Littérature scientifique sur le sujet « PRIORITIZE GENES »
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Articles de revues sur le sujet "PRIORITIZE GENES"
Gong, Lejun, Ronggen Yang, Chun Zhang, Quan Liu, Huakang Lee et Geng Yang. « RE-RANKING FOR PRIORITIZATION OF DISEASE-RELATED GENES ». Biomedical Engineering : Applications, Basis and Communications 28, no 04 (août 2016) : 1650027. http://dx.doi.org/10.4015/s1016237216500277.
Texte intégralZhang, Yi, Tao Wang, Yan Wang, Kun Xia, Jinchen Li et Zhongsheng Sun. « Targeted sequencing and integrative analysis to prioritize candidate genes in neurodevelopmental disorders ». Molecular Neurobiology 58, no 8 (15 avril 2021) : 3863–73. http://dx.doi.org/10.1007/s12035-021-02377-y.
Texte intégralXin, Huang, Wang Changchen, Liu Lei, Yang Meirong, Zhang Ye et Pan Bo. « The Phenolyzer Suite : Prioritizing the Candidate Genes Involved in Microtia ». Annals of Otology, Rhinology & ; Laryngology 128, no 6 (2 avril 2019) : 556–62. http://dx.doi.org/10.1177/0003489419840052.
Texte intégralTranchevent, L. C., F. B. Capdevila, D. Nitsch, B. De Moor, P. De Causmaecker et Y. Moreau. « A guide to web tools to prioritize candidate genes ». Briefings in Bioinformatics 12, no 1 (21 mars 2010) : 22–32. http://dx.doi.org/10.1093/bib/bbq007.
Texte intégralRylander, Ragnar. « Genes and Agents : How to Prioritize to Prevent Disease ». Archives of Environmental Health : An International Journal 50, no 5 (octobre 1995) : 333–34. http://dx.doi.org/10.1080/00039896.1995.9935963.
Texte intégralAsefa, Nigus G., Zoha Kamali, Satyajit Pereira, Ahmad Vaez, Nomdo Jansonius, Arthur A. Bergen et Harold Snieder. « Bioinformatic Prioritization and Functional Annotation of GWAS-Based Candidate Genes for Primary Open-Angle Glaucoma ». Genes 13, no 6 (13 juin 2022) : 1055. http://dx.doi.org/10.3390/genes13061055.
Texte intégralCabrera-Andrade, Alejandro, Andrés López-Cortés, Gabriela Jaramillo-Koupermann, César Paz-y-Miño, Yunierkis Pérez-Castillo, Cristian R. Munteanu, Humbert González-Díaz, Alejandro Pazos et Eduardo Tejera. « Gene Prioritization through Consensus Strategy, Enrichment Methodologies Analysis, and Networking for Osteosarcoma Pathogenesis ». International Journal of Molecular Sciences 21, no 3 (5 février 2020) : 1053. http://dx.doi.org/10.3390/ijms21031053.
Texte intégralSomepalli, Gowthami, Sarthak Sahoo, Arashdeep Singh et Sridhar Hannenhalli. « Prioritizing and characterizing functionally relevant genes across human tissues ». PLOS Computational Biology 17, no 7 (16 juillet 2021) : e1009194. http://dx.doi.org/10.1371/journal.pcbi.1009194.
Texte intégralMahmood, Iqra, Asif Nadeem, Masroor Ellahi Babar, Muhammad Muddassir Ali, Maryam Javed, Aisha Siddiqa, Tanveer Hussain et Muhammad Tariq Pervez. « Systematic and Integrated Analysis Approach to Prioritize Mastitis Resistant Genes ». Pakistan Journal of Zoology 49, no 1 (2016) : 101–6. http://dx.doi.org/10.17582/journal.pjz/2017.49.1.101.106.
Texte intégralOliver, Karen L., Vesna Lukic, Natalie P. Thorne, Samuel F. Berkovic, Ingrid E. Scheffer et Melanie Bahlo. « Harnessing Gene Expression Networks to Prioritize Candidate Epileptic Encephalopathy Genes ». PLoS ONE 9, no 7 (9 juillet 2014) : e102079. http://dx.doi.org/10.1371/journal.pone.0102079.
Texte intégralThèses sur le sujet "PRIORITIZE GENES"
Alcon, Timothy C. « Using a seed-network to query multiple large-scale gene expression datasets from the developing retina in order to identify and prioritize experimental targets ». [Ames, Iowa : Iowa State University], 2009. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:1473175.
Texte intégralCHAHAL, ASHISH. « ANALYSIS AND ANNOTATION OF EXOME SEQUENCING DATA TO IDENTIFY AND PRIORITIZE GENES RESPONSIBLE FOR PROSTATE ADENOCARCINOMA ». Thesis, 2015. http://dspace.dtu.ac.in:8080/jspui/handle/repository/15573.
