Some new results on majority-logic codes for correction of random errors

The main advantages of random error-correcting majority-logic codes and majority-logic decoding in general are well known and two-fold. Firstly, they offer a partial solution to a classical coding theory problem, that of decoder complexity. Secondly, a majority-logic decoder inherently corrects many more random error patterns than the minimum distance of the code implies is possible. The solution to the decoder complexity is only a partial one because there are circumstances under which a majority-logic decoder is too complex and expensive to implement. [Continues.

Understanding the autism assessment experience for young people

Purpose: Government reports highlight global statistics of the number of autistic people admitted to psychiatric inpatient settings, however it is not clear the types of settings included in these reports, or the rate compared to non-autistic people. Literature reporting on autism demonstrates high rates of co-occurring mental health difficulties for autistic people, including more severe and life-threatening incidents often leading to inpatient admissions. National guidance suggests autistic people should be offered specialist care and treatment however, it is often reported this population are admitted to unsuitable, generic settings. This meta-analysis aims to synthesise the empirical literature reporting prevalence of autistic people in generic inpatient settings, with the aim to emphasise the over-representation. Method: A systematic search of three databases (Ovid PsycInfo, Ovid Embase and Ovid Medline) was conducted on 25th July 2022. Specific search criteria were used to identify papers reporting on autistic people and psychiatric inpatient settings. Returned studies were reviewed using established inclusion and exclusion criteria. Data from the included studies were extracted and analysed. A quality assessment including risk of bias and design hierarchy were undertaken and subgroup analyses were performed. Results: Fifteen studies were included in the review and rated in terms of methodological quality. The meta-analysis estimated the prevalence of autistic people in psychiatric inpatient settings to be 11%, with a 95% confidence interval of 6-16% (13% for child inpatient settings and 4% for adult inpatient settings). The prevalence rate found by the review is much higher than the prevalence of autistic people in the general population. Significantly higher prevalence was estimated for studies of children vs. adults. High levels of heterogeneity were explored statistically. Discussion: This review indicates that autistic people are over-represented in psychiatric inpatient settings. Differences in recruitment of autistic people, detection of autism, the settings themselves and referral pathways for autistic patients to inpatient settings may play a role in the prevalence rates found. Furthermore, the level of reporting bias was found to be significant where unclear reporting of prevalence figures suggested smaller event rates and may have missed the full autistic population in their calculations

Blood donation in a multicultural Australia-complexities of cultural misunderstanding and intergenerational conflict for African communities

Australia is a multicultural country, with 44% of the population either born overseas or having one overseas born parent (Australian Bureau of Statistics 2007). While Australia purports to embrace and leverage these cultural differences, this does possibly raise issues in regards to marketing to a range of culturally different groups within the community (Nwankwo and Lindridge 1998). Many organisations will potentially be unable to develop strategies targeting multiple cultural groups (Wilkinson and Cheng 1999). However, Australian nonprofit marketers may have a more pressing need to target distinctive cultural segments, especially as they often have a mission designed to foster wider social inclusion or to address the needs of specific cultural groups (Centre for Culture, Ethnicity and Health 2004, Renzaho 2007). This requires that marketers develop culturally relevant marketing activities going beyond simply advertising in different languages (Noble and Camit 2005). This paper seeks to outline some of the cultural challenges related to donating blood using Sub-Saharan African migrants as an example

FlyBase 102—advanced approaches to interrogating FlyBase

FlyBase (http://flybase.org) is the leading website and database of Drosophila genes and genomes. Whether you are using the fruit fly Drosophila melanogaster as an experimental system or wish to understand Drosophila biological knowledge in relation to human disease or to other model systems, FlyBase can help you successfully find the information you are looking for. Here, we demonstrate some of our more advanced searching systems and highlight some of our new tools for searching the wealth of data on FlyBase. The first section explores gene function in FlyBase, using our TermLink tool to search with Controlled Vocabulary terms and our new RNA-Seq Search tool to search gene expression. The second section of this article describes a few ways to search genomic data in FlyBase, using our BLAST server and the new implementation of GBrowse 2, as well as our new FeatureMapper tool. Finally, we move on to discuss our most powerful search tool, QueryBuilder, before describing pre-computed cuts of the data and how to query the database programmatically

Natural language processing in aid of FlyBase curators.

BACKGROUND: Despite increasing interest in applying Natural Language Processing (NLP) to biomedical text, whether this technology can facilitate tasks such as database curation remains unclear. RESULTS: PaperBrowser is the first NLP-powered interface that was developed under a user-centered approach to improve the way in which FlyBase curators navigate an article. In this paper, we first discuss how observing curators at work informed the design and evaluation of PaperBrowser. Then, we present how we appraise PaperBrowser's navigational functionalities in a user-based study using a text highlighting task and evaluation criteria of Human-Computer Interaction. Our results show that PaperBrowser reduces the amount of interactions between two highlighting events and therefore improves navigational efficiency by about 58% compared to the navigational mechanism that was previously available to the curators. Moreover, PaperBrowser is shown to provide curators with enhanced navigational utility by over 74% irrespective of the different ways in which they highlight text in the article. CONCLUSION: We show that state-of-the-art performance in certain NLP tasks such as Named Entity Recognition and Anaphora Resolution can be combined with the navigational functionalities of PaperBrowser to support curation quite successfully.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

