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  1. 22321
    por Utley, Adam, Lee, Kelvin P., Hicar, Mark
    Publicado 2020
    “…We then looked at genes which were significantly upregulated in the most terminally differentiated cells from each patient. 50 genes were significantly higher in the COVID-19 and KD populations, and 54 in MIS-C. Using gene ontology analysis in COVID-19 and KD, we saw increased expression of transcripts involved in protein trafficking, redox responses, and respiratory metabolism. …”
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    CD28 Expression Distinguishes Plasma Cell Fate in Pediatric Patients Suffering from COVID-19/Kawasaki's Disease Vs MIS-C
  2. 22322
    “…Innovation in addressing disability should shift focus from the ontology of diseases to shared disease mechanisms, in particular ageing-related fibrotic degeneration. …”
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    Urinary peptidomic profiles to address age-related disabilities: a prospective population study
  3. 22323
    “…Motif analysis showed that LchiWRKYs contained 20 motifs, and different phylogenetic groups contained conserved motif. Gene ontology (GO) analysis showed that LchiWRKYs were mainly enriched in two categories, i.e., biological process and molecular function. …”
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    Genome-wide identification of the Liriodendron chinense WRKY gene family and its diverse roles in response to multiple abiotic stress
  4. 22324
    “…RESULTS: A total of 4954 differentially expressed genes (DEGs) were detected after ASFV Ken12/1 infection, including 3055, 1771, and 128 DEGs in the high, medium, and low doses, respectively. Gene ontology and KEGG pathway analysis showed that the DEGs were enriched for genes involved in the innate immune response, inflammatory response, autophagy, and apoptosis in lethal dose groups. …”
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    Transcriptome profile of spleen tissues from locally-adapted Kenyan pigs (Sus scrofa) experimentally infected with three varying doses of a highly virulent African swine fever virus genotype IX isolate: Ken12/busia.1 (ken-1033)
  5. 22325
    por Cao, Jing, Yuan, Lei
    Publicado 2022
    “…An integrated co-expression network analysis was conducted to identify differentially expressed lncRNAs and differentially expressed mRNAs in patients with HCM. Then, gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were explored to identify the biological functions and signaling pathways of the co-expression network. …”
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    Identification of key genes for hypertrophic cardiomyopathy using integrated network analysis of differential lncRNA and gene expression
  6. 22326
    “…Differential expressed genes of HBEGF+ were shown in heatmap and volcano plot and used to run gene ontology (GO) enrichment analysis. Next, bulk RNA-seq datasets of synovium under different conditions (health, osteoarthritis (OA), rheumatoid arthritis, before and after classical treatment) were compared to show expression change of HBEGF and gene markers that are mainly expressed by HBEGF+ fibroblasts such as CLIC5, PDGFD, BDH2, and ENPP1. …”
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    Identification of HBEGF+ fibroblasts in the remission of rheumatoid arthritis by integrating single-cell RNA sequencing datasets and bulk RNA sequencing datasets
  7. 22327
    “…METHODS: The active components and putative targets of YCHD were predicted using a network pharmacology approach. Gene Ontology biological process and Kyoto Encyclopedia of Genes and Genomes path enrichment analysis were carried out by cluster profile. …”
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    The mechanism of Yinchenhao decoction in treating obstructive-jaundice-induced liver injury based on Nrf2 signaling pathway
  8. 22328
    “…Of these, 18 proteins were upregulated and 14 were downregulated by ≥ twofold (p < 0.05) in OVCAR5 CBPR cells. Gene ontology enrichment analysis amongst upregulated proteins revealed an overrepresentation of biological processes consistent with EMT in the resistant cell line. …”
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    Platinum-resistance in epithelial ovarian cancer: an interplay of epithelial–mesenchymal transition interlinked with reprogrammed metabolism
  9. 22329
    “…Based on this, we constructed a protein‒protein interaction network, performed gene ontology and KEGG enrichment analyses, and conducted pathway network analysis to elucidate the correlation between the active ingredients in ZLJT and signaling pathways. …”
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    A real-world study and network pharmacology analysis of EGFR-TKIs combined with ZLJT to delay drug resistance in advanced lung adenocarcinoma
  10. 22330
    “…The expression of AKR1B10 positively correlated with lymph node metastasis, tumor size, Ki67 expression, and p53 expression, but inversely correlated with overall and disease-free survival rates. Gene Ontology analysis showed that AKR1B10 activity contributes to cell proliferation. …”
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    AKR1B10 promotes breast cancer cell proliferation and migration via the PI3K/AKT/NF-κB signaling pathway
  11. 22331
    por Glinsky, Gennadi V.
