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Relevant bibliographies by topics / Multi-omic analysis

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Academic literature on the topic 'Multi-omic analysis'

Author: Grafiati

Published: 4 May 2024

Last updated: 26 July 2025

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Journal articles on the topic "Multi-omic analysis"

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Lancaster, Samuel M., Akshay Sanghi, Si Wu, and Michael P. Snyder. "A Customizable Analysis Flow in Integrative Multi-Omics." Biomolecules 10, no. 12 (2020): 1606. http://dx.doi.org/10.3390/biom10121606.

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The number of researchers using multi-omics is growing. Though still expensive, every year it is cheaper to perform multi-omic studies, often exponentially so. In addition to its increasing accessibility, multi-omics reveals a view of systems biology to an unprecedented depth. Thus, multi-omics can be used to answer a broad range of biological questions in finer resolution than previous methods. We used six omic measurements—four nucleic acid (i.e., genomic, epigenomic, transcriptomics, and metagenomic) and two mass spectrometry (proteomics and metabolomics) based—to highlight an analysis work

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Li, Jin, Feng Chen, Hong Liang, and Jingwen Yan. "MoNET: an R package for multi-omic network analysis." Bioinformatics 38, no. 4 (2021): 1165–67. http://dx.doi.org/10.1093/bioinformatics/btab722.

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Abstract Motivation The increasing availability of multi-omic data has enabled the discovery of disease biomarkers in different scales. Understanding the functional interaction between multi-omic biomarkers is becoming increasingly important due to its great potential for providing insights of the underlying molecular mechanism. Results Leveraging multiple biological network databases, we integrated the relationship between single nucleotide polymorphisms (SNPs), genes/proteins and metabolites, and developed an R package Multi-omic Network Explorer Tool (MoNET) for multi-omic network analysis.

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Morota, Gota. "30 Mutli-omic data integration in quantitative genetics." Journal of Animal Science 97, Supplement_2 (2019): 15. http://dx.doi.org/10.1093/jas/skz122.027.

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Abstract The advent of high-throughput technologies has generated diverse omic data including single-nucleotide polymorphisms, copy-number variation, gene expression, methylation, and metabolites. The next major challenge is how to integrate those multi-omic data for downstream analyses to enhance our biological insights. This emerging approach is known as multi-omic data integration, which is in contrast to studying each omic data type independently. I will discuss challenging issues in developing algorithms and methods for multi-omic data integration. The particular focus will be given to th

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Boekel, Jorrit, John M. Chilton, Ira R. Cooke, et al. "Multi-omic data analysis using Galaxy." Nature Biotechnology 33, no. 2 (2015): 137–39. http://dx.doi.org/10.1038/nbt.3134.

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Sangaralingam, Ajanthah, Abu Z. Dayem Ullah, Jacek Marzec, et al. "‘Multi-omic’ data analysis using O-miner." Briefings in Bioinformatics 20, no. 1 (2017): 130–43. http://dx.doi.org/10.1093/bib/bbx080.

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von der Heyde, Silvia, Margarita Krawczyk, Julia Bischof, et al. "Clinically relevant multi-omic analysis of colorectal cancer." Journal of Clinical Oncology 38, no. 15_suppl (2020): e16063-e16063. http://dx.doi.org/10.1200/jco.2020.38.15_suppl.e16063.

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e16063 Background: Cancer is a highly heterogeneous disease, both intra- and inter-individually consisting of complex phenotypes and systems biology. Although genomic data has contributed greatly towards the identification of cancer-specific mutations and the progress of precision medicine, genomic alterations are only one of several important biological drivers of cancer. Furthermore, single-layer omics represent only a small piece of the cancer biology puzzle and provide only partial clues to connecting genotype with clinically relevant phenotypic data. A more integrated approach is urgently

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Beheshti, Ramin, Steven Hicks, and Patrick Frangos. "Multi-omic Analysis Enhances Prediction Of Infantile Wheezing." Journal of Allergy and Clinical Immunology 151, no. 2 (2023): AB210. http://dx.doi.org/10.1016/j.jaci.2022.12.654.

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Davitavyan, Suren, Gevorg Martirosyan, Gohar Mkrtchyan, et al. "Integrated analysis of -omic landscapes in breast cancer subtypes." F1000Research 13 (June 3, 2024): 564. http://dx.doi.org/10.12688/f1000research.148778.1.

