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2022-06
"paPAML: An Improved Computational Tool to Explore Selection Pressure on Protein-Coding Sequences" by Lynn Ogoniak, Norbert Grundmann and others
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2022-05-14
"Mobilome of Apicomplexa Parasites" by Rodriguez and Makalowski has been published by Genes.
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2022-04-27
"Software evaluation for de novo detection of transposons" by Rodriguez and Makalowski has been published by Mobile DNA.
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2022-04-01
"From telomere to telomere: The transcriptional and epigenetic state of human repeat elements” by T2T consortium has been published by Science.
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2022-02-12
"Global research alliance in infectious disease: a collaborative effort to combat infectious diseases through dissemination of portable sequencing” by GRAID consortium that IoB is part of has been published by BMC Research Notes.
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2021-08-05
Congratulations to Reza and Matias on the excellent contribution on TE-driven DNA transductions in the human genome
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2021-05-29
"Somatic Functional Deletions of Upstream Open Reading Frame-Associated Initiation and Termination Codons in Human Cancer" was published by MDPI
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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]
2018-11-15 11:50