Developing a Mammalian Behaviour Ontology

The use of the Entity + Quality (EQ) model in phenotypic descriptions is dependent on the use of specialised domain ontologies to define the entity under observation. A domain currently lacking a specialised ontology is mammalian behaviour, and so the Mammalian Behaviour Ontology is being constructed to address this. Top-level class distinctions are made between behavioural activities and behavioural functions of individuals, and those between two or more individuals. The ontology is manually developed and encourages contributions from domain experts

Who gets to imagine transformative change? Participation and representation in biodiversity assessments

The Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) has been mandated to assess transformative change in order to identify pathways for achieving the 2050 Vision for Biodiversity. Yet, the topic of transformative change raises significant new challenges for biodiversity assessments because it combines scientifically plausible projections about the drivers and trends of biodiversity loss with normative and collective visions of a sustainable world for nature and people. In this commentary, we argue that assessments of visions of a sustainable world should also ask ‘whose values and visions count?’ because different values and visions influence which voices and perspectives are considered relevant for generating scientific knowledge for transformative change. In particular, we argue that this situation requires rethinking modes of participation and co-production in assessments of transformative change: from consulting different groups as potential ‘users’ of assessments to seeing how visions of a sustainable world are represented through the selection of evidence and actors. In other words, assessments need to be less concerned about the inclusion and exclusion of actors, and more concerned about how these actors bring the perspectives of others with them

Forms of Innovation Inspired by Open Educational Resources: A Post-Project Analysis

It has been argued that Open Educational Resources (OER) present opportunities for innovation in education. However, there has been a lack of retrospective analysis of the forms of innovation that can emerge through OER, and the processes and challenges these entail. This paper presents a post-project analysis of the diverse uses and impacts of open courses produced through an international OER initiative. A thematic analysis of retrospective interviews and documentation from this case study is reported on, guided by a review of relevant concepts from innovation and OER literature. Through this we identify three archetypal forms through which the OER created opportunities for innovation: Specific Adoption; Preferred Practice; and Foundations for Innovation. We identify drivers and inhibitors through which these forms of innovation interacted with each other in this initiative. This elaborates on the notion that a single existing model does not capture the multi-faceted relationships between innovation and OER

The magic triangle goes MAD: experimental phasing with a bromine derivative

5-Amino-2,4,6-tribromoisophthalic acid is used as a phasing tool for protein structure determination by MAD phasing. It is the second representative of a novel class of compounds for heavy-atom derivatization that combine heavy atoms with amino and carboxyl groups for binding to proteins

Global-scale regionalization of hydrologic model parameters

Current state-of-the-art models typically applied at continental to global scales (hereafter called macroscale) tend to use a priori parameters, resulting in suboptimal streamflow (Q) simulation. For the first time, a scheme for regionalization of model parameters at the global scale was developed. We used data from a diverse set of 1787 small-to-medium sized catchments ( 10-10,000 km(2)) and the simple conceptual HBV model to set up and test the scheme. Each catchment was calibrated against observed daily Q, after which 674 catchments with high calibration and validation scores, and thus presumably good-quality observed Q and forcing data, were selected to serve as donor catchments. The calibrated parameter sets for the donors were subsequently transferred to 0.5 degrees grid cells with similar climatic and physiographic characteristics, resulting in parameter maps for HBV with global coverage. For each grid cell, we used the 10 most similar donor catchments, rather than the single most similar donor, and averaged the resulting simulated Q, which enhanced model performance. The 1113 catchments not used as donors were used to independently evaluate the scheme. The regionalized parameters outperformed spatially uniform (i.e., averaged calibrated) parameters for 79% of the evaluation catchments. Substantial improvements were evident for all major Koppen-Geiger climate types and even for evaluation catchments>5000 km distant from the donors. The median improvement was about half of the performance increase achieved through calibration. HBV with regionalized parameters outperformed nine state-of-the-art macroscale models, suggesting these might also benefit from the new regionalization scheme. The produced HBV parameter maps including ancillary data are available via

Entwicklung einer Beobachtungsdatengrundlage für DEKLIM und statistische Analyse der Klimavariabilität : Abschlussbericht zum DEKLIM-Forschungsvorhaben mit dem Förderkennzeichen 01LD0032im Auftrag des Bundesministeriums für Bildung und Forschung

Aus mehreren Datenquellen wurde ein neuer globaler Niederschlagsdatensatz für die Zeit 1951-2000 generiert, der unter der Bedingung einer Mindestverfügbarkeit von 90 % genau 9.343 Stationen umfasst. Die betreffenden Zeitreihen wurden einer umfassenden Qualitätskontrolle unterzogen, was zu äußerst zahlreichen Korrekturen führte, einschließlich Tests auf Ausreißer und Homogenität sowie Homogenisierung. Daraus entstand ein Gitterpunktdatensatz in 0,5° x 0,5°- Auflösung, was für die Landgebiete (ausgenommen Grönland und Antarktis) rund 71.000 Gitterpunkte ergibt, und über INTERNET frei verfügbar bereitgestellt. Davon ausgehend und unter Nutzung weiterer vorliegender Datensätze, insbesondere der Temperatur, wurden zunächst einige grundlegende Untersuchungen zur globalen und regionalen Klima- und Niederschlagsvariabilität durchgeführt. Diese Arbeiten umfassten Analysen der Veränderungen des global gemittelten Niederschlages und potentieller Einflussgrößen, die Neuberechnung der globalen Klimaklassifikation nach Köppen, Untersuchungen zur raumzeitlichen Struktur von Niederschlagsänderungen global sowie speziell in Afrika und schließlich Analysen der raumzeitlichen Beziehungen zwischen großräumiger atmosphärischer Zirkulation und Niederschlag im nordatlantisch-europäischen Bereich. Für weitergehende statistische Analysen wurde eine neue Methode der vollständigen Zeitreihenmodellierung entwickelt, um die die in diesen Reihen enthaltenen signifikanten Variationskomponenten durch Regressionstechniken zu erfassen und in ihrem raumzeitlichen Verhalten darzustellen. Dabei lag ein Schwerpunkt dieser Arbeiten auf der Extremwertanalyse, die es nun gestattet, unabhängig vom Verteilungstyp für beliebige Schwellenwerte den zeitlichen Verlauf der Unter- sowie Überschreitungswahrscheinlichkeit anzugeben und somit zu erkennen, inwieweit das Klima extremer geworden ist. Dabei zeigte sich je nach Region die Gumbel- oder die Weibull-Verteilung als geeignet. Regionale Schwerpunkte waren dabei u.a. Deutschland bzw. Europa, auch hinsichtlich der Erstellung neuer Klimatrendkarten nach der üblichen linearen Methode (der kleinsten Quadrate) sowie der innovativen. Weiterhin wurden nach der innovativen Methode Klimamodelldaten des Hamburger Max-Planck-Instituts für Meteorologie (IPCC Szenario A2) hinsichtlich des Niederschlag-Extremverhaltens in Europa untersucht. Schließlich erfolgte eine Abschätzung der Wiederkehrzeiten täglicher Extremniederschläge in Deutschland und deren Unsicherheit

