Steven Salzberg has a post at his Genomics, Evolution, and Pseudoscience blog arguing that one easy way for the US federal government to save millions of dollars would be to shut down the National Center for Complementary and Alternative Medicine. Noting that he submitted the idea to the Obama transition team, he writes, "We need to at least show the incoming administration that some of us believe that the government should only support evidence-based medicine, not pseudoscience." Steven Novella at Science-Based Medicine adds in his own post, "[CAM] is not science-based. It has therefore always been an inherent contradiction to carve out special funding for scientific research into claims that are not based upon science in the first place."
In a blog post at Omics! Omics!, Keith Robison warns that the genomics community may be forgetting valuable lessons it's learned over the years — in particular, the need for attention to detail and keeping your workflow problem-free. "Contamination of various sorts has plagued genome projects from the get-go," he writes. A few checks of publicly available sequence data showed a high rate of contaminants, which led him to urging people to check and recheck sequencing pipelines. "The solution is to run filters — search everything you do against vectors, E.coli and other common contaminants. In addition, especially in this day-and-age, "if your 'human' mRNA sequence doesn't match the genome, you've got some 'splaining to do," he adds.
Learn to Be Nosy
DrugMonkey blogs about how much postdocs should get to know about their advisors' grant funding, salary, lab budget, and more. The answer: as much as possible. DrugMonkey recommends that postdocs skip past the uncomfortable part and ask their PIs these details, since knowing them will be critical as the postdocs move on to set up their own labs. "Budgeting and grant management are essential parts of postdoctoral training," DrugMonkey writes. "It may require a slightly awkward conversation with your PI but this is an essential part of career training. Your PI should be happy to bring you up to speed in this critical area."
Create or Recycle
Michael Barton at Bioinformatics Zen offered some suggestions on when to reuse code and when to start from scratch. Functions for common tasks, such as reading Fasta files or parsing Blast results, already exist and are kept in readily available libraries such as BioPerl. Using those will save you time and give you code that's already been debugged, he says. If you have to write code yourself, he recommends keeping it short and simple — use a version control system, document, and keep it open source. And when you're done, don't forget to contribute it back to the community for the next scientist who wants to do the same thing.