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Capobianco E.,CRS4 Bioinformatics Laboratory
Journal of Computational Science | Year: 2011

Networks represent a main methodological instrument in systems biology applications. In particular, modularity is widely investigated in the attempt to elucidate the regulative and correlative nature of gene and protein associations, respectively. However, modular maps are only approximate representations due to two main factors. First, the resolution spectrum that has to be covered is wide and method-dependent. Second, the randomness underlying network dynamics and influencing them through fluctuations and system perturbations, is difficult to measure. We investigate both aspects by an application to the yeast protein interactome network, and suggest that a non-extensive characterization of entropy may play a role for elucidating both random and biological variation. © 2011 Elsevier B.V. Source


Capobianco E.,CRS4 Bioinformatics Laboratory
Mathematical Biosciences | Year: 2010

High-throughput microarray technologies measure the abundance of thousands of mRNA targets simultaneously. Due to the usual disparity between a few available samples (from limited conditions or time course points) and many gene expression values (entire genomes), a complex high-dimensional genomic system has to be analyzed, for instance by reverse engineering methods. The latter aim to reconstruct gene networks from experimentally observed expression changes caused by various kinds of perturbations. In particular, elucidating regulatory paths and assessing their reliability across replicates are central topics in this article. The reconstruction problem requires efficiency and accuracy from numerical optimization algorithms and statistical inference techniques. To this end, we focus on methods but also on the available experimental information produced in technical replicates. We propose a model-based approach based on a few steps. First, feature selection is performed by a projective method aimed to combine the gene measurements observed across replicates. Second, a quite heuristic sieving strategy is pursued to bypass the usual recourse to averaging. Third, the impact of dimensionality reduction on the biological system under study is evaluated. Evidence is obtained from the application of our approach to microarray time course experimental replicated data, and suggests that gene features, once identified, can be used for stabilization purposes relatively to the replicate variability. Both quantitative representation and qualitative assessment of the observed gene feature interference are reported in order to decipher specific gene regulatory map and the pathway-associated dynamics. © 2010 Elsevier Inc. Source


Floris M.,CRS4 Bioinformatics Laboratory | Masciocchi J.,University of Bordeaux Segalen | Fanton M.,University of Padua | Moro S.,University of Padua
Nucleic Acids Research | Year: 2011

pepMMsMIMIC is a novel web-oriented peptidomimetic compound virtual screening tool based on a multi-conformers three-dimensional (3D)-similarity search strategy. Key to the development of pepMMsMIMIC has been the creation of a library of 17 million conformers calculated from 3.9 million commercially available chemicals collected in the MMsINC® database. Using as input the 3D structure of a peptide bound to a protein, pepMMsMIMIC suggests which chemical structures are able to mimic the protein-protein recognition of this natural peptide using both pharmacophore and shape similarity techniques. We hope that the accessibility of pepMMsMIMIC (freely available at http://mms.dsfarm.unipd. it/pepMMsMIMIC) will encourage medicinal chemists to de-peptidize protein-protein recognition processes of biological interest, thus increasing the potential of in silico peptidomimetic compound screening of known small molecules to expedite drug development. © 2011 The Author(s). Source


Uva P.,CRS4 Bioinformatics Laboratory | Lahm A.,I.R.B.M. | Sbardellati A.,CRS4 Bioinformatics Laboratory | Grigoriadis A.,Kings College London | And 2 more authors.
PLoS ONE | Year: 2010

Despite the wide use of cell lines in cancer research, the extent to which their surface properties correspond to those of primary tumors is poorly characterized. The present study addresses this problem from a transcriptional standpoint, analyzing the expression of membrane protein genes - the Membranome - in primary tumors and immortalized in-vitro cultured tumor cells. 409 human samples, deriving from ten independent studies, were analyzed. These comprise normal tissues, primary tumors and tumor derived cell lines deriving from eight different tissues: brain, breast, colon, kidney, leukemia, lung, melanoma, and ovary. We demonstrated that the Membranome has greater power than the remainder of the transcriptome when used as input for the automatic classification of tumor samples. This feature is maintained in tumor derived cell lines. In most cases primary tumors show maximal similarity in Membranome expression with cell lines of same tissue origin. Differences in Membranome expression between tumors and cell lines were analyzed also at the pathway level and biological themes were identified that were differentially regulated in the two settings. Moreover, by including normal samples in the analysis, we quantified the degree to which cell lines retain the Membranome up- and down- regulations observed in primary tumors with respect to their normal counterparts. We showed that most of the Membranome up-regulations observed in primary tumors are lost in the in-vitro cultured cells. Conversely, the majority of Membranome genes down-regulated upon tumor transformation maintain lower expression levels also in the cell lines. This study points towards a central role of Membranome genes in the definition of the tumor phenotype. The comparative analysis of primary tumors and cell lines identifies the limits of cell lines as a model for the study of cancer-related processes mediated by the cell surface. Results presented allow for a more rational use of the cell lines as a model of cancer. © 2010 Uva et al. Source


Masotti A.,Bambino Gesu Childrens Hospital | Uva P.,CRS4 Bioinformatics Laboratory | Davis-Keppen L.,University of South Dakota | Basel-Vanagaite L.,Pediatric Genetics Unit | And 12 more authors.
American Journal of Human Genetics | Year: 2015

Keppen-Lubinsky syndrome (KPLBS) is a rare disease mainly characterized by severe developmental delay and intellectual disability, microcephaly, large prominent eyes, a narrow nasal bridge, a tented upper lip, a high palate, an open mouth, tightly adherent skin, an aged appearance, and severe generalized lipodystrophy. We sequenced the exomes of three unrelated individuals affected by KPLBS and found de novo heterozygous mutations in KCNJ6 (GIRK2), which encodes an inwardly rectifying potassium channel and maps to the Down syndrome critical region between DIRK1A and DSCR4. In particular, two individuals shared an in-frame heterozygous deletion of three nucleotides (c.455-457del) leading to the loss of one amino acid (p.Thr152del). The third individual was heterozygous for a missense mutation (c.460G>A) which introduces an amino acid change from glycine to serine (p.Gly154Ser). In agreement with animal models, the present data suggest that these mutations severely impair the correct functioning of this potassium channel. Overall, these results establish KPLBS as a channelopathy and suggest that KCNJ6 (GIRK2) could also be a candidate gene for other lipodystrophies. We hope that these results will prompt investigations in this unexplored class of inwardly rectifying K+ channels. © 2015 The American Society of Human Genetics. Source

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