International Journal of Molecular Zoology 2024, Vol.14, No.1, 31-43 http://animalscipublisher.com/index.php/ijmz 39 accurate developmental biology models can be constructed, and a deeper understanding of the commonalities and differences in developmental processes between different species can be gained. Blencowe et al. (2019) discussed the challenges, opportunities, and progress in network modeling of single-cell omics data. They identified unique challenges and opportunities in single-cell omics data modeling and provided an overview of recently developed network modeling methods aimed at capturing dynamic networks, intracellular networks, and intercellular interaction or communication networks. Strzelecka et al. (2018) used single-cell omics to analyze human diseases in model systems and clinical settings, focusing on the use of single-cell omics in cellular and animal disease models as well as human patient samples, emphasizing the potential of these methods to further improve various pathological diagnoses and treatments. These studies indicate that although building cross species developmental biology models faces challenges, single-cell omics provides a unique opportunity to gain a deeper understanding of the complexity and dynamics of biological systems. By integrating and analyzing single-cell data from different species, researchers can uncover common and unique molecular mechanisms that control cell development and function. 3.3 Application of cross species developmental biology models in human diseases Cross species developmental biology models play an important role in understanding the mechanisms of occurrence and development of human diseases. These models not only help reveal conservatism and diversity in human development, but also provide powerful tools for disease research. Among them, the use of stem cell models, gene editing, and large-scale animal models is crucial in understanding the mechanisms of human disease occurrence and developing new therapies. Sterneckert et al. (2014) studied the use of stem cell models to study human diseases. Due to their self-renewal and differentiation abilities, stem cells are highly suitable for generating disease models and obtaining a large number of cells needed for drug development and transplantation therapy. Induced pluripotent stem cells (iPSCs) have been proven to be the most practical for simulating human diseases, and combined with gene editing techniques, models of genetically complex diseases can be generated. Lin and Musunuru (2016) studied genomic engineering tools for constructing disease cell models, and comparative genomics methods and multi species biology are valuable tools for genetic analysis. Cross species connections, especially those between genes with human disease status mutations and their homologous genes in model organisms, can be particularly powerful because gene function data and experimental methods in model organisms can reveal the molecular mechanisms of diseases. Rogers (2019) studied engineered large animal models to simulate human diseases. Although genetically engineered mice are the most commonly used species and have made significant contributions to understanding basic biology, disease mechanisms, and drug development, they often fail to accurately reproduce important aspects of human diseases, thus limiting their practicality as translational research tools. Developing disease models in species more similar to humans may provide a better environment for studying disease pathogenesis and testing new treatment methods. By comparing the gene expression and regulatory mechanisms during development between humans and other species, scientists can discover key genes and signaling pathways associated with specific diseases. For example, disease models constructed using model organisms such as mice or zebrafish can simulate the process of human disease occurrence (Beck et al., 2021), thereby revealing the molecular mechanisms and pathophysiological processes of diseases. The cross species developmental biology model provides an important platform for drug screening and the development of therapeutic strategies. By testing candidate drugs or treatment methods in these models, scientists can evaluate their efficacy and safety, and predict their therapeutic effects in humans. This method accelerates the drug development process and provides more options for clinical treatment.
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