Search results for "INFORMATICS"

A technique to search functional similarities in PPI networks

2009

We describe a method to search for similarities across protein-protein interaction networks of different organisms. The technique core consists in computing a maximum weight matching of bipartite graphs resulting from comparing the neighbourhoods of proteins belonging to different networks. Both quantitative and reliability information are exploited. We tested the method on the networks of S. cerevisiae, D. melanogaster and C. elegans. The experiments showed that the technique is able to detect functional orthologs when the sole sequence similarity does not prove itself sufficient. They also demonstrated the capability of our approach in discovering common biological processes involving unc…

Bi-GRAPPIN: Bipartite graph based protein-protein interaction networks similarity search

2007

Discovering meaningful protein-protein interaction modules by a co-clustering based approach

2008

Asymmetric Global Alignment of Protein-Protein Interaction Graph Databases

2010

Discovering Protein Complexes in Protein Interaction Networks

2009

New Trends in Graph Mining

2010

Searching for repeated features characterizing biological data is fundamental in computational biology. When biological networks are under analysis, the presence of repeated modules across the same network (or several distinct ones) is shown to be very relevant. Indeed, several studies prove that biological networks can be often understood in terms of coalitions of basic repeated building blocks, often referred to as network motifs.This work provides a review of the main techniques proposed for motif extraction from biological networks. In particular, main intrinsic difficulties related to the problem are pointed out, along with solutions proposed in the literature to overcome them. Open ch…

Protein-protein interaction network querying by a "focus and zoom" approach

2008

We propose an approach to network querying in protein-protein interaction networks based on bipartite graph weighted matching. An algorithm is presented that first “focuses” the potentially relevant portion of the target graph by performing a global alignment of this one with the query graph, and then “zooms” on the actual matching nodes by considering their topological arrangement, hereby obtaining a (possibly) approximated occurrence of the query graph within the target graph. Approximation is related to node insertions, node deletions and edge deletions possibly intervening in the query graph. The technique manages networks of arbitrary topology. Moreover, edge labels are used to represe…

Preface to "Computational Approaches: Drug Discovery and Design in Medicinal Chemistry and Bioinformatics"

2021

Fast comparison of DNA sequences by oligonucleotide profiling

2008

Provisional abstact and full-text PDF files correspond to the article as it appeared upon acceptance. Fully formatted PDF and final abstract will be made available soon.

Sparse Manifold Clustering and Embedding to discriminate gene expression profiles of glioblastoma and meningioma tumors.

2013

Sparse Manifold Clustering and Embedding (SMCE) algorithm has been recently proposed for simultaneous clustering and dimensionality reduction of data on nonlinear manifolds using sparse representation techniques. In this work, SMCE algorithm is applied to the differential discrimination of Glioblastoma and Meningioma Tumors by means of their Gene Expression Profiles. Our purpose was to evaluate the robustness of this nonlinear manifold to classify gene expression profiles, characterized by the high-dimensionality of their representations and the low discrimination power of most of the genes. For this objective, we used SMCE to reduce the dimensionality of a preprocessed dataset of 35 single…