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Aydin Albayrak    - research student -


aydinalbay@su.sabanciuniv.edu

Journal articles

2011
Verena Seidl-Seiboth, Sabine Gruber, Ugur Sezerman, Torsten Schwecke, Aydin Albayrak, Torsten Neuhof, Hans von Döhren, Scott E Baker, Christian P Kubicek (2011)  Novel Hydrophobins from Trichoderma Define a New Hydrophobin Subclass: Protein Properties, Evolution, Regulation and Processing.   J Mol Evol Mar  
Abstract: Hydrophobins are small proteins, characterised by the presence of eight positionally conserved cysteine residues, and are present in all filamentous asco- and basidiomycetes. They are found on the outer surfaces of cell walls of hyphae and conidia, where they mediate interactions between the fungus and the environment. Hydrophobins are conventionally grouped into two classes (class I and II) according to their solubility in solvents, hydropathy profiles and spacing between the conserved cysteines. Here we describe a novel set of hydrophobins from Trichoderma spp. that deviate from this classification in their hydropathy, cysteine spacing and protein surface pattern. Phylogenetic analysis shows that they form separate clades within ascomycete class I hydrophobins. Using T. atroviride as a model, the novel hydrophobins were found to be expressed under conditions of glucose limitation and to be regulated by differential splicing.
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2010
Aydin Albayrak, Hasan H Otu, Ugur O Sezerman (2010)  Clustering of protein families into functional subtypes using Relative Complexity Measure with reduced amino acid alphabets.   BMC Bioinformatics 11: 08  
Abstract: Phylogenetic analysis can be used to divide a protein family into subfamilies in the absence of experimental information. Most phylogenetic analysis methods utilize multiple alignment of sequences and are based on an evolutionary model. However, multiple alignment is not an automated procedure and requires human intervention to maintain alignment integrity and to produce phylogenies consistent with the functional splits in underlying sequences. To address this problem, we propose to use the alignment-free Relative Complexity Measure (RCM) combined with reduced amino acid alphabets to cluster protein families into functional subtypes purely on sequence criteria. Comparison with an alignment-based approach was also carried out to test the quality of the clustering.
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