Petrovsky Nikolai, Silva Diego, Brusic Vladimir
Medical Informatics Centre, University of Canberra, Bruce ACT 2601, Australia.
Novartis Found Symp. 2003;254:23-32; discussion 33-42, 98-101, 250-2.
Advances in computational science, despite their enormous potential, have been surprisingly slow to impact on clinical practice. This paper examines the potential of bioinformatics to advance clinical immunology across a number of key examples including the use of computational immunology to improve renal transplantation outcomes, identify novel genes involved in immunological disorders, decipher the relationship between antigen presentation pathways and human disease, and predict allergenicity. These examples demonstrate the enormous potential for immunoinformatics to advance clinical and experimental immunology. The acceptance of immunoinformatic techniques by clinical and research immunologists will need robust standards of data quality, system integrity and properly validated immunoinformatic systems. Such validation, at a minimum, will require appropriately designed clinical studies conducted according to Good Clinical Practice standards. This strategy will enable immunoinformatics to achieve its full potential to advance and shape clinical immunology in the future.
计算科学尽管具有巨大潜力，但其对临床实践产生影响的速度却出奇地缓慢。本文通过多个关键实例探讨了生物信息学推进临床免疫学的潜力，这些实例包括利用计算免疫学改善肾移植结果、识别免疫紊乱中涉及的新基因、解读抗原呈递途径与人类疾病之间的关系以及预测变应原性。这些实例证明了免疫信息学推进临床和实验免疫学的巨大潜力。临床和研究免疫学家要接受免疫信息学技术，就需要有严格的数据质量标准、系统完整性标准以及经过充分验证的免疫信息学系统。至少，这种验证将需要按照良好临床实践标准进行适当设计的临床研究。这一策略将使免疫信息学在未来充分发挥其推进和塑造临床免疫学的潜力。
