A bioinformatics approach towards bronchopulmonary dysplasia

Background and Objective: Bronchopulmonary dysplasia (BPD) is the most common morbidity associated with prematurity and remains a significant clinical challenge. Bioinformatic approaches, such as genomics, transcriptomics, and proteomics, have emerged as novel methods for studying the underlying mechanisms driving BPD pathogenesis. These methods can be used alongside clinical data to develop a better understanding of BPD and potentially identify the most at risk neonates within the first few weeks of neonatal life. The objective of this review is to provide an overview of the current state-of-the-art in bioinformatics for BPD research. Methods: We conducted a literature review of bioinformatics approaches for BPD using PubMed. The following keywords were used: "biomedical informatics", "bioinformatics", "bronchopulmonary dysplasia", and "omics". Key Content and Findings: This review highlighted the importance of omic-approaches to better understand BPD and potential avenues for future research. We described the use of machine learning (ML) and the need for systems biology methods for integrating large-scale data from multiple tissues. We summarized a handful of studies that utilized bioinformatics for BPD in order to better provide a view of where things currently stand, identify areas of ongoing research, and concluded with challenges that remain in the field. Conclusions: Bioinformatics has the potential to enable a more comprehensive understanding of BPD pathogenesis, facilitating a personalized and precise approach to neonatal care. As we continue to push the boundaries of biomedical research, biomedical informatics (BMI) will undoubtedly play a key role in unraveling new frontiers in disease understanding, prevention, and treatment.