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In this paper, we study the Maximum Internal Spanning Tree Problem (MIST). Given an undirected simple graph G , the task for the Maximum Internal Spanning Tree problem is to find a spanning tree of G with maximum number of internal vertices. We present an approximation algorithm with performance ratio 4 3 , which improves upon the best known performance ratio 3 2. Our algorithm benefits from a new observation for bounding the number of internal vertices of a spanning tree. We can also give an example to show that the performance ratio 4 3 is actually tight for this algorithm. Finally, we show that MIST is Max-SNP-hard. [ABSTRACT FROM AUTHOR]

Abstract Background The ability to predict protein-protein binding sites has a wide range of applications, including signal transduction studies, de novo drug design, structure identification and comparison of functional sites. The interface in a complex involves two structurally matched protein subunits, and the binding sites can be predicted by identifying structural matches at protein surfaces. Results We propose a method which enumerates “all” the configurations (or poses) between two proteins (3D coordinates of the two subunits in a complex) and evaluates each configuration by the interaction between its components using the Atomic Contact Energy function. The enumeration is achieved efficiently by exploring a set of rigid transformations. Our approach incorporates a surface identification technique and a method for avoiding clashes of two subunits when computing rigid transformations. When the optimal transformations according to the Atomic Contact Energy function are identified, the corresponding binding sites are given as predictions. Our results show that this approach consistently performs better than other methods in binding site identification. Conclusions Our method achieved a success rate higher than other methods, with the prediction quality improved in terms of both accuracy and coverage. Moreover, our method is being able to predict the configurations of two binding proteins, where most of other methods predict only the binding sites. The software package is available at http://sites.google.com/site/guofeics/dobi for non-commercial use.

Translocation has been long learned as a basic operation to rearrange the structure of a genome. Translocation sorting asks to find a shortest sequence of translocations that transforms one genome into another, which has attracted attention of many scientists in algorithm design. Signed translocation sorting can be solved in polynomial time. Unsigned translocation sorting turns out to be NP-Hard and Max-SNP-Hard. The best known approximation algorithm by now for unsigned translocation sorting can achieve a performance ratio 1.408. In this paper, we propose a new approximation algorithm for unsigned translocation sorting which can achieve a asymptotic performance ratio 1.375. [ABSTRACT FROM AUTHOR]

Although plenty of structural variant detecting approaches for human genomes can be looked up in the literatures, little has been acknowledged on the effectiveness of those structural variant softwares for plant genomes. Moreover, it has been demonstrated frequent occurrences for those structural variant detecting softwares to find too many false structural variants. In this paper, we devote to detect deletions, insertions, and inversions, in total of three kinds of structural variants occurring in Hedou12 genome in contrast to Williams82 genome. To find more potential structural variants, we try to develop new principles to detect discordant and split read map sets supporting structural variants. Aiming to enhance the precision of structural variant detections, we propose two new sequencing characteristic based probability models, which use the sequencing parameters of Hedou12 genome as well as the parameters for Hedou12 paired-end reads to be aligned onto Williams82, to evaluate the probability for a potential structural variant to occur in. To remove the false members from those potential structural variants, we propose a set cover problem model to describe formally on which potential structural variants it should accept to achieve as high as possible a probability summation. This will achieve a solution with more credible structural variants, which can be verified by comparing with DELLY version 0.5.8 and LUMPY version 0.2.2.3. Our algorithm has been verified to be able to find deletions, insertions, and inversions in Hedou12 in contrast to Williams82 DELLY as well as LUMPY fails to find. [ABSTRACT FROM AUTHOR]

Research based on the gravity model has shown that non‐economic factors affect international trade, and recent studies have shown that people's perception affects economic exchange. In this study, we explore the effects of attitudes on bilateral trade. Using survey data from the Pew Research Center's Global Attitudes Projects for 68 countries from 2002 to 2015, we find that a more favourable attitude of a country towards another country will increase the former country's imports from the latter. The result is robust to an endogeneity check, to different measures of attitudes and to different estimation methods. However, heterogeneity is observed across different types of goods and countries. The result holds for trade in intermediate and consumer goods, but the effects are not statistically significant for capital goods. The effects are statistically significant for bilateral trade between different country groups, except for high‐income countries' imports from non‐high‐income countries. [ABSTRACT FROM AUTHOR]