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Dive into the research topics where Luciano Milanesi is active.

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Featured researches published by Luciano Milanesi.


Journal of Molecular Evolution | 1997

Analysis of donor splice sites in different eukaryotic organisms

Igor B. Rogozin; Luciano Milanesi

We present here a new algorithm for functional site analysis. It is based on four main assumptions: each variation of nucleotide composition makes a different contribution to the overall binding free energy of interaction between a functional site and another molecule; nonfunctioning site-like regions (pseudosites) are absent or rare in genomes; there may be errors in the sample of sites; and nucleotides of different site positions are considered to be mutually dependent. In this algorithm, the site set is divided into subsets, each described by a certain consensus. Donor splice sites of the human protein-coding genes were analyzed. Comparing the results with other methods of donor splice site prediction has demonstrated a more accurate prediction of consensus sequences AG/GU(A,G), G/GUnAG, /GU(A,G)AG, /GU(A,G)nGU, and G/GUA than is achieved by weight matrix and consensus (A,C)AG/GU(A,G)AGU with mismatches. The probability of the first type error, El, for the obtained consensus set was about 0.05, and the probability of the second type error, E2, was 0.15. The analysis demonstrated that accuracy of the functional site prediction could be improved if one takes into account correlations between the site positions. The accuracy of prediction by using human consensus sequences was tested on sequences from different organisms. Some differences in consensus sequences for the plant Arabidopsis sp., the invertebrate Caenorhabditis sp., and the fungus Aspergillus sp. were revealed. For the yeast Saccharomyces sp. only one conservative consensus, /GUA(U,A,C)G(U,A,C), was revealed (El = 0.03, E2 = 0.03). Yeast is a very interesting model to use for analysis of molecular mechanisms of splicing.


European Neuropsychopharmacology | 2013

Blood microRNA changes in depressed patients during antidepressant treatment

Luisella Bocchio-Chiavetto; Elisabetta Maffioletti; Paola Bettinsoli; Caterina Giovannini; Stefano Bignotti; Daniela Tardito; Dario Corrada; Luciano Milanesi; Massimo Gennarelli

MicroRNAs (miRNAs) are potent modulators of protein expression that play key roles in brain pathways regulating neurogenesis and synaptic plasticity. These small RNAs may be critical for the pathophysiology of mental disorders and may influence the effectiveness of psychotropic drugs. To investigate the possible involvement of miRNAs in the mechanism of action of antidepressants (AD), we conducted a whole-miRNome quantitative analysis with qRT-PCR of the changes in the blood of 10 depressed subjects after 12 weeks of treatment with escitalopram. Thirty miRNAs were differentially expressed after the AD treatment: 28 miRNAs were up-regulated, and 2 miRNAs were strongly down-regulated. miRNA target gene prediction and functional annotation analysis showed that there was a significant enrichment in several pathways associated with neuronal brain function (such as neuroactive ligand-receptor interaction, axon guidance, long-term potentiation and depression), supporting the hypothesis that the differentially regulated miRNAs may be involved in the AD mechanism.


BMC Systems Biology | 2010

A multilevel data integration resource for breast cancer study

Ettore Mosca; Roberta Alfieri; Ivan Merelli; Federica Viti; Andrea Calabria; Luciano Milanesi

BackgroundBreast cancer is one of the most common cancer types. Due to the complexity of this disease, it is important to face its study with an integrated and multilevel approach, from genes, transcripts and proteins to molecular networks, cell populations and tissues. According to the systems biology perspective, the biological functions arise from complex networks: in this context, concepts like molecular pathways, protein-protein interactions (PPIs), mathematical models and ontologies play an important role for dissecting such complexity.ResultsIn this work we present the Genes-to-Systems Breast Cancer (G2SBC) Database, a resource which integrates data about genes, transcripts and proteins reported in literature as altered in breast cancer cells. Beside the data integration, we provide an ontology based query system and analysis tools related to intracellular pathways, PPIs, protein structure and systems modelling, in order to facilitate the study of breast cancer using a multilevel perspective. The resource is available at the URL http://www.itb.cnr.it/breastcancer.ConclusionsThe G2SBC Database represents a systems biology oriented data integration approach devoted to breast cancer. By means of the analysis capabilities provided by the web interface, it is possible to overcome the limits of reductionist resources, enabling predictions that can lead to new experiments.


BMC Bioinformatics | 2005

Systematic analysis of human kinase genes: a large number of genes and alternative splicing events result in functional and structural diversity.

