CleanEx: a database of heterogeneous gene expression data based on a consistent gene nomenclature.

The main goal of CleanEx is to provide access to public gene expression data via unique gene names. A second objective is to represent heterogeneous expression data produced by different technologies in a way that facilitates joint analysis and cross-data set comparisons. A consistent and up-to-date gene nomenclature is achieved by associating each single experiment with a permanent target identifier consisting of a physical description of the targeted RNA population or the hybridization reagent used. These targets are then mapped at regular intervals to the growing and evolving catalogues of human genes and genes from model organisms. The completely automatic mapping procedure relies partly on external genome information resources such as UniGene and RefSeq. The central part of CleanEx is a weekly built gene index containing cross-references to all public expression data already incorporated into the system. In addition, the expression target database of CleanEx provides gene mapping and quality control information for various types of experimental resource, such as cDNA clones or Affymetrix probe sets. The web-based query interfaces offer access to individual entries via text string searches or quantitative expression criteria. CleanEx is accessible at: http://www.cleanex.isb-sib.ch/.

Patients, médecins et internet [Patients, doctors and the internet].

The majority of the Swiss population uses the internet to seek information about health. The objective is to be better informed, before or after the consultation. Doctors can advise their information-seeking patients about high quality websites, be it medical portals or websites dedicated to a specific pathology. Doctors should not see the internet as a threat but rather as an opportunity to strengthen the doctor-patient relationship.

Efficient bulk-loading on dynamic metric access methods

This paper presents a new technique and two algorithms to bulk-load data into multi-way dynamic metric access methods, based on the covering radius of representative elements employed to organize data in hierarchical data structures. The proposed algorithms are sample-based, and they always build a valid and height-balanced tree. We compare the proposed algorithm with existing ones, showing the behavior to bulk-load data into the Slim-tree metric access method. After having identified the worst case of our first algorithm, we describe adequate counteractions in an elegant way creating the second algorithm. Experiments performed to evaluate their performance show that our bulk-loading methods build trees faster than the sequential insertion method regarding construction time, and that it also significantly improves search performance. (C) 2009 Elsevier B.V. All rights reserved.

Information asymmetry and transaction costs in a cross-cultural business transaction

The intent of this paper is to provide a practitioners insight into the present and foreseeable future of problem of transaction cost economics related to culture and business etiquette that may increase the of complexity of business communication. We will also explore whether it impacts participant's mindsets regarding opportunistic or passive aggressive behavior. We will study the role of culture, ethics, information asymmetry, and legal systems regarding their importance towards the business contracts and lack of knowledge in local environments. We will make connections to contract theory strategies and objectives and recommend business practices. Furthermore, economic theory explores the role of the impossibility of the perfect contract. Historical and present day operational factors are examined for the determination of forward-looking contract law indications worldwide. This paper is intended provide a practitioners view with a global perspective of a multinational, mid-sized and small corporations giving consideration in a non-partisan and non-nationalistic view, yet examines the individual characteristics of the operational necessities and obligations of any corporation. The study will be general, yet cite specific articles to each argument and give adequate consideration to the intricacies of the global asymmetry of information. This paper defends that corporations of any kind and size should be aware of the risk of international business etiquette and cultural barriers that might jeopardize the savings you could obtain from engaging international suppliers.

Controllable assembly of graphene hybrid materials and their application in energy storage and conversion

