Current Bioinformatics - Volume 8, Issue 3, 2013

Identifying protein complexes from protein-protein interact ion (PPI) networks is an important issue in proteomics and bioinformatics. And various computational methods have been developed to solve it. In this paper, an approach called Hierarchical Link Clustering and Core-Attachment (HLC-CA) was proposed to detect protein complexes by integrating an HLC algorithm and the immanent core-attachment structure in protein Read More

One of the fundamental aims of life science is to gain insights into the functioning of an organism at systems level. Generation and systematic storage of enormous biological data in the post genomic era has made systems level studies a reality. For studies involving systems level investigation, metabolic pathways data inferred from intricate interactions amongst genes/enzymes/proteins are best suited and are bei Read More

Protein modules detection from protein-protein interaction network is the hot topic in the biological information process. In this paper, we present a rank strategy for deriving protein complex, in which both subcellular information and topological information of the network are combined. First, we locate the clusters based on the competing methods from protein-protein interaction network as candidate clusters and rank these clust Read More

Glioblastoma multiforme (GBM: grade IV astrocytoma) is the most common but lethal form of brain cancer. The median survival time of GBM patients is only 15 months. Only a few predictive markers have been reported for prognosis and treatment. This study integrates gene expression and protein-protein interaction data to search for pathways that are differentially regulated between long-term and short-term survivors Read More

Innovative models for analyzing high-throughput biological data are becoming of great significance in the post genomic era. Correlation networks are rapidly becoming powerful models for representing various types of biological relationships especially in the case of extracting knowledge from gene expression data. Data analysis using of other popular networks models in biology have revealed that structures within a graph mo Read More

A number of representations of protein networks have been reported. Further, while the existence of multiple types of interactomes and relationships between proteins has been accepted and discussed extensively, the exploration of these concepts and hypotheses using machine learning frameworks for protein interaction prediction in a multi-class setting has not yet been extensively accomplished. Essentially, thi Read More

Recent advances in proteomic and transcriptomic technologies resulted in the accumulation of vast amount of high-throughput data that span multiple biological processes and characteristics in different organisms. Much of the data come in the form of interaction networks and mRNA expression arrays. An important task in systems biology is functional modules discovery where the goal is to uncover well-connected sub Read More

Recent technical advances in identifying protein-protein interactions (PPIs) have generated the genomic-wide interaction data, collectively collectively referred to as the interactome. These interaction data give an insight into the underlying mechanisms of biological processes. However, the PPI data determined by experimental and computational methods include an extremely large number of false positives which are no Read More

Biological data about genes, proteins and biologically relevant molecules that are stored in databases may be associated to biological information (knowledge) such as experiments, properties and functions, response to drugs etc. Such knowledge is formally structured into ontologies that provide the best formalize to organize and store knowledge. In the biological field, Gene Ontology (GO) provides both a categorization of Read More

This paper investigates the use of computerized fractal analysis for objective characterization of the complexity of the epithelial-connective tissue interface in basal cell carcinoma and the ability of the technique to quantitatively discriminate among different diagnostic categories. Tumor boundaries were extracted by means of image analysis. The fractal dimension was calculated by using the box-counting method. The re Read More

Promoter region of a gene sequence of Eukaryotes is very important as it helps us to understand the mechanism of transcription regulation. The identification of this region is a complex problem as the signature for identification turns out to be fuzzy. Several in silico methods are available for identifying the promoter region, but the scope for new methods still exists. Reasonable prediction of promoter sequence (that can be te Read More

Identification of coding sequence from genomic DNA sequence is the major step in pursuit of gene identification. In the eukaryotic organism, gene structure consists of promoter, intron, start codon, exons and stop codon, etc. and to identify it, accurate labeling of the mentioned segments is necessary. Splice site is the ‘separation’ between exons and introns, the predicted accuracy of which is lower than 90% (in general) thou Read More

Essential proteins are necessary for the survival and development of organism. Many computational approaches have been proposed for predicting essential proteins based on protein-protein interaction (PPI) network. In this paper, we propose a new centrality algorithm for identifying essential proteins, named CSC algorithm. CSC algorithm integrates topology character of PPI network and in-degree of proteins in complexes. We Read More