Literatura académica sobre el tema "Meta-omics"
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Artículos de revistas sobre el tema "Meta-omics"
Rusk, Nicole. "A meta-network of -omics". Nature Methods 5, n.º 1 (enero de 2008): 25. http://dx.doi.org/10.1038/nmeth1165.
Texto completoMackelprang, Rachel, Scott R. Saleska, Carsten Suhr Jacobsen, Janet K. Jansson y Neslihan Taş. "Permafrost Meta-Omics and Climate Change". Annual Review of Earth and Planetary Sciences 44, n.º 1 (29 de junio de 2016): 439–62. http://dx.doi.org/10.1146/annurev-earth-060614-105126.
Texto completoTsoungos, Anastasios, Violeta Pemaj, Aleksandra Slavko, John Kapolos, Marina Papadelli y Konstantinos Papadimitriou. "The Rising Role of Omics and Meta-Omics in Table Olive Research". Foods 12, n.º 20 (15 de octubre de 2023): 3783. http://dx.doi.org/10.3390/foods12203783.
Texto completoSathyanarayanan, Anita, Rohit Gupta, Erik W. Thompson, Dale R. Nyholt, Denis C. Bauer y Shivashankar H. Nagaraj. "A comparative study of multi-omics integration tools for cancer driver gene identification and tumour subtyping". Briefings in Bioinformatics 21, n.º 6 (27 de noviembre de 2019): 1920–36. http://dx.doi.org/10.1093/bib/bbz121.
Texto completoMallick, Himel, Ali Rahnavard, Lauren J. McIver, Siyuan Ma, Yancong Zhang, Long H. Nguyen, Timothy L. Tickle et al. "Multivariable association discovery in population-scale meta-omics studies". PLOS Computational Biology 17, n.º 11 (16 de noviembre de 2021): e1009442. http://dx.doi.org/10.1371/journal.pcbi.1009442.
Texto completoAdeleke, Bartholomew Saanu y Olubukola Oluranti Babalola. "Meta-omics of endophytic microbes in agricultural biotechnology". Biocatalysis and Agricultural Biotechnology 42 (julio de 2022): 102332. http://dx.doi.org/10.1016/j.bcab.2022.102332.
Texto completoDarzi, Youssef, Gwen Falony, Sara Vieira-Silva y Jeroen Raes. "Towards biome-specific analysis of meta-omics data". ISME Journal 10, n.º 5 (1 de diciembre de 2015): 1025–28. http://dx.doi.org/10.1038/ismej.2015.188.
Texto completoJohnson, David R., Damian E. Helbling, Yujie Men y Kathrin Fenner. "Can meta-omics help to establish causality between contaminant biotransformations and genes or gene products?" Environmental Science: Water Research & Technology 1, n.º 3 (2015): 272–78. http://dx.doi.org/10.1039/c5ew00016e.
Texto completoQin, Xiaofa. "Can inflammatory bowel disease really be solved by the multiple -omics and meta-omics analyses?" Immunology Letters 165, n.º 2 (junio de 2015): 107–8. http://dx.doi.org/10.1016/j.imlet.2015.03.007.
Texto completoCembrowska-Lech, Danuta, Adrianna Krzemińska, Tymoteusz Miller, Anna Nowakowska, Cezary Adamski, Martyna Radaczyńska, Grzegorz Mikiciuk y Małgorzata Mikiciuk. "An Integrated Multi-Omics and Artificial Intelligence Framework for Advance Plant Phenotyping in Horticulture". Biology 12, n.º 10 (30 de septiembre de 2023): 1298. http://dx.doi.org/10.3390/biology12101298.
Texto completoTesis sobre el tema "Meta-omics"
Zandonà, Alessandro. "Predictive networks for multi meta-omics data integration". Doctoral thesis, Università degli studi di Trento, 2017. https://hdl.handle.net/11572/367893.
Texto completoZandonà, Alessandro. "Predictive networks for multi meta-omics data integration". Doctoral thesis, University of Trento, 2017. http://eprints-phd.biblio.unitn.it/2547/1/zandona2017_phdthesis.pdf.
Texto completoRoy, Alexandra-Sophie [Verfasser]. "Response of Thalassiosira oceanica and natural microbial communities to ocean acidification : a meta-omics comparison from unialgal cultures to mesocosms / Alexandra-Sophie Roy". Kiel : Universitätsbibliothek Kiel, 2017. http://d-nb.info/1138979929/34.
Texto completoDa, Silva Ophélie. "Structure de l'écosystème planctonique : apport des données à haut débit de séquençage et d'imagerie". Electronic Thesis or Diss., Sorbonne université, 2021. http://www.theses.fr/2021SORUS183.
