Academic literature on the topic 'Gene ontology'

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Journal articles on the topic "Gene ontology"

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Williams, Jennifer, and William Andersen. "Bringing Ontology to the Gene Ontology." Comparative and Functional Genomics 4, no. 1 (2003): 90–93. http://dx.doi.org/10.1002/cfg.253.

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Al-Mubaid, Hisham. "Gene multifunctionality scoring using gene ontology." Journal of Bioinformatics and Computational Biology 16, no. 05 (2018): 1840018. http://dx.doi.org/10.1142/s0219720018400188.

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Multifunctional genes are important genes because of their essential roles in human cells. Studying and analyzing multifunctional genes can help understand disease mechanisms and drug discovery. We propose a computational method for scoring gene multifunctionality based on functional annotations of the target gene from the Gene Ontology. The method is based on identifying pairs of GO annotations that represent semantically different biological functions and any gene annotated with two annotations from one pair is considered multifunctional. The proposed method can be employed to identify multi
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Akhmad, Dinar Munggaran. "PENGUKURAN KEMIRIPAN SEMANTIK BERBASIS GRAPH PADA GENE ONTOLOGY." Computatio : Journal of Computer Science and Information Systems 4, no. 2 (2020): 102. http://dx.doi.org/10.24912/computatio.v4i2.9678.

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Ontologi mendukung suatu sistem Knowledge Management dan membuka kemungkinan untuk berpindah dari pandangan berorientasi dokumen ke arah pengetahuan yang saling terkait dan dapat dimanfaatkan kembali secara lebih fleksibel dan dinamis. Salah satu dokumen ontology yang sangat berperan dalam dunia bioinformatika adalah Gene Ontology. Gene Ontology dibangun berbasis Graph, memuat banyak term/istilah tentang Gen pada makhluk hidup. Gen dapat melakukan mutasi dan hal ini menyebabkan resistensi terhadap segala jenis obat. Gen yang diketahui menyebabkan penyakit malaria resisten terhadap obat antimal
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Stevenson, Dennis, and Cecilia Zumajo-Cardona. "From Plant Ontology to Gene Ontology and back." Current Plant Biology 14 (September 2018): 66–69. http://dx.doi.org/10.1016/j.cpb.2018.09.009.

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Zhao, Liang. "GOBO: a Sub-Ontology API for Gene Ontology." IEIT Journal of Adaptive and Dynamic Computing 2011, no. 1 (2011): 29. http://dx.doi.org/10.5813/www.ieit-web.org/ijadc/2011.1.5.

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Lovering, R., P. Scambler, M. Hubank, R. Apweiler, and P. J. Talmud. "CARDIOVASCULAR GENE ONTOLOGY INITIATIVE." Atherosclerosis Supplements 9, no. 1 (2008): 101. http://dx.doi.org/10.1016/s1567-5688(08)70404-5.

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Joslyn, C. A., S. M. Mniszewski, A. Fulmer, and G. Heaton. "The Gene Ontology Categorizer." Bioinformatics 20, Suppl 1 (2004): i169—i177. http://dx.doi.org/10.1093/bioinformatics/bth921.

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Camon, E. "The Gene Ontology Annotation (GOA) Database: sharing knowledge in Uniprot with Gene Ontology." Nucleic Acids Research 32, no. 90001 (2004): 262D—266. http://dx.doi.org/10.1093/nar/gkh021.

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Peng, Jiajie, Tao Wang, Jixuan Wang, Yadong Wang, and Jin Chen. "Extending gene ontology with gene association networks." Bioinformatics 32, no. 8 (2015): 1185–94. http://dx.doi.org/10.1093/bioinformatics/btv712.

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Xie, Hanqing. "Gene Ontology-Facilitated Genome Analysis." Current Genomics 4, no. 7 (2003): 569–74. http://dx.doi.org/10.2174/1389202033490196.

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Dissertations / Theses on the topic "Gene ontology"

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Speer, Nora. "Funktionelles Clustering von Genen mit der Gene Ontology /." Berlin : Logos-Verl, 2006. http://deposit.d-nb.de/cgi-bin/dokserv?id=2875270&prov=M&dok_var=1&dok_ext=htm.