Regional perturbation of gene transcription is associated with intrachromosomal rearrangements and gene fusion transcripts in high grade ovarian cancer.

Genomic rearrangements are a hallmark of cancer biology and progression, allowing cells to rapidly transform through alterations in regulatory structures, changes in expression patterns, reprogramming of signaling pathways, and creation of novel transcripts via gene fusion events. Though functional gene fusions encoding oncogenic proteins are the most dramatic outcomes of genomic rearrangements, we investigated the relationship between rearrangements evidenced by fusion transcripts and local expression changes in cancer using transcriptome data alone. 9,953 gene fusion predictions from 418 primary serious ovarian cancer tumors were analyzed, identifying depletions of gene fusion breakpoints within coding regions of fused genes as well as an N-terminal enrichment of breakpoints within fused genes. We identified 48 genes with significant fusion-associated upregulation and furthermore demonstrate that significant regional overexpression of intact genes in patient transcriptomes occurs within 1 megabase of 78 novel gene fusions that function as central markers of these regions. We reveal that cancer transcriptomes select for gene fusions that preserve protein and protein domain coding potential. The association of gene fusion transcripts with neighboring gene overexpression supports rearrangements as mechanism through which cancer cells remodel their transcriptomes and identifies a new way to utilize gene fusions as indicators of regional expression changes in diseased cells with only transcriptomic data

WaveCNV: allele-specific copy number alterations in primary tumors and xenograft models from next-generation sequencing.

MotivationCopy number variations (CNVs) are a major source of genomic variability and are especially significant in cancer. Until recently microarray technologies have been used to characterize CNVs in genomes. However, advances in next-generation sequencing technology offer significant opportunities to deduce copy number directly from genome sequencing data. Unfortunately cancer genomes differ from normal genomes in several aspects that make them far less amenable to copy number detection. For example, cancer genomes are often aneuploid and an admixture of diploid/non-tumor cell fractions. Also patient-derived xenograft models can be laden with mouse contamination that strongly affects accurate assignment of copy number. Hence, there is a need to develop analytical tools that can take into account cancer-specific parameters for detecting CNVs directly from genome sequencing data.ResultsWe have developed WaveCNV, a software package to identify copy number alterations by detecting breakpoints of CNVs using translation-invariant discrete wavelet transforms and assign digitized copy numbers to each event using next-generation sequencing data. We also assign alleles specifying the chromosomal ratio following duplication/loss. We verified copy number calls using both microarray (correlation coefficient 0.97) and quantitative polymerase chain reaction (correlation coefficient 0.94) and found them to be highly concordant. We demonstrate its utility in pancreatic primary and xenograft sequencing data.Availability and implementationSource code and executables are available at https://github.com/WaveCNV. The segmentation algorithm is implemented in MATLAB, and copy number assignment is implemented [email protected] informationSupplementary data are available at Bioinformatics online

POTENTIALS AND CHALLENGES OF ARTIFICIAL INTELLIGENCE IN FINANCIAL TECHNOLOGIES

Artificial Intelligence (AI) made disruptive progress over the last years, becoming a key technology across industries. In particular, AI offers novel distinctive opportunities for intelligent services in fi-nancial technology companies (Financial technologies). However, given the opportunities of AI and its associated benefits, the question arises why financial technologies fail to leverage the full potential of AI. Drawing on existing literature, this paper elaborates on the opportunities and risks associated with AI in the financial sector. This paper makes two key contributions: First, we discover the present challenges in literature to demonstrate the need for explainable AI. Second, we reveal the lack of guidance for applying explainable AI in financial technologies. We derive recommendations for re-search, policy, and practice and argue for the increased elaboration of legal frameworks for the re-sponsible use of AI

Manipulation of subsurface carbon nanoparticles in Bi2Sr2CaCu2O8+δ using a scanning tunneling microscope

We present evidence that subsurface carbon nanoparticles in Bi2Sr2CaCu2O8+δ can be manipulated with nanometer precision using a scanning tunneling microscope. High-resolution images indicate that most of the carbon particles remain subsurface after transport observable as a local increase in height as the particle pushes up on the surface. Tunneling spectra in the vicinity of these protrusions exhibit semiconducting characteristics with a band gap of approximately 1.8 eV, indicating that the incorporation of carbon locally alters the electronic properties near the surface