Biomedical subjects

Giancarlo Mauri

Publications and source records attributed to Giancarlo Mauri.

5 recordsLinked to original sources

PubMed2006

MoD Tools: regulatory motif discovery in nucleotide sequences from co-regulated or homologous genes.

Understanding the complex mechanisms regulating gene expression at the transcriptional and post-transcriptional levels is one of the greatest challenges of the post-genomic era. The MoD (MOtif Discovery) Tools web server comprises a set of tools for the discovery of novel conserved sequence and structure motifs in nucleotide sequences, motifs that in turn are good candidates for regulatory activity. The server includes the following programs: Weeder, for the discovery of conserved transcription factor binding sites (TFBSs) in nucleotide sequences from co-regulated genes; WeederH, for the discovery of conserved TFBSs and distal regulatory modules in sequences from homologous genes; RNAProfile, for the discovery of conserved secondary structure motifs in unaligned RNA sequences whose secondary structure is not known. In this way, a given gene can be compared with other co-regulated genes or with its homologs, or its mRNA can be analyzed for conserved motifs regulating its post-transcriptional fate. The web server thus provides researchers with different strategies and methods to investigate the regulation of gene expression, at both the transcriptional and post-transcriptional levels. Available at http://www.pesolelab.it/modtools/ and http://www.beacon.unimi.it/modtools/.

Binding Sites↗

PubMed2004

Weeder Web: discovery of transcription factor binding sites in a set of sequences from co-regulated genes.

One of the greatest challenges that modern molecular biology is facing is the understanding of the complex mechanisms regulating gene expression. A fundamental step in this process requires the characterization of regulatory motifs playing key roles in the regulation of gene expression at transcriptional and post-transcriptional levels. In particular, transcription is modulated by the interaction of transcription factors with their corresponding binding sites. Weeder Web is a web interface to Weeder, an algorithm for the automatic discovery of conserved motifs in a set of related regulatory DNA sequences. The motifs found are in turn likely to be instances of binding sites for some transcription factor. Other than providing access to the program, the interface has been designed so to make usage of the program itself as simple as possible, and to require very little prior knowledge about the length and the conservation of the motifs to be found. In fact, the interface automatically starts different runs of the program, each one with different parameters, and provides the user with an overall summary of the results as well as some 'advice' on which motifs look more interesting according to their statistical significance and some simple considerations. The web interface is available at the address www.pesolelab.it by following the 'Tools' link.

Algorithms↗

PubMed2004

RNAProfile: an algorithm for finding conserved secondary structure motifs in unaligned RNA sequences.

The recent interest sparked due to the discovery of a variety of functions for non-coding RNA molecules has highlighted the need for suitable tools for the analysis and the comparison of RNA sequences. Many trans-acting non-coding RNA genes and cis-acting RNA regulatory elements present motifs, conserved both in structure and sequence, that can be hardly detected by primary sequence analysis alone. We present an algorithm that takes as input a set of unaligned RNA sequences expected to share a common motif, and outputs the regions that are most conserved throughout the sequences, according to a similarity measure that takes into account both the sequence of the regions and the secondary structure they can form according to base-pairing and thermodynamic rules. Only a single parameter is needed as input, which denotes the number of distinct hairpins the motif has to contain. No further constraints on the size, number and position of the single elements comprising the motif are required. The algorithm can be split into two parts: first, it extracts from each input sequence a set of candidate regions whose predicted optimal secondary structure contains the number of hairpins given as input. Then, the regions selected are compared with each other to find the groups of most similar ones, formed by a region taken from each sequence. To avoid exhaustive enumeration of the search space and to reduce the execution time, a greedy heuristic is introduced for this task. We present different experiments, which show that the algorithm is capable of characterizing and discovering known regulatory motifs in mRNA like the iron responsive element (IRE) and selenocysteine insertion sequence (SECIS) stem-loop structures. We also show how it can be applied to corrupted datasets in which a motif does not appear in all the input sequences, as well as to the discovery of more complex motifs in the non-coding RNA.

3' Untranslated Regions↗

PubMed2004

In silico representation and discovery of transcription factor binding sites.

Understanding the complex mechanisms governing basic biological processes requires the characterisation of regulatory motifs modulating gene expression at transcriptional and post-transcriptional level. In particular, extent, chronology and cell-specificity of transcription are modulated by the interaction of transcription factors with their corresponding binding sites, mostly located near (or sometimes quite far away from) the transcription start site of the gene. The constantly growing amount of genomic data, complemented by other sources of information such as expression data derived from microarray experiments, has opened new opportunities to researchers in this field. Many different methods have been proposed for the identification of transcription factor binding sites in the regulatory regions of co-expressed genes: unfortunately this is a very challenging problem both from the computational and the biological viewpoint. This paper provides a survey of existing methods proposed for the problem, focusing both on the ideas underlying them and their availability to the scientific community.

Algorithms↗

PubMed2003

P systems with deadlock.

Rewriting P systems with parallel application of evolution rules, as defined in Besozzi et al. [Parallel rewriting P systems with deadlock. In: Hagiya, M., Ohuchi, A. (Eds.), Pre-Proceedings of DNA8 Conference, Hokkaido University, Japan, June 2002a, pp. 171-183], are considered here. Different kinds of parallelism methods are defined for string rewriting. The notion of deadlock is then introduced to describe situations where rules with mixed target indications are simultaneously applied to a common string. The generative power of parallel P systems with deadlock is analyzed, with respect to Lindenmayer systems, and some relations among different types of parallel P systems with or without deadlock, allowing to rewrite all occurrences of a single symbol, or all the symbols applying either any of the rules or only those belonging to a specific set (table) of rules are studied. Some open problems are also formulated.

Algorithms↗