Biological function is mediated and controlled to a large extent by interactions among proteins. The study of interactions about proteins has lead to the accumulation of a large amount of data, also referred to as protein-protein interaction (PPI) data. ...

Motions of the IgG structure are evaluated using normal mode analysis and a new time dependent form of the elastic network model, to detect hinges, the dominance of low frequency modes, and the most important internal motions. We also evaluate the ...

The first step in the development of any rationally designed or "immunome-derived" vaccine is the identification of a target organism and associated protein antigens. Once identified, candidate proteins may be evaluated for T cell epitope content. T ...

One useful application of pattern matching algorithms is identification of major histocompatability complex (MHC) ligands and T-cell epitopes. Peptides that bind to MHC molecules and interact with T cell receptors to stimulate the immune system are ...

Two major obstacles to the development of B-cell epitope prediction for peptide-based vaccine design are (1) the prevailing binary classification paradigm, which mandates the problematic dichotomization of continuous outcome variables, and (2) failure ...

In this work, we present a software application that runs as a plugin over the OptFlux Metabolic Engineering platform allowing the topological analysis of metabolic networks. The major aim of this tool is to allow the interconnection between phenotype ...

In this paper, we described our approach for selecting potential biomarkers based on gene co-expression network (GCN) analysis. We present an efficient GCN finding algorithm and applied it to search for predictive markers in glioblastoma using the TCGA ...

Understanding protein interactions is essential to gain insights into the biological processes at the whole cell level. The high-throughput experimental techniques for determining protein-protein interactions (PPI) are error prone and expensive with low ...

The problem of large scale computational drug screening is considered in this paper. A new concept of Mode-of-Action (MoA) network, or MoNet, is introduced to model the relationship of therapeutic effectiveness between different drugs. A new algorithm ...

Microarray gene expression data provide a unique information resource for learning biological networks using "reverse engineering" methods. However, there are a variety of cases in which we know which genes are involved in a given pathology of interest, ...

The computational identification of miRNA target sites in an mRNA transcript is a challenging problem. In this paper, we describe an integrative approach to efficiently predict the miRNA:mRNA interactions by data-mining of massive parallel sequencing ...

The integration of information across carefully selected species and experimental platforms is emerging as a powerful technique for selecting potential therapeutic targets for human diseases: this method enables a holistic view of the experimental ...

It is fundamental and essential to elucidate how cancer-related genes interact with each other. In this study, we build two undirected graphs: one is a graph consisting of edges only observed in tumor samples, and the other is a graph consisting of ...

We present a new and faster algorithm for predicting coevolving proteins from pairs of protein distance matrices that are free to differ in size and scale, based on the initial work in [3]. The new algorithm has a more effective pruning strategy for ...

More than two meters of DNA is organized inside a five micrometer nucleus of every human cell. This is accomplished by the wrapping of DNA around protein "spools" (histones) to form nucleosomes. Some DNA sequences are more likely to be organized into ...

Human lipoxygenases (LOX) play important roles in the biosynthesis of leukotrienes which contribute to inflammation in asthma and bronchitis. Specific inhibitors that can modulate the physiological and pathological effects of these potent signaling ...

Glycomics is a discipline of biology that deals with the structure and function of glycans (or carbohydrates). Analytical techniques such as mass spectrometry (MS) and nuclear magnetic resonance (NMR) are having a significant impact on the field of ...

MicroRNAs are a newly identified class of small regulatory RNAs that target more than 30% protein-coding genes. Elevating evidence shows that miRNA play a critical role in many biological and metabolic processes, including developmental timing, tissue ...

A number of models and algorithms have been proposed in the past for gene regulatory network (GRN) inference; however, none of them address the effects of the size of the time-series microarray expression data in terms of number of time-points. In this ...

Retroviruses are of great importance due to their associations with diseases and their significance in understanding the evolution of species. In this paper we study the problem of classifying unknown DNA sequence fragments as retroviruses, genes or non-...