Visual exploration of alternative taxonomies through concepts

A graphical user interface is presented that allows users of taxonomic data to explore concept relationships between conflicting but related taxonomic classifications.Ecological analyses that use taxonomic metadata depend on accurate naming of specimens and taxa, and if the metadata involves several taxonomies, care has to be taken to match concepts between them. To perform this accurately requires expert-defined concept relationships, which are more complex yet more representative than the simple one-to-one mappings found through simple name matching, and can accommodate nomenclatural changes and differences in classification technique (cf ‘lumpers’ versus ‘splitters’). In the SEEK-Taxon (Scientific Environment for Ecological Knowledge) project we aim to help users of taxonomic datasets untangle and understand these relationships through a prototype visual interface which graphically displays these relationship structures, allowing users to comprehend such information and more accurately name their data.     

Word learning and the cerebral hemispheres: from serial to parallel processing of written words

Reading familiar words differs from reading unfamiliar non-words in two ways. First, word reading is faster and more accurate than reading of unfamiliar non-words. Second, effects of letter length are reduced for words, particularly when they are presented in the right visual field in familiar formats. Two experiments are reported in which right-handed participants read aloud non-words presented briefly in their left and right visual fields before and after training on those items. The non-words were interleaved with familiar words in the naming tests. Before training, naming was slow and error prone, with marked effects of length in both visual fields. After training, fewer errors were made, naming was faster, and the effect of length was much reduced in the right visual field compared with the left. We propose that word learning creates orthographic word forms in the mid-fusiform gyrus of the left cerebral hemisphere. Those word forms allow words to access their phonological and semantic representations on a lexical basis. But orthographic word forms also interact with more posterior letter recognition systems in the middle/inferior occipital gyri, inducing more parallel processing of right visual field words than is possible for any left visual field stimulus, or for unfamiliar non-words presented in the right visual field.     

IMPORTANCE OF REFERENCE STANDARDS IN TRAINING PANELISTS

When training a sensory evaluation panel, reference standards play an important role in developing appropriate terminology, establishing intensity ranges and showing the action of an ingredient. In addition, use of reference standards reduces the amount of training time while providing documentation for terminology. Product characteristics can be demonstrated through reference standards for application in plant quality assurance programs as well as for project planning in new product development, product maintenance (i.e., shelf-life), product improvement and cost reduction programs.     

Quid significat nomen? (What's in a name?)

For the purposes of classification and effective communication among scientists, organisms must have unequivocal names. The binomial naming system of species was devised and popularized by Linnaeus in the 18th Century. His "Botanical Latin" is an artificial language first adopted for naming plants and is now internationally accepted as a naming system for both plants and animals. Genus and species names are based on Latin and Greek words which describe characteristics of the organism, as well as words from more modern sources, such as the name of the discoverer or place of discovery. Naming follows certain rules and all of the word endings are Latinized. The history of naming parasites is interesting and the molecular age may influence naming in the future.     

Some comments on the classification of African vegetation

Abstract. Problems of naming African vegetation units are discussed, and related to the AETFAT vegetation scheme and other recent publications. Particularly, the distinction is emphasized between the terms forest and woodland, which are often considered synonyms. In other cases, no precise and ecologically meaningful definitions are presented, which leads to confusion and superfluous terms. More strict rules for the definition and application of vegetation terminology are proposed, and suggested as basic information to be given in vegetation literature.     

High confidence rule mining for microarray analysis

We present an association rule mining method for mining high confidence rules, which describe interesting gene relationships from microarray datasets. Microarray datasets typically contain an order of magnitude more genes than experiments, rendering many data mining methods impractical as they are optimised for sparse datasets. A new family of row-enumeration rule mining algorithms have emerged to facilitate mining in dense datasets. These algorithms rely on pruning infrequent relationships to reduce the search space by using the support measure. This major shortcoming results in the pruning of many potentially interesting rules with low support but high confidence. We propose a new row-enumeration rule mining method, MaxConf, to mine high confidence rules from microarray data. MaxConf is a support-free algorithm which directly uses the confidence measure to effectively prune the search space. Experiments on three microarray datasets show that MaxConf outperforms support-based rule mining with respect to scalability and rule extraction. Furthermore, detailed biological analyses demonstrate the effectiveness of our approach -- the rules discovered by MaxConf are substantially more interesting and meaningful compared with support-based methods.     

Proposed Nomenclature for Mutants of Adenoviruses

In accord with the nomenclature proposed for mutants of simian virus 40 the same rules, with minor modifications, are recommended for naming mutants of adenoviruses. It is further suggested that these rules, which pertain to a system of classification based primarily upon complementation analysis, also be applied to mutants of other DNA-containing animal viruses.     