Hybrid Elektrodenmaterialien (HEM) sind der Schlüssel zu grundlegenden Fortschritten in der Energiespeicherung und Systemen zur Energieumwandlung, einschließlich Lithium-Ionen-Batterien (LiBs), Superkondensatoren (SCs) und Brennstoffzellen (FCs). Die faszinierenden Eigenschaften von Graphen machen es zu einem guten Ausgangsmaterial für die Darstellung von HEM. Jedoch scheitern traditionelle Verfahren zur Herstellung von Graphen-HEM (GHEM) scheitern häufig an der fehlenden Kontrolle über die Morphologie und deren Einheitlichkeit, was zu unzureichenden Grenzflächenwechselwirkungen und einer mangelhaften Leistung des Materials führt. Diese Arbeit konzentriert sich auf die Herstellung von GHEM über kontrollierte Darstellungsmethoden und befasst sich mit der Nutzung von definierten GHEM für die Energiespeicherung und -umwandlung. Die große Volumenausdehnung bildet den Hauptnachteil der künftigen Lithium-Speicher-Materialien. Als erstes wird ein dreidimensionaler Graphen Schaumhybrid zur Stärkung der Grundstruktur und zur Verbesserung der elektrochemischen Leistung des Fe3O4 Anodenmaterials dargestellt. Der Einsatz von Graphenschalen und Graphennetzen realisiert dabei einen doppelten Schutz gegen die Volumenschwankung des Fe3O4 bei dem elektrochemischen Prozess. Die Leistung der SCs und der FCs hängt von der Porenstruktur und der zugänglichen Oberfläche, beziehungsweise den katalytischen Stellen der Elektrodenmaterialien ab. Wir zeigen, dass die Steuerung der Porosität über Graphen-basierte Kohlenstoffnanoschichten (HPCN) die zugängliche Oberfläche und den Ionentransport/Ladungsspeicher für SCs-Anwendungen erhöht. Desweiteren wurden Stickstoff dotierte Kohlenstoffnanoschichten (NDCN) für die kathodische Sauerstoffreduktion (ORR) hergestellt. Eine maßgeschnittene Mesoporosität verbunden mit Heteroatom Doping (Stickstoff) fördert die Exposition der aktiven Zentren und die ORR-Leistung der metallfreien Katalysatoren. Hochwertiges elektrochemisch exfoliiertes Graphen (EEG) ist ein vielversprechender Kandidat für die Darstellung von GHEM. Allerdings ist die kontrollierte Darstellung von EEG-Hybriden weiterhin eine große Herausforderung. Zu guter Letzt wird eine Bottom-up-Strategie für die Darstellung von EEG Schichten mit einer Reihe von funktionellen Nanopartikeln (Si, Fe3O4 und Pt NPs) vorgestellt. Diese Arbeit zeigt einen vielversprechenden Weg für die wirtschaftliche Synthese von EEG und EEG-basierten Materialien.

A PROCESS FOR ACHIEVING COMPARABLE DATA FROM HETEROGENEOUS DATABASES

The current state of health and biomedicine includes an enormity of heterogeneous data ‘silos’, collected for different purposes and represented differently, that are presently impossible to share or analyze in toto. The greatest challenge for large-scale and meaningful analyses of health-related data is to achieve a uniform data representation for data extracted from heterogeneous source representations. Based upon an analysis and categorization of heterogeneities, a process for achieving comparable data content by using a uniform terminological representation is developed. This process addresses the types of representational heterogeneities that commonly arise in healthcare data integration problems. Specifically, this process uses a reference terminology, and associated "maps" to transform heterogeneous data to a standard representation for comparability and secondary use. The capture of quality and precision of the “maps” between local terms and reference terminology concepts enhances the meaning of the aggregated data, empowering end users with better-informed queries for subsequent analyses. A data integration case study in the domain of pediatric asthma illustrates the development and use of a reference terminology for creating comparable data from heterogeneous source representations. The contribution of this research is a generalized process for the integration of data from heterogeneous source representations, and this process can be applied and extended to other problems where heterogeneous data needs to be merged.

Use of Medical Subject Headings (MeSH) in Portuguese for categorizing web-based healthcare content

