Inhalt des Dokuments
Forschungsinterressen
- Proteinstrukturvorhersage
- Protein Klassifizierung/ Homologiesuche
- Machinelles Lernen
Lebenslauf
- 03/2013-heute
Wissenschaftlicher Mitarbeiter im Robotics & Biology Lab, TU Berlin (Prof. Oliver Brock). - 11/2012
Master Sc. in Informatik mit Schwerpunkt Intelligente Systeme an der Technische Universität Berlin. - 02/2011-12/2011
Studentische Hilfskraft Neuronale Informationsverarbeitung Gruppe, Technische Universität Berlin (Prof. Klaus Obermayer). - 09/2009-08/2010
Austauschstudent an der Shanghai Jiaotong University (TU-Berlin Stipendium) - 03/2010
Bachelor Sc. in Informatik an der Technische Universität Berlin. - 04/2009-08/2009
Studentische Hilfskraft Daimler Center for Automotive Information Technology Innovations, Technische Universität Berlin
Publikationen
| Zitatschlüssel | Mabrouk-et-al2016 |
|---|---|
| Autor | Mahmoud Mabrouk and Tim Werner and Michael Schneider and Ines Putz and Oliver Brock |
| Seiten | 87–104 |
| Jahr | 2016 |
| DOI | 10.1002/prot.24950 |
| Journal | Proteins: Structure, Function, and Bioinformatics |
| Jahrgang | 84(Suppl 1) |
| Notiz | http://dx.doi.org/10.1002/prot.24950 |
| Zusammenfassung | The CASP experiment is a biannual benchmark for assessing protein structure prediction methods. In CASP11, RBO Aleph ranked as one of the top-performing automated servers in the free modeling category. This category consists of targets for which structural templates are not easily retrievable. We analyze the performance of RBO Aleph and show that its success in CASP was a result of its ab initio structure prediction protocol. A detailed analysis of this protocol demonstrates that two components unique to our method greatly contributed to prediction quality: residue–residue contact prediction by EPC-map and contact-guided conformational space search by model-based search (MBS). Interestingly, our analysis also points to a possible fundamental problem in evaluating the performance of protein structure prediction methods: Improvements in components of the method do not necessarily lead to improvements of the entire method. This points to the fact that these components interact in ways that are poorly understood. This problem, if indeed true, represents a significant obstacle to community-wide progress. |
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