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An expanded evaluation of protein function prediction methods shows an improvement in accuracy
(2016)
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.
Genetisch bedingte und genetisch mitbedingte Erkrankungen im Krankengut einer Allgemeinarztpraxis
(2003)
Statistische Erfassung von genetisch bedingten und genetisch mitbedingten Erkrankungen einer Allgemeinarztpraxis. Es soll verdeutlicht werden, dass die Allgemeinmedizin und die Humangenetik im Rahmen der drastischen genetischen Entwicklung der Forschung enger zusammenarbeiten und die Lehre in der Ausbildung der Allgemeinmediziner intensivierte werden sollte.
While the place of birth plays a crucial role for women’s birth experiences, the interest in out-of-hospital births has increased during the Covid-19 pandemic. Related to this, various international policies recommend enabling women to choose where to give birth. We aimed to analyze Swiss women’s choice between birth hospitals and birth centers. Employing spatial accessibility analysis, we incorporated four data types: highly disaggregated population data, administrative data, street network data, addresses of birth hospitals and birth centers. 99.8% of Swiss women of childbearing age were included in the analysis (N = 1.896.669). We modelled car travel times from a woman’s residence to the nearest birth hospital and birth center. If both birth settings were available within 30 minutes, a woman was considered to have a true choice. Only 58.2% of women had a true choice. This proportion varied considerably across Swiss federal states. The main barrier to a true choice was limited accessibility of birth centers. Median travel time to birth hospitals was 9.8 (M = 12.5), to birth centers 23.9 minutes (M = 28.5). Swiss women are insufficiently empowered to exercise their reproductive autonomy as their choice of place of birth is significantly limited by geographical constraints. It is an ethical and medical imperative to provide women with a true choice. We provide high-resolution insights into the accessibility of birth settings and strong arguments to (re-)examine the need for further birth centers (and birth hospitals) in specific geographical areas. Policy-makers are obligated to improve the accessibility of birth centers to advance women’s autonomy and enhance maternal health outcomes after childbirth. The Covid-19 pandemic offers an opportunity to shift policy.
Inherited cardiomyopathies are characterized by clinical and genetic heterogeneity that challenge genetic diagnostics. In this study, we examined the diagnostic benefit of exome data compared to targeted gene panel analyses, and we propose new candidate genes. We performed exome sequencing in a cohort of 61 consecutive patients with a diagnosis of cardiomyopathy or primary arrhythmia, and we analyzed the data following a stepwise approach. Overall, in 64% of patients, a variant of interest (VOI) was detected. The detection rate in the main sub-cohort consisting of patients with dilated cardiomyopathy (DCM) was much higher than previously reported (25/36; 69%). The majority of VOIs were found in disease-specific panels, while a further analysis of an extended panel and exome data led to an additional diagnostic yield of 13% and 5%, respectively. Exome data analysis also detected variants in candidate genes whose functional profile suggested a probable pathogenetic role, the strongest candidate being a truncating variant in STK38. In conclusion, although the diagnostic yield of gene panels is acceptable for routine diagnostics, the genetic heterogeneity of cardiomyopathies and the presence of still-unknown causes favor exome sequencing, which enables the detection of interesting phenotype–genotype correlations, as well as the identification of novel candidate genes.