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Leveraging Data from Mass Spectrometry to Improve Cross-Links

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Cross-Links are experimentally derived distance constraints that can be used to guide protein structure prediction. The current cross-linking data is obtained from multiple mass spectrometer runs and pre-filtered. In the pre-fltering step we lose a lot of information. For instance, there is ambiguity in the data that is currently handled in a greedy fashion. The idea of this project is to go one step back and look at the "raw" data from the mass spectrometry experiments. The hope is by including external information and dealing directly with the ambiguity in the data we can improve the number of cross-links and/or need fewer experiments for a similar yield. more to: Leveraging Data from Mass Spectrometry to Improve Cross-Links

Leveraging Crosslinks for Template Retrieval

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Cross-Link Mass Spectometry is an experimental technique that provides residue distance constraints on the native structure. The method has been previously used to guide ab initio protein structure prediction. You will develop in this thesis a method that leverages cross-links to find homologous structures to the target in the PDB. For that, you will compare the distance constraints provided by cross-links with simulated cross-links for the templates from the PDB. more to: Leveraging Crosslinks for Template Retrieval

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