MetaboQuest: A Suite of Tools for Metabolite Annotation
MetaboQuest:代谢物注释工具套件
基本信息
- 批准号:10395223
- 负责人:
- 金额:$ 99.79万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-02-11 至 2024-01-31
- 项目状态:已结题
- 来源:
- 关键词:AddressAdoptedBiochemicalBiocompatible MaterialsBiologicalComputing MethodologiesConsumptionCoupledCustomDataData AnalysesData AnalyticsDatabasesDecision MakingDependenceDetectionDevelopmentDiseaseEvaluationFingerprintGenomicsGoalsGraphHumanIsotopesKnowledgeLibrariesLinkLiquid ChromatographyManualsMass Spectrum AnalysisMeasuresMethodsNetwork-basedOrganismPathway AnalysisPathway interactionsPatternPerformancePhasePrivacyProteomicsResourcesRoleRunningSamplingSmall Business Innovation Research GrantStatistical ModelsSystems BiologyTestingTimeUncertaintyValidationVisualizationadductanalysis pipelinebasebiomarker discoverycloud basedcomputerized toolscostdeep learningdesigndrug discoveryin silicoinnovationmetabolomicstooltranscriptomicsweb interface
项目摘要
MetaboQuest: A Suite of Tools for Metabolite Annotation
PROJECT SUMMARY
Metabolomics aims at high throughput detection, quantification, and identification of metabolites in biological
samples. The use of liquid chromatography coupled with mass spectrometry (LC-MS) has risen in prominence
in the field of metabolomics due to its ability to analyze a sizable number of metabolites with a limited amount of
biological material. However, in a typical untargeted metabolomics analysis of human samples by LC-MS, about
70% of the detected peaks represent unknown analytes mainly because existing mass spectral libraries cover
only a small fraction of known compounds, but also due to uncertainty in peak picking, alignment of peaks, and
recognizing isotopic peaks and adduct forms. These challenges have kept at bay the pace of development of
data analytics pipelines for metabolomics and its integration with other omics studies. The goal of this Phase II
SBIR proposal is to make metabolomics studies on a par with other omics studies such as genomics,
transcriptomics, and proteomics, for which well-established pipelines are available. By doing so, we will
accelerate the role of metabolomics in systems biology approaches for various applications including biomarker
and drug discovery. To achieve this goal, we propose to develop a cloud-based platform that allows customers
to build pipelines for analysis of LC-MS-based untargeted metabolomics data, starting from peak detection to
metabolite annotation. This will be accomplished by implementing a suite of innovative tools that can be
assembled into customized pipelines and by enhancing metabolite annotation accuracy through integration of
information derived from multiple resources including compound databases, pathways, biochemical networks,
and mass spectral libraries. Aim 1 of this proposal will focus on developing a suite of tools to enable: (1) peak
detection, alignment, and quality assessment; (2) adduct and isotopic peak recognition; (3) mass-based search
against multiple compound databases; (4) expert-based evaluation of putative IDs; (5) isotopic pattern analysis;
(6) network-based evaluation of putative IDs; (7) spectral matching of MS/MS data against experimental and in-
silico fragmentation patterns; (8) deep learning-based prediction of compound fingerprints; and (9) integrative
assessment of putative metabolite IDs via a probabilistic model. Aim 2 will assemble the tools developed in Aim
1 into a cloud-based platform, MetaboQuest, which provides users with interactive visualization of peaks, isotopic
patterns, networks, and mass spectra. Furthermore, Aim 2 will focus on integrating into MetaboQuest a pipeline
builder that allows users to create pipelines by linking modules and run them remotely through a modular
interactive web interface. Aim 3 will perform a comprehensive evaluation of MetaboQuest in terms of metabolite
annotation accuracy, number of annotated metabolites, and computational efficiency compared to other existing
tools. Accuracy in metabolite annotation will be evaluated via experimental methods in which MS/MS data from
unknown analytes and reference compounds are compared, and by using LC-MS/MS data from multiple
metabolomics studies that consist of ground-truth information. Successful implementation and validation of
MetaboQuest will contribute to addressing the major bottleneck in metabolomics - metabolite identification,
thereby eliminating the need for manual verification of putative metabolite IDs and enhancing the contribution of
metabolomics studies, specifically in disease biomarker and drug discovery.
MetaboQuest:一套代谢物注释工具
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Dawit Mengistu其他文献
Dawit Mengistu的其他文献
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{{ truncateString('Dawit Mengistu', 18)}}的其他基金
Understanding Dysregulated Crosstalk Between Regulatory T Cells and Lung Dendritic Cells in the Pathogenesis of Chronic Obstructive Pulmonary Disease
了解慢性阻塞性肺疾病发病机制中调节性 T 细胞和肺树突状细胞之间的失调串扰
- 批准号:
10460830 - 财政年份:2022
- 资助金额:
$ 99.79万 - 项目类别:
MetaboQuest: A Suite of Tools for Metabolite Annotation
MetaboQuest:代谢物注释工具套件
- 批准号:
10570907 - 财政年份:2022
- 资助金额:
$ 99.79万 - 项目类别:
Understanding Dysregulated Crosstalk Between Regulatory T Cells and Lung Dendritic Cells in the Pathogenesis of Chronic Obstructive Pulmonary Disease
了解慢性阻塞性肺疾病发病机制中调节性 T 细胞和肺树突状细胞之间的失调串扰
- 批准号:
10746742 - 财政年份:2022
- 资助金额:
$ 99.79万 - 项目类别:
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