Unavailable names in the Myotis nattereri species complex

The discovery of new species of mammals in Europe is a rare event, but owing to recent progress in genetic methods used to survey current biodiversity, such discoveries have been accumulating during the last decades. The naming of these new taxa has important bearings in conservation, as this is the first step needed for them to be recognised by the scientific community but also legally. The naming of new animal species, however, needs to follow the strict rules of the International Code of Zoological Nomenclature in order to be available and to provide a stable basis for further taxonomic research. We report here a case where new names have been improperly proposed to designate distinctive lineages in the Natterer's bat species complex. As these new names do not follow several mandatory rules imposed by the Code, they are declared unavailable and are not to be used for further taxonomy studies.     

R-Coffee: a method for multiple alignment of non-coding RNA

R-Coffee is a multiple RNA alignment package, derived from T-Coffee, designed to align RNA sequences while exploiting secondary structure information. R-Coffee uses an alignment-scoring scheme that incorporates secondary structure information within the alignment. It works particularly well as an alignment improver and can be combined with any existing sequence alignment method. In this work, we used R-Coffee to compute multiple sequence alignments combining the pairwise output of sequence aligners and structural aligners. We show that R-Coffee can improve the accuracy of all the sequence aligners. We also show that the consistency-based component of T-Coffee can improve the accuracy of several structural aligners. R-Coffee was tested on 388 BRAliBase reference datasets and on 11 longer Cmfinder datasets. Altogether our results suggest that the best protocol for aligning short sequences (less than 200 nt) is the combination of R-Coffee with the RNA pairwise structural aligner Consan. We also show that the simultaneous combination of the four best sequence alignment programs with R-Coffee produces alignments almost as accurate as those obtained with R-Coffee/Consan. Finally, we show that R-Coffee can also be used to align longer datasets beyond the usual scope of structural aligners. R-Coffee is freely available for download, along with documentation, from the T-Coffee web site (www.tcoffee.org).     

The WISER metadatabase: the key to more than 100 ecological datasets from European rivers, lakes and coastal waters

In ecological sciences, the role of metadata (i.e. key information about a dataset) to make existing datasets visible and discoverable has become increasingly important. Within the EU-funded WISER project (Water bodies in Europe: Integrative Systems to assess Ecological status and Recovery), we designed a metadatabase to allow scientists to find the optimal data for their analyses. An online questionnaire helped to collect metadata from the data providers and an online query tool (http://www.wiser.eu/results/meta-database/) facilitated data evaluation. The WISER metadatabase currently holds information on 114 datasets (22 river, 71 lake, 1 general freshwater and 20 coastal/transitional datasets), which also can be accessed by external scientists. We evaluate if generally used metadata standards (e.g. Darwin Core, ISO 19115, CSDGM, EML) are suitable for such specific purposes as WISER and suggest at least the linkage with standard metadata fields. Furthermore, we discuss whether the simple metadata documentation is enough for others to reuse a dataset and why there is still reluctance to publish both metadata and primary research data (i.e. time and financial constraints, misuse of data, abandoning intellectual property rights). We emphasise that metadata publication has major advantages as it makes datasets detectable by other scientists and generally makes a scientist’s work more visible.     

A DATA MANAGER for the health information system Berlin.

The needs for permanently changing the logical and physical structure of a medical datebase during the development of a health information system have initiated the project of implementing a DATA MANAGER. The concept of the DATA MANAGER covers facilities for the development of the logical data structure model including documentation of the model and programming support for application programs accessing the health information system (HIS) database. The outstanding facilities of the INTERLISP system have been found to be appropriate for writing the DATA MANAGER. A first data structure model, on which the DATA MANAGER will operate, is roughly outlined.     

A program package for quantitative analysis of histologic structure and remodeling dynamics of bone

Quantitative bone histology has become an increasingly valuable tool for the management and diagnosis of metabolic bone disease. A new computer-assisted method for quantitative analysis of bone histology which combines the advantages of discriminatory input by the investigator with a significant reduction of evaluation time is presented.These programs allow the analysis of a sufficient number of subjects from different populations for the establishment of normative data, and are useful in the diagnosis and documentation of the treatment of metabolic bone disease.     

Simplifying the decision matrix for estimating fine root production by the sequential soil coring approach

Sequential soil coring is a commonly used approach to measure seasonal root biomass and necromass, from which root production can be estimated by maximum–minimum, sum of changes, compartment-flow model, and/or decision matrix methods. Among these methods, decision matrix is the most frequently used. However, the decision matrix, often underestimating fine root production, is frequently misused in research due to inadequate documentation of its underlying logic. In this paper, we reviewed the decision matrix method and provided mathematical logic for the development of the matrix, by which not only root production but also mortality and decomposition rates can be calculated. To ease its use for large datasets, we developed simplified equations to facilitate computation of root production, mortality and decomposition to be used in MS Excel or R. We also presented results from calculations by an example using empirical data from boreal forests to show proper calculations of root production, mortality and decomposition. The simplified decision matrix presented here shall promote its application in ecology, especially for large datasets.     