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The subtypes of breast cancer exhibit diverse histology, molecular features, therapeutic response, aggressiveness, and patient outcomes. Multi-omics high-throughput technologies, which are widely used in cancer research, generated waste amounts of multimodal omic datasets calling for new approaches of integrated analyses to uncover patterns of transcriptomic, genomic, and epigenetic changes in breast cancer subtypes and connect them to disease clinical characteristics. Here, we applied multi-layer self-organizing map (ml-SOM) algorithms to PAM50-classified TCGA breast cancer samples to disenta

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Tayrine, de Souza Rocha Pedro Augusto Farias de Souza Victor Hugo Santiago Costa Pinto Regiane Silva Kawasaki Francês Sintia Silva de Almeida Vinicius Augusto Carvalho de Abreu. "MULTIDIMENSIONAL VISUALIZATION FOR MULTI-OMICS DATA ANALYSIS." Revista ft 27, no. 124 (2023): 19. https://doi.org/10.5281/zenodo.8126719.

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High-throughput studies of biological systems are rapidly accumulating a large body of omic-scale data. The analysis of data that constitute various types of omics (Genomics, Metagenomics, Transcriptomics and Proteomics) from different experiments, play a role in the process of asking new questions that correlate between different combinations of these types of data. Thus, a systemic view is needed that addresses the use of the integration of these omics. The visualization of information or the use of a multidimensional view is increasingly relevant in the multi-omics theme. This article seeks

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Escriba-Montagut, Xavier, Yannick Marcon, Augusto Anguita-Ruiz, et al. "Federated privacy-protected meta- and mega-omics data analysis in multi-center studies with a fully open-source analytic platform." PLOS Computational Biology 20, no. 12 (2024): e1012626. https://doi.org/10.1371/journal.pcbi.1012626.

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The importance of maintaining data privacy and complying with regulatory requirements is highlighted especially when sharing omic data between different research centers. This challenge is even more pronounced in the scenario where a multi-center effort for collaborative omics studies is necessary. OmicSHIELD is introduced as an open-source tool aimed at overcoming these challenges by enabling privacy-protected federated analysis of sensitive omic data. In order to ensure this, multiple security mechanisms have been included in the software. This innovative tool is capable of managing a wide r

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Dissertations / Theses on the topic "Multi-omic analysis"

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Bilbrey, Emma A. "Seeding Multi-omic Improvement of Apple." The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1594907111820227.

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Thavamani, Abhishek [Verfasser], and Alfred [Akademischer Betreuer] Nordheim. "Integrated multi-omic analysis of HCC formation in the SRF-VP16iHep mouse model / Abhishek Thavamani ; Betreuer: Alfred Nordheim." Tübingen : Universitätsbibliothek Tübingen, 2018. http://d-nb.info/1173699864/34.

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VITRIOLO, ALESSANDRO. "MULTI-OMIC DECONVOLUTION OF THE REGULATORY NETWORKS UNDERLYING NEURODEVELOPMENTAL AND AUTISM SPECTRUM DISORDERS: A MULTIDIMENTIONAL ANALYSIS FOR A NEW DISEASE MODELLING PARADIGM." Doctoral thesis, Università degli Studi di Milano, 2019. http://hdl.handle.net/2434/609586.

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Recent literature has highlighted that mutations causing neurodevelopmental syndromes are particularly enriched in genes related to chromatin regulation and synaptic functions. While the latter could be easily predicted, the former shed seeds to the flourishing of epigenomic studies focused on this type of disorders. Intriguingly, most of such disorders couple different shades of intellectual disabilities with peculiar cranio-facial features and systemic defects which are shared, opposite or unique across them. I have set up a dynamic framework of analysis, that encompasses the comparison of m

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Carriot, Nathan. "Caractérisation de la production métabolique de biofilms marins. : Vers une application à l'étude de biofilms complexes in situ." Electronic Thesis or Diss., Toulon, 2022. http://www.theses.fr/2022TOUL0001.

