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Michael Remmert

Publications and source records attributed to Michael Remmert.

4 recordsLinked to original sources

HHrep: de novo protein repeat detection and the origin of TIM barrels.

HHrep is a web server for the de novo identification of repeats in protein sequences, which is based on the pairwise comparison of profile hidden Markov models (HMMs). Its main strength is its sensitivity, allowing it to detect highly divergent repeat units in protein sequences whose repeats could as yet only be detected from their structures. Examples include sequences with beta-propellor fold, ferredoxin-like fold, double psi barrels or (betaalpha)8 (TIM) barrels. We illustrate this with proteins from four superfamilies of TIM barrels by revealing a clear 4- and 8-fold symmetry, which we detect solely from their sequences. This symmetry might be the trace of an ancient origin through duplication of a betaalphabetaalpha or betaalpha unit. HHrep can be accessed at http://hhrep.tuebingen.mpg.de.

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HHsenser: exhaustive transitive profile search using HMM-HMM comparison.

HHsenser is the first server to offer exhaustive intermediate profile searches, which it combines with pairwise comparison of hidden Markov models. Starting from a single protein sequence or a multiple alignment, it can iteratively explore whole superfamilies, producing few or no false positives. The output is a multiple alignment of all detected homologs. HHsenser's sensitivity should make it a useful tool for evolutionary studies. It may also aid applications that rely on diverse multiple sequence alignments as input, such as homology-based structure and function prediction, or the determination of functional residues by conservation scoring and functional subtyping.HHsenser can be accessed at http://hhsenser.tuebingen.mpg.de/. It has also been integrated into our structure and function prediction server HHpred (http://hhpred.tuebingen.mpg.de/) to improve predictions for near-singleton sequences.

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The MPI Bioinformatics Toolkit for protein sequence analysis.

The MPI Bioinformatics Toolkit is an interactive web service which offers access to a great variety of public and in-house bioinformatics tools. They are grouped into different sections that support sequence searches, multiple alignment, secondary and tertiary structure prediction and classification. Several public tools are offered in customized versions that extend their functionality. For example, PSI-BLAST can be run against regularly updated standard databases, customized user databases or selectable sets of genomes. Another tool, Quick2D, integrates the results of various secondary structure, transmembrane and disorder prediction programs into one view. The Toolkit provides a friendly and intuitive user interface with an online help facility. As a key feature, various tools are interconnected so that the results of one tool can be forwarded to other tools. One could run PSI-BLAST, parse out a multiple alignment of selected hits and send the results to a cluster analysis tool. The Toolkit framework and the tools developed in-house will be packaged and freely available under the GNU Lesser General Public Licence (LGPL). The Toolkit can be accessed at http://toolkit.tuebingen.mpg.de.

Computational Biology↗

Identification of plant microRNA homologs.

MicroRNAs (miRNAs) are a recently discovered class of non-coding RNAs that regulate gene and protein expression in plants and animals. MiRNAs have so far been identified mostly by specific cloning of small RNA molecules, complemented by computational methods. We present a computational identification approach that is able to identify candidate miRNA homologs in any set of sequences, given a query miRNA. The approach is based on a sequence similarity search step followed by a set of structural filters.

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