Texto completoPlanktonic organisms are key actors in oceanic ecosystems, which support trophic networks and play a major role in biogeochemical cycles and climate regulation. While the spatio-temporal distribution of planktonic diversity can be investigated at several levels, from the gene to the ecosystem, identifying the underlying mechanisms is challenging. Indeed, the structure of diversity results from different evolutionary and ecological processes that can act simultaneously. Since the beginning of the 21st century, the oceanic environment has been increasingly monitored. Numerous observation platforms have been deployed, leading to the acquisition of a large amount of data for multiple environmental characteristics. At the same time, technologies for studying living organisms have been developed. Thus, an unprecedented sampling of planktonic organisms has taken place. In particular, high-throughput sequencing and imaging data provide molecular, taxonomic and functional information at several biological levels. The objective of this thesis was to explore the structure of planktonic ecosystems using high-throughput sequencing and imaging data. Coupling with environmental data could contribute to a better understanding of the spatial distribution of planktonic diversity, from species to communities. In the first part, the genetic diversity of protists was studied at the species level. The hypothesis was that metagenomics could provide access to the poorly characterized spatial organization of the intraspecific protist genetic diversity, as well as to the mechanisms underlying it. In a second part, the link between genetic diversity and functional diversity was explored. Transparency was targeted. This functional trait is little explored at the community level and its molecular basis is poorly identified. A data-driven approach allowed this trait to emerge from imaging data, leading to the exploration of its biogeography and molecular basis. In the last part, the high potential of complementarity between sequencing, imaging and environmental datasets was explored, in order to highlight the multi-scale structure of the planktonic ecosystem and to identify its global structure. Finally, all the results were discussed to highlight the contributions that these data can provide to the understanding of planktonic ecosystems, as well as the limitations they can face
Benoiston, Anne-Sophie. "Méta-omique et méta-données environnementales : vers une nouvelle compréhension de la pompe à carbone biologique". Electronic Thesis or Diss., Sorbonne université, 2019. https://accesdistant.sorbonne-universite.fr/login?url=https://theses-intra.sorbonne-universite.fr/2019SORUS182.pdf.
Texto completoThe biological carbon pump encompasses a series of processes including the primary production of organic matter in the surface ocean, its export to deeper waters and its remineralization. The common highlighted actors are diatoms because of their contribution to primary production and carbon export and copepods for their production of fecal pellets. However, the biological pump is the result of complex interactions among organisms rather than their independent actions. Besides, although size distribution and mineral composition of phytoplankton in surface was shown to significantly influence the strength of carbon export, it is unknown whether meta-omic data can efficiently predict the processes of the biological carbon pump. In this thesis, I first propose to revisit the study of the biological carbon pump in the oligotrophic ocean by defining biogeochemical states of the ocean based on the relative contribution of primary production, carbon export and flux attenuation in Tara Oceans sampling stations. The analysis of the states in terms of microbial composition and interactions inferred from metabarcoding data revealed that variation in associations rather than lineages presence seems to drive the states of the biological carbon pump. Then, by using meta-omics and environmental parameters from the Tara Oceans expeditions, I propose the first study trying to predict biogeochemical states from biological abundances derived from environmental DNA, with the goal of providing a list of biomarkers
Costa, João Carlos Sequeira. "Development of an automated pipeline for meta-omics data analysis". Master's thesis, 2017. http://hdl.handle.net/1822/56113.
Texto completoKnowing what lies around us has been a goal for many decades now, and the new advances in sequencing technologies and in meta-omics approaches have permitted to start answering some of the main questions of microbiology - what is there, and what is it doing? The exponential growth of omics studies has been answered by the development of some bioinformatic tools capable of handling Metagenomics (MG) analysis, with a scarce few integrating such analysis with Metatranscriptomics (MT) or Metaproteomics (MP) studies. Furthermore, the existing tools for meta-omics analysis are usually not user friendly, usually limited to command-line usage. Because of the variety in meta-omics approaches, a standard workflow is not possible, but some routines exist, which may be implemented in a single tool, thereby facilitating the work of laboratory professionals. In the framework of this master thesis, a pipeline for integrative MG and MT data analysis was developed. This pipeline aims to retrieve comprehensive comparative gene/transcript expression results obtained from different biological samples. The user can access the data at the end of each step and summaries containing several parameters of evaluation of the previous step, and final graphical representations, like Krona plots and Differential Expression (DE) heatmaps. Several quality reports are also generated. The pipeline was constructed with tools tested and validated for meta-omics data analysis. Selected tools include FastQC, Trimmomatic and SortMeRNA for preprocessing, MetaSPAdes and Megahit for assembly, MetaQUAST and Bowtie2 for reporting on the quality of the assembly, FragGeneScan and DIAMOND for annotation and DeSEQ2 for DE analysis. Firstly, the tools were tested separately and then integrated in several python wrappers to construct the software Meta-Omics Software for Community Analysis (MOSCA). MOSCA performs preprocessing of MG and MT reads, assembly of the reads, annotation of the assembled contigs, and a final data analysis. Real datasets were used to test the capabilities of the tool. Since different types of files can be obtained along the workflow, it is possible to perform further analyses to obtain additional information and/or additional data representations, such as metabolic pathway mapping.
