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https://www.selleckchem.com/products/sgc-0946.html Lp(a) APS was constant across concentration quintiles and, overall, lower than APS based on currently published data, whereas results were similar for apoA-I and apoB. CONCLUSION Using a fully Biological Variation Data Critical Appraisal Checklist (BIVAC)-compliant protocol, our study data confirm BV estimates of Lp(a) listed in the European Federation of Clinical Chemistry and Laboratory Medicine database and reinforce concerns expressed in recent articles regarding the suitability of older APS recommendations for Lp(a) measurements. Given the heterogeneity of Lp(a), more BIVAC-compliant studies on large numbers of individuals of different ethnic groups would be desirable. © American Association for Clinical Chemistry 2020. All rights reserved. For permissions, please email journals.permissions@oup.com.SUMMARY The exponential growth in available genomic data is expected to reach full sequencing of a million genomes in the coming decade. Improving and developing methods to analyze these genomes and to reveal their utility is of major interest in a wide variety of fields such as comparative and functional genomics, evolution and bioinformatics. Phylogenetic profiling is an established method for predicting functional interactions between proteins based on similarities in their evolutionary patterns across species. Proteins that function together (i.e. generate complexes, interact in the same pathways or improve adaptation to environmental niches) tend to show coordinated evolution across the tree of life. The normalized phylogenetic profiling (NPP) method takes into account minute changes in proteins across species to identify protein co-evolution. Despite the success of this method, it is still not clear what set of parameters is required for optimal use of co-evolution in predicting functional interactions. Moreover, it is not clear if pathway evolution or function should direct parameter choice. Here we create a r

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