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Systematic analysis of gene expression patterns associated with postmortem interval in human tissues
Open accessAbstract
Postmortem mRNA degradation is considered to be the major concern in gene expression research utilizing human postmortem tissues. A key factor in this process is the postmortem interval (PMI), which is defined as the interval between death and sample collection. However, global patterns of postmortem mRNA degradation at individual gene levels across diverse human tissues remain largely unknown. In this study, we performed a systematic analysis of alteration of gene expression associated with PMI in human tissues. From the Genotype-Tissue Expression (GTEx) database, we evaluated gene expression levels of 2,016 high-quality postmortem samples from 316 donors of European descent, with PMI ranging from 1 to 27 hours. We found that PMI-related mRNA degradation is tissue-specific, gene-specific, and even genotype-dependent, thus drawing a more comprehensive picture of PMI-associated gene expression across diverse human tissues. Additionally, we also identified 266 differentially variable (DV) genes, such as DEFB4B and IFNG, whose expression is significantly dispersed between short PMI (S-PMI) and long PMI (L-PMI) groups. In summary, our analyses provide a comprehensive profile of PMI-associated gene expression, which will help interpret gene expression patterns in the evaluation of postmortem tissues.
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Cites
Hierarchical Grouping to Optimize an Objective Function
Ward, J. H. (1963) · Journal of the American Statistical Association · doi:10.1080/01621459.1963.10500845 · Cited by 21,341
DAVID: Database for Annotation, Visualization, and Integrated Discovery
Dennis, G., Sherman, B. T., Hosack, D. A., Yang, J., Gao, W., Lane, H. C., & Lempicki, R. A. (2003) · Genome Biology · doi:10.1186/gb-2003-4-5-p3 · Cited by 9,327
Controlling the false discovery rate in behavior genetics research
Benjamini, Y., Drai, D., Elmer, G., Kafkafi, N., & Golani, I. (2001) · Behavioural Brain Research · doi:10.1016/s0166-4328(01)00297-2 · Cited by 4,146
Robust Tests for the Equality of Variances
Brown, M. B., & Forsythe, A. B. (1974) · Journal of the American Statistical Association · doi:10.1080/01621459.1974.10482955 · Cited by 3,216
The RIN: an RNA integrity number for assigning integrity values to RNA measurements
Schroeder, A., Mueller, O., Stocker, S., Salowsky, R., Leiber, M., Gassmann, M., Lightfoot, S., Menzel, W., Granzow, M., & Ragg, T. (2006) · BMC Molecular Biology · doi:10.1186/1471-2199-7-3 · Cited by 2,623
The human transcriptome across tissues and individuals
Melé, M., Ferreira, P. G., Reverter, F., DeLuca, D. S., Monlong, J., Sammeth, M., Young, T. R., Goldmann, J. M., Pervouchine, D. D., Sullivan, T. J., et al. (2015) · Science · doi:10.1126/science.aaa0355 · Cited by 1,304
The highways and byways of mRNA decay
Garneau, N. L., Wilusz, J., & Wilusz, C. J. (2007) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm2104 · Cited by 1,294
The Many Pathways of RNA Degradation
Houseley, J. M., & Tollervey, D. W. (2009) · Cell · doi:10.1016/j.cell.2009.01.019 · Cited by 1,220
Stegle, O., Parts, L., Piipari, M., Winn, J., & Durbin, R. (2012) · Nature Protocols · doi:10.1038/nprot.2011.457 · Cited by 1,049
Optimizing illumina next-generation sequencing library preparation for extremely at-biased genomes