O objectivo da microbiologia, e em particular daqueles que se dedicam ao estudo de comunidades microbianas, é descobrir o que compõe as comunidades, e a função de cada microrganismo no seio da comunidade. Graças aos avanços nas técnicas de sequenciação, em particular no desenvolvimento de tecnologias de Next Generation Sequencing, surgiram abordagens de meta-ómicas que têm vindo a ajudar a responder a estas questões. Várias ferramentas foram desenvolvidas para lidar com estas questões, nomeadamente lidando com dados de Metagenómica (MG), e algumas poucas integrando esse tipo de análise com estudos de Metatranscriptómica (MT) e Metaproteómica (MP). Além da escassez de ferramentas bioinformáticas, as que já existem não costumam ser facilmente manipuláveis por utilizadores com pouca experiencia em informática, e estão frequentemente limitadas a uso por linha de comando. Um formato geral para uma ferramenta de análise meta-ómica não é possível devido à grande variedade de aplicações. No entanto, certas aplicações possuem certas rotinas, que são passíveis de serem implementadas numa ferramenta, facilitando assim o trabalho dos profissionais de laboratório. Nesta tese, uma pipeline integrada para análise de dados de MG e MT foi desenvolvida, pretendendo determinar a expressão de genes/transcriptos entre diferentes amostras biológicas. O utilizador tem disponíveis os resultados de cada passo, sumários com vários parâmetros para avaliação do procedimento, e representações gráficas como gráficos Krona e heatmaps de expressão diferencial. Vários relatórios sobre a qualidade dos resultados obtidos também são gerados. A ferramenta foi construída baseada em ferramentas e procedimentos testados e validados com análise de dados de meta-ómica. Essas ferramentas são FastQC, Trimmomatic e SortMeRNA para pré-processamento, Megahit e MetaSPAdes para assemblagem, MetaQUAST e Bowtie2 para controlo da qualidade dos contigs obtidos na assemblagem, FragGeneScan e DIAMOND para anotação e DeSEQ2 para análise de expressão diferencial. As ferramentas foram testadas uma a uma, e depois integradas em diferentes wrappers de python para compôr a Meta-Omics Software for Community Analysis (MOSCA). A MOSCA executa pré-processamento de reads de MG e MT, assemblagem das reads, anotação dos contigs assemblados, e uma análise de dados final Foram usados dados reais para testar as capacidades da MOSCA. Como podem ser obtidos diferentes tipos de ficheiros ao longo da execução da MOSCA, é possível levar a cabo análises posteriores para obter informação adicional e/ou representações de dados adicionais, como mapeamento de vias metabólicas.
Annavajhala, Medini. "Meta-omics-derived structure, function, and activity of mixed microbial communities driving biological nutrient removal and recovery". Thesis, 2017. https://doi.org/10.7916/D864023F.
Texto completoPark, Mee Rye. "Elucidating Microbial Community Structure, Function and Activity in Engineered Biological Nitrogen Removal Processes using Meta-omics Approaches". Thesis, 2017. https://doi.org/10.7916/D8BR94RN.
Texto completoLibros sobre el tema "Meta-omics"
Park, Mee Rye. Elucidating Microbial Community Structure, Function and Activity in Engineered Biological Nitrogen Removal Processes using Meta-omics Approaches. [New York, N.Y.?]: [publisher not identified], 2017.
Buscar texto completoUnlocking the Potential of Carbonaceous Resource Recovery from the Arrested Anaerobic Digestion of Food Waste: Engineering Design and Meta-omics Analysis. [New York, N.Y.?]: [publisher not identified], 2022.
Buscar texto completoKirchman, David L. Genomes and meta-omics for microbes. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198789406.003.0005.
Texto completoTseng, George, Debashis Ghosh y Xianghong Jasmine Zhou. Integrating Omics Data. Cambridge University Press, 2015.
Buscar texto completoIntegrating Omics Data. Cambridge University Press, 2015.
