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2018-01-04
"Transcriptional interference by small transcripts in proximal promoter regions" by Pande et al. has been published by Nucleic Acids Research.
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2017-12-29
"The emerging picture of the mitochondrial protein import complexes of Amoebozoa supergroup" by Wojtkowska, Buczek et al. has been published by BMC Genomics.
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2017-09-05
Juan Manuel Galvez, welcome to our institute!
2017-09-05
Julian-Hendrik Matschke, welcome to our institute!
2017-07-11
Congratulations Philipp Fervers for for the successful defense of his doctoral thesis.
2017-07-24
Yukie Kashima, welcome to our institute!
2017-07-11
"Inferring clonal structure in HTLV-1-infected individuals: towards bridging the gap between analysis and visualization” by Farmanbar et al. has bee published by Human Genomics.
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2017-07-03
Welcome Reza Halabian, our new PhD student..
2017-06-27
"Sequencing and phasing cancer mutations in lung cancers using a long-read portable sequencer” by Suzuki et al. has bee published by DNA Research.
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2017-06-14
"Serotyping dengue virus with isothermal amplification and a portable sequencer.” by Yamagishi at al. has been published by Scientific Reports.
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Visualizing Sequence Similarity of Protein Families

Classification of proteins into families is one of the main goals of functional analysis. Proteins are usually assigned to a family on the basis of the presence of family-specific patterns, domains, or structural elements. Whereas proteins belonging to the same family are generally similar to each other, the extent of similarity varies widely across families. Some families are characterized by short, well-defined motifs, whereas others contain longer, less-specific motifs. We present a simple method for visualizing such differences. We applied our method to the Arabidopsis thaliana families listed at The Arabidopsis Information Resource (TAIR) Web site and for 76% of the nontrivial families (families with more than one member), our method identifies simple similarity measures that are necessary and sufficient to cluster members of the family together. Our visualization method can be used as part of an annotation pipeline to identify potentially incorrectly defined families. We also describe how our method can be extended to identify novel families and to assign unclassified proteins into known families.

One result of our work is the discovery that, despite the wide variety of methods used in the construction of protein families, 76% of all analyzed Arabidopsis thaliana families are fully clusterable by the proposed simple parameter schemes. Our results also show relationships between families that shar/ members, and help identify potentially incorrect family assignments. We also show how our results could be used to identify novel families and assign unclassified proteins to known families.

Reference: Veeramachaneni V. and Makalowski W. (2004) Visualizing sequence similarity of protein families. Genome Research, 14 (6): 1160-1169.[Reprint]
2012-11-19 14:06