Some biological data on cetaceans populations present in the western coasts of Ireland

Ireland’s waters constitute one of the richest habitats for cetaceans in Europe. Marine mammals, particularly cetaceans, are known to be definitive hosts of digestive parasites from the Fm.Anisakidae. The main aim of this study is to collect and compile all the information available out there regarding parasites of the Fm. Anisakidae and their definitive hosts. Secondary objectives are to relate the presence of cetacean species with the presence of parasites of the Fm. Anisakidae and to determine whether this greater number of cetaceans relates to a greater level of parasitism. Prevalence and burdens of anisakids in definitive hosts vary widely with host species, geographic location, and season. Results from several post-mortem exams are given. However, they cannot be compared due to differences in collecting techniques. Anisakis simplex is the most commonly and widespread parasite found in the majority of the samples and in a majornumber of hosts, which include harbour porpoise, short-beaked common dolphin and bottlenose dolphin. Studies on harbour porpoise obtained prevalences of Anisakis spp. of 46% (n=26) and of 100% (n= 12). Another study in common dolphin reported a prevalence of 68% (n=25). Several reasons could influence the variations in the presence of Anisakis. Studies on commerciallyexploited fish have reported prevalences of Anisakis simplex ranging from 65-100% in wildAtlantic salmon and from 42-53.4% in Atlantic cod

Some biological data on cetaceans populations present in the western coasts of Ireland

Ireland’s waters constitute one of the richest habitats for cetaceans in Europe. Marine mammals, particularly cetaceans, are known to be definitive hosts of digestive parasites from the Fm.Anisakidae. The main aim of this study is to collect and compile all the information available out there regarding parasites of the Fm. Anisakidae and their definitive hosts. Secondary objectives are to relate the presence of cetacean species with the presence of parasites of the Fm. Anisakidae and to determine whether this greater number of cetaceans relates to a greater level of parasitism. Prevalence and burdens of anisakids in definitive hosts vary widely with host species, geographic location, and season. Results from several post-mortem exams are given. However, they cannot be compared due to differences in collecting techniques. Anisakis simplex is the most commonly and widespread parasite found in the majority of the samples and in a major number of hosts, which include harbour porpoise, short-beaked common dolphin and bottlenose dolphin. Studies on harbour porpoise obtained prevalences of Anisakis spp. of 46% (n=26) and of 100% (n= 12). Another study in common dolphin reported a prevalence of 68% (n=25). Several reasons could influence the variations in the presence of Anisakis. Studies on commercially exploited fish have reported prevalences of Anisakis simplex ranging from 65-100% in wild Atlantic salmon and from 42-53.4% in Atlantic cod

The BioDICE Taverna plugin for clustering and visualization of biological data: a workflow for molecular compounds exploration

Background: In many experimental pipelines, clustering of multidimensional biological datasets is used to detect hidden structures in unlabelled input data. Taverna is a popular workflow management system that is used to design and execute scientific workflows and aid in silico experimentation. The availability of fast unsupervised methods for clustering and visualization in the Taverna platform is important to support a data-driven scientific discovery in complex and explorative bioinformatics applications. Results: This work presents a Taverna plugin, the Biological Data Interactive Clustering Explorer (BioDICE), that performs clustering of high-dimensional biological data and provides a nonlinear, topology preserving projection for the visualization of the input data and their similarities. The core algorithm in the BioDICE plugin is Fast Learning Self Organizing Map (FLSOM), which is an improved variant of the Self Organizing Map (SOM) algorithm. The plugin generates an interactive 2D map that allows the visual exploration of multidimensional data and the identification of groups of similar objects. The effectiveness of the plugin is demonstrated on a case study related to chemical compounds. Conclusions: The number and variety of available tools and its extensibility have made Taverna a popular choice for the development of scientific data workflows. This work presents a novel plugin, BioDICE, which adds a data-driven knowledge discovery component to Taverna. BioDICE provides an effective and powerful clustering tool, which can be adopted for the explorative analysis of biological datasets.

Investigation of a new GRASP-based clustering algorithm applied to biological data

A large amount of biological data has been produced in the last years. Important knowledge can be extracted from these data by the use of data analysis techniques. Clustering plays an important role in data analysis, by organizing similar objects from a dataset into meaningful groups. Several clustering algorithms have been proposed in the literature. However, each algorithm has its bias, being more adequate for particular datasets. This paper presents a mathematical formulation to support the creation of consistent clusters for biological data. Moreover. it shows a clustering algorithm to solve this formulation that uses GRASP (Greedy Randomized Adaptive Search Procedure). We compared the proposed algorithm with three known other algorithms. The proposed algorithm presented the best clustering results confirmed statistically. (C) 2009 Elsevier Ltd. All rights reserved.

Biological data for the neotropical termite Nasutitermes globiceps (Isoptera: Termitidae: Nasutitermitinae)

Nasutitermes globiceps is a Neotropical termite, considered a pest in Brazil. It has been reported to cause damage to wood of buildings, transmission poles, fences, trees and stored material. Nest architecture of this arboreal Nasutitermes is described in a small area of natural vegetation of Sāo Paulo state. Polycalism and polygyny are reported as reproductive mechanisms present in the species.

A Simpler and More Accurate AUTO-HDS Framework for Clustering and Visualization of Biological Data

In [1], the authors proposed a framework for automated clustering and visualization of biological data sets named AUTO-HDS. This letter is intended to complement that framework by showing that it is possible to get rid of a user-defined parameter in a way that the clustering stage can be implemented more accurately while having reduced computational complexity

Assessing the gain of biological data integration in gene networks inference

Background: A current challenge in gene annotation is to define the gene function in the context of the network of relationships instead of using single genes. The inference of gene networks (GNs) has emerged as an approach to better understand the biology of the system and to study how several components of this network interact with each other and keep their functions stable. However, in general there is no sufficient data to accurately recover the GNs from their expression levels leading to the curse of dimensionality, in which the number of variables is higher than samples. One way to mitigate this problem is to integrate biological data instead of using only the expression profiles in the inference process. Nowadays, the use of several biological information in inference methods had a significant increase in order to better recover the connections between genes and reduce the false positives. What makes this strategy so interesting is the possibility of confirming the known connections through the included biological data, and the possibility of discovering new relationships between genes when observed the expression data. Although several works in data integration have increased the performance of the network inference methods, the real contribution of adding each type of biological information in the obtained improvement is not clear. Methods: We propose a methodology to include biological information into an inference algorithm in order to assess its prediction gain by using biological information and expression profile together. We also evaluated and compared the gain of adding four types of biological information: (a) protein-protein interaction, (b) Rosetta stone fusion proteins, (c) KEGG and (d) KEGG+GO. Results and conclusions: This work presents a first comparison of the gain in the use of prior biological information in the inference of GNs by considering the eukaryote (P. falciparum) organism. Our results indicates that information based on direct interaction can produce a higher improvement in the gain than data about a less specific relationship as GO or KEGG. Also, as expected, the results show that the use of biological information is a very important approach for the improvement of the inference. We also compared the gain in the inference of the global network and only the hubs. The results indicates that the use of biological information can improve the identification of the most connected proteins.

VR Based Visualization and Exploration of Plant Biological Data

This paper investigates the use of virtual reality (VR) technologies to facilitate the analysis of plant biological data in distinctive steps in the application pipeline. Reconstructed three-dimensional biological models (primary polygonal models) transferred to a virtual environment support scientists' collaborative exploration of biological datasets so that they obtain accurate analysis results and uncover information hidden in the data. Examples of the use of virtual reality in practice are provided and a complementary user study was performed.