Buscar texto completoTseng, George C., Debashis Ghosh y Xianghong Jasmine Zhou. Integrating Omics Data. Cambridge University Press, 2015.
Buscar texto completoCapítulos de libros sobre el tema "Meta-omics"
Srivastava, Nidhi y Indira P. Sarethy. "Rhizosphere Fingerprints: Novel Biomolecules Via Meta-Omics Technology". En Omics Science for Rhizosphere Biology, 171–88. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-0889-6_10.
Texto completoAlisoltani, Arghavan, Akebe Luther King Abia y Linda Bester. "Shared Microbiome in Different Ecosystems: A Meta-Omics Perspective". En Microbial Genomics in Sustainable Agroecosystems, 1–20. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-32-9860-6_1.
Texto completoPonnusamy, Mohanraj, Chinnan Velmurugan Karthikeyan y Babu Ramanathan. "Meta-omics in Detection of Silkworm Gut Microbiome Diversity". En Microbial Genomics in Sustainable Agroecosystems, 359–70. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-32-9860-6_17.
Texto completoWani, Atif Khurshid, Daljeet Singh Dhanjal, Nahid Akhtar, Chirag Chopra, Abhineet Goyal y Reena Singh. "Role of Genomics, Metagenomics, and Other Meta-Omics Approaches for Expunging the Environmental Contaminants by Bioremediation". En Omics for Environmental Engineering and Microbiology Systems, 19–51. Boca Raton: CRC Press, 2022. http://dx.doi.org/10.1201/9781003247883-2.
Texto completoHassan, Muhammad Jawad, Muhammad Faheem y Sabba Mehmood. "Emerging OMICS and Genetic Disease". En Omics Technologies for Clinical Diagnosis and Gene Therapy: Medical Applications in Human Genetics, 93–113. BENTHAM SCIENCE PUBLISHERS, 2022. http://dx.doi.org/10.2174/9789815079517122010010.
Texto completoTripathi, Lokesh Kumar y Tapan Kumar Nailwal. "Metagenomics: Applications of functional and structural approaches and meta-omics". En Recent Advancements in Microbial Diversity, 471–505. Elsevier, 2020. http://dx.doi.org/10.1016/b978-0-12-821265-3.00020-7.
Texto completoTilgam, Jyotsana, Deepanshu Jayaswal, Mushineni Ashajyothi, Jyoti Prakash Singh, Adarsh Kumar y Hillol Chakdar. "Meta-omics approaches for understanding and exploring soil microbial communities for sustainable agriculture". En Applications of Metagenomics, 3–22. Elsevier, 2024. http://dx.doi.org/10.1016/b978-0-323-98394-5.00013-4.
Texto completoMargret, Arockiya Anita, S. Aishwarya, A. Arun y R. Jasmine. "Interface of ‘meta-omics’ in gut biome remediation to unravel the complications of environmental pollutants". En Metagenomics to Bioremediation, 183–206. Elsevier, 2023. http://dx.doi.org/10.1016/b978-0-323-96113-4.00024-x.
Texto completoSamanta, Brajogopal y Pattigundla Swathi. "Macroalgal Epiphytic Microbiome: A Potential Source of Novel Drugs". En Marine Ecology: Current and Future Developments, 184–205. BENTHAM SCIENCE PUBLISHERS, 2023. http://dx.doi.org/10.2174/9789815051995123030008.
Texto completoIslam, Ekramul. "Meta-Omics Studies of Microbial Communities in Hollow Fiber Membrane Biofilm Reactors Treating Contaminants in Water Resources: Recent Advances". En Wastewater Treatment, 457–70. Elsevier, 2021. http://dx.doi.org/10.1016/b978-0-12-821881-5.00022-2.
Texto completoActas de conferencias sobre el tema "Meta-omics"
Bernier-Latmani, Rizlan, Karen Viacava, Jiangtao Qiao, Karin Lederballe Meibom, Andrew Janowczyk, Suresh Poudel, Robert Hettich, Him Shrestha, Nicolas Jacquemin y Matthew Reid. "Identification of active arsenic-methylating organisms in anaerobic soil enrichment cultures using meta-omics". En Goldschmidt2021. France: European Association of Geochemistry, 2021. http://dx.doi.org/10.7185/gold2021.7580.
Texto completoGui, H., D. Hu, P. Sleiman, S. Xiao, M. Yang, S. Hochstadt, D. Dynkowski et al. "Whole-Genome Sequencing Based Meta-Analysis of Asthma Exacerbations from the Asthma Translational Genomic Collaborative (ATGC) of the Trans-Omics for Precision Medicine (TOPMed) Program". En 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.a1382.
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