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Aleksakhin, Vladyslav. "Visualization of gene ontology and cluster analysis results." Thesis, Linnéuniversitetet, Institutionen för datavetenskap, fysik och matematik, DFM, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:lnu:diva-21248.

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The purpose of the thesis is to develop a new visualization method for Gene Ontologiesand hierarchical clustering. These are both important tools in biology andmedicine to study high-throughput data such as transcriptomics and metabolomicsdata. Enrichment of ontology terms in the data is used to identify statistically overrepresentedontology terms, that give insight into relevant biological processes orfunctional modules. Hierarchical clustering is a standard method to analyze andvisualize data to nd relatively homogeneous clusters of experimental data points.Both methods support the analysis
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Macholan, Robert Daniel. "Analysis of Gene Expression Data for Gene Ontology Based Protein Function Prediction." University of Akron / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=akron1301529255.

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Kim, Jong Woo. "A Novel Approach to Ontology Management." Digital Archive @ GSU, 2010. http://digitalarchive.gsu.edu/cis_diss/39.

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The term ontology is defined as the explicit specification of a conceptualization. While much of the prior research has focused on technical aspects of ontology management, little attention has been paid to the investigation of issues that limit the widespread use of ontologies and the evaluation of the effectiveness of ontologies in improving task performance. This dissertation addresses this void through the development of approaches to ontology creation, refinement, and evaluation. This study follows a multi-paper model focusing on ontology creation, refinement, and its evaluation. The f
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King, James Lowell. "Gene Ontology-Guided Force-Directed Visualization of Protein Interaction Networks." Diss., NSUWorks, 2019. https://nsuworks.nova.edu/gscis_etd/1066.

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Protein interaction data is being generated at unprecedented rates thanks to advancements made in high throughput techniques such as mass spectrometry and DNA microarrays. Biomedical researchers, operating under budgetary constraints, have found it difficult to scale their efforts to keep up with the ever-increasing amount of available data. They often lack the resources and manpower required to analyze the data using existing methodologies. These research deficiencies impede our ability to understand diseases, delay the advancement of clinical therapeutics, and ultimately costs lives. One of
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Rego, Fernanda Orpinelli Ramos do. "Modelagem computacional de famílias de proteínas microbianas relevantes para produção de bioenergia." Universidade de São Paulo, 2015. http://www.teses.usp.br/teses/disponiveis/95/95131/tde-28082015-222248/.

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Modelos ocultos de Markov (HMMs - hidden Markov models) são ferramentas essenciais para anotação automática de proteínas. Por muitos anos, bancos de dados de famílias de proteínas baseados em HMMs têm sido disponibilizados para a comunidade científica (e.g. TIGRfams). Muitos esforços também têm sido dedicados à geração automática de HMMs de famílias de proteínas (e.g. PANTHER). No entanto, HMMs manualmente curados de famílias de proteínas permanecem como o padrão-ouro para anotação de genomas. Neste contexto, este trabalho teve como principal objetivo a geração de cerca de 80 famílias de prote
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Helgadóttir, Hanna Sigrún. "Using semantic similarity measures across Gene Ontology to predict protein-protein interactions." Thesis, University of Skövde, School of Humanities and Informatics, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-971.

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<p>Living cells are controlled by proteins and genes that interact through complex molecular pathways to achieve a specific function. Therefore, determination of protein-protein interaction is fundamental for the understanding of the cell’s lifecycle and functions. The function of a protein is also largely determined by its interactions with other proteins. The amount of protein-protein interaction data available has multiplied by the emergence of large-scale technologies for detecting them, but the drawback of such measures is the relatively high amount of noise present in the data. It is tim
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Macmullen, W. John Marchionini Gary. "Contextual analysis of variation and quality in human-curated gene ontology annotations." Chapel Hill, N.C. : University of North Carolina at Chapel Hill, 2007. http://dc.lib.unc.edu/u?/etd,774.

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Thesis (Ph. D.)--University of North Carolina at Chapel Hill, 2007.<br>Title from electronic title page (viewed Dec. 18, 2007). "... in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the School of Information and Library Science." Discipline: Information and Library Science; Department/School: Information and Library Science, School of.
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Welter, Danielle. "Investigating “Gene Ontology”- based semantic similarity in the context of functional genomics." Thesis, Cardiff University, 2011. http://orca.cf.ac.uk/14292/.

