PINTA: a web server for network-based gene prioritization from expression data

PINTA (available at http://www.esat.kuleuven.be/pinta/; this web site is free and open to all users and there is no login requirement) is a web resource for the prioritization of candidate genes based on the differential expression of their neighborhood in a genome-wide protein–protein interaction network. Our strategy is meant for biological and medical researchers aiming at identifying novel disease genes using disease specific expression data. PINTA supports both candidate gene prioritization (starting from a user defined set of candidate genes) as well as genome-wide gene prioritization and is available for five species (human, mouse, rat, worm and yeast). As input data, PINTA only requires disease specific expression data, whereas various platforms (e.g. Affymetrix) are supported. As a result, PINTA computes a gene ranking and presents the results as a table that can easily be browsed and downloaded by the user

Identifying hypothetical genetic influences on complex disease phenotypes

<p>Abstract</p> <p>Background</p> <p>Statistical interactions between disease-associated loci of complex genetic diseases suggest that genes from these regions are involved in a common mechanism impacting, or impacted by, the disease. The computational problem we address is to discover relationships among genes from these interacting regions that may explain the observed statistical interaction and the role of these genes in the disease phenotype.</p> <p>Results</p> <p>We describe a heuristic algorithm for generating hypothetical gene relationships from loci associated with a complex disease phenotype. This approach, called Prioritizing Disease Genes by Analysis of Common Elements (PDG-ACE), mines biomedical keywords from text descriptions of genes and uses them to relate genes close to disease-associated loci. A keyword common to, and significantly over-represented in, a pair of gene descriptions may represent a preliminary hypothesis about the biological relationship between the genes, and suggest the role the genes play in the disease phenotype.</p> <p>Conclusion</p> <p>Our experimentation shows that the approach finds previously published relationships, while failing to find relationships that don't exist. The results also indicate that the approach is robust to differences in keyword vocabulary. We outline a brief case study in which results from a recently published Type 2 Diabetes association study are used to identify potential hypotheses.</p

Emergence of contact injuries in invasion team sports : an ecological dynamics rationale

The incidence of contact injuries in team sports is considerable, and injury mechanisms need to be comprehensively understood to facilitate the adoption of preventive measures. In Association Football, evidence shows that the highest prevalence of contact injuries emerges in one-on-one interactions. However, previous studies have tended to operationally report injury mechanisms in isolation, failing to provide a theoretical rationale to explain how injuries might emerge from interactions between opposing players. In this position paper, we propose an ecological dynamics framework to enhance current understanding of behavioural processes leading to contact injuries in team sports. Based on previous research highlighting the dynamics of performer–environment interactions, contact injuries are proposed to emerge from symmetry-breaking processes during on-field interpersonal interactions among competing players and the ball. Central to this approach is consideration of candidate control parameters that may provide insights on the information sources used by players to reduce risk of contact injuries during performance. Clinically, an ecological dynamics analysis could allow sport practitioners to design training sessions based on selected parameter threshold values as primary and/or secondary preventing measures during training and rehabilitation sessions

Predicting volleyball serve-reception at group level

In a group-serve-reception task, how does serve-reception become effective? We addressed "who" receives/passes the ball, what task-related variables predict action mode selection and whether the action mode selected was associated with reception efficacy. In 182 serve-receptions we tracked the ball and the receivers' heads with two video-cameras to generate 3D world-coordinates reconstructions. We defined receivers' reception-areas based on Voronoi diagrams (VD). Our analyses of the data showed that this approach was accurate in describing "who" receives the serve in 95.05% of the times. To predict action mode selection, we used variables related to: serve kinematics, receiver's movement and on-court positioning, the relation between receiver and his closest partner, and interactions between receiver-ball and receiver-target. Serve's higher initial velocities together with higher maximum height, as well as smaller longitudinal distances between receiver and target increased the chances for the use of the overhand pass. Conversely, decreasing alignment of the receiver with the ball and the target increased the chances of using the underhand-lateral pass. Finally, the use of the underhand-lateral pass was associated with lower quality receptions. Behavioural variability's relevance for serve-reception training is discussed