Oyola, S. O., Otto, T. D., Gu, Y., Maslen, G. L., Manske, M., Campino, S. G., Turner, D., MacInnis, B. L., Kwiatkowski, D. P., Swerdlow, H., et al. (2012) · BMC Genomics · doi:10.1186/1471-2164-13-1 · Cited by 654
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Hodge, R. D., Bakken, T. E., Miller, J. A., Smith, K. A., Barkan, E. R., Graybuck, L. T., Close, J. L., Long, B., Johansen, N., Penn, O., et al. (2019) · Nature · doi:10.1038/s41586-019-1506-7 · Cited by 1,775
Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder
Gandal, M. J., Zhang, P., Hadjimichael, E., Walker, R. L., Chen, C., Liu, S., Won, H., van Bakel, H., Varghese, M., Wang, Y., et al. (2018) · Science · doi:10.1126/science.aat8127 · Cited by 1,247
Grubman, A., Chew, G., Ouyang, J. F., Sun, G., Choo, X. Y., McLean, C., Simmons, R. K., Buckberry, S., Vargas-Landin, D. B., Poppe, D., et al. (2019) · Nature Neuroscience · doi:10.1038/s41593-019-0539-4 · Cited by 956
A practical guide to linking brain-wide gene expression and neuroimaging data
Arnatkevičiūtė, A., Fulcher, B., & Fornito, A. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.01.011 · Cited by 831
Transcriptional signature in microglia associated with Aβ plaque phagocytosis
Grubman, A., Choo, X. Y., Chew, G., Ouyang, J. F., Sun, G., Croft, N. P., Rossello, F. J., Simmons, R., Buckberry, S., Landin, D. V., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-23111-1 · Cited by 357
Profiling cell identity and tissue architecture with single-cell and spatial transcriptomics
Gulati, G. S., D'Silva, J. P., Liu, Y., Wang, L., & Newman, A. M. (2024) · Nature Reviews Molecular Cell Biology · doi:10.1038/s41580-024-00768-2 · Cited by 347
Self-citationDetection of SARS-CoV-2 in Human Retinal Biopsies of Deceased COVID-19 Patients
Casagrande, M. K., Fitzek, A., Püschel, K., Aleshcheva, G., Schultheiß, H., Berneking, L., Spitzer, M. S., & Schultheiß, M. (2020) · Ocular Immunology and Inflammation · doi:10.1080/09273948.2020.1770301 · Cited by 295
Genomics, convergent neuroscience and progress in understanding autism spectrum disorder
Willsey, H. R., Willsey, A. J., Wang, B., & State, M. W. (2022) · Nature reviews. Neuroscience · doi:10.1038/s41583-022-00576-7 · Cited by 239
Lieberman, N. A. P., DeGolier, K., Kovar, H. M., Davis, A. D., Hoglund, V. J., Stevens, J., Winter, C., Deutsch, G. H., Furlan, S. N., Vitanza, N. A., et al. (2018) · Neuro-Oncology · doi:10.1093/neuonc/noy145 · Cited by 194
Martins-Ferreira, R., Calafell-Segura, J., Leal, B., Rodríguez-Ubreva, J., Martínez-Saez, E., Mereu, E., Pinho E Costa, P., Laguna, A., & Ballestar, E. (2025) · Nature Communications · doi:10.1038/s41467-025-56124-1 · Cited by 123
Cancer biology as revealed by the research autopsy
Iacobuzio–Donahue, C. A., Michael, C., Baez, P., Kappagantula, R. L., Hooper, J. E., & Hollman, T. J. (2019) · Nature reviews. Cancer · doi:10.1038/s41568-019-0199-4 · Cited by 89
Forensic transcriptome analysis using massively parallel sequencing
Haas, C., Neubauer, J., Salzmann, A. P., Hanson, E., & Ballantyne, J. (2021) · Forensic Science International Genetics · doi:10.1016/j.fsigen.2021.102486 · Cited by 86
Anderson, A. G., Rogers, B. B., Loupe, J. M., Rodriguez-Nunez, I., Roberts, S. C., White, L. M., Brazell, J. N., Bunney, W. E., Bunney, B. G., Watson, S. J., et al. (2023) · Cell Genomics · doi:10.1016/j.xgen.2023.100263 · Cited by 82