Luciano Milanesi; Mauro Petrillo; Leandra Sepe; Angelo Boccia; Nunzio D'Agostino; Myriam Passamano; Salvatore Di Nardo; Gianluca Tasco; Rita Casadio; Giovanni Paolella

BackgroundProtein kinases are a well defined family of proteins, characterized by the presence of a common kinase catalytic domain and playing a significant role in many important cellular processes, such as proliferation, maintenance of cell shape, apoptosys. In many members of the family, additional non-kinase domains contribute further specialization, resulting in subcellular localization, protein binding and regulation of activity, among others. About 500 genes encode members of the kinase family in the human genome, and although many of them represent well known genes, a larger number of genes code for proteins of more recent identification, or for unknown proteins identified as kinase only after computational studies.ResultsA systematic in silico study performed on the human genome, led to the identification of 5 genes, on chromosome 1, 11, 13, 15 and 16 respectively, and 1 pseudogene on chromosome X; some of these genes are reported as kinases from NCBI but are absent in other databases, such as KinBase. Comparative analysis of 483 gene regions and subsequent computational analysis, aimed at identifying unannotated exons, indicates that a large number of kinase may code for alternately spliced forms or be incorrectly annotated. An InterProScan automated analysis was perfomed to study domain distribution and combination in the various families. At the same time, other structural features were also added to the annotation process, including the putative presence of transmembrane alpha helices, and the cystein propensity to participate into a disulfide bridge.ConclusionThe predicted human kinome was extended by identifiying both additional genes and potential splice variants, resulting in a varied panorama where functionality may be searched at the gene and protein level. Structural analysis of kinase proteins domains as defined in multiple sources together with transmembrane alpha helices and signal peptide prediction provides hints to function assignment. The results of the human kinome analysis are collected in the KinWeb database, available for browsing and searching over the internet, where all results from the comparative analysis and the gene structure annotation are made available, alongside the domain information. Kinases may be searched by domain combinations and the relative genes may be viewed in a graphic browser at various level of magnification up to gene organization on the full chromosome set.


BMC Bioinformatics | 2016

Methods for the integration of multi-omics data: mathematical aspects.

Matteo Bersanelli; Ettore Mosca; Daniel Remondini; Enrico Giampieri; Claudia Sala; Gastone Castellani; Luciano Milanesi

BackgroundMethods for the integrative analysis of multi-omics data are required to draw a more complete and accurate picture of the dynamics of molecular systems. The complexity of biological systems, the technological limits, the large number of biological variables and the relatively low number of biological samples make the analysis of multi-omics datasets a non-trivial problem.Results and ConclusionsWe review the most advanced strategies for integrating multi-omics datasets, focusing on mathematical and methodological aspects.


Rejuvenation Research | 2011

Association Study on Long-Living Individuals from Southern Italy Identifies rs10491334 in the CAMKIV Gene That Regulates Survival Proteins.

Alberto Malovini; Maddalena Illario; Guido Iaccarino; Francesco Villa; Anna Ferrario; Roberta Roncarati; Chiara Viviani Anselmi; Valeria Novelli; Erminia Cipolletta; Elena Leggiero; Alessandro Orro; Maria Rosaria Rusciano; Luciano Milanesi; Antonella Maione; Gianluigi Condorelli; Riccardo Bellazzi; Annibale Alessandro Puca

Long-living individuals (LLIs) are used to study exceptional longevity. A number of genetic variants have been found associated in LLIs to date, but further identification of variants would improve knowledge on the mechanisms regulating the rate of aging. Therefore, we performed a genome-wide association study on 410 LLIs and 553 young control individuals with a 317K single-nucleotide polymorphism (SNP) chip to identify novel traits associated with aging. Among the top (p < 1 × 10(-4)) SNPs initially identified, we found rs10491334 (CAMKIV) (odds ratio [OR] = 0.55; 95% confidence interval [CI] 0.42-0.73; p = 2.88 × 10(-5)), a variant previously reported associated with diastolic blood pressure, associated also in a replication set of 116 LLIs and 160 controls (OR = 0.54; 95% CI 0.32-0.90; p = 9 × 10(-3)). Furthermore, in vitro analysis established that calcium/calmodulin-dependent protein kinase IV (CAMKIV) activates the survival proteins AKT, SIRT1, and FOXO3A, and we found that homozygous carriers of rs10491334 have a significant reduction in CAMKIV expression. This, together with the observed reduction in minor-allele carriers among centenarians, points to a detrimental role for the SNP. In conclusion, prolongevity genes are activated by CAMKIV, the levels of which are influenced by rs10491334, a SNP associated with human longevity.


IEEE Transactions on Nanobioscience | 2006

Grid-Enabled High-Throughput In Silico Screening Against Influenza A Neuraminidase

Jean Salzemann; Nicolas Jacq; Hsin-Yen Chen; Li-Yung Ho; Ivan Merelli; Luciano Milanesi; Vincent Breton; S. C. Lin; Ying-Ta Wu

Encouraged by the success of the first EGEE biomedical data challenge against malaria (WISDOM) , the second data challenge battling avian flu was kicked off in April 2006 to identify new drugs for the potential variants of the influenza A virus. Mobilizing thousands of CPUs on the Grid, the six-week-long high-throughput screening activity has fulfilled over 100 CPU years of computing power and produced around 600 gigabytes of results on the Grid for further biological analysis and testing. In the paper, we demonstrate the impact of a worldwide Grid infrastructure to efficiently deploy large-scale virtual screening to speed up the drug design process. Lessons learned through the data challenge activity are also discussed


