Rallis Dimitrios, Baltogianni Maria, Kapetaniou Konstantina, Kosmeri Chrysoula, Giapros Vasileios
Neonatal Intensive Care Unit, School of Medicine, University of Ioannina, 45110 Ioannina, Greece.
Department of Pediatrics, School of Medicine, University of Ioannina, 45110 Ioannina, Greece.
J Pers Med. 2024 Jul 18;14(7):767. doi: 10.3390/jpm14070767.
Bioinformatics is a scientific field that uses computer technology to gather, store, analyze, and share biological data and information. DNA sequences of genes or entire genomes, protein amino acid sequences, nucleic acid, and protein-nucleic acid complex structures are examples of traditional bioinformatics data. Moreover, proteomics, the distribution of proteins in cells, interactomics, the patterns of interactions between proteins and nucleic acids, and metabolomics, the types and patterns of small-molecule transformations by the biochemical pathways in cells, are further data streams. Currently, the objectives of bioinformatics are integrative, focusing on how various data combinations might be utilized to comprehend organisms and diseases. Bioinformatic techniques have become popular as novel instruments for examining the fundamental mechanisms behind neonatal diseases. In the first few weeks of newborn life, these methods can be utilized in conjunction with clinical data to identify the most vulnerable neonates and to gain a better understanding of certain mortalities, including respiratory distress, bronchopulmonary dysplasia, sepsis, or inborn errors of metabolism. In the current study, we performed a literature review to summarize the current application of bioinformatics in neonatal medicine. Our aim was to provide evidence that could supply novel insights into the underlying mechanism of neonatal pathophysiology and could be used as an early diagnostic tool in neonatal care.
生物信息学是一个利用计算机技术收集、存储、分析和共享生物数据与信息的科学领域。基因或整个基因组的DNA序列、蛋白质氨基酸序列、核酸以及蛋白质 - 核酸复合结构都是传统生物信息学数据的例子。此外,蛋白质组学(细胞中蛋白质的分布)、相互作用组学(蛋白质与核酸之间的相互作用模式)以及代谢组学(细胞中生化途径中小分子转化的类型和模式)是更多的数据流。目前,生物信息学的目标是综合性的,专注于如何利用各种数据组合来理解生物体和疾病。生物信息学技术已成为研究新生儿疾病背后基本机制的新型工具而受到欢迎。在新生儿生命的最初几周,这些方法可与临床数据结合使用,以识别最脆弱的新生儿,并更好地理解某些死亡原因,包括呼吸窘迫、支气管肺发育不良、败血症或先天性代谢缺陷。在本研究中,我们进行了文献综述,以总结生物信息学在新生儿医学中的当前应用。我们的目的是提供证据,为新生儿病理生理学的潜在机制提供新的见解,并可作为新生儿护理中的早期诊断工具。