7 papers · ranked by Valyu relevance
Adarsh Arun, Jana Weber, Zhen Guo, Alexei Lapkin
As the chemical sector looks to decarbonize, one promising solution is the utilization of bio-feedstocks and biowaste to produce functional molecules. There is, therefore, great interest in understanding how and where to integrate these resources within chemical supply chains. To assist such efforts, screening…
Authors not listed
High-quality data preprocessing is essential for untargeted metabolomics experiments, where increasing dataset scale and complexity demand adaptable, robust, and reproducible software solutions. Modern preprocessing tools must evolve to integrate seamlessly with downstream analysis platforms, ensuring efficient and…
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In the data-driven discovery of high-performance thermoelectric (TE) materials, the lack of high-quality data remains a key bottleneck. Addressing this issue, we introduce the Systematically Verified Thermoelectric (sysTEm) dataset. Leveraging the physical relationships between transport properties, we curated and…
Eftychia Eva Kontou, Axel Walter, Timo Sachsenberg, Tilmann Weber + 5 more
Metabolomics experiments generate highly complex datasets, which are time and work-intensive, sometimes even error-prone if inspected manually. Therefore, new methods for automated, fast, reproducible, and accurate data processing and dereplication are required. Here, we present UmetaFlow, a computational workflow for…
Hunter Dlugas, Xiang Zhang, Seongho Kim
In mass spectrometry (MS)-based metabolomics, compound identification relies on Liquid Chromatography-MS (LC-MS) and Gas Chromatography-MS (GC-MS). The most popular and efficient approach for this purpose is the comparison of similarity scores between experimental spectra and reference spectra. Among the various single…
Eftychia Eva Kontou, Axel Walter, Oliver Alka, Julianus Pfeuffer + 5 more
Metabolomics experiments generate highly complex datasets, which are time and work-intensive, sometimes even error-prone if inspected manually. Therefore, new methods for automated, fast, reproducible, and accurate data processing and dereplication are required. Here, we present UmetaFlow, a computational workflow for…
Authors not listed
We present TAPAS (Transient Absorption Processing and Analysis Software), an open-source, Python-based graphical platform that covers the entire transient absorption (TA) workflow, from raw data import and preprocessing to visualization, global and target fitting, and statistical evaluation. Users operate TAPAS through…