Exploring the Proximity Effect in Mo/Au Bilayers

We report on the sensitivity of superconducting transition temperature (T c ) to the individual layers' thickness in Mo/Au proximity bilayers to be used in transition-edge sensors (TESs). The achieved good reproducibility and quality of the bilayers allow a clear determination of the superconducting critical temperature T c as a function of the Mo and Au thicknesses. One objective of this work is to analyse the quality of the Mo/Au interface and to assess the possible effects of the double Au layer we use to fabricate these bilayers and TESs based on them. Experimental data are analysed on the basis of Usadel equations using the model developed by Martinis and co-workers, in which the proximity effect in the bilayer is mainly governed by the interface transparency between the superconductor and the normal metal. We find that this model describes quite well the behavior of T c , even for quite thick Au layers, and that the double Au layer does not play any relevant role on the proximity effect

Exploring the Proximity Effect in Mo/Au Bilayers

We report on the sensitivity of superconducting transition temperature (T c ) to the individual layers' thickness in Mo/Au proximity bilayers to be used in transition-edge sensors (TESs). The achieved good reproducibility and quality of the bilayers allow a clear determination of the superconducting critical temperature T c as a function of the Mo and Au thicknesses. One objective of this work is to analyse the quality of the Mo/Au interface and to assess the possible effects of the double Au layer we use to fabricate these bilayers and TESs based on them. Experimental data are analysed on the basis of Usadel equations using the model developed by Martinis and co-workers, in which the proximity effect in the bilayer is mainly governed by the interface transparency between the superconductor and the normal metal. We find that this model describes quite well the behavior of T c , even for quite thick Au layers, and that the double Au layer does not play any relevant role on the proximity effect

Large current-induced broadening of the superconducting transition in Mo/Au transition edge sensors

The R(T, I) shape of the superconducting transition in transition edge sensors (TESs) is of crucial importance to determine their ultimate performance. This paper reports a study of the temperature and current dependences of the transition of Mo/Au TESs, focused on the low resistance region, where these devices preferentially operate. A large broadening of the transition is observed when increasing the applied current. An empirical analytic expression for R(T, I) is found, which describes the transition of devices with different critical temperatures, from R = 0 up to at least 30% R-n (in some cases nearly 80% R-n). Several mechanisms for this behaviour are considered; results show that a current assisted vortex pair unbinding mechanism (Berezinskii-Kosterlitz-Thouless transition) could be the possible origin for this behaviour. Finally, the consequences of the current-induced transition broadening for TES properties and operation are outlined

FFPred: an integrated feature-based function prediction server for vertebrate proteomes

One of the challenges of the post-genomic era is to provide accurate function annotations for large volumes of data resulting from genome sequencing projects. Most function prediction servers utilize methods that transfer existing database annotations between orthologous sequences. In contrast, there are few methods that are independent of homology and can annotate distant and orphan protein sequences. The FFPred server adopts a machine-learning approach to perform function prediction in protein feature space using feature characteristics predicted from amino acid sequence. The features are scanned against a library of support vector machines representing over 300 Gene Ontology (GO) classes and probabilistic confidence scores returned for each annotation term. The GO term library has been modelled on human protein annotations; however, benchmark performance testing showed robust performance across higher eukaryotes. FFPred offers important advantages over traditional function prediction servers in its ability to annotate distant homologues and orphan protein sequences, and achieves greater coverage and classification accuracy than other feature-based prediction servers. A user may upload an amino acid and receive annotation predictions via email. Feature information is provided as easy to interpret graphics displayed on the sequence of interest, allowing for back-interpretation of the associations between features and function classes

Development of Cryogenic Current Comparators with DC Squid Readout for the Calibration of Electrical Standards

For the realization of the electrical quantum metrology triangle (V-A-Ω) a device to amplify very small currents with high precision is needed. The cryogenic current comparator (CCC) is by far the best instrument to do this. In order to make a very current sensitive CCC for calibration of electrical standards, we have developed optimum dc Superconducting QUantum Interference Devices (SQUIDs). The design, fabrication and characterisation of these devices is presented. The measurements concern the flux-to-voltage transfer and the noise properties, especially the input current noise. The optimisation of the flux transformer circuit that links the CCC with the SQUID will be treated. In addition, typical fabrication aspects of the CCC as the wires and tube assembly, the shields and the support system will be addressed