Numerical relations and skill level constrain co-adaptive behaviors of agents in sports teams

Similar to other complex systems in nature (e.g., a hunting pack, flocks of birds), sports teams have been modeled as social neurobiological systems in which interpersonal coordination tendencies of agents underpin team swarming behaviors. Swarming is seen as the result of agent co-adaptation to ecological constraints of performance environments by collectively perceiving specific possibilities for action (affordances for self and shared affordances). A major principle of invasion team sports assumed to promote effective performance is to outnumber the opposition (creation of numerical overloads) during different performance phases (attack and defense) in spatial regions adjacent to the ball. Such performance principles are assimilated by system agents through manipulation of numerical relations between teams during training in order to create artificially asymmetrical performance contexts to simulate overloaded and underloaded situations. Here we evaluated effects of different numerical relations differentiated by agent skill level, examining emergent inter-individual, intra- and inter-team coordination. Groups of association football players (national - NLP and regional-level - RLP) participated in small-sided and conditioned games in which numerical relations between system agents were manipulated (5v5, 5v4 and 5v3). Typical grouping tendencies in sports teams (major ranges, stretch indices, distances of team centers to goals and distances between the teams' opposing line-forces in specific team sectors) were recorded by plotting positional coordinates of individual agents through continuous GPS tracking. Results showed that creation of numerical asymmetries during training constrained agents' individual dominant regions, the underloaded teams' compactness and each team's relative position on-field, as well as distances between specific team sectors. We also observed how skill level impacted individual and team coordination tendencies. Data revealed emergence of co-adaptive behaviors between interacting neurobiological social system agents in the context of sport performance. Such observations have broader implications for training design involving manipulations of numerical relations between interacting members of social collectives

Neurobiological degeneracy and affordance perception support functional intra-individual variability of inter-limb coordination during ice climbing

This study investigated the functional intra-individual movement variability of ice climbers differing in skill level to understand how icefall properties were used by participants as affordances to adapt inter-limb coordination patterns during performance. Seven expert climbers and seven beginners were observed as they climbed a 30 m icefall. Movement and positioning of the left and right hand ice tools, crampons and the climber's pelvis over the first 20 m of the climb were recorded and digitized using video footage from a camera (25 Hz) located perpendicular to the plane of the icefall. Inter-limb coordination, frequency and types of action and vertical axis pelvis displacement exhibited by each climber were analysed for the first five minutes of ascent. Participant perception of climbing affordances was assessed through: (i) calculating the ratio between exploratory movements and performed actions, and (ii), identifying, by self-confrontation interviews, the perceptual variables of environmental properties, which were significant to climbers for their actions. Data revealed that experts used a wider range of upper and lower limb coordination patterns, resulting in the emergence of different types of action and fewer exploratory movements, suggesting that effective holes in the icefall provided affordances to regulate performance. In contrast, beginners displayed lower levels of functional intra-individual variability of motor organization, due to repetitive swinging of ice tools and kicking of crampons to achieve and maintain a deep anchorage, suggesting lack of perceptual attunement and calibration to environmental properties to support climbing performanc

Understanding Action and Adventure Sports Participation-An Ecological Dynamics Perspective.

Previous research has considered action and adventure sports using a variety of associated terms and definitions which has led to confusing discourse and contradictory research findings. Traditional narratives have typically considered participation exclusively as the pastime of young people with abnormal characteristics or personalities having unhealthy and pathological tendencies to take risks because of the need for thrill, excitement or an adrenaline 'rush'. Conversely, recent research has linked even the most extreme forms of action and adventure sports to positive physical and psychological health and well-being outcomes. Here, we argue that traditional frameworks have led to definitions, which, as currently used by researchers, ignore key elements constituting the essential merit of these sports. In this paper, we suggest that this lack of conceptual clarity in understanding cognitions, perception and action in action and adventure sports requires a comprehensive explanatory framework, ecological dynamics which considers person-environment interactions from a multidisciplinary perspective. Action and adventure sports can be fundamentally conceptualized as activities which flourish through creative exploration of novel movement experiences, continuously expanding and evolving beyond predetermined environmental, physical, psychological or sociocultural boundaries. The outcome is the emergence of a rich variety of participation styles and philosophical differences within and across activities. The purpose of this paper is twofold: (a) to point out some limitations of existing research on action and adventure sports; (b) based on key ideas from emerging research and an ecological dynamics approach, to propose a holistic multidisciplinary model for defining and understanding action and adventure sports that may better guide future research and practical implications