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Le phénomène de biofouling est un processus naturel qui impacte toutes les surfaces immergées en milieu marin engendrant des problèmes économiques et écologiques majeurs à l’échelle planétaire. Il est notamment induit par la formation de biofilms marins correspondant à la colonisation des surfaces immergées par des bactéries s’organisant en communautés en s’entourant d’une matrice de substances polymériques extracellulaires (EPS). L’objectif de ce travail est l’utilisation et le développement de méthodologies permettant l’étude et la compréhension de l’étape précurseur de ce phénomène. La corr

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Ciaccio, Roberto <1990&gt. "Multi-omic analyses of the MYCN network unveil new potential vulnerabilities in childhood neuroblastoma." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amsdottorato.unibo.it/9930/1/PhD%20thesis%20Ciaccio%20Roberto_2021.pdf.

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Neuroblastoma is the first neurogenic-extracranial solid cancer occurring in infancy and childhood. The genetic aberration most commonly associated with a poor prognosis is MYCN gene’s amplification. We hypothesize that effective anti-MYC therapeutics can be developed by understanding the regulation and function of N-MYC in neuroblastoma. Since N-MYC is an intrinsically disordered protein, it is still challenging to target this transcription factor, however, the model is shifting significantly after discovering novel therapeutic targets that impact MYC-driven tumorigenesis. The following work

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Wang, Dongxue [Verfasser], Bernhard [Akademischer Betreuer] Küster, Bernhard [Gutachter] Küster, and Julien [Gutachter] Gagneur. "Comprehensive characterization of the human proteome by multi-omic analyses / Dongxue Wang ; Gutachter: Bernhard Küster, Julien Gagneur ; Betreuer: Bernhard Küster." München : Universitätsbibliothek der TU München, 2018. http://d-nb.info/1172415145/34.

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(10723641), Nathaphon Yu King Hing. "A Multi-Omic Characterization Of The Calvin-Benson-Bassham Cycle In Cyanobacteria." Thesis, 2021.

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Cyanobacteria are photosynthetic organisms with the potential to sustainably produce carbon-based end products by fixing carbon dioxide from the atmosphere. Optimizing the growth or biochemical production in cyanobacteria is an ongoing challenge in metabolic engineering. Rational design of metabolic pathways requires a deep understanding of regulatory mechanisms. Hence, a deeper understanding of photosynthetic regulation of the influence of the environment on metabolic fluxes provides exciting possibilities for enhancing the photosynthetic Calvin-Benson-Bassham cycle. One approach to study met

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Sharma, Supriya. "Integrative analysis of complex genomic and epigenomic maps." Thesis, 2018. https://hdl.handle.net/2144/27437.

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Modern healthcare research demands collaboration across disciplines to build preventive measures and innovate predictive capabilities for curing diseases. Along with the emergence of cutting-edge computational and statistical methodologies, data generation and analysis has become cheaper in the last ten years. However, the complexity of big data due to its variety, volume, and velocity creates new challenges for biologists, physicians, bioinformaticians, statisticians, and computer scientists. Combining data from complex multiple profiles is useful to better understand cellular functions and p

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Tassinari, Anna. "Multi-omic biomarker discovery and network analyses to elucidate the molecular mechanisms of lung cancer premalignancy." Thesis, 2017. https://hdl.handle.net/2144/27344.

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Lung cancer (LC) is the leading cause of cancer death in the US, claiming over 160,000 lives annually. Although CT screening has been shown to be efficacious in reducing mortality, the limited access to screening programs among high-risk individuals and the high number of false positives contribute to low survival rates and increased healthcare costs. As a result, there is an urgent need for preventative therapeutics and novel interception biomarkers that would enhance current methods for detection of early-stage LC. This thesis addresses this challenge by examining the hypothesis that tra

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Gagliardi, Miriam. "Integrative analyses of multi-omic data applied to the study of a rare human disease, the ICF syndrome." Tesi di dottorato, 2016. http://www.fedoa.unina.it/11107/1/Tesi_Miriam_Gagliardi.pdf.

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Application of the next-generation sequencing (NGS) technology has transformed epigenetic studies, generating large datasets that can be analyzed in different ways to answer a multitude of questions. Data integration is an essential step to understand intricate biological processes, such as the epigenetic control of gene regulation. Recent "multi-omic" studies proposed the intriguing possibility that the intragenic DNA methylation would play a role in processing of transcripts during transcription modulating the elongation or splicing. Indeed a kinetic model, in which epigenetic modifications

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Book chapters on the topic "Multi-omic analysis"

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Mason, Christopher E., Sandra G. Porter, and Todd M. Smith. "Characterizing Multi-omic Data in Systems Biology." In Systems Analysis of Human Multigene Disorders. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-8778-4_2.

