Big data - a 21st century science Maginot Line? No-boundary thinking: shifting from the big data paradigm.

Whether your interests lie in scientific arenas, the corporate world, or in government, you have certainly heard the praises of big data: Big data will give you new insights, allow you to become more efficient, and/or will solve your problems. While big data has had some outstanding successes, many are now beginning to see that it is not the Silver Bullet that it has been touted to be. Here our main concern is the overall impact of big data; the current manifestation of big data is constructing a Maginot Line in science in the 21st century.

Whole-genome analyses resolve early branches in the tree of life of modern birds.

To better determine the history of modern birds, we performed a genome-scale phylogenetic analysis of 48 species representing all orders of Neoaves using phylogenomic methods created to handle genome-scale data. We recovered a highly resolved tree that confirms previously controversial sister or close relationships. We identified the first divergence in Neoaves, two groups we named Passerea and Columbea, representing independent lineages of diverse and convergently evolved land and water bird species.

Metagenomes from thawing low-soil-organic-carbon mineral cryosols and permafrost of the canadian high arctic.

Microbial release of greenhouse gases from thawing permafrost is a global concern. Seventy-six metagenomes were generated from low-soil-organic-carbon mineral cryosols from Axel Heiberg Island, Nunavut, Canada, during a controlled thawing experiment. Permafrost thawing resulted in an increase in anaerobic fermenters and sulfate-reducing bacteria but not methanogens.

Optimizing high performance computing workflow for protein functional annotation.

Functional annotation of newly sequenced genomes is one of the major challenges in modern biology. With modern sequencing technologies, the protein sequence universe is rapidly expanding. Newly sequenced bacterial genomes alone contain over 7.

No-boundary thinking in bioinformatics research.

Currently there are definitions from many agencies and research societies defining "bioinformatics" as deriving knowledge from computational analysis of large volumes of biological and biomedical data. Should this be the bioinformatics research focus? We will discuss this issue in this review article. We would like to promote the idea of supporting human-infrastructure (HI) with no-boundary thinking (NT) in bioinformatics (HINT).