Applied Bioinformatics and Public Health Microbiology: challenges, discoveries and innovations during a pandemic

Cunningham-Oakes, Edward; Trivett, Hannah

doi:10.1099/mgen.0.000757

Cited by 4 publications

(2 citation statements)

References 47 publications

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“…CCR1, a chemokine receptor that plays a key role in neutrophil recruitment, may be a potential strategy for the treatment of renal fibrosis. Also, MTNR1A melatonin restores the expression level of PRPC in a high glucose state through Akt phosphorylation, thereby preventing the fibrosis induced by high glucose (36). These findings suggest that melatonin may be an effective drug in the treatment of hyperglycemia-induced renal fibrosis.…”

Section: Discussionmentioning

confidence: 73%

Bioinformatics analysis of the potential regulatory mechanisms of renal fibrosis and the screening and identification of factors related to human renal fibrosis

Wang¹,

Wu²,

Li³

et al. 2022

Transl Androl Urol

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Background: This paper aimed to identify the key genes and potential mechanisms of renal fibrosis, and provide methods of evaluation and new ideas for the early diagnosis and treatment of renal fibrosis. Methods:The GSE102515 dataset was searched from the Gene Expression Omnibus (GEO) database was searched, the differential genes were screened out, and the down-regulated and up-regulated genes were identified. Enrichment analysis of differential genes in the development of renal fibrosis was carried out using the DAVID database, differential genes were analyzed using the STRING database, and Cytoscape software was used for visual processing.Results: Eighteen up-regulated genes and ten down-regulated genes were screened. Differential genes are mainly involved in the integrin-mediated signaling pathway and mitotic sister chromatid binding, etc. We found that the molecular functions (MFs) of the differential genes are phospholipid binding and regulatory region DNA binding, etc. Moreover, the cellular components (CCs) of the differential genes are mainly related to low-density lipoprotein (LDL) particles and nuclei. Screening revealed that ADM, ARRB1, AVPR2, CCR1, MTNR1A, PTH, and S1PR2 were core genes in the interaction network of renal fibrosis riskrelated proteins.Conclusions: In this study, the differential genes in the occurrence of renal fibrosis were screened out via dataset analysis. It was found that ADM, ARRB1, AVPR2, CCR1, MTNR1A, PTH, and S1PR2 may be important participants in the development of renal fibrosis, which provides analytical support for the identification of valuable markers of renal fibrosis.

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Section: Discussionmentioning

confidence: 73%

Bioinformatics analysis of the potential regulatory mechanisms of renal fibrosis and the screening and identification of factors related to human renal fibrosis

Wang¹,

Wu²,

Li³

et al. 2022

Transl Androl Urol

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“…• Aparición del SARS-CoV-2 y las primeras investigaciones de su composición: El coronavirus-2 (SARS-Cov-2) se trata de un síndrome respiratorio severo altamente transmisible las primeras investigaciones fueron realizadas en animales que potencialmente pueden ser reservorios del virus (Buonocore et al, 2020;Frankish et al, 2021), debido a que las investigaciones arrojaron grandes cantidades de datos y esto se debían almacenar, evaluar y analizar adecuadamente, se desarrollaron o actualizaron importantes herramientas bioinformáticas y aplicación de enfoque in silicio (Bauer et al, 2020;Tan et al, 2023), incluyendo también enfoques a otras enfermedades infecciosas (Cunningham Oakes & Trivett, 2022).…”

Section: Discussionunclassified

Bioinformática utilizada en la detección del covid-19; Análisis del desarrollo bioinformático en el ámbito computacional en América Latina.

Solórzano-Zambrano,

Demera-Ureta

2024

COCIRI

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Los avances en la tecnología son fundamentales para el descubrimiento de las características que poseen los diferentes virus presentados en la actualidad, como es el caso de la bioinformática con respecto a la pandemia por covid-19, los métodos utilizados en la secuenciación genómica del virus han contribuido de manera significativa en el análisis de considerables cantidades de datos obteniendo información relevante durante la evolución del virus, aportando en el desarrollo de plataformas y medicamentos que ayudaron a la disminuir el impacto causado por el SARS-CoV-2. La bioinformática se conoce como una disciplina que combina la biología con la informática y tecnología de información que mediante técnicas aplicadas en los algoritmos de procesamiento de datos, análisis estadísticos y modelado computacional extraen los conocimientos útiles de datos biológicos los mismos que son utilizados en diferentes campos generando cada vez más precisión en sus resultados y sobre todo que los expertos incursionen con esta disciplina en sus diferentes estudios e investigaciones. Este artículo tiene como objetivo realizar una revisión sistemática de la literatura científica a partir de estudios que contengan información relevante respecto a tecnología bioinformática. El desarrollo de esta disciplina es limitado en países que conforman el territorio de América Latina, esto a partir de diversos factores económicos y de infraestructura, sin embargo, existen países que han apostado al desarrollo computacional con la tecnología bioinformática a través del desarrollo de herramientas e investigaciones documentales lo cual les permite establecer un patrón a partir de los datos.

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Flu‐CED: A comparative transcriptomics database of influenza virus‐infected human and animal models

Wu,

Wang,

Xue

et al. 2024

Anim Models and Exp Med

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BackgroundThe continuing emergence of influenza virus has highlighted the value of public databases and related bioinformatic analysis tools in investigating transcriptomic change caused by different influenza virus infections in human and animal models.MethodsWe collected a large amount of transcriptome research data related to influenza virus‐infected human and animal models in public databases (GEO and ArrayExpress), and extracted and integrated array and metadata. The gene expression matrix was generated through strictly quality control, balance, standardization, batch correction, and gene annotation. We then analyzed gene expression in different species, virus, cells/tissues or after antibody/vaccine treatment and imported sample metadata and gene expression datasets into the database.ResultsOverall, maintaining careful processing and quality control, we collected 8064 samples from 103 independent datasets, and constructed a comparative transcriptomics database of influenza virus named the Flu‐CED database (Influenza comparative expression database, https://flu.com‐med.org.cn/). Using integrated and processed transcriptomic data, we established a user‐friendly website for realizing the integration, online retrieval, visualization, and exploration of gene expression of influenza virus infection in different species and the biological functions involved in differential genes. Flu‐CED can quickly query single and multi‐gene expression profiles, combining different experimental conditions for comparative transcriptome analysis, identifying differentially expressed genes (DEGs) between comparison groups, and conveniently finding DEGs.ConclusionFlu‐CED provides data resources and tools for analyzing gene expression in human and animal models infected with influenza virus that can deepen our understanding of the mechanisms underlying disease occurrence and development, and enable prediction of key genes or therapeutic targets that can be used for medical research.

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Applied Bioinformatics and Public Health Microbiology: challenges, discoveries and innovations during a pandemic

Cited by 4 publications

References 47 publications

Bioinformatics analysis of the potential regulatory mechanisms of renal fibrosis and the screening and identification of factors related to human renal fibrosis

Bioinformatics analysis of the potential regulatory mechanisms of renal fibrosis and the screening and identification of factors related to human renal fibrosis

Bioinformática utilizada en la detección del covid-19; Análisis del desarrollo bioinformático en el ámbito computacional en América Latina.

Flu‐CED: A comparative transcriptomics database of influenza virus‐infected human and animal models

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