Additional Gene Ontology structure for improved biological reasoning

Myhre, Simen; Tveit, Henrik; Møllestad, Torulf; Lægreid, Astrid

doi:10.1093/bioinformatics/btl334

Cited by 179 publications

(145 citation statements)

References 14 publications

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“…GO terms were predicted using Blast2GO (version 2.5.2) (Conesa et al 2005). GO terms were augmented with Interpro annotations using ANNEX (Myhre et al 2006). MapMan bins were annotated with Mercator (Lohse et al 2014).…”

Section: Feature Annotationmentioning

confidence: 99%

Venus flytrap carnivorous lifestyle builds on herbivore defense strategies

et al. 2016

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Although the concept of botanical carnivory has been known since Darwin's time, the molecular mechanisms that allow animal feeding remain unknown, primarily due to a complete lack of genomic information. Here, we show that the transcriptomic landscape of the Dionaea trap is dramatically shifted toward signal transduction and nutrient transport upon insect feeding, with touch hormone signaling and protein secretion prevailing. At the same time, a massive induction of general defense responses is accompanied by the repression of cell death–related genes/processes. We hypothesize that the carnivory syndrome of Dionaea evolved by exaptation of ancient defense pathways, replacing cell death with nutrient acquisition.

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Section: Feature Annotationmentioning

confidence: 99%

Venus flytrap carnivorous lifestyle builds on herbivore defense strategies

et al. 2016

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“…On the other hand, domain-specific information extraction systems regarding event-level information with automatic causality recognition are proposed in [18]. Human gene ontologies are described in [19,20]. U-Compare, an integrated text mining and NLP system based on the Unstructured Information Management (UIMA) Framework (UIMA: http://uima.apache.org/), is presented in [21].…”

Section: Previous Workmentioning

confidence: 99%

Tensor-Based Semantically-Aware Topic Clustering of Biomedical Documents

et al. 2017

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Abstract:Biomedicine is a pillar of the collective, scientific effort of human self-discovery, as well as a major source of humanistic data codified primarily in biomedical documents. Despite their rigid structure, maintaining and updating a considerably-sized collection of such documents is a task of overwhelming complexity mandating efficient information retrieval for the purpose of the integration of clustering schemes. The latter should work natively with inherently multidimensional data and higher order interdependencies. Additionally, past experience indicates that clustering should be semantically enhanced. Tensor algebra is the key to extending the current term-document model to more dimensions. In this article, an alternative keyword-term-document strategy, based on scientometric observations that keywords typically possess more expressive power than ordinary text terms, whose algorithmic cornerstones are third order tensors and MeSH ontological functions, is proposed. This strategy has been compared against a baseline using two different biomedical datasets, the TREC (Text REtrieval Conference) genomics benchmark and a large custom set of cognitive science articles from PubMed.

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“…org) from the best hits obtained from the BLASTx search against the nonredundant database (Myhre et al, 2006;Gotz et al, 2008). These results were then sorted by GO categories using in-house Perl scripts.…”

Section: Annotation Of Mrnasmentioning

confidence: 99%

Differential gene expression in pre-laying and laying period ovaries of Sichuan White geese (Anser cygnoides)

Ding¹,

Han²,

Zhao³

et al. 2015

Genet. Mol. Res.

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ABSTRACT. Geese are an economically important poultry species worldwide. Their superior meat production performance and meat quality make them a popular food. However, they are not bred worldwide because their poor laying capacity increases farming costs. To gain a global view of the genes that are differentially expressed between prelaying (P) and laying (L) periods and to develop a database for further studies, we performed large-scale transcriptome sequencing of ovarian tissue collected from Anser cygnoides. In total, 30,151,422 raw reads, with an average length of 151 bp and a total length of 4,552,864,722 bp, were obtained. After primers and adaptors were removed, 19,167,132 clean reads, with an average length of 134.5 bp and a total length of 2,577,297,281 bp, were obtained, among which 1,268,906,694 bp and 1,308,390,587 bp were from L and P ovarian tissue, respectively. The 16,605 assembled sequences were further functionally annotated by comparing their sequences to different protein and functional domain databases and assigning gene ontology (GO) terms. Of these, 511 assembled sequences were considered differentially expressed based on the 2-fold method, among which 396 were assigned at least one GO term. Digital expression analysis using the Kyoto encyclopedia of genes and genomes annotation identified 121 genes that were differentially expressed in the P vs L periods. Five of these are of special interest for further investigation of their roles in determining high reproductive performance. This study provides valuable information and sequence resources for uncovering genes determining high egg-laying performance and for future functional genomics analysis of geese.

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Additional Gene Ontology structure for improved biological reasoning

Abstract: The Second GO is publicly available through the GO Annotation Toolbox (GOAT.no): http://www.goat.no.

Cited by 179 publications

References 14 publications

Venus flytrap carnivorous lifestyle builds on herbivore defense strategies

Venus flytrap carnivorous lifestyle builds on herbivore defense strategies

Tensor-Based Semantically-Aware Topic Clustering of Biomedical Documents

Differential gene expression in pre-laying and laying period ovaries of Sichuan White geese (Anser cygnoides)

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