A new phylogenetics approach and algorithm with which to chart the evolutionary history of organisms is presented. It utilizes mass spectral data produced from the proteolytic digestion of proteins, rather than partial or complete gene or translated gene sequences. The concept and validity of the approach is demonstrated herein using both theoretical and experimental mass data, together with the translated gene sequences of the hemagglutinin protein of the influenza virus. A comparison of the mass trees with conventional sequenced-based phylogenetic trees, using two separate tree comparison algorithms, reveals a high degree of similarity and congruence among the trees. Given that the mass map data can be generated more rapidly than gene sequences, even when next generation parallel sequencing is employed, mass trees offer new opportunities and advantages for phylogenetic analysis.
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
The ISME Journal: Multidisciplinary Journal of Microbial Ecology is the official Journal of the International Society for Microbial Ecology, publishing high-quality, original research papers, short communications, commentary articles and reviews in the rapidly expanding and diverse discipline of microbial ecology.
By applying the strengths of corporate models for effective teamwork, academic scientists can drive transdisciplinary research and accelerate biomedical translation.
Transdisciplinary (TD) investigations occur when individuals or teams from different disciplines converge to conduct research focused on solving a specific problem that cannot be solved by a single discipline. Working at the intersections of disciplines allows TD research teams to create new science while fostering a higher plane of enquiry—the unearthing of solutions to complex human health and societal problems. Academic medical centers are strategically positioned to drive local, national, and global TD biomedical research. However, academia’s disciplinary-bound culture—organized physically and conceptually around specific content areas—limits TD research and challenges scientists who are working within a university’s traditional department-based organization. In quest of solutions, we explore the characteristics of high-performing corporate teams that might be adapted for use in academic TD research and discuss the premise that collaborations between academic and industry teams present opportunities to harness the unique strengths of each.
Dmitry Alexeev's insight:
impressive how this is inline with what we are doing now in our team and it thought to the basis of interdisplinary research
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.
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