Preliminary testing of River Habitat Survey features for the aims of the WFD hydro-morphological assessment: an overview from the STAR Project

The UK River Habitat Survey (RHS) method for the assessment of hydro-morphological features was applied within the EU STAR project simultaneously with the collection of biological data. A subset of data from 79 sites affected by hydro-morphological alteration and belonging to 7 different stream types was analysed. The different features recorded within RHS were evaluated separately considering the characteristics associated with banks, channel and riparian zone. Different scores were assigned to selected features representing hydro-morphological alteration and naturalness of habitat. The ability of the different compartments to represent the quality gradient of sites was investigated. In addition, the link between macroinvertebrate community and hydro-morphological data was investigated, directly relating indices and metrics calculated from taxa list collected in a site to scores assigned to the RHS features. The sections highly affected by morphological alteration were channel geometry and bank profile. Metrics showing the best correlation with the features selected were EPT taxa, ASPT and ICMi (Inter-calibration Common Metric index). Among the indices studied, the HQA score (Habitat Quality Assessment) apparently played the most important role in structuring biological communities and the lentic-lotic character of rivers was also important. Electronic supplementary material Electronic supplementary material is available for this article at and accessible for authorised users.     

Petilla terminology: nomenclature of features of GABAergic interneurons of the cerebral cortex

Neuroscience produces a vast amount of data from an enormous diversity of neurons. A neuronal classification system is essential to organize such data and the knowledge that is derived from them. Classification depends on the unequivocal identification of the features that distinguish one type of neuron from another. The problems inherent in this are particularly acute when studying cortical interneurons. To tackle this, we convened a representative group of researchers to agree on a set of terms to describe the anatomical, physiological and molecular features of GABAergic interneurons of the cerebral cortex. The resulting terminology might provide a stepping stone towards a future classification of these complex and heterogeneous cells. Consistent adoption will be important for the success of such an initiative, and we also encourage the active involvement of the broader scientific community in the dynamic evolution of this project.     

Supporting genotype-phenotype correlation with the rare metabolic diseases database Ramedis

To gain further knowledge about rare genetic diseases, a world wide method for data collection via the Internet has been established. This new approach will improve collecting valuable data from single case reports. Ramedis saves standardised patient data which will be usable for statistics, longitudinal examinations and cooperative studies in future time. Embedded in the scene of the German Human Genome Project, Ramedis directly will enable phenotype-genotype correlations. Beside the better characterisation of clinical heterogeneity of rare metabolic diseases, there may be a great benefit for the treatment of these patients in whom prospective studies are otherwise expensive and difficult to perform. This contribution presents the motivation for this system, introduces features, current state and the future of the project. Additionally, first experiences of using Ramedis by health professionals are explained.     

Occurrence and variability of River Habitat Survey features across Europe and the consequences for data collection and evaluation

River Habitat Survey (RHS) data collected for the EU-funded STAR project was used to identify hydromorphological characteristic features of rivers in four European regions namely: lowlands; mountain; the Alps; and the Mediterranean. Using RHS attributes, Habitat Quality Assessment (HQA) – a measure of natural habitat diversity, and Habitat Modification Score (HMS) – a measure of anthropogenic modification, we identified considerable differences in frequency, diversity and evenness of features between the regions. A relatively small subset of features clearly distinguish the hydromorphological characters of lowland, Alpine and southern European rivers. It was more difficult to distinguish mountain rivers from Alpine rivers. The highest statistical differences are observed between Lowland and Mountain region. Within the four regions studied the RHS attributes that most strongly influence the HQA and HMS indices were identified. We conclude that specific effort should be made to ensure these are recorded properly as part of the quality control of RHS data. Electronic supplementary material Electronic supplementary material is available for this article at and accessible for authorised users.     

Data mining parasite genomes

The term 'data mining' can be used to describe any process where useful information is extracted from data with a large background of 'noise'. In the context of a genome project, several stages involve data mining. Amongst the sequence data, 'signals' need to be detected that indicate the presence of interesting features. Often this involves differentiating between transcribed and non-transcribed bases to predict coding regions. After detection, defining the roles of these sequences involves sifting through multiple lines of evidence. If these roles are accurately reflected in genome annotation, they can be used by researchers to frame queries and interrogate the data further.     

Seeking Social Inventions to Improve the Transition to Adulthood

Social inventions are new ways of solving human problems. This article reports on an action research project designed to find social inventions to reduce structural lag in four programs that support the transition to adulthood of marginalized youth in Latin America. The investigators engaged youth and staff members in identifying important questions, collecting and interpreting data, and using findings to improve their practices. Their issues aligned with social setting features: activities, resources, roles, and norms. Among their social inventions were “the life project,” the role of mentor, youth responsibility, and new norms of reflection introduced by action research, which not only revealed social inventions but generated them as well. Interaction with external parties contributed to this process: the investigators, “local researchers” engaged as part of the project, participants in conferences convened for participants. Rather than recommending social inventions for adoption in other locations, we recommend using action research to generate local social inventions.     

