A study of factors related to primary grade spelling: correlations of factors studied.

Thesis (Ed.M.)--Boston Universit

MouseCyc: a curated biochemical pathways database for the laboratory mouse

MouseCyc is a database of curated metabolic pathways for the laboratory mouse

The Gene Ontology resource: enriching a GOld mine.

The Gene Ontology Consortium (GOC) provides the most comprehensive resource currently available for computable knowledge regarding the functions of genes and gene products. Here, we report the advances of the consortium over the past two years. The new GO-CAM annotation framework was notably improved, and we formalized the model with a computational schema to check and validate the rapidly increasing repository of 2838 GO-CAMs. In addition, we describe the impacts of several collaborations to refine GO and report a 10% increase in the number of GO annotations, a 25% increase in annotated gene products, and over 9,400 new scientific articles annotated. As the project matures, we continue our efforts to review older annotations in light of newer findings, and, to maintain consistency with other ontologies. As a result, 20 000 annotations derived from experimental data were reviewed, corresponding to 2.5% of experimental GO annotations. The website (http://geneontology.org) was redesigned for quick access to documentation, downloads and tools. To maintain an accurate resource and support traceability and reproducibility, we have made available a historical archive covering the past 15 years of GO data with a consistent format and file structure for both the ontology and annotations

Investigation of COVID-19 comorbidities reveals genes and pathways coincident with the SARS-CoV-2 viral disease.

The emergence of the SARS-CoV-2 virus and subsequent COVID-19 pandemic initiated intense research into the mechanisms of action for this virus. It was quickly noted that COVID-19 presents more seriously in conjunction with other human disease conditions such as hypertension, diabetes, and lung diseases. We conducted a bioinformatics analysis of COVID-19 comorbidity-associated gene sets, identifying genes and pathways shared among the comorbidities, and evaluated current knowledge about these genes and pathways as related to current information about SARS-CoV-2 infection. We performed our analysis using GeneWeaver (GW), Reactome, and several biomedical ontologies to represent and compare common COVID-19 comorbidities. Phenotypic analysis of shared genes revealed significant enrichment for immune system phenotypes and for cardiovascular-related phenotypes, which might point to alleles and phenotypes in mouse models that could be evaluated for clues to COVID-19 severity. Through pathway analysis, we identified enriched pathways shared by comorbidity datasets and datasets associated with SARS-CoV-2 infection

Automated generation of gene summaries at the Alliance of Genome Resources

Short paragraphs that describe gene function, referred to as gene summaries, are valued by users of biological knowledgebases for the ease with which they convey key aspects of gene function. Manual curation of gene summaries, while desirable, is difficult for knowledgebases to sustain. We developed an algorithm that uses curated, structured gene data at the Alliance of Genome Resources (Alliance; www.alliancegenome.org) to automatically generate gene summaries that simulate natural language. The gene data used for this purpose include curated associations (annotations) to ontology terms from the Gene Ontology, Disease Ontology, model organism knowledgebase (MOK)-specific anatomy ontologies and Alliance orthology data. The method uses sentence templates for each data category included in the gene summary in order to build a natural language sentence from the list of terms associated with each gene. To improve readability of the summaries when numerous gene annotations are present, we developed a new algorithm that traverses ontology graphs in order to group terms by their common ancestors. The algorithm optimizes the coverage of the initial set of terms and limits the length of the final summary, using measures of information content of each ontology term as a criterion for inclusion in the summary. The automated gene summaries are generated with each Alliance release, ensuring that they reflect current data at the Alliance. Our method effectively leverages category-specific curation efforts of the Alliance member databases to create modular, structured and standardized gene summaries for seven member species of the Alliance. These automatically generated gene summaries make cross-species gene function comparisons tenable and increase discoverability of potential models of human disease. In addition to being displayed on Alliance gene pages, these summaries are also included on several MOK gene pages

Social Difficulties in Youth with Autism With and Without Anxiety and ADHD Symptoms

Social difficulties inherent to autism spectrum disorder are often linked with co‐occurring symptoms of anxiety and attention deficit hyperactivity disorder (ADHD). The present study sought to examine the relation between such co‐occurring symptoms and social challenges. Parents of adolescents with autism (N = 113) reported upon social challenges via the social responsiveness scale (SRS) and anxiety and ADHD symptomatology via the Child Behavior Checklist. Results revealed differences in SRS scores across co‐occurring symptom subgroups (Anxiety, ADHD, Both, Neither)—namely, adolescents with autism and anxiety as well as those with autism, anxiety, and ADHD showed greater scores on the SRS than the other groups. Implications for research and clinical practice are discussed and recommendations are offered. Lay Summary Anxiety and attention deficit hyperactivity disorder (ADHD) symptoms are related to greater social challenges for adolescents with autism spectrum disorder. The present study found that autism with anxiety and autism with anxiety and ADHD, was related to greater social difficulties than autism alone. Findings provide further support for the intertwined nature of anxiety and ADHD symptoms in autism. What this may mean for research and clinical practice is considered and recommendations are suggested

Social Difficulties in Youth with Autism With and Without Anxiety and ADHD Symptoms