Williamson, A., Norris, D. M., Yin, X., Broadaway, K. A., Moxley, A. H., Vadlamudi, S., Wilson, E. P., Jackson, A., Ahuja, V., Andersen, M. K., et al. (2023) · Nature Genetics · doi:10.1038/s41588-023-01408-9 · Cited by 84
Dachet, F., Brown, J. B., Valyi-Nagy, T., Narayan, K. D., Serafini, A., Boley, N., Gingeras, T. R., Celniker, S. E., Mohapatra, G., & Loeb, J. A. (2021) · Scientific Reports · doi:10.1038/s41598-021-85801-6 · Cited by 81
Post-mortem changes in metabolomic profiles of human serum, aqueous humor and vitreous humor
Zelentsova, E. A., Yanshole, L. V., Melnikov, A. D., Kudryavtsev, I. S., Novoselov, V. P., & Tsentalovich, Y. P. (2020) · Metabolomics · doi:10.1007/s11306-020-01700-3 · Cited by 75
COVID-19 autopsy cases: detection of virus in endocrine tissues
Poma, A. M., Bonuccelli, D., Giannini, R., Macerola, E., Vignali, P., Ugolini, C., Torregrossa, L., Proietti, A., Pistello, M., Basolo, A., et al. (2021) · Journal of Endocrinological Investigation · doi:10.1007/s40618-021-01628-y · Cited by 75
Tu, C., Du, T., Shao, C., Liu, Z., Li, L., & Shen, Y. (2018) · Forensic Science Medicine and Pathology · doi:10.1007/s12024-018-9973-y · Cited by 75
A Genetics Perspective on the Role of the (Neuro)Immune System in Schizophrenia
Birnbaum, R., & Weinberger, D. R. (2019) · Schizophrenia Research · doi:10.1016/j.schres.2019.02.005 · Cited by 70
On the cross-population generalizability of gene expression prediction models
Keys, K. L., Mak, A. C. Y., White, M. J., Eckalbar, W. L., Dahl, A., Mefford, J., Mikhaylova, A. V., Contreras, M. G., Elhawary, J. R., Eng, C. S., et al. (2020) · PLoS Genetics · doi:10.1371/journal.pgen.1008927 · Cited by 71
Considerations for building and using integrated single-cell atlases
Hrovatin, K., Sikkema, L., Shitov, V. A., Heimberg, G., Shulman, M., Oliver, A. J., Mueller, M. F., Ibarra, I. L., Wang, H., Ramírez-Suástegui, C., et al. (2024) · Nature Methods · doi:10.1038/s41592-024-02532-y · Cited by 72
Zhang, Z., Zamojski, M., Smith, G. R., Willis, T. L., Yianni, V., Mendelev, N., Pinças, H., Seenarine, N., Amper, M. A. S., Vasoya, M., et al. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.110467 · Cited by 69
Durán, R. C., González-Orozco, J. C., Velasco, I., & Wu, J. Q. (2022) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2022.884748 · Cited by 64
Temporal changes in the gene expression heterogeneity during brain development and aging
Işıldak, U., Somel, M., Thornton, J. M., & Dönertaş, H. M. (2020) · Scientific Reports · doi:10.1038/s41598-020-60998-0 · Cited by 53
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Ma, S., & Lim, S. B. (2021) · Biomedicines · doi:10.3390/biomedicines9040368 · Cited by 50
Locci, E., Stocchero, M., Noto, A., Chighine, A., Natali, L., Napoli, P. E., Caria, R., De‐Giorgio, F., Nioi, M., & d’Aloja, E. (2019) · Metabolomics · doi:10.1007/s11306-019-1533-2 · Cited by 47
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Yoon, S., Kim, S. E., Ko, Y., Jeong, G. H., Lee, K. H., Lee, J., Solmi, M., Jacob, L., Smith, L., Stickley, A., et al. (2022) · Molecular Psychiatry · doi:10.1038/s41380-022-01476-z · Cited by 50
Zapico, S. C., & Adserias‐Garriga, J. (2022) · Forensic Sciences · doi:10.3390/forensicsci2010013 · Cited by 44
Dissecting the transcriptome in cardiovascular disease
Robinson, E. L., Baker, A. H., Brittan, M., McCracken, I. R., Condorelli, G., Emanueli, C., Srivastava, P. K., Gaetano, C., Thum, T., Vanhaverbeke, M., et al. (2021) · Cardiovascular Research · doi:10.1093/cvr/cvab117 · Cited by 43