Improved and automated prediction of effective siRNA

Short interfering RNAs are used in functional genomics studies to knockdown a single gene in a reversible manner. The results of siRNA experiments are highly dependent on the choice of siRNA sequence. In order to evaluate siRNA design rules, we collected a database of 398 siRNAs of known efficacy from 92 genes. We used this database to evaluate previously proposed rules from smaller datasets, and to find a new set of rules that are optimal for the entire database. We also trained a regression tree with full cross-validation. It was however difficult to obtain the same precision as methods previously tested on small datasets from one or two genes. We show that those methods are overfitting as they work poorly on independent validation datasets from multiple genes. Our new design rules can predict siRNAs with efficacy >/= 50% in 91% of cases, and with efficacy >/=90% in 52% of cases, which is more than a twofold improvement over random selection. Software for designing siRNAs is available online via a web server at or as a standalone version for high-throughput applications.     

Protein sequence redundancy reduction: comparison of various method

Non-redundant protein datasets are of utmost importance in bioinformatics. Constructing such datasets means removing protein sequences that overreach certain similarity thresholds. Several programs such as 'Decrease redundancy', 'cd-hit', 'Pisces', 'BlastClust' and 'SkipRedundant' are available. The issue that we focus on here is to what extent the non-redundant datasets produced by different programs are similar to each other. A systematic comparison of the features and of the outputs of these programs, by using subsets of the UniProt database, was performed and is described here. The results show high level of overlap between non-redundant datasets obtained with the same program fed with the same initial dataset but different percentage of identity threshold, and moderate levels of similarity between results obtained with different programs fed with the same initial dataset and the same percentage of identity threshold. We must be aware that some differences may arise and the use of more than one computer application is advisable.     

Getting a grip on proteomics data – Proteomics Data Collection (ProDaC)

In proteomics, rapid developments in instrumentation led to the acquisition of increasingly large data sets. Correspondingly, ProDaC was founded in 2006 as a Coordination Action project within the 6th European Union Framework Programme to support data sharing and community‐wide data collection. The objectives of ProDaC were the development of documentation and storage standards, setup of a standardized data submission pipeline and collection of data. Ending in March 2009, ProDaC has delivered a comprehensive toolbox of standards and computer programs to achieve these goals.     

Criteria for assessing Italian <Emphasis Type="Italic">ex situ</Emphasis> collections of threatened plants

The ex situ conservation of plant species is a challenge for all signatories of the Convention on Biological Diversity to meet. In Italy, all conservation-related issues are supervised by the Ministry for the Environment and Protection of Land and Sea, but so far no national plan has been drafted, let alone funded, for ex situ plant conservation. As a contribution towards the establishment of a scientifically based policy, a national project has been launched, under the coordination of the Botanic Garden of Palermo. In its framework, the Botanic Garden of Pisa is developing a set of criteria for assessing Italian ex situ collections of threatened plant species. The criteria will be applied to datasets obtained by the Italian seedbanks through questionnaires. Requested data include resources and procedures, documentation systems, facilities and accessions. The expected results consist of the production of printed or electronic material concerning a) the technical-scientific profile of the Italian seed banks and of their collections; b) the ecogeographic profile of seed collections of selected species and c) the evaluation of the method used for gathering and analysing data. The project is currently under way and the results are due by September 2010. The documents and protocols which will be produced within the project will enable a stronger interaction of the Italian seed banks with other national and European seed bank networks.     

Evaluation of the sensitivity of a medical data-mining application to the number of elements in small databases

Data-mining methods can be used to generate rules, or identify patterns, from medical data to assist clinical diagnosis and decision-making. However, in the initial stages of a clinical study on a new diagnostic approach, there could be a limited medical dataset available; or the medical characteristics could mean that the number of patients involved in the study will never be large. Diagnoses made using the rules discovered from such small medical databases should be considered suspect unless a confidence range for a particular diagnosis can be established. A method to evaluate the sensitivity and reliability of data-mining with small databases is presented in this paper. Efron's bootstrap method for statistical testing was used to assess the accuracy of the rules produced during the training step of the data-mining algorithm. The case study for validating this new approach was based on a limited-sized mammographic database previously used to discover associations between the diagnostic features of breast masses in mammograms and the biopsy-based classification of the masses. Using the new approach, it was possible to distinguish between the association rules that were sensitive to the size of the training datasets from those that were not. The methods proposed should lead to an efficient way for validating the patterns discovered in medical data-mining applications using small datasets.     

International service learning programs: ethical issues and recommendations

Inequities in global health are increasingly of interest to health care providers in developed countries. In response, many academic healthcare programs have begun to offer international service learning programs. Participants in these programs are motivated by ethical principles, but this type of work presents significant ethical challenges, and no formalized ethical guidelines for these activities exist. In this paper the ethical issues presented by international service learning programs are described and recommendations are made for how academic healthcare programs can carry out international service learning programs in a way that minimizes ethical conflicts and maximizes benefits for all stakeholders. Issues related to project sustainability and community involvement are emphasized.