Sentence examples for art annotation from inspiring English sources

We confirmed that this is the case for the potato genome by analyzing six state of the art annotation pipelines.

Experimental results on two standard annotation datasets have shown the effectiveness of the proposed method by comparing with several state-of-the-art annotation methods.

Furthermore, we evaluate six state-of-the-art annotation pipelines and show that their predictions are markedly dissimilar (Jaccard similarity coefficient of 0.27 between pipelines on average).

With ClinVar and CADD, VariantDB thus contains two state-of-the-art annotation resources to interpret the functional impact of variants, in addition to several other widely used annotation sources.

Our approach to utilize state-of-the-art functional annotation and implement trans-ethnic association analysis for discovery and fine-mapping offers a framework for further follow-up and characterization of GWAS signals of complex trait loci.

Our experiments show that, using only a linear classifier, the newly learned features produce results on the CAL500 dataset comparable to state-of-the-art music annotation and retrieval systems.

Finally, using experimentally validated functional variants from the literature and variants possibly implicated in disease by previous studies, we rigorously compare FUN-LDA with state-of-the-art functional annotation methods and show that FUN-LDA has better prediction accuracy and higher resolution than these methods.

Detailed functional characterizations are thus required to further explore the evolutionary traits of genes linked to particular cellular processes, facilitated by state of the art functional annotations provided by the Gene Ontology (GO) (GO-Consortium 2010) and InterPro (Hunter et al. 2009) resources.

The low throughput and labor-intensive nature of Edman degradation and two dimensional gel electrophoresis approaches make them incompatible with state of the art high throughput annotation pipelines.

As emerged from the ENCODE Genome Annotation Assessment Project (EGASP) [ 8, 17], a community experiment to access the state of the art in genome annotation within the human ENCODE regions [ 18– 20], programs relying on extrinsic evidence such as expressed sequence tags (ESTs) or mRNA sequences were found to be the most accurate in reproducing the manually curated annotations [ 8].

The state-of-the-art in probabilistic annotation established by Rogers et al. (2009) did not include an integrative computational implementation, a practical connection to public biological databases such as KEGG or MetaCyc (Altman et al., 2013) or a network-based output visualization schema.