BackgroundRecent research has provided fascinating indications and evidence that the host health is linked to its microbial inhabitants. Due to the development of high-throughput sequencing technologies, more and more data covering microbial composition changes in different disease types are emerging. However, this information is dispersed over a wide variety of medical and biomedical disciplines.DescriptionDisbiome is a database which collects and presents published microbiota-disease information in a standardized way. The diseases are classified using the MedDRA classification system and the micro-organisms are linked to their NCBI and SILVA taxonomy. Finally, each study included in the Disbiome database is assessed for its reporting quality using a standardized questionnaire.ConclusionsDisbiome is the first database giving a clear, concise and up-to-date overview of microbial composition differences in diseases, together with the relevant information of the studies published. The strength of this database lies within the combination of the presence of references to other databases, which enables both specific and diverse search strategies within the Disbiome database, and the human annotation which ensures a simple and structured presentation of the available data.

a b s t r a c tEthnopharmacological relevance: N-Alkylamides (NAAs) are a promising group of bioactive compounds, which are anticipated to act as important lead compounds for plant protection and biocidal products, functional food, cosmeceuticals and drugs in the next decennia. These molecules, currently found in more than 25 plant families and with a wide structural diversity, exert a variety of biologicalpharmacological effects and are of high ethnopharmacological importance. However, information is scattered in literature, with different, often unstandardized, pharmacological methodologies being used. Therefore, a comprehensive NAA database (acronym: Alkamid) was constructed to collect the available structural and functional NAA data, linked to their occurrence in plants (family, tribe, species, genus). Materials and methods: For loading information in the database, literature data was gathered over the period 1950-2010, by using several search engines. In order to represent the collected information about NAAs, the plants in which they occur and the functionalities for which they have been examined, a relational database is constructed and implemented on a MySQL back-end. Results: The database is supported by describing the NAA plant-, functional-and chemical-space. The chemical space includes a NAA classification, according to their fatty acid and amine structures. Conclusions: The Alkamid database (publicly available on the website http://alkamid.ugent.be/) is not only a central information point, but can also function as a useful tool to prioritize the NAA Q8 choice in the evaluation of their functionality, to perform data mining leading to quantitative structure-property relationships (QSPRs), functionality comparisons, clustering, plant biochemistry and taxonomic evaluations.

Quorum-sensing (QS) peptides are biologically attractive molecules, with a wide diversity of structures and prone to modifications altering or presenting new functionalities. Therefore, the Quorumpeps database (http://quorumpeps.ugent.be) is developed to give a structured overview of the QS oligopeptides, describing their microbial origin (species), functionality (method, result and receptor), peptide links and chemical characteristics (3D-structure-derived physicochemical properties). The chemical diversity observed within this group of QS signalling molecules can be used to develop new synthetic bio-active compounds.

Peptides are able to cross the blood-brain barrier (BBB) through various mechanisms, opening new diagnostic and therapeutic avenues. However, their BBB transport data are scattered in the literature over different disciplines, using different methodologies reporting different influx or efflux aspects. Therefore, a comprehensive BBB peptide database (Brainpeps) was constructed to collect the BBB data available in the literature. Brainpeps currently contains BBB transport information with positive as well as negative results. The database is a useful tool to prioritize peptide choices for evaluating different BBB responses or studying quantitative structure-property (BBB behaviour) relationships of peptides. Because a multitude of methods have been used to assess the BBB behaviour of compounds, we classified these methods and their responses. Moreover, the relationships between the different BBB transport methods have been clarified and visualized.

An increasing number of studies demonstrate the ability of peptides to cross the blood-brain barrier (BBB), opening perspectives for a new class of therapeutics for central nervous system diseases. However, information on the BBB transport of peptides suffer from a wide variety in used methods and experimental set-up. Therefore, it is currently difficult, if not impossible, to classify peptides according to their BBB influx characteristics. To allow direct comparison of BBB influx results of peptides, we introduce a classification method and unified response for BBB influx transport of peptides. First, the results of BBB influx response types (i.e. Kin (MTR), Kin (Perfusion), Pin vitro and Pin vivo), which quantitatively express brain influx, were classified into five classes of BBB influx magnitude based on the distribution of these results for the individual response types. Then, these classes were converted to a BBBin-response, representing a scaled value ranging from zero (no influx) to ten (high influx), independent from the BBB influx response type from which it was derived. This unified response can immediately be applied for new BBB influx results of peptides and represents a ballpark figure for BBB influx and allows direct comparison and ranking of peptides independent of the response type.

The human external ears, or pinnae, have an intriguing shape and, like most parts of the human external body, bilateral symmetry is observed between left and right. It is a well-known part of our auditory sensory system and mediates the spatial localization of incoming sounds in 3D from monaural cues due to its shape-specific filtering as well as binaural cues due to the paired bilateral locations of the left and right ears. Another less broadly appreciated aspect of the human pinna shape is its uniqueness from one individual to another, which is on the level of what is seen in fingerprints and facial features. This makes pinnae very useful in human identification, which is of great interest in biometrics and forensics. Anatomically, the type of symmetry observed is known as matching symmetry, with structures present as separate mirror copies on both sides of the body, and in this work we report the first such investigation of the human pinna in 3D. Within the framework of geometric morphometrics, we started by partitioning ear shape, represented in a spatially dense way, into patterns of symmetry and asymmetry, following a two-factor ANOVA design. Matching symmetry was measured in all substructures of the pinna anatomy. However, substructures that 'stick out' such as the helix, tragus, and lobule also contained a fair degree of asymmetry. In contrast, substructures such as the conchae, antitragus, and antihelix expressed relatively stronger degrees of symmetric variation in relation to their levels of asymmetry. Insights gained from this study were injected into an accompanying identification setup exploiting matching symmetry where improved performance is demonstrated. Finally, possible implications of the results in the context of ear recognition as well as sound localization are discussed.

Dealing with a huge quantity of semi-structured documents and the extraction of information therefrom is an important topic that is getting a lot of attention. Methods that allow to accurately define where the data can be found are then pivotal in constructing a robust solution, allowing for imperfections and structural changes in the source material. In this paper we investigate a wrapper induction method that revolves around aligning XPath elements (steps), allowing a user to generalise upon training examples he gives to the data extraction system. The alignment is based on a modification of the well known Levenshtein edit distance. When the training example XPaths have been aligned with each other they are subsequently merged into the path that generalises, as precise as possible, the examples, so it can be used to accurately fetch the required data from the given source material.

Identifying people using their biometric data is a problem that is getting increasingly more attention. This paper investigates a method that allows the matching of people in the context of victim identification by using their ear biometric data. A high quality picture (taken professionally) is matched against a set of low quality pictures (family albums). In this paper soft computing methods are used to model different kinds of uncertainty that arise when manually annotating the pictures. More specifically, we study the use of bipolar satisfaction degrees to explicitly handle the bipolar information about the available ear biometrics.