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Detecting genetic interactions without running an exhaustive search is a difficult problem. We present a new heuristic, multiSURF*, which can detect these interactions with high accuracy and in time linear in the number of genes. Our algorithm is an ...

Integrative systems biology approaches build, evaluate, and combine data from thousands of diverse experiments. These strategies rely on methods that effectively identify and summarize gene-gene relationships within individual experiments. For gene-...

Networks are commonly used to represent and analyze large and complex systems of interacting elements. We build a human phenotype network (HPN) of over 600 physical attributes, diseases, and behavioral traits; based on more than 6,000 genetic variants (...

Rarely occurring genetic variants are hypothesized to influence human diseases, but statistically associating these rare variants to disease is challenging due to a lack of statistical power in most feasibly sized datasets. Several statistical tests ...

Biomarker discovery using mass spectrometry (MS) data is very useful in disease detection and drug discovery. The process of biomarker discovery in MS data must start with feature selection as the number of features in MS data is extremely large (e.g. ...

The maintenance of sexual populations has been an ongoing issue for evolutionary biologists, largely due to the two-fold cost of sexual versus asexual reproduction. Many explanations have been proposed to explain the benefits of sex, including the role ...

The Multiobjective Artificial Bee Colony with Differential Evolution (MO-ABC/DE) is a new hybrid multiobjective evolutionary algorithm proposed for solving optimization problems. One important optimization problem in Bioinformatics is the Motif ...

The task of predicting protein functions using computational techniques is a major research area in the field of bioinformatics. Casting the task into a classification problem makes it challenging, since the classes (functions) to be predicted are ...

Isometric feature mapping (Isomap) has proven high potential for nonlinear dimensionality reduction in a wide range of application domains. Isomap finds low-dimensional data projections by preserving global geometrical properties, which are expressed in ...

Genome-wide association studies (GWAS) have become a powerful and affordable tool to study the genetic variations associated with common human diseases. However, only few of the loci found are associated with a moderate or large increase in disease risk ...

Stressis a major problem facing our world today and affects everyday lives providing motivation to develop an objective understanding of stress during typicalactivities. Physiological and physical response signals showing symptoms for stress can be used ...

The fast measurement of millions of sequence variations across the genome is possible with the current technology. As a result, a difficult challenge arise in bioinformatics: the identification of combinations of interacting DNA sequence variations ...

Recently, swarm intelligence algorithms have been applied successfully to a wide variety of optimization problems in Computational Biology. Phylogenetic inference represents one of the key research topics in this area. Throughout the years, controversy ...

In this paper authors perform a variability analysis of a Stochastic Petri Net (SPN) model of the Tissue Factor induced coagulation cascade, one of the most complex biochemical networks. This pathway has been widely analyzed in literature mostly with ...

Recently published evaluations of the topology and weight evolving artificial neural network algorithm Cartesian genetic programming evolved artificial neural networks (CGPANN) have suggested it as a potentially powerful tool for bioinformatics ...

Wetlands are artificial basins that exploit the capabilities of some species of plants to purify water from pollutants. The design process is currently long and laborious: such vegetated areas are inserted within the basin by trial and error, since ...

Peptides play a key role in the development of drug candidates and diagnostic interventions, respectively. The design of peptides is cost-intensive and difficult in general for several well-known reasons. Multi-objective evolutionary algorithms (MOEAs) ...

Multifactor Dimensionality Reduction (MDR) is a widely-used data-mining method for detecting and interpreting epistatic effects that do not display significant main effects. MDR produces a reduced-dimensionality representation of a dataset which ...

Gene regulatory networks arise in all living cells, allowing the control of gene expression patterns. The study of their circuitry has revealed that certain subgraphs of interactions or motifs appear at anomalously high frequencies. We investigate here ...