FlyBase 101 – the basics of navigating FlyBase

FlyBase (http://flybase.org) is the leading database and web portal for genetic and genomic information on the fruit fly Drosophila melanogaster and related fly species. Whether you use the fruit fly as an experimental system or want to apply Drosophila biological knowledge to another field of study, FlyBase can help you successfully navigate the wealth of available Drosophila data. Here, we review the FlyBase web site with novice and less-experienced users of FlyBase in mind and point out recent developments stemming from the availability of genome-wide data from the modENCODE project. The first section of this paper explains the organization of the web site and describes the report pages available on FlyBase, focusing on the most popular, the Gene Report. The next section introduces some of the search tools available on FlyBase, in particular, our heavily used and recently redesigned search tool QuickSearch, found on the FlyBase homepage. The final section concerns genomic data, including recent modENCODE (http://www.modencode.org) data, available through our Genome Browser, GBrowse

FAIR, ethical, and coordinated data sharing for COVID-19 response: a scoping review and cross-sectional survey of COVID-19 data sharing platforms and registries

Data sharing is central to the rapid translation of research into advances in clinical medicine and public health practice. In the context of COVID-19, there has been a rush to share data marked by an explosion of population-specific and discipline-specific resources for collecting, curating, and disseminating participant-level data. We conducted a scoping review and cross-sectional survey to identify and describe COVID-19-related platforms and registries that harmonise and share participant-level clinical, omics (eg, genomic and metabolomic data), imaging data, and metadata. We assess how these initiatives map to the best practices for the ethical and equitable management of data and the findable, accessible, interoperable, and reusable (FAIR) principles for data resources. We review gaps and redundancies in COVID-19 data-sharing efforts and provide recommendations to build on existing synergies that align with frameworks for effective and equitable data reuse. We identified 44 COVID-19-related registries and 20 platforms from the scoping review. Data-sharing resources were concentrated in high-income countries and siloed by comorbidity, body system, and data type. Resources for harmonising and sharing clinical data were less likely to implement FAIR principles than those sharing omics or imaging data. Our findings are that more data sharing does not equate to better data sharing, and the semantic and technical interoperability of platforms and registries harmonising and sharing COVID-19-related participant-level data needs to improve to facilitate the global collaboration required to address the COVID-19 crisis

An open and transparent process to select ELIXIR Node Services as implemented by ELIXIR-UK

ELIXIR is the European infrastructure established specifically for the sharing and sustainability of life science data. To provide up-to-date resources and services, ELIXIR needs to undergo a continuous process of refreshing the services provided by its national Nodes. Here we present the approach taken by ELIXIR-UK to address the advice by the ELIXIR Scientific Advisory Board that Nodes need to develop “mechanisms to ensure that each Node continues to be representative of the Bioinformatics efforts within the country”. ELIXIR-UK put in place an open and transparent process to identify potential ELIXIR resources within the UK during late 2015 and early to mid-2016. Areas of strategic strength were identified and Expressions of Interest in these priority areas were requested from the UK community. A set of criteria were established, in discussion with the ELIXIR Hub, and prospective ELIXIR-UK resources were assessed by an independent committee set up by the Node for this purpose. Of 19 resources considered, 14 were judged to be immediately ready to be included in the UK ELIXIR Node’s portfolio. A further five were placed on the Node’s roadmap for future consideration for inclusion. ELIXIR-UK expects to repeat this process regularly to ensure its portfolio continues to reflect its community’s strengths

FlyBase: enhancing Drosophila Gene Ontology annotations

FlyBase (http://flybase.org) is a database of Drosophila genetic and genomic information. Gene Ontology (GO) terms are used to describe three attributes of wild-type gene products: their molecular function, the biological processes in which they play a role, and their subcellular location. This article describes recent changes to the FlyBase GO annotation strategy that are improving the quality of the GO annotation data. Many of these changes stem from our participation in the GO Reference Genome Annotation Project—a multi-database collaboration producing comprehensive GO annotation sets for 12 diverse species

The Drosophila phenotype ontology

BACKGROUND: Phenotype ontologies are queryable classifications of phenotypes. They provide a widely-used means for annotating phenotypes in a form that is human-readable, programatically accessible and that can be used to group annotations in biologically meaningful ways. Accurate manual annotation requires clear textual definitions for terms. Accurate grouping and fruitful programatic usage require high-quality formal definitions that can be used to automate classification. The Drosophila phenotype ontology (DPO) has been used to annotate over 159,000 phenotypes in FlyBase to date, but until recently lacked textual or formal definitions. RESULTS: We have composed textual definitions for all DPO terms and formal definitions for 77% of them. Formal definitions reference terms from a range of widely-used ontologies including the Phenotype and Trait Ontology (PATO), the Gene Ontology (GO) and the Cell Ontology (CL). We also describe a generally applicable system, devised for the DPO, for recording and reasoning about the timing of death in populations. As a result of the new formalisations, 85% of classifications in the DPO are now inferred rather than asserted, with much of this classification leveraging the structure of the GO. This work has significantly improved the accuracy and completeness of classification and made further development of the DPO more sustainable. CONCLUSIONS: The DPO provides a set of well-defined terms for annotating Drosophila phenotypes and for grouping and querying the resulting annotation sets in biologically meaningful ways. Such queries have already resulted in successful function predictions from phenotype annotation. Moreover, such formalisations make extended queries possible, including cross-species queries via the external ontologies used in formal definitions. The DPO is openly available under an open source license in both OBO and OWL formats. There is good potential for it to be used more broadly by the Drosophila community, which may ultimately result in its extension to cover a broader range of phenotypes