Biomedical subjects

Sabino Liuni

Publications and source records attributed to Sabino Liuni.

13 recordsLinked to original sources

PubMed2006

Selection of relevant genes in cancer diagnosis based on their prediction accuracy.

MOTIVATIONS: One of the main problems in cancer diagnosis by using DNA microarray data is selecting genes relevant for the pathology by analyzing their expression profiles in tissues in two different phenotypical conditions. The question we pose is the following: how do we measure the relevance of a single gene in a given pathology? METHODS: A gene is relevant for a particular disease if we are able to correctly predict the occurrence of the pathology in new patients on the basis of its expression level only. In other words, a gene is informative for the disease if its expression levels are useful for training a classifier able to generalize, that is, able to correctly predict the status of new patients. In this paper we present a selection bias free, statistically well founded method for finding relevant genes on the basis of their classification ability. RESULTS: We applied the method on a colon cancer data set and produced a list of relevant genes, ranked on the basis of their prediction accuracy. We found, out of more than 6500 available genes, 54 overexpressed in normal tissues and 77 overexpressed in tumor tissues having prediction accuracy greater than 70% with p-value <or=0.05. CONCLUSIONS: The relevance of the selected genes was assessed (a) statistically, evaluating the p-value of the estimate prediction accuracy of each gene; (b) biologically, confirming the involvement of many genes in generic carcinogenic processes and in particular for the colon; (c) comparatively, verifying the presence of these genes in other studies on the same data-set.

Biomarkers, Tumor↗

PubMed2005

A new strategy to identify novel genes and gene isoforms: Analysis of human chromosomes 15, 21 and 22.

We present here a novel methodology for the identification of genome regions potentially spanning one or more protein coding genes. It is based on the detection of clusters of conserved sequence tags whose evolutionary dynamics, based on the observation of an excess bias of synonymous substitutions at nucleotide level and of conservative replacements at protein level, suggests a likely protein coding role. A benchmark test carried out on a 236 Mbp of human-mouse syntenic regions from human chromosomes 15, 21 and 22 identified 25 CST clusters potentially containing unannotated genes. A further annotation update of the human genome assembly revealed that 11/25 clusters actually contained a total of 20 validated genes and 10 of the remaining 14 clusters had several experimental evidence in support of the presence of protein coding genes. These findings demonstrate the effectiveness and high prediction reliability of the proposed methodology which could specifically be applied to the annotation of novel genome sequences.

Animals↗

PubMed2005

Regularized Least Squares Cancer classifiers from DNA microarray data.

BACKGROUND: The advent of the technology of DNA microarrays constitutes an epochal change in the classification and discovery of different types of cancer because the information provided by DNA microarrays allows an approach to the problem of cancer analysis from a quantitative rather than qualitative point of view. Cancer classification requires well founded mathematical methods which are able to predict the status of new specimens with high significance levels starting from a limited number of data. In this paper we assess the performances of Regularized Least Squares (RLS) classifiers, originally proposed in regularization theory, by comparing them with Support Vector Machines (SVM), the state-of-the-art supervised learning technique for cancer classification by DNA microarray data. The performances of both approaches have been also investigated with respect to the number of selected genes and different gene selection strategies. RESULTS: We show that RLS classifiers have performances comparable to those of SVM classifiers as the Leave-One-Out (LOO) error evaluated on three different data sets shows. The main advantage of RLS machines is that for solving a classification problem they use a linear system of order equal to either the number of features or the number of training examples. Moreover, RLS machines allow to get an exact measure of the LOO error with just one training. CONCLUSION: RLS classifiers are a valuable alternative to SVM classifiers for the problem of cancer classification by gene expression data, due to their simplicity and low computational complexity. Moreover, RLS classifiers show generalization ability comparable to the ones of SVM classifiers also in the case the classification of new specimens involves very few gene expression levels.

Algorithms↗

PubMed2005

GenoMiner: a tool for genome-wide search of coding and non-coding conserved sequence tags.

