1,085 research outputs found

    The Gene Ontology knowledgebase in 2023

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    The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project

    Women’s views about current and future management of Ductal Carcinoma in Situ (DCIS): a mixed-methods study

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    Management of low-risk ductal carcinoma in situ (DCIS) is controversial, with clinical trials currently assessing the safety of active monitoring amidst concern about overtreatment. Little is known about general community views regarding DCIS and its management. We aimed to explore women's understanding and views about low-risk DCIS and current and potential future management options. This mixed-method study involved qualitative focus groups and brief quantitative questionnaires. Participants were screening-aged (50-74 years) women, with diverse socioeconomic backgrounds and no personal history of breast cancer/DCIS, recruited from across metropolitan Sydney, Australia. Sessions incorporated an informative presentation interspersed with group discussions which were audio-recorded, transcribed and analysed thematically. Fifty-six women took part in six age-stratified focus groups. Prior awareness of DCIS was limited, however women developed reasonable understanding of DCIS and the relevant issues. Overall, women expressed substantial support for active monitoring being offered as a management approach for low-risk DCIS, and many were interested in participating in a hypothetical clinical trial. Although some women expressed concern that current management may sometimes represent overtreatment, there were mixed views about personally accepting monitoring. Women noted a number of important questions and considerations that would factor into their decision making. Our findings about women's perceptions of active monitoring for DCIS are timely while results of ongoing clinical trials of monitoring are awaited, and may inform clinicians and investigators designing future, similar trials. Exploration of offering well-informed patients the choice of non-surgical management of low-risk DCIS, even outside a clinical trial setting, may be warranted

    Rapid identification of drought tolerant sugarcane epimutants via in vitro chimera dissolution and near infrared screening ex vitro

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    Drought is an important stress factor with increased severity due to climate change. Previous research characterised drought-tolerant sugarcane epimutants over several rounds of ex vitro screening on vegetatively derived survivors. In the present work, a quicker in vitro chimera dissolution over four stress rounds is reported in cultivar N41. Overall, epimutants were significantly taller (1.32‚Äď2.20¬†cm), had wider leaves (up to 0.40¬†cm) and thicker stems (0.26‚Äď0.37¬†cm) than the stressed control (S N41) with up to 0.92¬†cm height, 0.27¬†cm leaf width, and 0.18¬†cm stem diameter over the last three in vitro stress rounds. The Dry 8, Dry 5, Dry 2, Dry 3, and Dry 1 were identified as lines tolerant to osmotic and heat stress. When detached leaves were treated with polyethylene glycol for 7 days, Dry 8 and Dry 5 showed significantly higher green leaf areas of 90.02 and 80.29%, respectively, than S N41 with 60.23%. Following ex vitro drought selection, Dry 8 had a rapid growth rate (0.39¬†cm/day) compared with S N41 (0.23¬†cm/day). Based on near-infrared spectroscopy (NIRS) data, Dry 1, Dry 2, Dry 5, and Dry 8 were grouped with the non-stressed control (NS N41). The Dry 5 and Dry 8 epilines were persistently tolerant to osmotic, heat and drought stresses in pot-based bioassays and were identified as the best epilines in the study. These results suggest that stable epilines with drought tolerance potential can be obtained through in vitro screening methods and ex vitro NIR-based phenotyping, allowing a more rapid throughput of useful lines than in previous studies

    The Gene Ontology knowledgebase in 2023

    No full text
    The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project

    The Gene Ontology Knowledgebase in 2023

    No full text
    : The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and non-coding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains and updates the GO knowledgebase. The GO knowledgebase consists of three components: 1) the Gene Ontology - a computational knowledge structure describing functional characteristics of genes; 2) GO annotations - evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and 3) GO Causal Activity Models (GO-CAMs) - mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised and updated in response to newly published discoveries, and receives extensive QA checks, reviews and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, as well as guidance on how users can best make use of the data we provide. We conclude with future directions for the project

    Erratum to: Searches for long-lived charged particles in pp collisions at s \sqrt{\textrm{s}} = 7 and 8 TeV