Biomedical subjects

Marc Rehmsmeier

Publications and source records attributed to Marc Rehmsmeier.

12 recordsLinked to original sources

PubMed2006

RNAhybrid: microRNA target prediction easy, fast and flexible.

In the elucidation of the microRNA regulatory network, knowledge of potential targets is of highest importance. Among existing target prediction methods, RNAhybrid [M. Rehmsmeier, P. Steffen, M. Höchsmann and R. Giegerich (2004) RNA, 10, 1507-1517] is unique in offering a flexible online prediction. Recently, some useful features have been added, among these the possibility to disallow G:U base pairs in the seed region, and a seed-match speed-up, which accelerates the program by a factor of 8. In addition, the program can now be used as a webservice for remote calls from user-implemented programs. We demonstrate RNAhybrid's flexibility with the prediction of a non-canonical target site for Caenorhabditis elegans miR-241 in the 3'-untranslated region of lin-39. RNAhybrid is available at http://bibiserv.techfak.uni-bielefeld.de/rnahybrid.

3' Untranslated Regions↗

PubMed2006

jPREdictor: a versatile tool for the prediction of cis-regulatory elements.

Gene regulation is the process through which an organism effects spatial and temporal differences in gene expression levels. Knowledge of cis-regulatory elements as key players in gene regulation is indispensable for the understanding of the latter and of the development of organisms. Here we present the tool jPREdictor for the fast and versatile prediction of cis-regulatory elements on a genome-wide scale. The prediction is based on clusters of individual motifs and any combination of these into multi-motifs with selectable minimal and maximal distances. Individual motifs can be of heterogenous classes, such as simple sequence motifs or position-specific scoring matrices. Cluster scores are weighted occurrences of multi-motifs, where the weights are derived from positive and negative training sets. We illustrate the flexibility of the jPREdictor with a new predic-tion of Polycomb/Trithorax Response Elements in Drosophila melanogaster. jPREdictor is available as a graphical user interface for online use and for download at http://bibiserv.techfak.uni-bielefeld.de/jpredictor.

Animals↗

PubMed2006

Beyond Mfold: recent advances in RNA bioinformatics.

Computational analysis of RNA secondary structure is a classical field of biosequence analysis, which has recently gained momentum due to the manyfold regulatory functions of RNA that have become apparent. We present five recent computational approaches that address the problems of synoptic folding space analysis, pseudoknot prediction, structure alignment, comparative structure prediction, and miRNA target prediction. All these programs are in current use and are available via the Bielefeld Bioinformatics Server at .

Animals↗

PubMed2006

Complete probabilistic analysis of RNA shapes.

BACKGROUND: Soon after the first algorithms for RNA folding became available, it was recognised that the prediction of only one energetically optimal structure is insufficient to achieve reliable results. An in-depth analysis of the folding space as a whole appeared necessary to deduce the structural properties of a given RNA molecule reliably. Folding space analysis comprises various methods such as suboptimal folding, computation of base pair probabilities, sampling procedures and abstract shape analysis. Common to many approaches is the idea of partitioning the folding space into classes of structures, for which certain properties can be derived. RESULTS: In this paper we extend the approach of abstract shape analysis. We show how to compute the accumulated probabilities of all structures that share the same shape. While this implies a complete (non-heuristic) analysis of the folding space, the computational effort depends only on the size of the shape space, which is much smaller. This approach has been integrated into the tool RNA shapes, and we apply it to various RNAs. CONCLUSION: Analyses of conformational switches show the existence of two shapes with probabilities approximately 2/3 vs. 1/3, whereas the analysis of a microRNA precursor reveals one shape with a probability near to 1.0. Furthermore, it is shown that a shape can outperform an energetically more favourable one by achieving a higher probability. From these results, and the fact that we use a complete and exact analysis of the folding space, we conclude that this approach opens up new and promising routes for investigating and understanding RNA secondary structure.

Algorithms↗

PubMed2006

Prediction of microRNA targets.