GenoMiner is a software tool that searches for regions of similarity between user-submitted genome or transcript sequences and user-specified whole genome assemblies. The program then identifies conserved sequence tags (CSTs) in these homologous regions and provides a prediction of their coding or non-coding nature. The analysis is carried out through three steps: (1) definition of sequence regions homologous to the query sequence in the selected target genomes by a fast BLAT alignment; (2) identification of CSTs by a more sensitive BLAST-like alignment between the query and the homologous regions in the target genomes and (3) assessment of the coding or non-coding nature of detected CSTs through the computation of a suitable coding potential score. GenoMiner allows the user to search the query sequence against a number of vertebrate genome assemblies in a single run providing a user-friendly graphical output.

Algorithms↗

PubMed2005

UTRdb and UTRsite: a collection of sequences and regulatory motifs of the untranslated regions of eukaryotic mRNAs.

The 5' and 3' untranslated regions of eukaryotic mRNAs play crucial roles in the post-transcriptional regulation of gene expression through the modulation of nucleo-cytoplasmic mRNA transport, translation efficiency, subcellular localization and message stability. UTRdb is a curated database of 5' and 3' untranslated sequences of eukaryotic mRNAs, derived from several sources of primary data. Experimentally validated functional motifs are annotated (and also collated as the UTRsite database) and cross-links to genomic and protein data are provided. The integration of UTRdb with genomic and protein data has allowed the implementation of a powerful retrieval resource for the selection and extraction of UTR subsets based on their genomic coordinates and/or features of the protein encoded by the relevant mRNA (e.g. GO term, PFAM domain, etc.). All internet resources implemented for retrieval and functional analysis of 5' and 3' untranslated regions of eukaryotic mRNAs are accessible at http://www.ba.itb.cnr.it/UTR/.

3' Untranslated Regions↗

PubMed2004

DNAfan: a software tool for automated extraction and analysis of user-defined sequence regions.

SUMMARY: DNAfan (DNA Feature ANalyzer) is a tool combining sequence-filtering and pattern searching. DNAfan automatically extracts user-defined sets of sequence fragments from large sequence sets. Fragments are defined by annotated gene feature keys and co- or non-occurring patterns within the feature or close to it. A gene feature parser and a pattern-based filter tool localizes and extracts the specific subset of sequences. The selected sequence data can subsequently be retrieved for analyses or further processed with DNAfan to find the occurrence of specific patterns or structural motifs. DNAfan is a powerful tool for pattern analysis. Its filter features restricts the pattern search to a well-defined set of sequences, allowing drastic reduction in false positive hits. AVAILABILITY: http://bighost.ba.itb.cnr.it:8080/Framework.

Algorithms↗

PubMed2004

CSTminer: a web tool for the identification of coding and noncoding conserved sequence tags through cross-species genome comparison.

The identification and characterization of genome tracts that are highly conserved across species during evolution may contribute significantly to the functional annotation of whole-genome sequences. Indeed, such sequences are likely to correspond to known or unknown coding exons or regulatory motifs. Here, we present a web server implementing a previously developed algorithm that, by comparing user-submitted genome sequences, is able to identify statistically significant conserved blocks and assess their coding or noncoding nature through the measure of a coding potential score. The web tool, available at http://www.caspur.it/CSTminer/, is dynamically interconnected with the Ensembl genome resources and produces a graphical output showing a map of detected conserved sequences and annotated gene features.

Animals↗

PubMed2003

Computational identification of protein coding potential of conserved sequence tags through cross-species evolutionary analysis.

The identification of conserved sequence tags (CSTs) through comparative genome analysis may reveal important regulatory elements involved in shaping the spatio-temporal expression of genetic information. It is well known that the most significant fraction of CSTs observed in human-mouse comparisons correspond to protein coding exons, due to their strong evolutionary constraints. As we still do not know the complete gene inventory of the human and mouse genomes it is of the utmost importance to establish if detected conserved sequences are genes or not. We propose here a simple algorithm that, based on the observation of the specific evolutionary dynamics of coding sequences, efficiently discriminates between coding and non-coding CSTs. The application of this method may help the validation of predicted genes, the prediction of alternative splicing patterns in known and unknown genes and the definition of a dictionary of non-coding regulatory elements.

Algorithms↗

PubMed2003

PatSearch: A program for the detection of patterns and structural motifs in nucleotide sequences.

