{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:37:28Z","timestamp":1760243848924,"version":"build-2065373602"},"reference-count":22,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2011,5,12]],"date-time":"2011-05-12T00:00:00Z","timestamp":1305158400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Viruses"],"abstract":"<jats:p>The continuing use of high-throughput assays to investigate cellular responses to infection is providing a large repository of information. Due to the large number of differentially expressed transcripts, often running into the thousands, the majority of these data have not been thoroughly investigated. Advances in techniques for the downstream analysis of high-throughput datasets are providing additional methods for the generation of additional hypotheses for further investigation. The large number of experimental observations, combined with databases that correlate particular genes and proteins with canonical pathways, functions and diseases, allows for the bioinformatic exploration of functional networks that may be implicated in replication or pathogenesis. Herein, we provide an example of how analysis of published high-throughput datasets of cellular responses to hemorrhagic fever virus infection can generate additional functional data. We describe enrichment of genes involved in metabolism, post-translational modification and cardiac damage; potential roles for specific transcription factors and a conserved involvement of a pathway based around cyclooxygenase-2. We believe that these types of analyses can provide virologists with additional hypotheses for continued investigation.<\/jats:p>","DOI":"10.3390\/v3050613","type":"journal-article","created":{"date-parts":[[2011,5,12]],"date-time":"2011-05-12T13:25:07Z","timestamp":1305206707000},"page":"613-619","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Meta-Analysis of High-Throughput Datasets Reveals Cellular Responses Following Hemorrhagic Fever Virus Infection"],"prefix":"10.3390","volume":"3","author":[{"given":"Gavin C.","family":"Bowick","sequence":"first","affiliation":[{"name":"Department of Microbiology & Immunology, Institute for Human Infections & Immunity, University of Texas Medical Branch, Galveston, TX 77555, USA"},{"name":"Center for Biodefense and Emerging Infectious Diseases, Sealy Center for Vaccine Development, University of Texas Medical Branch, Galveston, TX 77555, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alexander J.","family":"McAuley","sequence":"additional","affiliation":[{"name":"Department of Microbiology & Immunology, Institute for Human Infections & Immunity, University of Texas Medical Branch, Galveston, TX 77555, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2011,5,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1032","DOI":"10.1038\/nature03985","article-title":"A network-based analysis of systemic inflammation in humans","volume":"437","author":"Calvano","year":"2005","journal-title":"Nature"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"McLeay, R.C., and Bailey, T.L. 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