    Publicado 2022
    “…GSEA of LTR7-linked MOS genes identified more than 2200 significantly enriched records of human common and rare diseases and gene signatures of 466 significantly enriched records of Human Phenotype Ontology traits, including Autosomal Dominant (92 genes) and Autosomal Recessive (93 genes) Inheritance. …”
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    Molecular diversity and phenotypic pleiotropy of ancient genomic regulatory loci derived from human endogenous retrovirus type H (HERVH) promoter LTR7 and HERVK promoter LTR5_Hs and their contemporary impacts on pathophysiology of Modern Humans
  12. 22332
    “…Functional analysis for identified cell subsets was annotated by Gene Ontology term(6). Differentiation trajectories of non-hematopoietic cells and cell-cell crosstalk were also evaluated. …”
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    Poster 116: Integrated scRNA-seq and spatial transcriptomics analysis uncovers distinct cellular populations and transcriptomes in human hip synovium between patients with femoroacetabular impingement and osteoarthritis.
  13. 22333
    “…Examples of coding sources are medical terminologies [eg, SNOMED CT, RxNorm, LOINC and open biomedical ontologies (OBO) foundry ontologies, eg, gene ontology (GO), functional model of anatomy, OBI, and others]. …”
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    2327: Prescription opioid dependence in Western New York: Using data analytics to find an answer to the opioid epidemic
  14. 22334
    por Fachal, Laura, Aschard, Hugues, Beesley, Jonathan, Barnes, Daniel R., Allen, Jamie, Kar, Siddhartha, Pooley, Karen A., Dennis, Joe, Michailidou, Kyriaki, Turman, Constance, Soucy, Penny, Lemaçon, Audrey, Lush, Michael, Tyrer, Jonathan P., Ghoussaini, Maya, Marjaneh, Mahdi Moradi, Jiang, Xia, Agata, Simona, Aittomäki, Kristiina, Alonso, M. Rosario, Andrulis, Irene L., Anton-Culver, Hoda, Antonenkova, Natalia N., Arason, Adalgeir, Arndt, Volker, Aronson, Kristan J., Arun, Banu K., Auber, Bernd, Auer, Paul L., Azzollini, Jacopo, Balmaña, Judith, Barkardottir, Rosa B., Barrowdale, Daniel, Beeghly-Fadiel, Alicia, Benitez, Javier, Bermisheva, Marina, Białkowska, Katarzyna, Blanco, Amie M., Blomqvist, Carl, Blot, William, Bogdanova, Natalia V., Bojesen, Stig E., Bolla, Manjeet K., Bonanni, Bernardo, Borg, Ake, Bosse, Kristin, Brauch, Hiltrud, Brenner, Hermann, Briceno, Ignacio, Brock, Ian W., Brooks-Wilson, Angela, Brüning, Thomas, Burwinkel, Barbara, Buys, Saundra S., Cai, Qiuyin, Caldés, Trinidad, Caligo, Maria A., Camp, Nicola J., Campbell, Ian, Canzian, Federico, Carroll, Jason S., Carter, Brian D., Castelao, Jose E., Chiquette, Jocelyne, Christiansen, Hans, Chung, Wendy K., Claes, Kathleen B.M., Clarke, Christine L., Collée, J. Margriet, Cornelissen, Sten, Couch, Fergus J., Cox, Angela, Cross, Simon S., Cybulski, Cezary, Czene, Kamila, Daly, Mary B., de la Hoya, Miguel, Devilee, Peter, Diez, Orland, Ding, Yuan Chun, Dite, Gillian S., Domchek, Susan M., Dörk, Thilo, dos-Santos-Silva, Isabel, Droit, Arnaud, Dubois, Stéphane, Dumont, Martine, Duran, Mercedes, Durcan, Lorraine, Dwek, Miriam, Eccles, Diana M., Engel, Christoph, Eriksson, Mikael, Evans, D. Gareth, Fasching, Peter A., Fletcher, Olivia, Floris, Giuseppe, Flyger, Henrik, Foretova, Lenka, Foulkes, William D., Friedman, Eitan, Fritschi, Lin, Frost, Debra, Gabrielson, Marike, Gago-Dominguez, Manuela, Gambino, Gaetana, Ganz, Patricia A., Gapstur, Susan M., Garber, Judy, García-Sáenz, José A., Gaudet, Mia M., Georgoulias, Vassilios, Giles, Graham