Texte intégralLin, Shu-Ju, et 林書如. « Use of Pathway Score in Bayesian Model to Quantify and Prioritize Pathway Association and Gene Ranking ». Thesis, 2019. http://ndltd.ncl.edu.tw/handle/yx3fab.
Texte intégral國立臺灣大學
流行病學與預防醫學研究所
107
Cancer is an important topic of global concern. Some cancers are closely related to genetic aberrations. Not only is there a large number of new cancer patients per year, but the number of deaths due to cancer is also high. Genetic testing can help understand one’s disease risk and may prevent disease occurrence, if the causal key genes can be identified. Therefore, many researchers focus on identifying the key genes, among more than 20,000 human genes. Researchers need a lot of time and money to find key genes. In order to reduce costs, providing a prioritized list may help to find key genes. Currently, methods for screening genes associated with diseases are roughly classified into three types, such as the single marker tests, gene-set analysis methods, and pathway analysis, to provide candidate genes or candidate gene sets. Some statistical methods find disease-related genes from a single marker test, such as the T test or Chi-square test. However, due to the large number of biomarkers, scientists need to face the issue of multiple testing. Single marker test did not consider the relationship between genes. Genes do not work alone and need to work with other genes to affect a biological process. Therefore, rather than focusing on the effect of a single gene on biological processes, the effect of a group of genes should be considered. So there is a second type of method to find disease-related genes in a group of genes, such as the Gene Set Enrichment Analysis (GSEA), Over Representation Analysis (ORA), Globa test, and Fisher''s method. A pathway is a collection of genes containing biological meaning. The pathway represents a biological process carried out by a group of genes. The third method uses pathways to find related genes, such as Signaling Pathway Impact Analysis (SPIA). Currently, such methods do not consider simultaneously several competing pathways; they do not incorporate the relationship between pathways, nor account for the relationship between genes. This study will provide a novel method to overcome the limitations of current methods. This study not only considers the relationship between genes in the pathway but also considers the competition between several pathways and the relationship between pathways. Bayesian Approach to Prioritizing Pathway (BAPP), a novel method proposed under the above conditions, provides a list of ordered candidate pathways associated with the disease. The BAPP can further search for key genes in the primary pathway, and provide disease-related key genes. BAPP can be applied on the common pathway database, Kyoto Encyclopedia of Genes and Genomes (KEGG). Simulations show that BAPP performs well. Whether it is prioritizing candidate pathways or key genes, BAPP can control the type I error rate under 0.05. BAPP correctly ranks candidate pathways at a higher accuracy than other methods and can find true key genes. This novel method is applied to a breast cancer study and a glioblastoma multiforme study. In breast cancer data, BAPP identifies the primary pathway of breast cancer as the Jak-STAT signaling pathway, and further identifies 37 key genes in this pathway. The Taste transduction pathway that has not been reported to associate with breast cancer is ranked last by BAPP. In the glioblastoma multiforme study, BAPP identifies Long-term potentiation as the primary pathway, and from which four key genes are identified.
Livres sur le sujet "PRIORITIZE GENES"
Schutte, Nienke M., Meike Bartels et Eco JC de Geus. Genetics of physical activity and physical fitness. Sous la direction de Neil Armstrong et Willem van Mechelen. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780198757672.003.0020.
Texte intégralRaykoff, Ivan. Liberace’s Musical/Material Appeal. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780199935321.013.175.
Texte intégralMiller, Timothy. This Machine Plays Country Music. Sous la direction de Travis D. Stimeling. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780190248178.013.27.
Texte intégralChapitres de livres sur le sujet "PRIORITIZE GENES"
Nicolás, Marisa Fabiana, Maiana de Oliveira Cerqueira e Costa, Pablo Ivan P. Ramos, Marcelo Trindade dos Santos, Ernesto Perez-Rueda, Marcelo A. Marti, Dario Fernandez Do Porto et Adrian G. Turjanski. « Integrating Omics Data to Prioritize Target Genes in Pathogenic Bacteria ». Dans Networks in Systems Biology, 217–76. Cham : Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-51862-2_10.
Texte intégralDemneh, Sayedeh Razieh Abdollahi, Sama Goliaei et Zahra Razaghi Moghadam. « Associating Protein Interactions with Disease Comorbidity to Prioritize Colorectal Cancer Genes ». Dans International Conference on Biomedical and Health Informatics, 91–95. Singapore : Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-4505-9_15.
Texte intégralKaimal, Vivek, Divya Sardana, Eric E. Bardes, Ranga Chandra Gudivada, Jing Chen et Anil G. Jegga. « Integrative Systems Biology Approaches to Identify and Prioritize Disease and Drug Candidate Genes ». Dans Methods in Molecular Biology, 241–59. Totowa, NJ : Humana Press, 2010. http://dx.doi.org/10.1007/978-1-61737-954-3_16.
Texte intégralMilano, Marianna. « Using Gene Ontology to Annotate and Prioritize Microarray Data ». Dans Methods in Molecular Biology, 273–87. New York, NY : Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-1839-4_18.