The microbiological data base of the data bank project BD1

The aim of the project BD1 (Biotechnology Data Bank 1) is to improve the data processing for research in biotechnology. In BD1, data of several classes of objects and methods are compiled. A data file conception consisting of object data files, method data files and feature data files was created, which can be easily extended to further classes, and which allows the combination of different classes of features to the same class of objects. There are two main approaches to use BD1: 1. making available informations on certain biotechnological objects, 2. the identification of unknown objects by means of their feature pattern. The microbiological data base and the possibilities of data base search are presented by example of lactic acid bacteria.     

BioMoby extensions to the Taverna workflow management and enactment software

Background  

As biology becomes an increasingly computational science, it is critical that we develop software tools that support not only bioinformaticians, but also bench biologists in their exploration of the vast and complex data-sets that continue to build from international genomic, proteomic, and systems-biology projects. The BioMoby interoperability system was created with the goal of facilitating the movement of data from one Web-based resource to another to fulfill the requirements of non-expert bioinformaticians. In parallel with the development of BioMoby, the European myGrid project was designing Taverna, a bioinformatics workflow design and enactment tool. Here we describe the marriage of these two projects in the form of a Taverna plug-in that provides access to many of BioMoby's features through the Taverna interface.     

Industrial Ecosystem Development at the Metropolitan Level

This article presents the result of a two-year project funded by the U.S. Environmental Protection Agency to identify potential by-products partnerships between industries in a six-county metropolitan area in North Carolina, U.S.A. The project gathered data from 182 industries and institutions in the region regarding (1) by-products that might be usable by other, nearby firms, and (2) the inputs they used that might be furnished from another facility's by-products. These data, which were also linked to geographic information system maps, were used to identify potential regional partnerships for the reuse of materials, water, and energy. Of the 182 participating facilities, probable or possible partnerships were found for 48% during the limited project period. This project demonstrated the value of a local facilitator and the value of specific techniques for identifying and promoting potential by-products partnerships.     

Self modeling with flexible, random time transformations

Methods for modeling sets of complex curves where the curves must be aligned in time (or in another continuous predictor) fall into the general class of functional data analysis and include self-modeling regression and time-warping procedures. Self-modeling regression (SEMOR), also known as a shape invariant model (SIM), assumes the curves have a common shape, modeled nonparametrically, and curve-specific differences in amplitude and timing, traditionally modeled by linear transformations. When curves contain multiple features that need to be aligned in time, SEMOR may be inadequate since a linear time transformation generally cannot align more than one feature. Time warping procedures focus on timing variability and on finding flexible time warps to align multiple data features. We draw on these methods to develop a SIM that models the time transformations as random, flexible, monotone functions. The model is motivated by speech movement data from the University of Wisconsin X-ray microbeam speech production project and is applied to these data to test the effect of different speaking conditions on the shape and relative timing of movement profiles.     

GEOquery: a bridge between the Gene Expression Omnibus (GEO) and BioConductor

Microarray technology has become a standard molecular biology tool. Experimental data have been generated on a huge number of organisms, tissue types, treatment conditions and disease states. The Gene Expression Omnibus (Barrett et al., 2005), developed by the National Center for Bioinformatics (NCBI) at the National Institutes of Health is a repository of nearly 140,000 gene expression experiments. The BioConductor project (Gentleman et al., 2004) is an open-source and open-development software project built in the R statistical programming environment (R Development core Team, 2005) for the analysis and comprehension of genomic data. The tools contained in the BioConductor project represent many state-of-the-art methods for the analysis of microarray and genomics data. We have developed a software tool that allows access to the wealth of information within GEO directly from BioConductor, eliminating many the formatting and parsing problems that have made such analyses labor-intensive in the past. The software, called GEOquery, effectively establishes a bridge between GEO and BioConductor. Easy access to GEO data from BioConductor will likely lead to new analyses of GEO data using novel and rigorous statistical and bioinformatic tools. Facilitating analyses and meta-analyses of microarray data will increase the efficiency with which biologically important conclusions can be drawn from published genomic data. Availability: GEOquery is available as part of the BioConductor project.     