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Gene functional annotations are an essential part of knowledge discovery in the analysis of large datasets, with the Gene Ontology [Ashburner et al., 2000] as the de facto standard for such annotations. A considerable number of approaches for quantifying functional similarity between gene products based on the semantic similarity between their annotations have been developed, but little guidance exists as to which of these measures are the most appropriate for different purposes. This was addressed here by comparing the performances of a number of similarity measures and associated parameters.
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Kharsikar, Saket. "A GENE ONTOLOGY BASED COMPUTATIONAL APPROACH FOR THE PREDICTION OF PROTEIN FUNCTIONS." University of Akron / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=akron1187026388.

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Books on the topic "Gene ontology"

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Dessimoz, Christophe, and Nives Škunca, eds. The Gene Ontology Handbook. Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4939-3743-1.

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Dessimoz, Christophe, and Nives Skunca. The Gene Ontology Handbook. Saint Philip Street Press, 2020.

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The Gene Ontology Handbook. Humana, 2018.

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Speer, Nora. Funktionelles Clustering Von Genen Mit Der Gene Ontology. Logos Verlag Berlin, 2006.

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Penney, James. Genet, Lacan and the Ontology of Incompletion. Bloomsbury Publishing Plc, 2023.

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Corry, Richard. Power and Influence. Oxford University Press, 2019. http://dx.doi.org/10.1093/oso/9780198840718.001.0001.

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This book investigates the metaphysical presuppositions of a common—and very successful—reductive approach to dealing with the complexity of the world. The reductive approach in question is one in which we study the components of a complex system in relative isolation, and use the information so gained to explain or predict the behaviour of the complex whole. So, for example, ecologists explain shifts in species population in terms of interactions between individuals, geneticists explain traits of an organism in terms of interactions between genes, and physicists explain the properties of a ga
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Bloomfield-Gadêlha, Connie, and Edith Hall, eds. Time, Tense, and Genre in Ancient Greek Literature. Oxford University PressOxford, 2025. https://doi.org/10.1093/9780191949302.001.0001.

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Abstract This volume examines the interplay of time, tense, and genre in ancient Greek literature, showing how these elements function as part of a dynamic, interconnected system. Through multivocal and reflexive analysis, it offers fresh perspectives on how texts reflect, construct, and challenge cultural conceptions of time. The book is structured to explore the relationship between philosophical time and literary time, with chapters arranged into three sections that correspond to the earliest questions asked by Greek philosophers: how do humans relate to gods (Metaphysics)? How do we know t
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Meizel, Katherine. Multivocality. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780190621469.001.0001.

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This book frames vocality as a particularly holistic way to investigate the voice in music, as a concept embodying all the implications with which voice is inscribed—the negotiation of sound and Self, individual and culture, medium and meaning, ontology and embodiment. Like identity, vocality is fluid, constructed and reconstructed continually; even the most iconic of singers do not simply exercise a static voice throughout a lifetime. The book highlights such singers in vocal motion, focusing on their transitions and transgressions across genre and gender boundaries, cultural borders, the lin
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Book chapters on the topic "Gene ontology"

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Wang, Jiguang. "Gene Ontology." In Encyclopedia of Systems Biology. Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-9863-7_489.

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Liu, Wenting, Kuiyu Chang, Jie Zheng, Jain Divya, Jung-Jae Kim, and Jagath C. Rajapakse. "Gene Regulatory Networks from Gene Ontology." In Bioinformatics Research and Applications. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38036-5_12.

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Bastos, Hugo P., Bruno Tavares, Catia Pesquita, Daniel Faria, and Francisco M. Couto. "Application of Gene Ontology to Gene Identification." In Methods in Molecular Biology. Humana Press, 2011. http://dx.doi.org/10.1007/978-1-61779-176-5_9.

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Zhdanova, Anna V. "Community-Driven Ontology Evolution: Gene Ontology Case Study." In Business Information Systems. Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-79396-0_11.