Forensic NMR metabolomics: one more arrow in the quiver
Locci, E., Bazzano, G., Chighine, A., Locco, F., Ferraro, E., Demontis, R., & d’Aloja, E. (2020) · Metabolomics · doi:10.1007/s11306-020-01743-6 · Cited by 40
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Gerra, M. C., Dallabona, C., & Cecchi, R. (2024) · International Journal of Legal Medicine · doi:10.1007/s00414-024-03165-8 · Cited by 40
Pérez‐Brocal, V., Magne, F., Ruiz‐Ruiz, S., Ponce, C. A., Bustamante, R. I., Martin, V. S., Gutierrez, M., Gatti, G., Vargas, S. L., & Moyá, A. (2019) · Scientific Reports · doi:10.1038/s41598-020-74137-2 · Cited by 35
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Lu, W., Zhou, Q., & Chen, Y. (2022) · Genomics · doi:10.1016/j.ygeno.2022.110429 · Cited by 32
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Procopio, N., & Bonicelli, A. (2024) · PROTEOMICS · doi:10.1002/pmic.202200335 · Cited by 32
Strete, G., Sălcudean, A., Cozma, A.-A., & Radu, C.-C. (2025) · Diagnostics · doi:10.3390/diagnostics15151954 · Cited by 25
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Tolbert, M., Finley, S. J., Visoná, S. D., Soni, S., Osculati, A. M. M., & Javan, G. T. (2018) · Gene · doi:10.1016/j.gene.2018.06.090 · Cited by 29
Discovery of novel hepatocyte eQTLs in African Americans
Zhong, Y., De, T., Alarcón, C., Park, C. S., Lec, B., & Perera, M. A. (2020) · PLoS Genetics · doi:10.1371/journal.pgen.1008662 · Cited by 28
Early postmortem interval estimation based on Cdc25b mRNA in rat cardiac tissue
Tao, L., Ma, J., Han, L., Xu, H., Zeng, Y. J., Yehui, L., Li, W., Ma, K., Xiao, B., & Chen, L. (2018) · Legal Medicine · doi:10.1016/j.legalmed.2018.09.004 · Cited by 25
Rauch, J., Steffen, J. F., Muntau, B., Gisbrecht, J., Pörtner, K., Herden, C., Niller, H. H., Bauswein, M., Rubbenstroth, D., Mehlhoop, U., et al. (2022) · Emerging Microbes & Infections · doi:10.1080/22221751.2022.2098831 · Cited by 25
Sobin, L. H., Barcus, M. E., Branton, P. A., Engel, K. B., Keen, J., Tabor, D. E., Ardlie, K., Greytak, S. R., Roche, N., Luke, B. T., et al. (2024) · Archives of Pathology & Laboratory Medicine · doi:10.5858/arpa.2023-0467-oa · Cited by 23
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Olney, K. C., Gibson, K. A., Cadiz, M. P., Rahimzadeh, N., Swarup, V., & Fryer, J. D. (2025) · eneuro · doi:10.1523/eneuro.0505-24.2025 · Cited by 22
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He, H., Liyanarachchi, S., Li, W., Comiskey, D. F., Yan, P. S., Bundschuh, R. A., Turkoglu, A. M., Brock, P. L., Ringel, M. D., & de la Chapelle, A. (2021) · Scientific Reports · doi:10.1038/s41598-021-93526-9 · Cited by 19
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Heng, Y., Dubbelaar, M. L., Marie, S. K. N., Boddeke, E., & Eggen, B. J. L. (2020) · Glia · doi:10.1002/glia.23948 · Cited by 18
Martínez-Rivera, V., Cárdenas-Monroy, C. A., Millán-Catalán, O., González-Corona, J. M., Huerta-Pacheco, N. S., Martínez-Gutiérrez, A. D., Villavicencio‐Queijeiro, A., Pedraza‐Lara, C., Hidalgo‐Miranda, A., Gómez, M. E. B., et al. (2021) · PeerJ · doi:10.7717/peerj.11102 · Cited by 18
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Subramanian, M. L., Stein, T. D., Siegel, N. H., Ness, S. D., Fiorello, M. G., Kim, D., & Roy, S. (2019) · Cells · doi:10.3390/cells8101122 · Cited by 17
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Индиаминов, С. И., Zhumanov, Z. E., & Blinova, S. A. (2020) · Forensic Medical Expertise · doi:10.17116/sudmed20206306145 · Cited by 16