Texte intégralMarshall, John M., et Ace R. North. « Modeling Priorities as Gene Drive Mosquito Projects Transition from Lab to Field ». Dans Mosquito Gene Drives and the Malaria Eradication Agenda, 197–237. New York : Jenny Stanford Publishing, 2023. http://dx.doi.org/10.1201/9781003308775-10.
Texte intégralRaychaudhuri, Soumya. « Text-Based Analysis of a Single Series of Gene Expression Measurements ». Dans Computational Text Analysis. Oxford University Press, 2006. http://dx.doi.org/10.1093/oso/9780198567400.003.0012.
Texte intégralHu, Hong, et Yang Dai. « Prioritize Transcription Factor Binding Sites for Multiple Co-Expressed Gene Sets Based on Lasso Multinomial Regression Models ». Dans Biotechnology, 940–68. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-8903-7.ch037.
Texte intégralLoreta Paun, Diana, et Alexandra Mirica. « Pheochromocytomas and Paragangliomas : Genotype-Phenotype Correlations ». Dans Pheochromocytoma, Paraganglioma and Neuroblastoma. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.95888.
Texte intégralAndrés de Pablo, Juan, Luis Javier Serrano, Mariano García-Arranz, Luis Romeu et Antonio Liras. « Gene and Cell Therapy in Dental Tissue Regeneration ». Dans Human Teeth – Structure and Composition of Dental Hard Tissues and Developmental Dental Defects [Working Title]. IntechOpen, 2021. http://dx.doi.org/10.5772/intechopen.97757.
Texte intégralAYDIN, İlhan. « ULUSAL SU ÜRÜNLERİ GEN BANKASI VE BİYOÇEŞİTLİLİĞE ETKİLERİ ». Dans BİYOÇEŞİTLİLİK VE EKOSİSTEMLER. TÜRKİYE BİLİMLER AKADEMİSİ, 2023. http://dx.doi.org/10.53478/tuba.978-625-8352-58-0.ch08.
Texte intégralActes de conférences sur le sujet "PRIORITIZE GENES"
Wu, Mengmeng, Wanwen Zeng, Wenqiang Liu, Yijia Zhang, Ting Chen et Rui Jiang. « Integrating embeddings of multiple gene networks to prioritize complex disease-associated genes ». Dans 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2017. http://dx.doi.org/10.1109/bibm.2017.8217651.
Texte intégralJanyasupab, Panisa, Apichat Suratanee et Kitiporn Plaimas. « Heterogeneous data analysis of hypertrophic cardiomyopathy to prioritize important genes ». Dans 2022 26th International Computer Science and Engineering Conference (ICSEC). IEEE, 2022. http://dx.doi.org/10.1109/icsec56337.2022.10049332.
Texte intégralYepes, Sally, Margaret Tucker, Hela Koka, Kristine Jones, Aurelie Vogt, Laurie Burdette, Wen Luo et al. « Abstract 1638 : Whole-exome sequencing and protein interaction networks to prioritize candidate genes for cutaneous melanoma susceptibility ». Dans 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.am2019-1638.
Texte intégralJhee, Jong Ho, Min-Young Song, Byung Gon Kim, Hyunjung Shin et Soo Youn Lee. « Transformer-Based Gene Scoring Model for Extracting Representative Characteristic of Central Dogma Process to Prioritize Pathogenic Genes Applying Breast Cancer Multi-omics Data ». Dans 2023 IEEE International Conference on Big Data and Smart Computing (BigComp). IEEE, 2023. http://dx.doi.org/10.1109/bigcomp57234.2023.00033.
Texte intégralWan, Cen. « Positive Feature Values Prioritized Hierarchical Dependency Constrained Averaged One-dependence Estimators for Gene Ontology Feature Spaces ». Dans 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2022. http://dx.doi.org/10.1109/bibm55620.2022.9995482.
Texte intégralHasanova, Aytakin. « PREDICTIVE GENETIC SCREENING ». Dans The First International Scientific-Practical Conference- “Modern Tendencies of Dialogue in Multidenominational Society : philosophical, religious, legal view”. IRETC MTÜ, 2020. http://dx.doi.org/10.36962/mtdms202029.
Texte intégralRapports d'organisations sur le sujet "PRIORITIZE GENES"
Дирда, Ірина Анатоліївна, Марина Вікторівна Малоіван et Анна Олександрівна Томіліна. The peculiarities of headlines in English discourse through the examples from Daily Mail and the New Yorker. Видавнича група «Наукові перспективи», mai 2023. http://dx.doi.org/10.31812/123456789/7074.
Texte intégralTel-Zur, Neomi, et Jeffrey J. Doyle. Role of Polyploidy in Vine Cacti Speciation and Crop Domestication. United States Department of Agriculture, janvier 2012. http://dx.doi.org/10.32747/2012.7697110.bard.
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