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Dimmer, Emily, Tanya Z. Berardini, Daniel Barrell, and Evelyn Camon. "Methods for Gene Ontology Annotation." In Plant Bioinformatics. Humana Press, 2007. http://dx.doi.org/10.1007/978-1-59745-535-0_24.

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Kim, Ju Han. "Molecular Pathways and Gene Ontology." In Genome Data Analysis. Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-13-1942-6_12.

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Ayoubi, P., L. Amirneni, L. Hall, et al. "Gene Ontology for Filamentous Fungi." In Biochemistry and Molecular Biology. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-662-06064-3_3.

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Gaudet, Pascale, Nives Škunca, James C. Hu, and Christophe Dessimoz. "Primer on the Gene Ontology." In Methods in Molecular Biology. Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4939-3743-1_3.

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Škunca, Nives, Richard J. Roberts, and Martin Steffen. "Evaluating Computational Gene Ontology Annotations." In Methods in Molecular Biology. Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4939-3743-1_8.

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Pati, Soumen K., Subhankar Mallick, Aruna Chakraborty, and Ankur Das. "Informative Gene Selection Using Clustering and Gene Ontology." In Advances in Intelligent Systems and Computing. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1498-8_37.

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Conference papers on the topic "Gene ontology"

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Visconti, Alessia, Francesca Cordero, Marco Botta, and Raffaele A. Calogero. "Gene Ontology Rewritten for Computing Gene Functional Similarity." In 2010 International Conference on Complex, Intelligent and Software Intensive Systems (CISIS). IEEE, 2010. http://dx.doi.org/10.1109/cisis.2010.30.

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Kustra, R., and A. Zagdanski. "Incorporating Gene Ontology in Clustering Gene Expression Data." In Proceedings. 19th IEEE International Symposium on Computer-Based Medical Systems. IEEE, 2006. http://dx.doi.org/10.1109/cbms.2006.100.

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Yang, Andy C., Hui-Huang Hsu, and Ming-Da Lu. "Applying gene ontology to microarray gene expression data analysis." In 2010 International Conference on System Science and Engineering (ICSSE). IEEE, 2010. http://dx.doi.org/10.1109/icsse.2010.5551740.

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Zuojian Tang, Sieu Phan, Youlian Pan, and A. F. Famili. "Prediction of Co-Regulated Gene Groups through Gene Ontology." In 2007 4th Symposium on Computational Intelligence in Bioinformatics and Computational Biology. IEEE, 2007. http://dx.doi.org/10.1109/cibcb.2007.4221221.

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Chen, Guanrao, Peter Larsen, Eyad Almasri, and Yang Dai. "Sample Scale-Free Gene Regulatory Network Using Gene Ontology." In Conference Proceedings. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2006. http://dx.doi.org/10.1109/iembs.2006.259261.

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Molaee Zadeh, Seyedeh, and Mohammad Moradi. "An Evaluation of Gene Ranking Methods by Gene Ontology." In 2006 8th international Conference on Signal Processing. IEEE, 2006. http://dx.doi.org/10.1109/icosp.2006.345951.

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Chen, Guanrao, Peter Larsen, Eyad Almasri, and Yang Dai. "Sample Scale-Free Gene Regulatory Network Using Gene Ontology." In Conference Proceedings. Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE, 2006. http://dx.doi.org/10.1109/iembs.2006.4398706.

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Wang, Tao, Hengbo Xu, Ranye Zhang, Yifu Xiao, Jiajie Peng, and Xuequn Shang. "Hypergraph-based Gene Ontology Embedding for Disease Gene Prediction." In 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2022. http://dx.doi.org/10.1109/bibm55620.2022.9995140.

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Zeng, Erliang, Giri Narasimhan, Lisa Schneper, and Kalai Mathee. "A Functional Network of Yeast Genes Using Gene Ontology Information." In 2008 IEEE International Conference on Bioinformatics and Biomedicine. IEEE, 2008. http://dx.doi.org/10.1109/bibm.2008.60.

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Couto, Francisco M., Mário J. Silva, and Pedro M. Coutinho. "Semantic similarity over the gene ontology." In the 14th ACM international conference. ACM Press, 2005. http://dx.doi.org/10.1145/1099554.1099658.

