69 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

    The Gene Ontology resource: enriching a GOld mine

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    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

    The Gene Ontology knowledgebase in 2023

    Get PDF
    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

    ГАЗОЧУТЛИВІ СЕНСОРИ НА ОСНОВІ СПОЛУК TCNQ

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    High sensitivity and selectivity of gas sensor based on TCNQ compounds have been illustrated. The comparative analysis of the sensor response to the action of various gases and water vapour has been performed. It is shown that amplitude and speed of sensor response to the action of breath gas exceed those to the action of other gases agents by more than 1-2 orders of magnitude. It testifies about high sensitivity of the sensors under investigation to this biological media.В работе проиллюстрированы высокая чувствительность и избирательность газовых сенсоров пассивного типа на основе соединений TCNQ. Проведен сопоставительный анализ отклика сенсора на действие различных газов и паров воды. Показано, что амплитуда отклика и параметры быстродействия в среде газа, выдыхаемого человеком, более чем на 1-2 порядка превышают соответствующие уровни сигналов при воздействии других агентов. Это свидетельствует о высокой чувствительности исследованных сенсоров по отношению к данной биологической среде.В роботі проілюстровані висока чутливість та вибірковість газових сенсорів пасивного типу на основі сполук TCNQ. Проведений порівняльний аналіз відгуку сенсора на дію різних газів і парів води. Показано, що амплітуда відгуку і параметри швидкодії в середовищі газу, який видихає людина, більш ніж на 1 – 2 порядки перевищує відповідні рівні сигналів при впливі інших агентів. Це свідчить про високу чутливість досліджених сенсорів по відношенню до даного біологічного середовища

    Chronic schizophrenics with positive symptomatology have shortened EEG microstate durations

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    Objective: In young, first-episode, never-treated schizophrenics compared with controls, (a) generally shorter durations of EEG microstates were reported (Koukkou et al., Brain Topogr 6 (1994) 251; Kinoshita et al., Psychiatry Res Neuroimaging 83 (1998) 58), and (b) specifically, shorter duration of a particular class of microstates (Koenig et al., Eur Arch Psychiatry Clin Neurosci 249 (1999) 205). We now examined whether older, chronic schizophrenic patients with positive symptomatology also show these characteristics. Methods: Multichannel resting EEG (62.2 s/subject) from two subject groups, 14 patients (36.1±10.2 years old) and 13 controls (35.1±8.2 years old), all males, was analyzed into microstates using a global approach for microstate analysis that clustered the microstates into 4 classes (Koenig et al., 1999). Results: (a) Hypothesis testing of general microstate shortening supported a trend (P=0.064). (b) Two-way repeated measure ANOVA (two subject groups×4 microstate classes) showed a significant group effect for microstate duration. Posthoc tests revealed that a microstate class with brain electric field orientation from left central to right central-posterior had significantly shorter microstates in patients than controls (68.5 vs. 76.1 ms, P=0.034). Conclusions: The results were in line with the results from young, never-treated, productive patients, thus suggesting that in schizophrenic information processing, one class of mental operations might intermittently cause deviant mental constructs because of premature termination of processing

    Unsteady behavior of wall-detached flow inside a steam turbine control valve

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    Wall-detached flow inside an ultra-supercritical steam turbine control valve was comprehensively investigated with detached-eddy simulation, proper orthogonal decomposition (POD), and flow reconstruction. The dependency of the wall-detached flow on the control valve’s opening ratio and pressure ratio was established first. Scattered wall-detached-flow, merged wall-detached-flow, and intersected wall-detached-flow were then identified by distinguishing the detachment scale of the wall-detached jet. Subsequently, flow analysis was conducted in terms of the statistical flow quantities, i.e., velocity fluctuation, turbulent kinetic energy, pressure loss, and pressure fluctuation. The statistical results demonstrated that the merged wall-detached-flow facilitated the most intensive velocity and pressure fluctuations inside the steam turbine control valve. The intersected wall-detached-flow encountered significant shock-wave reflections along the downstream pipe. By conducting POD analysis and flow reconstruction on the instantaneous flow snapshots, the dominant vortex structures and energetic pressure fluctuation modes were extracted to illustrate the wall-detached flow’s unsteady behavior. The results showed that the instabilities of the scattered wall-detached-flow were primarily represented by the horizontal flapping motion of the wall-detached jet. However, for the merged wall-detached-flow, both the vertical out-phase oscillation and the horizontal flapping motion of the wall-detached jet intensified, yielding essential axial pressure fluctuation modes. As for the intersected wall-detached-flow, due to the complex wave reflections and propagations, essential regions with velocity discontinuities and diagonal crosslines with intensive pressure fluctuations formed inside the valve pipe. These findings are of great practical significance for the operation and optimization of steam turbine control valves in thermal power plants
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