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Mahmoud Mabrouk

Lupe



Raum: MAR 5.065
Telefon: +49.30.314-73118

Forschungsinterressen

  • Proteinstrukturvorhersage
  • Protein Klassifizierung/ Homologiesuche
  • Machinelles Lernen

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Publikationen

RBO Aleph: Leveraging Novel Information Sources for Protein Structure Prediction
Zitatschlüssel Mabrouk-et-al2015
Autor Mahmoud Mabrouk and Ines Putz and Tim Werner and Michael Schneider and Moritz Neeb and Philipp Bartels and Oliver Brock
Seiten W343-W348
Jahr 2015
DOI 10.1093/nar/gkv357
Journal Nucleic Acids Research
Jahrgang 43 (W1)
Monat April
Notiz http://www.robotics.tu-berlin.de/fileadmin/fg170/Publikationen_pdf/NuclAcids2015Mabrouk.pdf
Zusammenfassung RBO Aleph is a novel protein structure prediction web server for template-based modeling, protein contact prediction and ab initio structure prediction. The server has a strong emphasis on modeling difficult protein targets for which templates cannot be detected. RBO Aleph's unique features are (i) the use of combined evolutionary and physicochemical information to perform residue–residue contact prediction and (ii) leveraging this contact information effectively in conformational space search. RBO Aleph emerged as one of the leading approaches to ab initio protein structure prediction and contact prediction during the most recent Critical Assessment of Protein Structure Prediction experiment (CASP11, 2014). In addition to RBO Aleph's main focus on ab initio modeling, the server also provides state-of-the-art template-based modeling services. Based on template availability, RBO Aleph switches automatically between template-based modeling and ab initio prediction based on the target protein sequence, facilitating use especially for non-expert users. The RBO Aleph web server offers a range of tools for visualization and data analysis, such as the visualization of predicted models, predicted contacts and the estimated prediction error along the model's backbone. The server is accessible at http://compbio.robotics.tu-berlin.de/rbo_aleph/.
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