Characterization of Chromosome Ends in the Filamentous Fungus Neurospora crassa

Telomeres and subtelomere regions have vital roles in cellular homeostasis and can facilitate niche adaptation. However, information on telomere/subtelomere structure is still limited to a small number of organisms. Prior to initiation of this project, the Neurospora crassa genome assembly contained only 3 of the 14 telomeres. The missing telomeres were identified through bioinformatic mining of raw sequence data from the genome project and from clones in new cosmid and plasmid libraries. Their chromosomal locations were assigned on the basis of paired-end read information and/or by RFLP mapping. One telomere is attached to the ribosomal repeat array. The remaining chromosome ends have atypical structures in that they lack distinct subtelomere domains or other sequence features that are associated with telomeres in other organisms. Many of the chromosome ends terminate in highly AT-rich sequences that appear to be products of repeat-induced point mutation, although most are not currently repeated sequences. Several chromosome termini in the standard Oak Ridge wild-type strain were compared to their counterparts in an exotic wild type, Mauriceville. This revealed that the sequences immediately adjacent to the telomeres are usually genome specific. Finally, despite the absence of many features typically found in the telomere regions of other organisms, the Neurospora chromosome termini still retain the dynamic nature that is characteristic of chromosome ends.     

Leukemia-related morphological features in blast cells

This paper investigates the use of image-processing methods to detect leukemia-related morphological differences in mononuclear blast cells. Routinely prepared Pappenheim-stained blood smears were scanned in a high-resolution color TV-microscope system. Eleven blast-cell classes (OMSBC, T-ALL, OMS, ALL, LBL, IBL, AUL, AML, AMOL, AMMOL, and CML) were analyzed with the nonparametric statistical software program "Classification and Regression Trees" (CART). This paper documents the initial statistical evaluation of 62 leukemia-related morphological features that directly measure and analyze the cell-related quantifiable differences occurring in the various blast cells. The 62 cell image features include both common cytophotometric features, and new texture and color features developed for this project. This study found that each leukemia specimen contains a dominant class of blasts that correlates with the specific leukemia, plus a distribution of blasts from related diseases. The present data suggest the existence of a distribution fingerprint pattern for each leukemia.     

Eu-social science: the role of internet social networks in the collection of bee biodiversity data

Background

Monitoring change in species diversity, community composition and phenology is vital to assess the impacts of anthropogenic activity and natural change. However, monitoring by trained scientists is time consuming and expensive.

Methodology/Principal Findings

Using social networks, we assess whether it is possible to obtain accurate data on bee distribution across the UK from photographic records submitted by untrained members of the public, and if these data are in sufficient quantity for ecological studies. We used Flickr and Facebook as social networks and Flickr for the storage of photographs and associated data on date, time and location linked to them. Within six weeks, the number of pictures uploaded to the Flickr BeeID group exceeded 200. Geographic coverage was excellent; the distribution of photographs covered most of the British Isles, from the south coast of England to the Highlands of Scotland. However, only 59% of photographs were properly uploaded according to instructions, with vital information such as ‘tags’ or location information missing from the remainder. Nevertheless, this incorporation of information on location of photographs was much higher than general usage on Flickr (∼13%), indicating the need for dedicated projects to collect spatial ecological data. Furthermore, we found identification of bees is not possible from all photographs, especially those excluding lower abdomen detail. This suggests that giving details regarding specific anatomical features to include on photographs would be useful to maximise success.

Conclusions/Significance

The study demonstrates the power of social network sites to generate public interest in a project and details the advantages of using a group within an existing popular social network site over a traditional (specifically-designed) web-based or paper-based submission process. Some advantages include the ability to network with other individuals or groups with similar interests, and thus increasing the size of the dataset and participation in the project.     

Comparative evaluation of microarray analysis software

A wide variety of software tools are available to analyze microarray data. To identify the optimum software for any project, it is essential to define specific and essential criteria on which to evaluate the advantages of the key features. In this review we describe the results of our comparison of several software tools. We then conclude with a discussion of the subset of tools that are most commonly used and describe the features that would constitute the “ideal microarray analysis software suite.”     

River and Riparian Restoration in the Southwest: Results of the National River Restoration Science Synthesis Project

Restoration activity has exponentially increased across the Southwest since 1990. Over 37,000 records were compiled into the National River Restoration Science Synthesis (NRRSS) database to summarize restoration trends and assess project effectiveness. We analyzed data from 576 restoration projects in the Southwest (NRRSS‐SW). More than 50% of projects were less than or equal to 3 km in length. The most common restoration project intent categories were riparian management, water quality management, in‐stream habitat improvement, and flow modification. Common project activities were well matched to goals. Conservative estimates of total restoration costs exceeded $500 million. Most restoration dollars have been allocated to flow modification and water quality management. Monitoring was linked to 28% of projects across the Southwest, as opposed to just 10% nationwide. Mean costs were statistically similar whether or not projects were monitored. Results from 48 telephone interviews provided validation of NRRSS‐SW database analyses but showed that project costs are often underreported within existing datasets. The majority of interviewees considered their projects to be successful, most often based upon observed improvements to biota or positive public reaction rather than evaluation of field data. The efficacy of restoration is difficult to ascertain given the dearth of information contained within most datasets. There is a great need for regional entities that not only track information on project implementation but also maintain and analyze monitoring data associated with restoration. Agencies that fund or regulate restoration should reward projects that emphasize monitoring and evaluation as much as project implementation.