress response in mammals“. Journal of Cell Biology 216, Nr. 7 (31.05.2017): 2027–45. http://dx.doi.org/10.1083/jcb.201702058.
Joseph, Serene, Jacquelyn M. Walejko, Sicong Zhang, Arthur S. Edison und Maureen Keller-Wood. „Maternal hypercortisolemia alters placental metabolism: a multiomics view“. American Journal of Physiology-Endocrinology and Metabolism 319, Nr. 5 (01.11.2020): E950—E960. http://dx.doi.org/10.1152/ajpendo.00190.2020.
Vasaikar, Suhas V., Abhijeet P. Deshmukh, Petra den Hollander, Sridevi Addanki, Nick Allen Kuburich, Sriya Kudaravalli, Robiya Joseph, Jeffrey T. Chang, Rama Soundararajan und Sendurai A. Mani. „EMTome: a resource for pan-cancer analysis of epithelial-mesenchymal transition genes and signatures“. British Journal of Cancer 124, Nr. 1 (10.12.2020): 259–69. http://dx.doi.org/10.1038/s41416-020-01178-9.
Sakallioglu, Isin Tuna, Bridget Tripp, Jacy Kubik, Carol A. Casey, Paul Thomes und Robert Powers. „Multiomics Approach Captures Hepatic Metabolic Network Altered by Chronic Ethanol Administration“. Biology 12, Nr. 1 (23.12.2022): 28. http://dx.doi.org/10.3390/biology12010028.
Li, Yuanyuan, Hang Li, Yuping Xie, Shuo Chen, Ritian Qin, Hangyan Dong, Yongliang Yu, Jianhua Wang, Xiaohong Qian und Weijie Qin. „An Integrated Strategy for Mass Spectrometry-Based Multiomics Analysis of Single Cells“. Analytical Chemistry 93, Nr. 42 (13.10.2021): 14059–67. http://dx.doi.org/10.1021/acs.analchem.0c05209.
Li, Yuanyuan, Hang Li, Yuping Xie, Shuo Chen, Ritian Qin, Hangyan Dong, Yongliang Yu, Jianhua Wang, Xiaohong Qian und Weijie Qin. „An Integrated Strategy for Mass Spectrometry-Based Multiomics Analysis of Single Cells“. Analytical Chemistry 93, Nr. 42 (13.10.2021): 14059–67. http://dx.doi.org/10.1021/acs.analchem.0c05209.
Yang, Chengcong, Lijun You, Lai-Yu Kwok, Hao Jin, Jiangying Peng, Zhixin Zhao und Zhihong Sun. „Strain-level multiomics analysis reveals significant variation in cheeses from different regions“. LWT 151 (November 2021): 112043. http://dx.doi.org/10.1016/j.lwt.2021.112043.
Van Pelt, Douglas W., Yalda A. Kharaz, Dylan C. Sarver, Logan R. Eckhardt, Justin T. Dzierzawski, Nathaniel P. Disser, Alex N. Piacentini, Eithne Comerford, Brian McDonagh und Christopher L. Mendias. „Multiomics analysis of the mdx/mTR mouse model of Duchenne muscular dystrophy“. Connective Tissue Research 62, Nr. 1 (15.07.2020): 24–39. http://dx.doi.org/10.1080/03008207.2020.1791103.
Ge, Siqi, Youxin Wang, Manshu Song, Xingang Li, Xinwei Yu, Hao Wang, Jing Wang, Qiang Zeng und Wei Wang. „Type 2 Diabetes Mellitus: Integrative Analysis of Multiomics Data for Biomarker Discovery“. OMICS: A Journal of Integrative Biology 22, Nr. 7 (Juli 2018): 514–23. http://dx.doi.org/10.1089/omi.2018.0053.
Feng, Zheng, Danyi Wang, Francesco Vallania, Neil Smith, Anupriya Tripathi und Juergen Scheuenpflug. „Abstract 5113: Liquid biopsy-based multiomics profiling using low-pass whole genome sequencing and proteomics with computational modeling reveals molecular correlates of disease severity in EGFR/ALK wild type NSCLC patients“. Cancer Research 82, Nr. 12_Supplement (15.06.2022): 5113. http://dx.doi.org/10.1158/1538-7445.am2022-5113.
Bisht, Vartika, Katrina Nash, Yuanwei Xu, Prasoon Agarwal, Sofie Bosch, Georgios V. Gkoutos und Animesh Acharjee. „Integration of the Microbiome, Metabolome and Transcriptomics Data Identified Novel Metabolic Pathway Regulation in Colorectal Cancer“. International Journal of Molecular Sciences 22, Nr. 11 (28.05.2021): 5763. http://dx.doi.org/10.3390/ijms22115763.
Ichihashi, Yasunori, Yasuhiro Date, Amiu Shino, Tomoko Shimizu, Arisa Shibata, Kie Kumaishi, Fumiaki Funahashi et al. „Multi-omics analysis on an agroecosystem reveals the significant role of organic nitrogen to increase agricultural crop yield“. Proceedings of the National Academy of Sciences 117, Nr. 25 (08.06.2020): 14552–60. http://dx.doi.org/10.1073/pnas.1917259117.
Ohashi, Hiroyuki, Mai Hasegawa, Kentaro Wakimoto und Etsuko Miyamoto-Sato. „Next-Generation Technologies for Multiomics Approaches Including Interactome Sequencing“. BioMed Research International 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/104209.
Ma, Yawen, und Zhuo Xi. „Integrated Analysis of Multiomics Data Identified Molecular Subtypes and Oxidative Stress-Related Prognostic Biomarkers in Glioblastoma Multiforme“. Oxidative Medicine and Cellular Longevity 2022 (22.09.2022): 1–15. http://dx.doi.org/10.1155/2022/9993319.
Li, Hanwen, Shaohua Chen und Hua Mi. „A Multiomics Profiling Based on Online Database Revealed Prognostic Biomarkers of BLCA“. BioMed Research International 2022 (25.05.2022): 1–19. http://dx.doi.org/10.1155/2022/2449449.
Liu, Dazhong, Pengfei Zhang, Jiaying Zhao, Lei Yang und Wei Wang. „Identification of Molecular Characteristics and New Prognostic Targets for Thymoma by Multiomics Analysis“. BioMed Research International 2021 (19.05.2021): 1–15. http://dx.doi.org/10.1155/2021/5587441.
Liu, Li, Jianjun Huang, Yan Liu, Xingshou Pan, Zhile Li, Liufang Zhou, Tengfang Lai et al. „Multiomics Analysis of Transcriptome, Epigenome, and Genome Uncovers Putative Mechanisms for Dilated Cardiomyopathy“. BioMed Research International 2021 (29.03.2021): 1–29. http://dx.doi.org/10.1155/2021/6653802.
Shen, Yiqing, Wensong Yang, Xin Xiong, Xinhui Li, Zhongsong Xiao, Jialun Yu, Fangyu Liu et al. „Integrated Multiomics Analysis Identifies a Novel Biomarker Associated with Prognosis in Intracerebral Hemorrhage“. Oxidative Medicine and Cellular Longevity 2021 (14.12.2021): 1–20. http://dx.doi.org/10.1155/2021/2510847.