基于质谱的计算代谢组学的最新进展。
Recent advances in mass spectrometry-based computational metabolomics.
机构信息
Section of Bioinformatics, Department of Metabolism, Digestion & Reproduction, Imperial College London, Burlington Danes Building, Hammersmith Hospital, Du Cane Road, London W12 0NN, UK.
Bioinformatics Group, Wageningen University & Research, Wageningen 6708 PB, the Netherlands; Department of Biochemistry, University of Johannesburg, Auckland Park, Johannesburg 2006, South Africa.
出版信息
Curr Opin Chem Biol. 2023 Jun;74:102288. doi: 10.1016/j.cbpa.2023.102288. Epub 2023 Mar 24.
The computational metabolomics field brings together computer scientists, bioinformaticians, chemists, clinicians, and biologists to maximize the impact of metabolomics across a wide array of scientific and medical disciplines. The field continues to expand as modern instrumentation produces datasets with increasing complexity, resolution, and sensitivity. These datasets must be processed, annotated, modeled, and interpreted to enable biological insight. Techniques for visualization, integration (within or between omics), and interpretation of metabolomics data have evolved along with innovation in the databases and knowledge resources required to aid understanding. In this review, we highlight recent advances in the field and reflect on opportunities and innovations in response to the most pressing challenges. This review was compiled from discussions from the 2022 Dagstuhl seminar entitled "Computational Metabolomics: From Spectra to Knowledge".
计算代谢组学领域汇集了计算机科学家、生物信息学家、化学家、临床医生和生物学家，旨在最大限度地提高代谢组学在广泛的科学和医学领域的影响力。随着现代仪器产生越来越复杂、分辨率越来越高、灵敏度越来越强的数据集，该领域不断发展。必须对这些数据集进行处理、注释、建模和解释，以实现生物学见解。代谢组学数据的可视化、整合（组内或组间）和解释技术随着数据库和知识资源的创新而发展，这些资源对于辅助理解至关重要。在这篇综述中，我们强调了该领域的最新进展，并思考了应对最紧迫挑战的机会和创新。这篇综述是从 2022 年达戈斯泰尔研讨会题为“计算代谢组学：从光谱到知识”的讨论中汇编而成的。
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