Project description:The Mammalian Methylation Consortium aimed to characterize the relationship between cytosine methylation levels and a) species characteristics such as maximum lifespan and b) individual sample characteristics such as age, sex, tissue type. Both supervised machine learning approaches and unsupervised machine learning approaches were applied to the data as described in the citations. To facilitate comparative analyses across species, the mammalian methylation consortium applied a single measurement platform (the mammalian methylation array, GPL28271) to n=15216 DNA samples derived from 70 tissue types of 348 different mammalian species (331 eutherian-, 15 marsupial-, and 2 monotreme species). Most of the CpGs are located in highly conserved stretches of DNA but not all CpGs apply to all species as detailed in the description of the platform, GPL28271 and on https://github.com/shorvath/MammalianMethylationConsortium/.
Project description:Despite direct or indirect efforts of proteomic community, the fraction of blind spots on the protein map is still significant. Almost 10% (?) of human master protein has no experimental validation up to now. Apparently, proteomics has reached the stage where all easy scores are achieved (?), and every next identification requires more intension and curiosity in expansion of unusual types of biomaterial and/or conditions. In this article we discuss the current state of missing proteins search conducted by eclectic Russian Consortium in frame of C-HPP. We accumulated various data, obtained by Russian Proteomic Consortium.