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Yaneske, Elisabeth, and Claudio Angione. "A Data- and Model-Driven Analysis Reveals the Multi-omic Landscape of Ageing." In Bioinformatics and Biomedical Engineering. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-56148-6_12.

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Tran, Suzanne, and Franck Bielle. "Management of Brain Biopsy Samples: From Histological Examination to Biobanking and Multi-omic Analysis." In Neuromethods. Springer US, 2025. https://doi.org/10.1007/978-1-0716-4514-7_8.

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Potenza, Antonella, Tatiana Carrozzini, Gemma Gorla, Giuliana Pollaci, and Laura Gatti. "Multi-Omic Analyses for Biomarker Discovery and Characterization of PNST." In Peripheral Nerve Sheath Tumors. Springer Nature Switzerland, 2024. https://doi.org/10.1007/978-3-031-76382-3_4.

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Tikunov, Andrey P., Jeremiah D. Tipton, Timothy J. Garrett, et al. "Green Chemistry Preservation and Extraction of Biospecimens for Multi-omic Analyses." In Methods in Molecular Biology. Springer US, 2022. http://dx.doi.org/10.1007/978-1-0716-1811-0_17.

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Yue, Zhao, and Zeti-Azura Mohamed-Hussein. "Integrative Analysis of Multi Omic Data." In Reference Module in Life Sciences. Elsevier, 2024. https://doi.org/10.1016/b978-0-323-95502-7.00233-5.

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Wang, Minghui, Yiyuan Liu, Eric Schadt, and Bin Zhang. "Multiscale Network Approaches to Decode the Complexity of Common Human Diseases." In Charney and Nestler's Neurobiology of Mental Illness, 6th ed., edited by Eric J. Nestler and Kafui Dzirasa. Oxford University PressNew York, 2025. https://doi.org/10.1093/med/9780197640654.003.0002.

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Abstract The study of common human diseases is embracing large-scale multi-omic data at both bulk and single-cell levels. The enormous amount of data provides an excellent opportunity to gain unprecedented insights into molecular mechanisms of diseases, but it also poses a great challenge in distinguishing signals from noises and causality from correlations at a system level. This chapter introduces a multiscale network analysis framework to integrate multiple modals of large-scale biological data in diseases into multiple complementary, actionable molecular network models that enable not only

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Savitha, S., R. Keerthana, K. Logeswaran, P. Keerthika, V. Sharmila, and M. Sangeetha. "Integration of Multi-Omics Data." In Advances in Computational Intelligence and Robotics. IGI Global, 2025. https://doi.org/10.4018/979-8-3693-9521-9.ch006.

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Integrating multi-omics data, such as proteomics, metabolomics, and genomes, in precision health provides revolutionary insights into biological systems and individualized treatment plans. This chapter focuses on AI-powered techniques for merging multi-omics data, made possible by high-throughput instruments such as next-generation sequencing and mass spectrometry. Single-omic techniques, which frequently overlook intricate molecular interactions essential to comprehending the etiology of disease, are outperformed by multi-omics integration. By capturing non-linear relationships and hierarchic

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Jayadev, S., M. Veena, and Siju Sebastian. "ARIMA Model on GST – A Predictive Analysis." In Business Analytics for Effective Decision Making. BENTHAM SCIENCE PUBLISHERS, 2024. http://dx.doi.org/10.2174/9789815238365124010004.

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The COVID-19 pandemic has inflicted a multi-sectoral impact on omic activities around the globe and is considered as the worst economic fallout since the Great Depression. Demand and supply disruptions have acutely affected trade and commerce. A downfall of global trade has been pointed out by WTO. Indirect taxes constitute an important source of development funds for developing economies. The implementation of GST has brought landmark gains in consolidating indirect taxes and thereby reducing the cascading effect of taxes. GST revenues have fluctuated during the pandemic period. Considering t

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Gülfidan, Gizem, Kazım Yalçın Arga, Dilek Demircan Çeker, and Abdullah Karadağ. "Çoklu-Omik Veri Entegrasyonu: Yöntem, Araç Ve Sağlık Uygulamaları." In Moleküler Biyoloji ve Genetik. Türkiye Bilimler Akademisi, 2023. http://dx.doi.org/10.53478/tuba.978-625-8352-48-1.ch26.

