TANGLE: Two-Level Support Vector Regression Approach for Protein Backbone Torsion Angle Prediction from Primary Sequences

Protein backbone torsion angles (Phi) and (Psi) involve two rotation angles rotating around the Cα-N bond (Phi) and the Cα-C bond (Psi). Due to the planarity of the linked rigid peptide bonds, these two angles can essentially determine the backbone geometry of proteins. Accordingly, the accurate prediction of protein backbone torsion angle from sequence information can assist the prediction of protein structures. In this study, we develop a new approach called TANGLE (Torsion ANGLE predictor) to predict the protein backbone torsion angles from amino acid sequences. TANGLE uses a two-level support vector regression approach to perform real-value torsion angle prediction using a variety of features derived from amino acid sequences, including the evolutionary profiles in the form of position-specific scoring matrices, predicted secondary structure, solvent accessibility and natively disordered region as well as other global sequence features. When evaluated based on a large benchmark dataset of 1,526 non-homologous proteins, the mean absolute errors (MAEs) of the Phi and Psi angle prediction are 27.8° and 44.6°, respectively, which are 1% and 3% respectively lower than that using one of the state-of-the-art prediction tools ANGLOR. Moreover, the prediction of TANGLE is significantly better than a random predictor that was built on the amino acid-specific basis, with the p-value<1.46e-147 and 7.97e-150, respectively by the Wilcoxon signed rank test. As a complementary approach to the current torsion angle prediction algorithms, TANGLE should prove useful in predicting protein structural properties and assisting protein fold recognition by applying the predicted torsion angles as useful restraints. TANGLE is freely accessible at http://sunflower.kuicr.kyoto-u.ac.jp/~sjn/TANGLE/

A framework for evolutionary systems biology

<p>Abstract</p> <p>Background</p> <p>Many difficult problems in evolutionary genomics are related to mutations that have weak effects on fitness, as the consequences of mutations with large effects are often simple to predict. Current systems biology has accumulated much data on mutations with large effects and can predict the properties of knockout mutants in some systems. However experimental methods are too insensitive to observe small effects.</p> <p>Results</p> <p>Here I propose a novel framework that brings together evolutionary theory and current systems biology approaches in order to quantify small effects of mutations and their epistatic interactions <it>in silico</it>. Central to this approach is the definition of fitness correlates that can be computed in some current systems biology models employing the rigorous algorithms that are at the core of much work in computational systems biology. The framework exploits synergies between the realism of such models and the need to understand real systems in evolutionary theory. This framework can address many longstanding topics in evolutionary biology by defining various 'levels' of the adaptive landscape. Addressed topics include the distribution of mutational effects on fitness, as well as the nature of advantageous mutations, epistasis and robustness. Combining corresponding parameter estimates with population genetics models raises the possibility of testing evolutionary hypotheses at a new level of realism.</p> <p>Conclusion</p> <p>EvoSysBio is expected to lead to a more detailed understanding of the fundamental principles of life by combining knowledge about well-known biological systems from several disciplines. This will benefit both evolutionary theory and current systems biology. Understanding robustness by analysing distributions of mutational effects and epistasis is pivotal for drug design, cancer research, responsible genetic engineering in synthetic biology and many other practical applications.</p

SMS counselling at a child helpline: counsellor strategies, children's stressors and well-being

Providing helpline services to children via texting (i.e. Short Message Service or SMS) is being used increasingly. However, little is known about the quality of SMS counselling and its effect on the service users. Through a quantitative content analysis of 448 SMS sessions at the Danish child helpline, we studied counsellor behaviour and session impact. We found higher levels of children’s well-being and empowerment after contacting the service. Multiple regression models showed that a positive impact of counselling was related to higher density of child-centred counsellor behaviour and moderate levels of problem-centred counsellor behaviour. These findings were consistent across most stressors with positive effects in the small-to-medium range. SMS counselling shows potential as a tool for counselling children and youth

Quality and safety of hospital discharge: a study on experiences and perceptions of patients, relatives and care providers

Item does not contain fulltextOBJECTIVE: To identify barriers experienced and perceived at discharge by physicians, nurses, patients and relatives. DESIGN: We developed questionnaires based on focus group interviews with hospital and community care providers, and individual interviews with patients and relatives. A survey was conducted among patients, relatives and related nurses and physicians from hospital and community care. SETTING: One university hospital and the related community care area in the Netherlands. PARTICIPANTS: Thirty health-care providers and eight patients and/or relatives participated in focus group and individual interviews. Questionnaires were returned by 344 health-care providers and 206 patients and relatives. RESULTS: Information from the hospital to community care is often incomplete, unclear and delayed. Especially hospital physicians (52%) and general practitioners (GPs; 63%) experience the quality of information exchanged from the hospital to the GP as poor. Coordination of care is often frustrated by a lack of care provider knowledge and collaboration. Hospital physicians (47%) and GPs (71%) feel that hospital physicians are often not sufficiently aware of the patient's home situation. Respectively, 59 and 81% experience that the GP is often not clearly informed about expected tasks and responsibilities at discharge. CONCLUSIONS: This is the first study that provides a clear picture of the experiences and perceptions of stakeholders regarding handovers at hospital discharge. Lack of knowledge, understanding and interest between hospital and community care providers are important causes for ineffective and unsafe discharge. The study suggests that improvement efforts should be focused more on these aspects, as primary conditions for improving hospital discharge