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Reports on the topic "Gene ontology"

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Ugarcina Perovic, Svetlana, Vedanth Ramji, Hui Chong, Yiqian Duan, and Luis Pedro Coelho. argNorm: Normalization of antibiotic resistance gene annotations to the Antibiotic Resistance Ontology (ARO). Queensland University of Technology, 2024. http://dx.doi.org/10.5204/rep.eprints.252448.

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Motivation: Currently available and frequently used tools for annotating antimicrobial resistance genes (ARGs) in genomes and metagenomes provide results using inconsistent nomenclature. This makes the comparison of different ARG annotation outputs challenging. The comparability of ARG annotation outputs can be improved by mapping gene names and their categories to a common controlled vocabulary such as the Antibiotic Resistance Ontology (ARO). Results: We developed argNorm, a command line tool and Python library, to normalize all detected genes across 6 ARG annotation tools (8 databases) to t
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Mukhopadhyay, Biswarup, Brett M. Tyler, Joao Setubal, and T. M. Murali. Gene Ontology Terms and Automated Annotation for Energy-Related Microbial Genomes. Office of Scientific and Technical Information (OSTI), 2017. http://dx.doi.org/10.2172/1406983.

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Borgwardt, Stefan, Marco Cerami, and Rafael Peñaloza. Subsumption in Finitely Valued Fuzzy EL. Technische Universität Dresden, 2015. http://dx.doi.org/10.25368/2022.212.

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Aus der Einleitung: Description Logics (DLs) are a family of knowledge representation formalisms that are successfully applied in many application domains. They provide the logical foundation for the Direct Semantics of the standard web ontology language OWL2. The light-weight DL EL, underlying the OWL2 EL profile, is of particular interest since all common reasoning problems are polynomial in this logic, and it is used in many prominent biomedical ontologies like SNOMEDCT and the Gene Ontology.
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Ruvinsky, Alicia, Maria Seale, R. Salter, and Natàlia Garcia-Reyero. An ontology for an epigenetics approach to prognostics and health management. Engineer Research and Development Center (U.S.), 2023. http://dx.doi.org/10.21079/11681/46632.

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Techniques in prognostics and health management have advanced considerably in the last few decades, enabled by breakthroughs in computational methods and supporting technologies. These predictive models, whether data-driven or physics-based, target the modeling of a system’s aggregate performance. As such, they generalize assumptions about the modelled system’s components, and are thus limited in their ability to represent individual components and the dynamic environmental factors that affect composite system health. To address this deficiency, we have developed an epigenetics-inspired knowle
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Levin, Ilan, Avtar K. Handa, Avraham Lalazar, and Autar K. Mattoo. Modulating phytonutrient content in tomatoes combining engineered polyamine metabolism with photomorphogenic mutants. United States Department of Agriculture, 2006. http://dx.doi.org/10.32747/2006.7587724.bard.

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Fruit constitutes a major component of our diet, providing fiber, vitamins, minerals, and many other phytonutrients that promote good health. Fleshy fruits, such as tomatoes, already contain high levels of several of these ingredients. Nevertheless, efforts have been invested in increasing and diversifying the content of phytonutrients, such as carotenoids and flavonoids, in tomato fruits. Increasing levels of phytonutrients, such as lycopene, is highly justified from the perspective of the lycopene extraction industry due to cost effectiveness reasons. Diversifying phytonutrients, in particul
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Terán Somohano, Alejandro, Tania Guadalupe Yáñez Flores, José Luis Íñiguez García, et al. Reporte sobre la familia en México 2023. Edited by José Antonio Terán Somohano. Editorial NUN, 2023. https://doi.org/10.59868/497141851615408241450.

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En el Reporte sobre la familia en México 2023 abordamos el cambio tecnológico y la cultura digital. Nuestro objetivo es sencillo: brindar herramientas conceptuales que sirvan para reflexionar sobre el tema. Presentamos un panorama del México digital a través de algunos datos sobre acceso a internet, demografía, salud mental y hábitos de lectura. También buscamos averiguar qué hace la gente en internet, qué redes sociales usa, qué videos ve, qué música escucha, entre otras cosas. Con ello podemos conocer las tendencias y los rasgos generales de la cultura digital en nuestro país y detectar cómo
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