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The central dogma (basic assumption) of molecular biology is the assumption of the process of coding DNA, which contains the genetic material, transferring information to RNA and regulating protein synthesis according to the instructions in the code. Later, the concept of metabolites, i.e. products formed as a result of metabolic processes, was added when proteins begin to function by folding into active structures. In short, by adding the suffix -omic, the concepts that study these structures are derived. These are genomics, transcriptomics, proteomics, and metabolomics, respectively. However

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Conference papers on the topic "Multi-omic analysis"

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Fan, Ziling, Yuan Zhou, and Habtom W. Ressom. "MOTA: Multi-omic integrative analysis for biomarker discovery." In 2019 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). IEEE, 2019. http://dx.doi.org/10.1109/embc.2019.8857049.

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Ma, Tianle, and Aidong Zhang. "Multi-view Factorization AutoEncoder with Network Constraints for Multi-omic Integrative Analysis." In 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2018. http://dx.doi.org/10.1109/bibm.2018.8621379.

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Lund, Jim, Shannon Bailey, Muhammad Ekram, et al. "Abstract 1333: High-quality multi-omic analysis of FFPE samples." In Proceedings: AACR Annual Meeting 2020; April 27-28, 2020 and June 22-24, 2020; Philadelphia, PA. American Association for Cancer Research, 2020. http://dx.doi.org/10.1158/1538-7445.am2020-1333.

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Stepniak, Amelia L., Zujian Xiong, Chaim T. Sneiderman, et al. "12 Comparative multi-omic analysis of antigen epitopes in gliomas." In SITC 39th Annual Meeting (SITC 2024) Abstracts. BMJ Publishing Group Ltd, 2024. http://dx.doi.org/10.1136/jitc-2024-sitc2024.0012.

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Zhang, Aidong. "Deep Learning and Networks for Integrative Analysis of Multi-Omic Data." In 2018 IEEE 8th International Conference on Computational Advances in Bio and Medical Sciences (ICCABS). IEEE, 2018. http://dx.doi.org/10.1109/iccabs.2018.8541962.

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Barefoot, Megan E., Rency S. Varghese, Yuan Zhou, Cristina Di Poto, Alessia Ferrarini, and Habtom W. Ressom. "Multi-omic Pathway and Network Analysis to Identify Biomarkers for Hepatocellular Carcinoma." In 2019 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). IEEE, 2019. http://dx.doi.org/10.1109/embc.2019.8856576.

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Vasquez, Jacob M., and Joel Desharnais. "Abstract 2854: Multi-omic considerations: Exploring LBgard blood tubes for proteomic analysis." In Proceedings: AACR Annual Meeting 2020; April 27-28, 2020 and June 22-24, 2020; Philadelphia, PA. American Association for Cancer Research, 2020. http://dx.doi.org/10.1158/1538-7445.am2020-2854.

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Khalyfa, A., Z. Qiao, M. Raju, et al. "Monocarboxylate Transporter-2 (MCT2) in Murine Model of Lung Cancer: A Multi-Omic Analysis." In American Thoracic Society 2021 International Conference, May 14-19, 2021 - San Diego, CA. American Thoracic Society, 2021. http://dx.doi.org/10.1164/ajrccm-conference.2021.203.1_meetingabstracts.a4695.

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Orlando, Krystal A., Jesse R. Raab, Jessica D. Lang, et al. "Abstract 4318: Identifying drivers of SMARCA4/BRG1-deficient SCCOHT tumorigenesis by integrative multi-omic analysis." In Proceedings: AACR Annual Meeting 2018; April 14-18, 2018; Chicago, IL. American Association for Cancer Research, 2018. http://dx.doi.org/10.1158/1538-7445.am2018-4318.

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Patel, Bhuvic, Thomas F. Barrett, Saad M. Khan, et al. "Multi-omic Analysis of Sporadic Vestibular Schwannoma Reveals a Nerve Injury-Like State and Novel Molecular Targets." In 33rd Annual Meeting North American Skull Base Society. Georg Thieme Verlag KG, 2024. http://dx.doi.org/10.1055/s-0044-1779830.

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Reports on the topic "Multi-omic analysis"

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Banfield, Jill. Multi-‘omic’ analyses of the dynamics, mechanisms, and pathways for carbon turnover in grassland soil under two climate regimes. Office of Scientific and Technical Information (OSTI), 2019. http://dx.doi.org/10.2172/1504276.

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