Introduction: Internet users are increasingly using the worldwide web to search for information relating to their health. This situation makes it necessary to create specialized tools capable of supporting users in their searches. Objective: To apply and compare strategies that were developed to investigate the use of the Portuguese version of Medical Subject Headings (MeSH) for constructing an automated classifier for Brazilian Portuguese-language web-based content within or outside of the field of healthcare, focusing on the lay public. Methods: 3658 Brazilian web pages were used to train the classifier and 606 Brazilian web pages were used to validate it. The strategies proposed were constructed using content-based vector methods for text classification, such that Naive Bayes was used for the task of classifying vector patterns with characteristics obtained through the proposed strategies. Results: A strategy named InDeCS was developed specifically to adapt MeSH for the problem that was put forward. This approach achieved better accuracy for this pattern classification task (0.94 sensitivity, specificity and area under the ROC curve). Conclusions: Because of the significant results achieved by InDeCS, this tool has been successfully applied to the Brazilian healthcare search portal known as Busca Saude. Furthermore, it could be shown that MeSH presents important results when used for the task of classifying web-based content focusing on the lay public. It was also possible to show from this study that MeSH was able to map out mutable non-deterministic characteristics of the web. (c) 2010 Elsevier Inc. All rights reserved.

Modeling sequencing errors by combining Hidden Markov models.

Among the largest resources for biological sequence data is the large amount of expressed sequence tags (ESTs) available in public and proprietary databases. ESTs provide information on transcripts but for technical reasons they often contain sequencing errors. Therefore, when analyzing EST sequences computationally, such errors must be taken into account. Earlier attempts to model error prone coding regions have shown good performance in detecting and predicting these while correcting sequencing errors using codon usage frequencies. In the research presented here, we improve the detection of translation start and stop sites by integrating a more complex mRNA model with codon usage bias based error correction into one hidden Markov model (HMM), thus generalizing this error correction approach to more complex HMMs. We show that our method maintains the performance in detecting coding sequences.

Toward interoperable bioscience data.

To make full use of research data, the bioscience community needs to adopt technologies and reward mechanisms that support interoperability and promote the growth of an open 'data commoning' culture. Here we describe the prerequisites for data commoning and present an established and growing ecosystem of solutions using the shared 'Investigation-Study-Assay' framework to support that vision.

The Universal Protein Resource (UniProt) in 2010.

The primary mission of UniProt is to support biological research by maintaining a stable, comprehensive, fully classified, richly and accurately annotated protein sequence knowledgebase, with extensive cross-references and querying interfaces freely accessible to the scientific community. UniProt is produced by the UniProt Consortium which consists of groups from the European Bioinformatics Institute (EBI), the Swiss Institute of Bioinformatics (SIB) and the Protein Information Resource (PIR). UniProt is comprised of four major components, each optimized for different uses: the UniProt Archive, the UniProt Knowledgebase, the UniProt Reference Clusters and the UniProt Metagenomic and Environmental Sequence Database. UniProt is updated and distributed every 3 weeks and can be accessed online for searches or download at http://www.uniprot.org.

Inherently self-calibrating non-Cartesian parallel imaging.

The use of self-calibrating techniques in parallel magnetic resonance imaging eliminates the need for coil sensitivity calibration scans and avoids potential mismatches between calibration scans and subsequent accelerated acquisitions (e.g., as a result of patient motion). Most examples of self-calibrating Cartesian parallel imaging techniques have required the use of modified k-space trajectories that are densely sampled at the center and more sparsely sampled in the periphery. However, spiral and radial trajectories offer inherent self-calibrating characteristics because of their densely sampled center. At no additional cost in acquisition time and with no modification in scanning protocols, in vivo coil sensitivity maps may be extracted from the densely sampled central region of k-space. This work demonstrates the feasibility of self-calibrated spiral and radial parallel imaging using a previously described iterative non-Cartesian sensitivity encoding algorithm.

Atlas-based segmentation of pathological MR brain images using a model of lesion growth.

We propose a method for brain atlas deformation in the presence of large space-occupying tumors, based on an a priori model of lesion growth that assumes radial expansion of the lesion from its starting point. Our approach involves three steps. First, an affine registration brings the atlas and the patient into global correspondence. Then, the seeding of a synthetic tumor into the brain atlas provides a template for the lesion. The last step is the deformation of the seeded atlas, combining a method derived from optical flow principles and a model of lesion growth. Results show that a good registration is performed and that the method can be applied to automatic segmentation of structures and substructures in brains with gross deformation, with important medical applications in neurosurgery, radiosurgery, and radiotherapy.