SmedGD: the Schmidtea mediterranea genome database

The planarian Schmidtea mediterranea is rapidly emerging as a model organism for the study of regeneration, tissue homeostasis and stem cell biology. The recent sequencing, assembly and annotation of its genome are expected to further buoy the biomedical importance of this organism. In order to make the extensive data associated with the genome sequence accessible to the biomedical and planarian communities, we have created the Schmidtea mediterranea Genome Database (SmedGD). SmedGD integrates in a single web-accessible portal all available data associated with the planarian genome, including predicted and annotated genes, ESTs, protein homologies, gene expression patterns and RNAi phenotypes. Moreover, SmedGD was designed using tools provided by the Generic Model Organism Database (GMOD) project, thus making its data structure compatible with other model organism databases. Because of the unique phylogenetic position of planarians, SmedGD (http://smedgd.neuro.utah.edu) will prove useful not only to the planarian research community, but also to those engaged in developmental and evolutionary biology, comparative genomics, stem cell research and regeneration

Manual GO annotation of predictive protein signatures: the InterPro approach to GO curation

InterPro amalgamates predictive protein signatures from a number of well-known partner databases into a single resource. To aid with interpretation of results, InterPro entries are manually annotated with terms from the Gene Ontology (GO). The InterPro2GO mappings are comprised of the cross-references between these two resources and are the largest source of GO annotation predictions for proteins. Here, we describe the protocol by which InterPro curators integrate GO terms into the InterPro database. We discuss the unique challenges involved in integrating specific GO terms with entries that may describe a diverse set of proteins, and we illustrate, with examples, how InterPro hierarchies reflect GO terms of increasing specificity. We describe a revised protocol for GO mapping that enables us to assign GO terms to domains based on the function of the individual domain, rather than the function of the families in which the domain is found. We also discuss how taxonomic constraints are dealt with and those cases where we are unable to add any appropriate GO terms. Expert manual annotation of InterPro entries with GO terms enables users to infer function, process or subcellular information for uncharacterized sequences based on sequence matches to predictive models

Quality of Computationally Inferred Gene Ontology Annotations

Gene Ontology (GO) has established itself as the undisputed standard for protein function annotation. Most annotations are inferred electronically, i.e. without individual curator supervision, but they are widely considered unreliable. At the same time, we crucially depend on those automated annotations, as most newly sequenced genomes are non-model organisms. Here, we introduce a methodology to systematically and quantitatively evaluate electronic annotations. By exploiting changes in successive releases of the UniProt Gene Ontology Annotation database, we assessed the quality of electronic annotations in terms of specificity, reliability, and coverage. Overall, we not only found that electronic annotations have significantly improved in recent years, but also that their reliability now rivals that of annotations inferred by curators when they use evidence other than experiments from primary literature. This work provides the means to identify the subset of electronic annotations that can be relied upon—an important outcome given that >98% of all annotations are inferred without direct curation

Infectious Disease Ontology

Technological developments have resulted in tremendous increases in the volume and diversity of the data and information that must be processed in the course of biomedical and clinical research and practice. Researchers are at the same time under ever greater pressure to share data and to take steps to ensure that data resources are interoperable. The use of ontologies to annotate data has proven successful in supporting these goals and in providing new possibilities for the automated processing of data and information. In this chapter, we describe different types of vocabulary resources and emphasize those features of formal ontologies that make them most useful for computational applications. We describe current uses of ontologies and discuss future goals for ontology-based computing, focusing on its use in the field of infectious diseases. We review the largest and most widely used vocabulary resources relevant to the study of infectious diseases and conclude with a description of the Infectious Disease Ontology (IDO) suite of interoperable ontology modules that together cover the entire infectious disease domain

FunSimMat: a comprehensive functional similarity database

Functional similarity based on Gene Ontology (GO) annotation is used in diverse applications like gene clustering, gene expression data analysis, protein interaction prediction and evaluation. However, there exists no comprehensive resource of functional similarity values although such a database would facilitate the use of functional similarity measures in different applications. Here, we describe FunSimMat (Functional Similarity Matrix, http://funsimmat.bioinf.mpi-inf.mpg.de/), a large new database that provides several different semantic similarity measures for GO terms. It offers various precomputed functional similarity values for proteins contained in UniProtKB and for protein families in Pfam and SMART. The web interface allows users to efficiently perform both semantic similarity searches with GO terms and functional similarity searches with proteins or protein families. All results can be downloaded in tab-delimited files for use with other tools. An additional XML–RPC interface gives automatic online access to FunSimMat for programs and remote services