Bayesian methods for small molecule identification Confident identification of small molecules remains a major challenge in untargeted metabolomics natural product research and related fields. Liquid chromatography tandem mass spectrometry is a predominant technique for the high throughput analysis of small molecules and can detect thousands of different compounds in a biological sample. The automated interpretation of the resulting tandem mass spectra is highly non trivial and many studies are limited to re discovering known compounds by searching mass spectra in spectral reference libraries. But these libraries are vastly incomplete and a large portion of measured compounds remains unidentified. This constitutes a major bottleneck in the comprehensive high throughput analysis of metabolomics data. In this thesis we present two computational methods that address different steps in the identification process of small molecules from tandem mass spectra. ZODIAC is a novel method for de novo — that is database independent — molecular formula annotation in complete datasets. It exploits similarities of compounds co occurring in a sample to find the most likely molecular formula for each individual compound. ZODIAC improves on the currently best performing method SIRIUS; on one dataset by 16.5 fold. We show that de novo molecular formula annotation is not just a theoretical advantage: We discover multiple novel molecular formulas absent from PubChem one of the biggest structure databases. Furthermore we introduce a novel scoring for CSI:FingerID a state of the art method for searching tandem mass spectra in a structure database. This scoring models dependencies between different molecular properties in a predicted molecular fingerprint via Bayesian networks. This problem has the unusual property that the marginal probabilities differ for each predicted query fingerprint. Thus we need to apply Bayesian networks in a novel non standard fashion. Modeling dependencies improves on the currently best scoring.