I describe the use of RNAhybrid, a program that predicts multiple potential binding sites of microRNAs (miRNAs) in large target RNAs. The core algorithm finds the energetically most favorable hybridization sites of a miRNA in a large potential target RNA. Intramolecular hybridizations, i.e., base pairings between target nucleotides or between miRNA nucleotides are, not allowed. For large targets, the time complexity of the algorithm is linear in the target length, allowing many long targets to be searched in a short time. Starting from the observation that the binding energies are results from an optimization procedure, we can model them as following an extreme value distribution. From this, we can calculate the statistical significance of individual binding sites, of multiple binding sites in a single target sequence, and of binding sites in comparative analyses of orthologous sequences across species. The latter involves the calculation of the effective number of orthologous sequences, which can be considerably smaller than the actual number, reflecting the statistical dependence of evolutionarily related sequences.

Algorithms↗

PubMed2005

RNAshapes: an integrated RNA analysis package based on abstract shapes.

We introduce RNAshapes, a new software package that integrates three RNA analysis tools based on the abstract shapes approach: the analysis of shape representatives, the calculation of shape probabilities and the consensus shapes approach. This new package is completely reimplemented in C and outruns the original implementations significantly in runtime and memory requirements. Additionally, we added a number of useful features like suboptimal folding with correct dangling energies, structure graph output, shape matching and a sliding window approach.

Algorithms↗

PubMed2004

Abstract shapes of RNA.

The function of a non-protein-coding RNA is often determined by its structure. Since experimental determination of RNA structure is time-consuming and expensive, its computational prediction is of great interest, and efficient solutions based on thermodynamic parameters are known. Frequently, however, the predicted minimum free energy structures are not the native ones, leading to the necessity of generating suboptimal solutions. While this can be accomplished by a number of programs, the user is often confronted with large outputs of similar structures, although he or she is interested in structures with more fundamental differences, or, in other words, with different abstract shapes. Here, we formalize the concept of abstract shapes and introduce their efficient computation. Each shape of an RNA molecule comprises a class of similar structures and has a representative structure of minimal free energy within the class. Shape analysis is implemented in the program RNAshapes. We applied RNAshapes to the prediction of optimal and suboptimal abstract shapes of several RNAs. For a given energy range, the number of shapes is considerably smaller than the number of structures, and in all cases, the native structures were among the top shape representatives. This demonstrates that the researcher can quickly focus on the structures of interest, without processing up to thousands of near-optimal solutions. We complement this study with a large-scale analysis of the growth behaviour of structure and shape spaces. RNAshapes is available for download and as an online version on the Bielefeld Bioinformatics Server.

5' Untranslated Regions↗

PubMed2004

Comparative homology agreement search: an effective combination of homology-search methods.

Many methods have been developed to search for homologous members of a protein family in databases, and the reliability of results and conclusions may be compromised if only one method is used, neglecting the others. Here we introduce a general scheme for combining such methods. Based on this scheme, we implemented a tool called comparative homology agreement search (chase) that integrates different search strategies to obtain a combined "E value." Our results show that a consensus method integrating distinct strategies easily outperforms any of its component algorithms. More specifically, an evaluation based on the Structural Classification of Proteins database reveals that, on average, a coverage of 47% can be obtained in searches for distantly related homologues (i.e., members of the same superfamily but not the same family, which is a very difficult task), accepting only 10 false positives, whereas the individual methods obtain a coverage of 28-38%.

Databases, Protein↗

PubMed2004

Fast and effective prediction of microRNA/target duplexes.