G., Glendon, Gord, Godwin, Andrew K., Goldberg, Mark S., Goldgar, David E., González-Neira, Anna, Tibiletti, Maria Grazia, Greene, Mark H., Grip, Mervi, Gronwald, Jacek, Grundy, Anne, Guénel, Pascal, Hahnen, Eric, Haiman, Christopher A., Håkansson, Niclas, Hall, Per, Hamann, Ute, Harrington, Patricia A., Hartikainen, Jaana M., Hartman, Mikael, He, Wei, Healey, Catherine S., Heemskerk-Gerritsen, Bernadette A.M., Heyworth, Jane, Hillemanns, Peter, Hogervorst, Frans B.L., Hollestelle, Antoinette, Hooning, Maartje J., Hopper, John L., Howell, Anthony, Huang, Guanmengqian, Hulick, Peter J., Imyanitov, Evgeny N., Isaacs, Claudine, Iwasaki, Motoki, Jager, Agnes, Jakimovska, Milena, Jakubowska, Anna, James, Paul A., Janavicius, Ramunas, Jankowitz, Rachel C., John, Esther M., Johnson, Nichola, Jones, Michael E., Jukkola-Vuorinen, Arja, Jung, Audrey, Kaaks, Rudolf, Kang, Daehee, Kapoor, Pooja Middha, Karlan, Beth Y., Keeman, Renske, Kerin, Michael J., Khusnutdinova, Elza, Kiiski, Johanna I., Kirk, Judy, Kitahara, Cari M., Ko, Yon-Dschun, Konstantopoulou, Irene, Kosma, Veli-Matti, Koutros, Stella, Kubelka-Sabit, Katerina, Kwong, Ava, Kyriacou, Kyriacos, Laitman, Yael, Lambrechts, Diether, Lee, Eunjung, Leslie, Goska, Lester, Jenny, Lesueur, Fabienne, Lindblom, Annika, Lo, Wing-Yee, Long, Jirong, Lophatananon, Artitaya, Loud, Jennifer T., Lubiński, Jan, MacInnis, Robert J., Maishman, Tom, Makalic, Enes, Mannermaa, Arto, Manoochehri, Mehdi, Manoukian, Siranoush, Margolin, Sara, Martinez, Maria Elena, Matsuo, Keitaro, Maurer, Tabea, Mavroudis, Dimitrios, Mayes, Rebecca, McGuffog, Lesley, McLean, Catriona, Mebirouk, Noura, Meindl, Alfons, Miller, Austin, Miller, Nicola, Montagna, Marco, Moreno, Fernando, Muir, Kenneth, Mulligan, Anna Marie, Muñoz-Garzon, Victor M., Muranen, Taru A., Narod, Steven A., Nassir, Rami, Nathanson, Katherine L., Neuhausen, Susan L., Nevanlinna, Heli, Neven, Patrick, Nielsen, Finn C., Nikitina-Zake, Liene, Norman, Aaron, Offit, Kenneth, Olah, Edith, Olopade, Olufunmilayo I., Olsson, Håkan, Orr, Nick, Osorio, Ana, Pankratz, V. Shane, Papp, Janos, Park, Sue K., Park-Simon, Tjoung-Won, Parsons, Michael T., Paul, James, Pedersen, Inge Sokilde, Peissel, Bernard, Peshkin, Beth, Peterlongo, Paolo, Peto, Julian, Plaseska-Karanfilska, Dijana, Prajzendanc, Karolina, Prentice, Ross, Presneau, Nadege, Prokofyeva, Darya, Pujana, Miquel Angel, Pylkäs, Katri, Radice, Paolo, Ramus, Susan J., Rantala, Johanna, Rau-Murthy, Rohini, Rennert, Gad, Risch, Harvey A., Robson, Mark, Romero, Atocha, Rossing, Caroline Maria, Saloustros, Emmanouil, Sánchez-Herrero, Estela, Sandler, Dale P., Santamariña, Marta, Saunders, Christobel, Sawyer, Elinor J., Scheuner, Maren T., Schmidt, Daniel F., Schmutzler, Rita K., Schneeweiss, Andreas, Schoemaker, Minouk J., Schöttker, Ben, Schürmann, Peter, Scott, Christopher, Scott, Rodney J., Senter, Leigha, Seynaeve, Caroline M, Shah, Mitul, Sharma, Priyanka, Shen, Chen-Yang, Shu, Xiao-Ou, Singer, Christian F., Slavin, Thomas P., Smichkoska, Snezhana, Southey, Melissa C., Spinelli, John J., Spurdle, Amanda B., Stone, Jennifer, Stoppa-Lyonnet, Dominique, Sutter, Christian, Swerdlow, Anthony J., Tamimi, Rulla M., Tan, Yen Yen, Tapper, William J., Taylor, Jack A., Teixeira, Manuel R., Tengström, Maria, Teo, Soo H., Terry, Mary Beth, Teulé, Alex, Thomassen, Mads, Thull, Darcy L., Tischkowitz, Marc, Toland, Amanda E., Tollenaar, Rob A.E.M., Tomlinson, Ian, Torres, Diana, Torres-Mejía, Gabriela, Troester, Melissa A., Truong, Thérèse, Tung, Nadine, Tzardi, Maria, Ulmer, Hans-Ulrich, Vachon, Celine M., van Asperen, Christi