Proteomics software package for the detection of cancer

用于检测癌症的蛋白质组学软件包

• 批准号: 6645273
• 负责人: Maciek Sasinowski
• 金额: $ 18.87万
• 依托单位: INCOGEN, INC.
• 依托单位国家: 美国
• 财政年份: 2003
• 资助国家: 美国
• 起止时间: 2003-04-01 至 2003-09-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6645273
• 关键词: Hodgkin's disease; acute myelogenous leukemia; clinical research; computer program /software; computer system design /evaluation; diagnosis design /evaluation; diagnosis quality /standard; early diagnosis; human tissue; mass spectrometry; neoplasm /cancer diagnosis; pediatric neoplasm /cancer; proteomics; serum

DESCRIPTION (provided by applicant): This SBIR project proposes the development of a software package containing bio-computational tools to facilitate accurate diagnosis of cancer based on classification of proteomics data obtained through mass spectrometry (MS). The software will accept MS data produced from a wide range of instruments but is specifically targeted toward MALDI/SELDI TOF analysis (Applied Biosystems, Ciphergen). The Phase I work will focus on exploring the applicability of various existing and modified statistical approaches for signal conditioning (Wiener filters) and classification (linear discriminant analysis, principal components analysis, support vector machines, Bayes method) of SELDI data derived from analysis of sera from individuals with pediatric Hodgkin's disease and acute myeloid leukemia. A software package to perform this task does not currently exist; therefore, the proposed research has significant potential for technical innovation. Cross-validation will be used to obtain an unbiased estimate of the performances of the classifiers. The TRIFT II equipment at the ARC (W&M) will be used to provide high-resolution MS TOF SIMS data to calibrate the SELDI equipment at EVMS. The Phase II project will leverage the research and proof-of-concept tools developed in Phase I to produce a commercial software package that will be licensed to researchers, as well as equipment manufacturers for inclusion with their instruments.

描述（由申请人提供）：该SBIR项目提出开发包含生物计算工具的软件包，以促进基于通过质谱（MS）获得的蛋白质组学数据分类的癌症准确诊断。该软件将接受由各种仪器产生的MS数据，但专门针对MALDI/SELDI TOF分析（Applied Biosystems，Ciphergen）。第一阶段的工作将侧重于探索各种现有的和修改的统计方法的适用性信号调理（维纳滤波器）和分类（线性判别分析，主成分分析，支持向量机，贝叶斯方法）的SELDI数据来自分析的血清从个人与小儿霍奇金病和急性髓性白血病。目前还不存在执行这项任务的软件包;因此，拟议的研究具有重大的技术创新潜力。交叉验证将用于获得分类器性能的无偏估计。ARC（W&M）的TRIFT II设备将用于提供高分辨率MS TOF西姆斯数据，以校准EVMS的SELDI设备。第二阶段项目将利用第一阶段开发的研究和概念验证工具来制作一个商业软件包，该软件包将被授权给研究人员以及设备制造商，以便与他们的仪器一起使用。

项目成果

Deconvolution filters to enhance resolution of dense time-of-flight survey spectra in the time-lag optimization range.

• DOI: 10.1002/rcm.2487
• 发表时间: 2006-06
• 期刊: Rapid communications in mass spectrometry : RCM
• 作者: D. Malyarenko;W. Cooke;E. Tracy;M. Trosset;O. Semmes;M. Sasinowski;D. Manos