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We present radio spectral analyses for a sample of 29 radio-quiet (RQ) and three radio-loud (RL) narrow-line Seyfert 1 galaxies (NLS1s) detected with the Australia Telescope Compact Array at both 5.5 and 9.0 GHz. The sample is characterized by Lbol/LEdd > 0.15. The radio slopes in 25 of the 29 RQ NLS1s are steep (α5.5–9.0 < −0.5), as found in earlier studies of RQ high Lbol/LEdd active galactic nuclei (AGN). This steep radio emission may be related to AGN-driven outflows, which are likely more prevalent in high Lbol/LEdd AGN. In two of the three RL NLS1s, the radio slopes are flat or inverted (α5.5–9.0 > −0.5), indicating a compact optically thick source, likely a relativistic jet. Archival data at 3.0, 1.4, and 0.843 GHz are also compiled, yielding a sample of 17 NLS1s detected in three bands or more. In nine objects, the radio spectra flatten at lower frequencies, with median slopes of α5.5–9.0 = −1.21 ± 0.17, flattening to α3.0–5.5 = −0.97 ± 0.27, and to α1.4–3.0 = −0.63 ± 0.16. A parabolic fit suggests a median spectral turnover of ∼1 GHz, which implies synchrotron self-absorption in a source with a size of only a fraction of 1 pc, possibly a compact wind or a weak jet. Two objects show significant spectral steepening to α < −2 above 3 or 5 GHz, which may suggest relic emission from past ejection of radio emitting plasma, of the order of a few years to a few decades ago. Finally, two objects present a single spectral slope consistent with star-forming activity.

 

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.

 

Abstract 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.