J., van der Kolk, Lizet E., van Rensburg, Elizabeth J., Vega, Ana, Viel, Alessandra, Vijai, Joseph, Vogel, Maartje J., Wang, Qin, Wappenschmidt, Barbara, Weinberg, Clarice R., Weitzel, Jeffrey N., Wendt, Camilla, Wildiers, Hans, Winqvist, Robert, Wolk, Alicja, Wu, Anna H., Yannoukakos, Drakoulis, Zhang, Yan, Zheng, Wei, Hunter, David, Pharoah, Paul D.P., Chang-Claude, Jenny, García-Closas, Montserrat, Schmidt, Marjanka K., Milne, Roger L., Kristensen, Vessela N., French, Juliet D., Edwards, Stacey L., Antoniou, Antonis C., Chenevix-Trench, Georgia, Simard, Jacques, Easton, Douglas F., Kraft, Peter, Dunning, Alison M.
    Publicado 2020
    “…Known cancer drivers, transcription factors and genes in the developmental, apoptosis, immune system and DNA integrity checkpoint gene ontology pathways, were over-represented among the highest confidence target genes.…”
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    Fine-mapping of 150 breast cancer risk regions identifies 191 likely target genes
  15. 22335
    “…Eilbeck K, Lewis SE, Mungall CJ, Yandell M, Stein L, Durbin R, Ashburner M. The Sequence Ontology: a tool for the unification of genome annotations. …”
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    4549 Reproducible Informatics for Reproducible Translational Research
  16. 22336
    por Splendiani, Andrea
    Publicado 2008
    “…RESULTS: RDFScape is a plugin that has been developed to extend a software oriented to biological analysis with support for reasoning on ontologies in the semantic web framework. We show with this plugin how the use of ontological knowledge in biological analysis can be extended through the use of inference. …”
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    RDFScape: Semantic Web meets Systems Biology
  17. 22337
    “…In an analysis of >300 anatomical contributed terms, the majority represented composite terms that necessitated combining terms within and across existing ontologies. Although these terms are not good candidates for community ontologies, they can be linked to structures contained within these ontologies. …”
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    Extending and using anatomical vocabularies in the stimulating peripheral activity to relieve conditions project
  18. 22338
    por Lehmann, J
    Publicado 2010
    “…However, recent progress in the field faces a lack of well structured ontologies with large amounts of instance data due to the fact that engineering such ontologies requires a considerable investment of resources. …”
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    Learning OWL class expressions
  19. 22339
    “…In Part 1, we derived a number of key terms of core cognition and two behavioral ontologies: coping and co-creation. OBJECTIVE: Our first aim is to extend the conceptual framework and two behavioral ontologies, while explaining, from first principles, the observed basic structure in identity development. …”
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    Coping and Co-creation: One Attempt and One Route to Well-being. Part 2. Application to Identity and Social Well-being
  20. 22340
    “…We have developed a method to transform phenotype ontologies into a formal representation, combine phenotype ontologies with anatomy ontologies, and apply a measure of semantic similarity to construct the PhenomeNET cross-species phenotype network. …”
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    PhenomeNET: a whole-phenome approach to disease gene discovery
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