The integration of bioinformatics predictions and experimental validation plays a pivotal role in advancing biological research, from understanding molecular mechanisms to developing therapeutic strategies. Bioinformatics tools and methods offer powerful means for predicting gene functions, protein interactions, and regulatory networks, but these predictions must be validated through experimental approaches to ensure their biological relevance. This review explores the various methods and technologies used for experimental validation, including gene expression analysis, protein-protein interaction verification, and pathway validation. We also discuss the challenges involved in translating computational predictions to experimental settings and highlight the importance of collaboration between bioinformatics and experimental research. Finally, emerging technologies, such as CRISPR gene editing, next-generation sequencing, and artificial intelligence, are shaping the future of bioinformatics validation and driving more accurate and efficient biological discoveries.

翻译：生物信息学预测与实验验证的整合在推动生物学研究中发挥着关键作用，从理解分子机制到开发治疗策略。生物信息学工具和方法为预测基因功能、蛋白质相互作用和调控网络提供了强大手段，但这些预测必须通过实验方法进行验证，以确保其生物学相关性。本综述探讨了用于实验验证的各种方法和技术，包括基因表达分析、蛋白质-蛋白质相互作用验证和通路验证。我们还讨论了将计算预测转化为实验环境所面临的挑战，并强调了生物信息学与实验研究之间协作的重要性。最后，新兴技术，如CRISPR基因编辑、新一代测序和人工智能，正在塑造生物信息学验证的未来，并推动更准确、更高效的生物学发现。