Literature Mining for the Discovery of Hidden Connections between Drugs, Genes and Diseases

The scientific literature represents a rich source for retrieval of knowledge on associations between biomedical concepts such as genes, diseases and cellular processes. A commonly used method to establish relationships between biomedical concepts from literature is co-occurrence. Apart from its use in knowledge retrieval, the co-occurrence method is also well-suited to discover new, hidden relationships between biomedical concepts following a simple ABC-principle, in which A and C have no direct relationship, but are connected via shared B-intermediates. In this paper we describe CoPub Discovery, a tool that mines the literature for new relationships between biomedical concepts. Statistical analysis using ROC curves showed that CoPub Discovery performed well over a wide range of settings and keyword thesauri. We subsequently used CoPub Discovery to search for new relationships between genes, drugs, pathways and diseases. Several of the newly found relationships were validated using independent literature sources. In addition, new predicted relationships between compounds and cell proliferation were validated and confirmed experimentally in an in vitro cell proliferation assay. The results show that CoPub Discovery is able to identify novel associations between genes, drugs, pathways and diseases that have a high probability of being biologically valid. This makes CoPub Discovery a useful tool to unravel the mechanisms behind disease, to find novel drug targets, or to find novel applications for existing drugs

Explicitly searching for useful inventions: dynamic relatedness and the costs of connecting versus synthesizing

Inventions combine technological features. When features are barely related, burdensomely broad knowledge is required to identify the situations that they share. When features are overly related, burdensomely broad knowledge is required to identify the situations that distinguish them. Thus, according to my first hypothesis, when features are moderately related, the costs of connecting and costs of synthesizing are cumulatively minimized, and the most useful inventions emerge. I also hypothesize that continued experimentation with a specific set of features is likely to lead to the discovery of decreasingly useful inventions; the earlier-identified connections reflect the more common consumer situations. Covering data from all industries, the empirical analysis provides broad support for the first hypothesis. Regressions to test the second hypothesis are inconclusive when examining industry types individually. Yet, this study represents an exploratory investigation, and future research should test refined hypotheses with more sophisticated data, such as that found in literature-based discovery research

Integrated Bio-Entity Network: A System for Biological Knowledge Discovery

A significant part of our biological knowledge is centered on relationships between biological entities (bio-entities) such as proteins, genes, small molecules, pathways, gene ontology (GO) terms and diseases. Accumulated at an increasing speed, the information on bio-entity relationships is archived in different forms at scattered places. Most of such information is buried in scientific literature as unstructured text. Organizing heterogeneous information in a structured form not only facilitates study of biological systems using integrative approaches, but also allows discovery of new knowledge in an automatic and systematic way. In this study, we performed a large scale integration of bio-entity relationship information from both databases containing manually annotated, structured information and automatic information extraction of unstructured text in scientific literature. The relationship information we integrated in this study includes protein–protein interactions, protein/gene regulations, protein–small molecule interactions, protein–GO relationships, protein–pathway relationships, and pathway–disease relationships. The relationship information is organized in a graph data structure, named integrated bio-entity network (IBN), where the vertices are the bio-entities and edges represent their relationships. Under this framework, graph theoretic algorithms can be designed to perform various knowledge discovery tasks. We designed breadth-first search with pruning (BFSP) and most probable path (MPP) algorithms to automatically generate hypotheses—the indirect relationships with high probabilities in the network. We show that IBN can be used to generate plausible hypotheses, which not only help to better understand the complex interactions in biological systems, but also provide guidance for experimental designs