Publications by authors named "Shinji Kanazawa"
Metabolomics can help identify candidate biomarker metabolites whose levels are altered in response to disease development or drug administration. However, assessment of the underlying molecular mechanism is challenging considering it depends on the researcher's knowledge. This study reports a novel method for the automated recommendation of keywords known in the literature that may be overlooked by researchers.
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- Peak picking is essential in chromatography for identifying the start and end points of peaks, but accurately labeling these points has been challenging due to overlaps in real data.
- A new method has been developed to generate fake chromatograms that include clearly defined peak boundaries, allowing for better training of deep learning neural networks.
- The resulting peak-picking neural networks exceeded the performance of traditional software and matched the accuracy of skilled operators, highlighting the importance of these generated fake chromatograms for future advancements in peak picking technology.