Computer Identification of Unknown Spectra (Chemistry)

本项目属于数据开发和利用领域 并与《化学文摘》合作 服务（CAS）进一步提高准确性和速度， 计算机程序，用于识别未知化合物， 它们的质谱和红外光谱 这些方案是 检索算法“基于概率的匹配（PBM）”和 解释算法“自训练解释和 回收系统（STIRS）"。 尤其重要的是 全面和有效地利用新的数据库， 大约13万种不同的质谱 最高性能 PBM和STIRS计划将与CAS一起开发， 他们在计算机结构方面的丰富经验 连接表操作及其完整文件 结构描述，最终用于其国际 在线服务， 在线GC/MS的PBM将进一步发展 更有效的数据库压缩，预过滤 技术、矢量公式和阵列处理机的使用 芯片 通过精确的质量将提高PBM和STIRS的准确性 高分辨率GC/MS仪器提供的数据， 红外光谱仪的结构信息。 STIRS将 还可以通过计算机识别最大 最佳匹配化合物的结构描述。

This project is in the area of data development and utilization and involves a collaborative effort with Chemical Abstracts Service (CAS) on further improvements in accuracy and speed in computer programs for identification of unknown compounds from their mass and infrared spectra. These programs are the retrieval algorithm "Probability Based Matching (PBM)" and the interpretive algorithm "Self-Training Interpretive and Retrieval System (STIRS)". Of particular importance will be comprehensive and efficient utilization of a new data base of around 130,000 different mass spectra. The highest performance PBM and STIRS programs will be developed with CAS, taking advantage of their extensive experience in computer structure manipulation and their complete files of connection-table structure descriptions, for ultimate use on their international on-line service, STN. PBM for on-line GC/MS will be made far more efficient with data base compression, pre-filter techniques, vector formulation, and use of array processor chips. PBM and STIRS accuracy will be improved by exact mass data available from high resolution GC/MS instruments and structural information from infrared spectrometers. STIRS will also be improved through computer identification of maximal structure descriptions of the best matching compounds.