Nephrology Dialysis Transplantation | 2010

Calcium kidney stones are associated with a haplotype of the Calcium-sensing receptor gene regulatory region

Giuseppe Vezzoli; Annalisa Terranegra; Teresa Arcidiacono; Giovanni Gambaro; Luciano Milanesi; Ettore Mosca; Laura Soldati

BACKGROUND Calcium-sensing receptor gene (CaSR) is a candidate to explain susceptibility to calcium kidney stones. Thus, we studied CaSR gene single-nucleotide polymorphisms (SNPs) and haplotypes associated with stones. METHODS Four hundred and sixty-three calcium stone formers and 213 healthy controls were genotyped for 21 SNPs mapping the whole CaSR gene. CaSR gene structure was studied. SNPs and haplotypes were analysed for association with stones. RESULTS Three haplotype blocks were identified in the CaSR gene. The first block was characterized by six SNPs and included gene promoters. The rs7652589 and rs1501899 SNPs and the CATTCA haplotype of the first block were significantly more frequent in normocitraturic calcium kidney stone formers than controls. The risk of stones was increased in normocitraturic homozygous patients and heterozygotes for the CATTCA haplotype. The rate of stones was higher in stone formers with the CATTCA haplotype. In a three-generation family, calcium stones were associated with the CATTCA haplotype. The bioinformatic analysis identified a new site for the octamer-binding transcription factor 1 in the presence of the variant alleles at the rs7652589 and rs1501899 SNPs. This transcription factor may downregulate the transcription of vitamin D-dependent genes and the CaSR expression. Conclusion. SNPs and CATTCA haplotype of the CaSR gene first block is associated with kidney stones in normocitraturic patients.


BMC Bioinformatics | 2005

ESTree db: a Tool for Peach Functional Genomics

Barbara Lazzari; Andrea Caprera; Alberto Vecchietti; Alessandra Stella; Luciano Milanesi; Carlo Pozzi

BackgroundThe ESTree db http://www.itb.cnr.it/estree/ represents a collection of Prunus persica expressed sequenced tags (ESTs) and is intended as a resource for peach functional genomics. A total of 6,155 successful EST sequences were obtained from four in-house prepared cDNA libraries from Prunus persica mesocarps at different developmental stages. Another 12,475 peach EST sequences were downloaded from public databases and added to the ESTree db. An automated pipeline was prepared to process EST sequences using public software integrated by in-house developed Perl scripts and data were collected in a MySQL database. A php-based web interface was developed to query the database.ResultsThe ESTree db version as of April 2005 encompasses 18,630 sequences representing eight libraries. Contig assembly was performed with CAP3. Putative single nucleotide polymorphism (SNP) detection was performed with the AutoSNP program and a search engine was implemented to retrieve results. All the sequences and all the contig consensus sequences were annotated both with blastx against the GenBank nr db and with GOblet against the viridiplantae section of the Gene Ontology db. Links to NiceZyme (Expasy) and to the KEGG metabolic pathways were provided. A local BLAST utility is available. A text search utility allows querying and browsing the database. Statistics were provided on Gene Ontology occurrences to assign sequences to Gene Ontology categories.ConclusionThe resulting database is a comprehensive resource of data and links related to peach EST sequences. The Sequence Report and Contig Report pages work as the web interface core structures, giving quick access to data related to each sequence/contig.


PLOS Computational Biology | 2012

Molecular mechanism of allosteric communication in Hsp70 revealed by molecular dynamics simulations.

Federica Chiappori; Ivan Merelli; Giorgio Colombo; Luciano Milanesi; Giulia Morra

Investigating ligand-regulated allosteric coupling between protein domains is fundamental to understand cell-life regulation. The Hsp70 family of chaperones represents an example of proteins in which ATP binding and hydrolysis at the Nucleotide Binding Domain (NBD) modulate substrate recognition at the Substrate Binding Domain (SBD). Herein, a comparative analysis of an allosteric (Hsp70-DnaK) and a non-allosteric structural homolog (Hsp110-Sse1) of the Hsp70 family is carried out through molecular dynamics simulations, starting from different conformations and ligand-states. Analysis of ligand-dependent modulation of internal fluctuations and local deformation patterns highlights the structural and dynamical changes occurring at residue level upon ATP-ADP exchange, which are connected to the conformational transition between closed and open structures. By identifying the dynamically responsive protein regions and specific cross-domain hydrogen-bonding patterns that differentiate Hsp70 from Hsp110 as a function of the nucleotide, we propose a molecular mechanism for the allosteric signal propagation of the ATP-encoded conformational signal.

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Ivan Merelli

National Research Council

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Ettore Mosca

National Research Council

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Alessandro Orro

National Research Council

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Federica Viti

National Research Council

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Andrea Clematis

National Research Council

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Roberta Alfieri

National Research Council

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