Regulation of gene expression at transcriptional and post-transcriptional level involves the interaction between short DNA or RNA tracts and the corresponding trans-acting protein factors. Detection of such cis-acting elements in genome-wide screenings may significantly contribute to genome annotation and comparative analysis as well as to target functional characterization experiments. We present here PatSearch, a flexible and fast pattern matcher able to search for specific combinations of oligonucleotide consensus sequences, secondary structure elements and position-weight matrices. It can also allow for mismatches/mispairings below a user fixed threshold. We report three different applications of the program in the search of complex patterns such as those of the iron responsive element hairpin-loop structure, the p53 responsive element and a promoter module containing CAAT-, TATA- and cap-boxes. PatSearch is available on the web at http://bighost.area.ba.cnr.it/BIG/PatSearch/.

Base Sequence↗

PubMed2003

PLMItRNA, a database on the heterogeneous genetic origin of mitochondrial tRNA genes and tRNAs in photosynthetic eukaryotes.

The updated version of PLMItRNA reports information and multialignments on 609 genes and 34 tRNA molecules active in the mitochondria of Viridiplantae (27 Embryophyta and 10 Chlorophyta), and photosynthetic algae (one Cryptophyta, four Rhodophyta and two Stramenopiles). Colour-code based tables reporting the different genetic origin of identified genes allow hyper-textual link to single entries. Promoter sequences identified for tRNA genes in the mitochondrial genomes of Angiospermae are also reported. The PLMItRNA database is accessible at http://bighost.area.ba.cnr.it/PLMItRNA/.

Chlorophyta↗

PubMed2002

Untranslated regions of mRNAs.

Gene expression is finely regulated at the post-transcriptional level. Features of the untranslated regions of mRNAs that control their translation, degradation and localization include stem-loop structures, upstream initiation codons and open reading frames, internal ribosome entry sites and various cis-acting elements that are bound by RNA-binding proteins.

Animals↗

PubMed2002

MitoNuc: a database of nuclear genes coding for mitochondrial proteins. Update 2002.

Mitochondria, besides their central role in energy metabolism, have recently been found to be involved in a number of basic processes of cell life and to contribute to the pathogenesis of many degenerative diseases. All functions of mitochondria depend on the interaction of nuclear and organelle genomes. Mitochondrial genomes have been extensively sequenced and analysed and data have been collected in several specialised databases. In order to collect information on nuclear coded mitochondrial proteins we developed MitoNuc, a database containing detailed information on sequenced nuclear genes coding for mitochondrial proteins in Metazoa. The MitoNuc database can be retrieved through SRS and is available via the web site http://bighost.area.ba.cnr.it/mitochondriome where other mitochondrial databases developed by our group, the complete list of the sequenced mitochondrial genomes, links to other mitochondrial sites and related information, are available. The MitoAln database, related to MitoNuc in the previous release, reporting the multiple alignments of the relevant homologous protein coding regions, is no longer supported in the present release. In order to keep the links among entries in MitoNuc from homologous proteins, a new field in the database has been defined: the cluster identifier, an alpha numeric code used to identify each cluster of homologous proteins. A comment field derived from the corresponding SWISS-PROT entry has been introduced; this reports clinical data related to dysfunction of the protein. The logic scheme of MitoNuc database has been implemented in the ORACLE DBMS. This will allow the end-users to retrieve data through a friendly interface that will be soon implemented.

Animals↗

PubMed2002

UTRdb and UTRsite: specialized databases of sequences and functional elements of 5' and 3' untranslated regions of eukaryotic mRNAs. Update 2002.

The 5'- and 3'-untranslated regions (5'- and 3'-UTRs) of eukaryotic mRNAs are known to play a crucial role in post-transcriptional regulation of gene expression modulating nucleo-cytoplasmic mRNA transport, translation efficiency, subcellular localization and stability. UTRdb is a specialized database of 5' and 3' untranslated sequences of eukaryotic mRNAs cleaned from redundancy. UTRdb entries are enriched with specialized information not present in the primary databases including the presence of nucleotide sequence patterns already demonstrated by experimental analysis to have some functional role. All these patterns have been collected in the UTRsite database so that it is possible to search any input sequence for the presence of annotated functional motifs. Furthermore, UTRdb entries have been annotated for the presence of repetitive elements. All Internet resources we implemented for retrieval and functional analysis of 5'- and 3'-UTRs of eukaryotic mRNAs are accessible at http://bighost.area.ba.cnr.it/BIG/UTRHome/.

3' Untranslated Regions↗