Several technical challenges in metagenomic data analysis, including assembling metagenomic sequence data or identifying operational taxonomic units, are both significant and well known. These forms of analysis are increasingly cited as conceptually flawed, given the extreme variation within traditionally defined species and rampant horizontal gene transfer. Furthermore, computational requirements of such analysis have hindered content-based organization of metagenomic data at large scale.
How can runners improve their performance, weight and fitness? Researchers have produced a mathematical model to optimize running, which could lead to personal e-coaching customized to each individual's physiological state. It also confirms a well-known fact in the sports community: runners who vary their speed spend their energy better and thus run longer. Mathematics gives them the opportunity to switch from simple statistical tools to personalized sporting advice.
Despite identifying abundant genes capable of conferring antibiotic resistance in soil microorganisms, a study finds that few are shared by human pathogens and that there is little transfer of the genes within the soil communities. See Letter p.612
The semantic comparisons of Gene Ontology (GO) annotations provide quantitative ways to compute similarities between genes and gene groups, and have became important basis for many bioinformatics analysis approaches. GOSemSim is an R package for semantic similarity computation among GO terms, sets of GO terms, gene products and gene clusters.
Nature is the international weekly journal of science: a magazine style journal that publishes full-length research papers in all disciplines of science, as well as News and Views, reviews, news, features, commentaries, web focuses and more, covering all branches of science and how science impacts upon all aspects of society and life.
Dmitry Alexeev's insight:
having a lot of data on metaaproteomics we are out to search all the possibilities data can provide
Cell-biological processes are regulated through a complex network of interactions between genes and their products. The processes, their activating conditions and the associated transcriptional responses are often unknown. Organism-wide modeling of network activation can reveal unique and shared mechanisms between tissues, and potentially as yet unknown processes. The same method can also be applied to cell-biological conditions in one or more tissues.
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