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Mireille Régnier

Publications and source records attributed to Mireille Régnier.

4 recordsLinked to original sources

Comparison of statistical significance criteria.

We study and compare two classes of statistical criteria to assess the significance of exceptional words. Indeed, the Z-score-like criteria, or the normal approximation that is a strict equivalent, suffer from several drawbacks in terms of sensitivity and specificity. Thanks to the combinatorial structure of words, a computation of the exact P-value has been made possible by recent mathematical results. We study here the drawbacks of the Z-score, the choice of the threshold and the tightness to the P-value. A major conclusion is that the normal approximation is always very poor and overestimates statistical significance.

Algorithms↗

Assessing computational tools for the discovery of transcription factor binding sites.

The prediction of regulatory elements is a problem where computational methods offer great hope. Over the past few years, numerous tools have become available for this task. The purpose of the current assessment is twofold: to provide some guidance to users regarding the accuracy of currently available tools in various settings, and to provide a benchmark of data sets for assessing future tools.

Amino Acid Motifs↗

Automatic RNA secondary structure prediction with a comparative approach.

This paper presents an algorithm, DCFold, that automatically predicts the common secondary structure of a set of aligned homologous RNA sequences. It is based on the comparative approach. Helices are searched in one of the sequences, called the 'target sequence', and compared to the helices in the other sequences, called the 'test sequences'. Our algorithm searches in the target sequence for palindromes that have a high probability to define helices that are conserved in the test sequences. This selection of significant palindromes is based on criteria that take into account their length and their mutation rate. A recursive search of helices, starting from these likely ones, is implemented using the 'divide and conquer' approach. Indeed, as pseudo-knots are not searched by DCFold, a selected palindrome (p, p') makes possible to divide the initial sequence into two sequences, the internal one and the one resulting from the concatenation of the two external ones. New palindromes can be searched independently in these subsequences. This algorithm was run on ribosomal RNA sequences and recovered very efficiently their common secondary structures.

Algorithms↗

Extraction of functional binding sites from unique regulatory regions: the Drosophila early developmental enhancers.

The early developmental enhancers of Drosophila melanogaster comprise one of the most sophisticated regulatory systems in higher eukaryotes. An elaborate code in their DNA sequence translates both maternal and early embryonic regulatory signals into spatial distribution of transcription factors. One of the most striking features of this code is the redundancy of binding sites for these transcription factors (BSTF). Using this redundancy, we explored the possibility of predicting functional binding sites in a single enhancer region without any prior consensus/matrix description or evolutionary sequence comparisons. We developed a conceptually simple algorithm, Scanseq, that employs an original statistical evaluation for identifying the most redundant motifs and locates the position of potential BSTF in a given regulatory region. To estimate the biological relevance of our predictions, we built thorough literature-based annotations for the best-known Drosophila developmental enhancers and we generated detailed distribution maps for the most robust binding sites. The high statistical correlation between the location of BSTF in these experiment-based maps and the location predicted in silico by Scanseq confirmed the relevance of our approach. We also discuss the definition of true binding sites and the possible biological principles that govern patterning of regulatory regions and the distribution of transcriptional signals.

Algorithms↗