MicroRNAs (miRNAs) are short RNAs that post-transcriptionally regulate the expression of target genes by binding to the target mRNAs. Although a large number of animal miRNAs has been defined, only a few targets are known. In contrast to plant miRNAs, which usually bind nearly perfectly to their targets, animal miRNAs bind less tightly, with a few nucleotides being unbound, thus producing more complex secondary structures of miRNA/target duplexes. Here, we present a program, RNA-hybrid, that predicts multiple potential binding sites of miRNAs in large target RNAs. In general, the program finds the energetically most favorable hybridization sites of a small RNA in a large RNA. Intramolecular hybridizations, that is, base pairings between target nucleotides or between miRNA nucleotides are not allowed. For large targets, the time complexity of the algorithm is linear in the target length, allowing many long targets to be searched in a short time. Statistical significance of predicted targets is assessed with an extreme value statistics of length normalized minimum free energies, a Poisson approximation of multiple binding sites, and the calculation of effective numbers of orthologous targets in comparative studies of multiple organisms. We applied our method to the prediction of Drosophila miRNA targets in 3'UTRs and coding sequence. RNAhybrid, with its accompanying programs RNAcalibrate and RNAeffective, is available for download and as a Web tool on the Bielefeld Bioinformatics Server (http://bibiserv.techfak.uni-bielefeld.de/rnahybrid/).

3' Untranslated Regions↗

PubMed2003

Genome-wide prediction of Polycomb/Trithorax response elements in Drosophila melanogaster.

Polycomb/Trithorax response elements (PRE/TREs) maintain transcriptional decisions to ensure correct cell identity during development and differentiation. There are thought to be over 100 PRE/TREs in the Drosophila genome, but only very few have been identified due to the lack of a defining consensus sequence. Here we report the definition of sequence criteria that distinguish PRE/TREs from non-PRE/TREs. Using this approach for genome-wide PRE/TRE prediction, we identify 167 candidate PRE/TREs, which map to genes involved in development and cell proliferation. We show that candidate PRE/TREs are bound and regulated by Polycomb proteins in vivo, thus demonstrating the validity of PRE/TRE prediction. Using the larger data set thus generated, we identify three sequence motifs that are conserved in PRE/TRE sequences.

Animals↗

PubMed2002

A novel approach to remote homology detection: jumping alignments.

We describe a new algorithm for protein classification and the detection of remote homologs. The rationale is to exploit both vertical and horizontal information of a multiple alignment in a well-balanced manner. This is in contrast to established methods such as profiles and profile hidden Markov models which focus on vertical information as they model the columns of the alignment independently and to family pairwise search which focuses on horizontal information as it treats given sequences separately. In our setting, we want to select from a given database of "candidate sequences" those proteins that belong to a given superfamily. In order to do so, each candidate sequence is separately tested against a multiple alignment of the known members of the superfamily by means of a new jumping alignment algorithm. This algorithm is an extension of the Smith-Waterman algorithm and computes a local alignment of a single sequence and a multiple alignment. In contrast to traditional methods, however, this alignment is not based on a summary of the individual columns of the multiple alignment. Rather, the candidate sequence is at each position aligned to one sequence of the multiple alignment, called the "reference sequence." In addition, the reference sequence may change within the alignment, while each such jump is penalized. To evaluate the discriminative quality of the jumping alignment algorithm, we compare it to profiles, profile hidden Markov models, and family pairwise search on a subset of the SCOP database of protein domains. The discriminative quality is assessed by median false positive counts (med-FP-counts). For moderate med-FP-counts, the number of successful searches with our method is considerably higher than with the competing methods.

Algorithms↗

PubMed2002

Phase4: automatic evaluation of database search methods.

It has become standard to evaluate newly devised database search methods in terms of sensitivity and selectivity and to compare them with existing methods. This involves the construction of a suitable evaluation scenario, the execution of the methods, the assessment of their performances, and the presentation of the results. Each of these four phases and their smooth connection usually imposes formidable work. To relieve the evaluator of this burden, a system has been designed with which evaluations can be effected rapidly. It is implemented in the programming language Python whose object-oriented features are used to offer a great flexibility in changing the evaluation design. A graphical user interface is provided which offers the usual amenities such as radio- and checkbuttons or file browsing facilities.

Data Interpretation, Statistical↗