Customised fragments libraries for protein structure prediction based on structural class annotations

Since our methodology produces models the quality of which is up to 7% higher in average than those generated by a standard fragment-based predictor, we believe it should be considered before conducting any fragment-based protein structure prediction. Despite such progress, ab initio prediction remains a challenging task, especially for proteins of average and large sizes. Apart from improving search strategies and energy functions, integration of additional constraints seems a promising route, especially if they can be accurately predicted from sequence alone

Profile hidden Markov models for foreground object modelling

Accurate background/foreground segmentation is a preliminary process essential to most visual surveillance applications. With the increasing use of freely moving cameras, strategies have been proposed to refine initial segmentation. In this paper, it is proposed to exploit the Vide-omics paradigm, and Profile Hidden Markov Models in particular, to create a new type of object descriptors relying on spatiotemporal information. Performance of the proposed methodology has been evaluated using a standard dataset of videos captured by moving cameras. Results show that usage of the proposed object descriptors allows better foreground extraction than standard approaches

Probabilistic grammatical model of protein language and its application to helix-helix contact site classification

BACKGROUND: Hidden Markov Models power many state‐of‐the‐art tools in the field of protein bioinformatics. While excelling in their tasks, these methods of protein analysis do not convey directly information on medium‐ and long‐range residue‐residue interactions. This requires an expressive power of at least context‐free grammars. However, application of more powerful grammar formalisms to protein analysis has been surprisingly limited. RESULTS: In this work, we present a probabilistic grammatical framework for problem‐specific protein languages and apply it to classification of transmembrane helix‐helix pairs configurations. The core of the model consists of a probabilistic context‐free grammar, automatically inferred by a genetic algorithm from only a generic set of expert‐based rules and positive training samples. The model was applied to produce sequence based descriptors of four classes of transmembrane helix‐helix contact site configurations. The highest performance of the classifiers reached AUCROC of 0.70. The analysis of grammar parse trees revealed the ability of representing structural features of helix‐helix contact sites. CONCLUSIONS: We demonstrated that our probabilistic context‐free framework for analysis of protein sequences outperforms the state of the art in the task of helix‐helix contact site classification. However, this is achieved without necessarily requiring modeling long range dependencies between interacting residues. A significant feature of our approach is that grammar rules and parse trees are human‐readable. Thus they could provide biologically meaningful information for molecular biologists

Study of the breathing pattern based on 4D data collected by a dynamic 3D body scanner

The 3D-MATIC Research Laboratory at the University of Glasgow is currently developing a dynamic 3D whole body scanner. The basic concept is to equip a studio space such that the "working volume" of the space is imaged from all directions using fixed stereo-pairs of TV cameras. The stereo-pair images, collected by the camera pairs at a frame rate of 25 Hz, are then processed using photogrammetric techniques to create a spatio-temporal 3D model of this space. Using these unique 4D data, it is now possible to study 3D shape deformations. We present some preliminary results of a study of the breathing pattern of a couple of subjects. This research investigates the accuracy of the data and how it compares with the measurement standards of the fashion industry. Finally we discuss the potential use of dynamic 3D scanners in the apparel industry