CycloBranch

CycloBranch generates de novo molecular formulas from liquid chromatography/mass spectrometry (LC/MS) and mass spectrometry imaging (MSI) data to identify and characterize unknown small molecules in metabolomics, natural product chemistry, and microbiology studies.

Key Features:

• De novo molecular formula generation: Database-free generation of molecular formulas for unknown compounds from mass spectrometry data.
• Data type support: Designed to work with LC/MS and mass spectrometry imaging (MSI) datasets.
• Isotope ratio filtering: Fine isotope ratio data filtering that distinguishes isotopic interferences such as ^34S/^13C_2 versus ^41K/^13C_2.
• Bimodal image fusion support: Applied for bimodal image fusion workflows in MSI for combined-data characterization.
• Metallophore characterization: Enables characterization tasks involving small molecules such as metallophores.
• Implementation: Implemented in C++ and released under the GNU General Public License.

Scientific Applications:

• Natural product chemistry: Identification of unknown natural products via de novo formula generation from MS data.
• Microbiology: Characterization of microbial metabolites and small molecules in microbiological studies.
• Food metabolomics: Analysis and identification of unknown compounds in food-related metabolomic datasets.
• Human metabolomics: Application to discovery and characterization of unknown metabolites in human samples.
• Plant metabolomics: Identification of plant-derived unknown small molecules and metabolites.
• Mass spectrometry imaging: Bimodal image fusion and small-molecule characterization in MSI experiments.

Methodology:

Performs database-free de novo molecular formula generation from LC/MS and MSI data and applies a fine isotope ratio filtering step to resolve isotopic interferences (e.g., ^34S/^13C_2 vs ^41K/^13C_2); implemented in C++.