An expanded evaluation of protein function prediction methods shows an improvement in accuracy

Background: A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging. Results: We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2. Conclusions: The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent. Keywords: Protein function prediction, Disease gene prioritizationpublishedVersio

An Expanded Evaluation of Protein Function Prediction Methods Shows an Improvement In Accuracy

Background: A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging. Results: We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2. Conclusions: The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent

<it>Kocuria varians </it>infection associated with brain abscess: A case report

<p>Abstract</p> <p>Background</p> <p><it>Kocuria</it>, established by Stackebrandt et al., previously was classified into <it>Micrococcus</it>. Only two species, <it>K. rosea </it>and <it>K. kristinae </it>are reported to be associated as pathogenic and found with catheter-related bacteremia and acute cholecystitis.</p> <p>Case presentation</p> <p>We herein report the first case of brain abscess caused by <it>Kocuria varians</it>, a gram-positive microorganism, in a 52-year-old man. Hematogenous spread is the probable pathogenesis.</p> <p>Conclusions</p> <p>This report presents a case of <it>Kocuria varians </it>brain abscess successfully treated with surgical excision combined with antimicrobial therapy. In addition, Vitek 2 system has been used to identify and differentiate between coagulase-negative staphylococcus.</p

Angiopoietin 2 Mediates the Differentiation and Migration of Neural Progenitor Cells in the Subventricular Zone after Stroke*

Ischemic stroke stimulates neurogenesis in the adult rodent brain. The molecules underlying stroke-induced neurogenesis have not been fully investigated. Using real-time reverse transcription-PCR, we found that stroke substantially up-regulated angiopoietin 2 (ANG2), a proangiogenic gene, expression in subventricular zone neural progenitor cells. Incubation of neural progenitor cells with recombinant human ANG2 significantly increased the number of β-III tubulin-positive cells, a marker of immature neurons, but did not alter the number of glial fibrillary acidic protein (GFAP)-positive cells, a marker of astrocytes, suggesting that ANG2 promotes neuronal differentiation. Blockage of the ANG2 receptor, Tie2, with small interference RNA (siRNA)-Tie2 attenuated recombinant human ANG2 (rhANG2)-increased β-III tubulin mRNA levels compared with levels in the progenitor cells transfected with control siRNA. Chromatin immunoprecipitation analysis revealed that CCAAT/enhancer-binding protein (C/EBPβ) up-regulated by rhANG2 bound to β-III tubulin, which is consistent with published data that there are several C/EBPβ binding sites in the promoter of β-III tubulin gene. In addition, rhANG2 enhanced migration of neural progenitor cells measured by single neurosphere assay. Blockage of Tie2 with siRNA-Tie2 and a Tie2-neutralizing antibody did not suppress ANG2-enhanced migration. However, inhibition of matrix metalloproteinases with GM6001 blocked ANG2-enhanced migration. Collectively, our data suggest that interaction of ANG2, a proangiogenic factor, with its receptor Tie2 promotes neural progenitor cell differentiation into neuronal lineage cells, whereas ANG2 regulates neural progenitor cell migration through matrix metalloproteinases, which do not require its receptor Tie2