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De‐Giorgio, F., Ciasca, G., D’Amico, R., Trombatore, P., D'Angelo, A. R., Rinaldi, P., Milano, F., Locci, E., Spirito, M. D., d’Aloja, E., et al. (2020) · International Journal of Legal Medicine · doi:10.1007/s00414-020-02370-5 · Cited by 15
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Bonadio, R. S., Nunes, L. B., Moretti, P. N. S., Mazzeu, J. F., Cagnin, S., Pic‐Taylor, A., & de Oliveira, S. F. (2021) · Scientific Reports · doi:10.1038/s41598-021-92268-y · Cited by 15
Profiling the unique protective properties of intracranial arterial endothelial cells
Hermkens, D. M. A., Stam, O. C. G., de Wit, N. M., Fontijn, R. D., Jongejan, A., Moerland, P. D., Mackaaij, C., Waas, I. S. E., Daemen, M. J. A. P., & de Vries, H. E. (2019) · Acta Neuropathologica Communications · doi:10.1186/s40478-019-0805-4 · Cited by 15
Analysis of human brain tissue derived from DBS surgery
Kangas, S. M., Teppo, J., Lahtinen, M., Suoranta, A., Ghimire, B. R., Mattila, P., Uusimaa, J., Varjosalo, M. T., Katisko, J., & Hinttala, R. (2022) · Translational Neurodegeneration · doi:10.1186/s40035-022-00297-y · Cited by 14
De‐Giorgio, F., Ciasca, G., Fecondo, G., Mazzini, A., Santo, R. D., Spirito, M. D., & Pascali, V. L. (2022) · International Journal of Legal Medicine · doi:10.1007/s00414-022-02801-5 · Cited by 13
Boroumand, M., Grassi, V. M., Castagnola, F., De‐Giorgio, F., d’Aloja, E., Vetrugno, G., Pascali, V. L., Vincenzoni, F., Iavarone, F., Faa, G., et al. (2022) · International Journal of Mass Spectrometry · doi:10.1016/j.ijms.2022.116952 · Cited by 13
Complexity of human death: its physiological, transcriptomic, and microbiological implications
Javan, G. T., Singh, K., Finley, S. J., Green, R. L., & Sen, C. K. (2024) · Frontiers in Microbiology · doi:10.3389/fmicb.2023.1345633 · Cited by 16
Antiga, L. G., Sibbens, L., Abakkouy, Y., Decorte, R., Bogaert, W. V. D., de Voorde, W. V., & Bekaert, B. (2021) · Scientific Reports · doi:10.1038/s41598-021-96095-z · Cited by 12
Signature transcriptome analysis of stage specific atherosclerotic plaques of patients
Verma, S., Kumar, A., Narang, R., Bisoi, A. K., & Mitra, D. K. (2022) · BMC Medical Genomics · doi:10.1186/s12920-022-01250-8 · Cited by 12
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Harakalova, M., & Asselbergs, F. (2018) · Wiley Interdisciplinary Reviews: Systems Biology and Medicine · doi:10.1002/wsbm.1419 · Cited by 11
Zhou, Z. C., Zhu, Y., Liu, Y., & Yin, Y. (2019) · Aging · doi:10.18632/aging.102196 · Cited by 11
Self-citationGrima, N., Henden, L., Watson, O. T., Blair, I. P., & Williams, K. L. (2021) · Journal of Neuropathology & Experimental Neurology · doi:10.1093/jnen/nlab129 · Cited by 11
Basova, L., Lindsey, A., McGovern, A. M., Ellis, R. J., & Marcondes, M. C. G. (2021) · Viruses · doi:10.3390/v13040544 · Cited by 10
Previderé, C., Bonin, S., Cuttaia, C., Argentiero, G., Livieri, T., Cecchetto, G., Oliva, A., & Fattorini, P. (2025) · International Journal of Legal Medicine · doi:10.1007/s00414-025-03480-8 · Cited by 9
Bhattacharya, A., Fon, E. A., Dagher, A., Iturria‐Medina, Y., Stratton, J. A., Savignac, C., Stanley, J., Hodgson, L. M., Hammou, B. A., Bennett, D. A. A., et al. (2026) · GigaScience · doi:10.1093/gigascience/giag059 · Cited by 9