Social difficulties inherent to autism spectrum disorder are often linked with co‐occurring symptoms of anxiety and attention deficit hyperactivity disorder (ADHD). The present study sought to examine the relation between such co‐occurring symptoms and social challenges. Parents of adolescents with autism (N = 113) reported upon social challenges via the social responsiveness scale (SRS) and anxiety and ADHD symptomatology via the Child Behavior Checklist. Results revealed differences in SRS scores across co‐occurring symptom subgroups (Anxiety, ADHD, Both, Neither)—namely, adolescents with autism and anxiety as well as those with autism, anxiety, and ADHD showed greater scores on the SRS than the other groups. Implications for research and clinical practice are discussed and recommendations are offered. Lay Summary Anxiety and attention deficit hyperactivity disorder (ADHD) symptoms are related to greater social challenges for adolescents with autism spectrum disorder. The present study found that autism with anxiety and autism with anxiety and ADHD, was related to greater social difficulties than autism alone. Findings provide further support for the intertwined nature of anxiety and ADHD symptoms in autism. What this may mean for research and clinical practice is considered and recommendations are suggested

Automated generation of gene summaries at the Alliance of Genome Resources.

Short paragraphs that describe gene function, referred to as gene summaries, are valued by users of biological knowledgebases for the ease with which they convey key aspects of gene function. Manual curation of gene summaries, while desirable, is difficult for knowledgebases to sustain. We developed an algorithm that uses curated, structured gene data at the Alliance of Genome Resources (Alliance; www.alliancegenome.org) to automatically generate gene summaries that simulate natural language. The gene data used for this purpose include curated associations (annotations) to ontology terms from the Gene Ontology, Disease Ontology, model organism knowledgebase (MOK)-specific anatomy ontologies and Alliance orthology data. The method uses sentence templates for each data category included in the gene summary in order to build a natural language sentence from the list of terms associated with each gene. To improve readability of the summaries when numerous gene annotations are present, we developed a new algorithm that traverses ontology graphs in order to group terms by their common ancestors. The algorithm optimizes the coverage of the initial set of terms and limits the length of the final summary, using measures of information content of each ontology term as a criterion for inclusion in the summary. The automated gene summaries are generated with each Alliance release, ensuring that they reflect current data at the Alliance. Our method effectively leverages category-specific curation efforts of the Alliance member databases to create modular, structured and standardized gene summaries for seven member species of the Alliance. These automatically generated gene summaries make cross-species gene function comparisons tenable and increase discoverability of potential models of human disease. In addition to being displayed on Alliance gene pages, these summaries are also included on several MOK gene pages

Genomes as geography: using GIS technology to build interactive genome feature maps

BACKGROUND: Many commonly used genome browsers display sequence annotations and related attributes as horizontal data tracks that can be toggled on and off according to user preferences. Most genome browsers use only simple keyword searches and limit the display of detailed annotations to one chromosomal region of the genome at a time. We have employed concepts, methodologies, and tools that were developed for the display of geographic data to develop a Genome Spatial Information System (GenoSIS) for displaying genomes spatially, and interacting with genome annotations and related attribute data. In contrast to the paradigm of horizontally stacked data tracks used by most genome browsers, GenoSIS uses the concept of registered spatial layers composed of spatial objects for integrated display of diverse data. In addition to basic keyword searches, GenoSIS supports complex queries, including spatial queries, and dynamically generates genome maps. Our adaptation of the geographic information system (GIS) model in a genome context supports spatial representation of genome features at multiple scales with a versatile and expressive query capability beyond that supported by existing genome browsers. RESULTS: We implemented an interactive genome sequence feature map for the mouse genome in GenoSIS, an application that uses ArcGIS, a commercially available GIS software system. The genome features and their attributes are represented as spatial objects and data layers that can be toggled on and off according to user preferences or displayed selectively in response to user queries. GenoSIS supports the generation of custom genome maps in response to complex queries about genome features based on both their attributes and locations. Our example application of GenoSIS to the mouse genome demonstrates the powerful visualization and query capability of mature GIS technology applied in a novel domain. CONCLUSION: Mapping tools developed specifically for geographic data can be exploited to display, explore and interact with genome data. The approach we describe here is organism independent and is equally useful for linear and circular chromosomes. One of the unique capabilities of GenoSIS compared to existing genome browsers is the capacity to generate genome feature maps dynamically in response to complex attribute and spatial queries

Family support in practice : voices from the field

This paper revisits core family support messages for social work practice in working with children and families, linking to findings from high-profile child protection cases in the UK and the Republic of Ireland. Drawing on a comparative study where these identified practice messages were explored through the lens of testimony of family support workers in the UK and Ireland, these core messages are examined. Operating with hard-to-engage children and parents, we hear how families and family support worker colleagues now view the core functions of child and family work across both jurisdictions (Ireland and England). The authors argue that by naming a more detailed set of practices that are deemed as most useful by families, based on the benefits and challenges of intensive family support work, key messages arise that have major resonance for social work and multiagency practice into the future. A basic message from this study is that valuable lessons on engagement and intervention with families can be drawn for professionals by examining the practice elements of this group of paraprofessionals in the child and family arena. This paper adds to debates on the role of support and intervention in social work and family support work