Name
Abstract | ||
|---|---|---|
Metabolomics is an expanding field of 'omics' that involves the identification and quantification of small molecules in cells, tissues and other complex biological samples. Metabolomics is emerging as a strong tool for disease treatments and drug developments. A major challenge in realizing the full potential of metabolomics to globally characterize metabolism lies in processing and analyzing the collected data. Obtaining meaningful biological information depends on reliably and efficiently resolving the chemical identities of the detected data features (unique mass and associated fragmentation spectrum in the case of mass spectrometry experiments). We propose in this poster a novel metabolomics data processing workflow to enhance the accuracy and performance of metabolite identification. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1145/3107411.3108189 | BCB |
Field | DocType | ISBN |
Data mining,Data processing,Annotation,Computer science,Metabolomics,Bioinformatics,Metabolite,Workflow | Conference | 978-1-4503-4722-8 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Neda Hassanpour | 1 | 0 | 0.34 |
| Nicholas Alden | 2 | 0 | 0.34 |
| Kyongbum Lee | 3 | 70 | 7.40 |
| Soha Hassoun | 4 | 535 | 241.27 |