Mondello, C., Stassi, C., Minutoli, L., Baldino, G., Alibrandi, A., Spatola, G. F., Uzzo, M. L., Micali, A. G., Puzzolo, D., Asmundo, A., et al. (2021) · Diagnostics · doi:10.3390/diagnostics11061062 · Cited by 9
Wang, S., Du, J., Shen, Q., Haas, C., & Neubauer, J. (2024) · International Journal of Legal Medicine · doi:10.1007/s00414-024-03329-6 · Cited by 8
Zar, M. S., Bibi, A., & Akhtar, M. S. (2025) · Forensic Science International · doi:10.1016/j.forsciint.2025.112779 · Cited by 8
Larriba, Y., Mason, I. C., Saxena, R., Scheer, F. A. J. L., & Rueda, C. (2023) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1011510 · Cited by 8
Lam, S., Kommadath, A., López-Campos, Ó., Prieto, N., Aalhus, J. L., Juarez, M. M., Dugan, M. E. R., & Vahmani, P. (2021) · PLoS ONE · doi:10.1371/journal.pone.0251868 · Cited by 8
Grubman, A., Choo, X. Y., Chew, G., Ouyang, J. F., Sun, G., Croft, N. P., Rossello, F. J., Simmons, R., Buckberry, S., Landin, D. V., et al. (2019) · doi:10.1101/639054 · Cited by 7
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Li, S., Liu, J., Song, H., Yan, Z., Hui, M., Zhao, M., Cong, B., & Wang, Z. (2025) · Forensic Science International · doi:10.1016/j.forsciint.2025.112683 · Cited by 7
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Payne, A. N., Prayugo, V., & Dolezal, A. G. (2024) · Journal of Invertebrate Pathology · doi:10.1016/j.jip.2024.108258 · Cited by 6
Li, B., Leung, S., Elishaev, M., Cheng, W.-L., Mocci, G., Björkegren, J., Lai, C. K., Singh, A., & Wang, Y. (2025) · International Journal of Molecular Sciences · doi:10.3390/ijms26051949 · Cited by 5
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Kamalipour, A., Ashraf, M. A., Moghimi, S., Moattari, A., Ashraf, M. J., Abbasi, F., Azodi, F., Oboudi, S., Pirbonyeh, N., Mokhtaryan, M., et al. (2021) · Ocular Immunology and Inflammation · doi:10.1080/09273948.2021.1980810 · Cited by 5
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Metadata
- Authors
- Zhu, Y., Wang, L., Yin, Y., & Yang, E.
- Affiliations
- Peking University (CN)
- Corresponding author
- Yin, Yuxin
- Yang, Ence
- Venue
- Scientific Reports
- Published
- 2017-07-14
- Volume
- 7
- Issue
- 1
- Pages
- 5435-5435
- ISSN
- 2045-2322 (ISSN-L)
- PMC
- PMC5511187
- OpenAlex
- W2734938713
- Cited by
- 129
- References
- 46
- Citations by year
- 2026: 12 · 2025: 15 · 2024: 17 · 2023: 9 · 2022: 19 · 2021: 21 · 2020: 13 · 2019: 15 · 2018: 8
- FWCI
- 4.02
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Scientific Reports (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Natural Science Foundation of China (111 Project, 31401132, B07001)
- Peking University
- Higher Education Discipline Innovation Project (B07001)
- National Key Research and Development Program of China (#2016YFA0500302)
- Peking University Health Science Center
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Molecular Biology Techniques and Applications
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gene expression and cancer classification
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Keywords
- postmortem interval, gene expression, tissue-specific gene expression, genotype-dependent gene expression, interferon-gamma, GTEx
- MeSH terms
- Autopsy, Cadaver, Genotype, Humans, Interferon-gamma, Organ Specificity, Postmortem Changes, RNA, Messenger, Time Factors, Gene Expression, Databases, Factual, Gene Expression Profiling, RNA Stability, beta-Defensins, White People
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