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Getting to know you (and your grants)


Much as I hate to admit it, I am a firm believer in the old adage that it’s not what you know, but whom. Like many people, I would rather believe that success is driven by ability and hard work, not by someone’s PDA directory.

But there’s something to be said for networking. Particularly in a field like this, where the seemingly far-flung pockets of integrated biology are actually comprised of a fairly tight band of incredibly well-connected people, making progress by collaborating with established contacts is a tried-and-true approach.

As one simple example, I found out recently that two industry people who were connected by this magazine have been so successful working together that they were instrumental in raising double-digit millions for a startup company (and people think I’m kidding when I say it pays to read Genome Technology).

One of the most important missions of the magazine is to help the integrated biology community define itself, in part by establishing these crucial connections between people. With that in mind, we approached this month’s cover story — our topic was government grants — in the most practical, easy-to-apply manner we could think of. We started with two basic questions: whom do you need to know when you apply for a government grant, and how can you make the grants you write even better?

The article introduces you to a number of these guardian angels: people from DOE, NSF, and NIH who write programs and whose job it is to help walk you through the process, from tips on applications to figuring out comments from a study section. We know that you’re not a grant novice, so the advice these gurus proffer is targeted at people who could use some suggestions on improving good grants, and some common mistakes they see from even the veteran grant writers. Be sure to take a moment to look at it: you’ll read about people you may not know, and we’ve also included a handy, clip-out reference guide compiling the top advice.

Don’t miss our technology feature this month on protein microarrays. We’ve been intrigued ever since we heard about this proteomics/biochips crossover tool, but wanted to know more about how scientists could decide if this technology is right for them. Turns out, these chips aren’t far enough along for that kind of story, so Senior Editor John MacNeil instead brings you an article on how they’re being developed, issues with content, and the challenges to getting them into your lab.

If I had to pick the most exciting feature in this issue, I’d have to choose this month’s Pattern Recognition. In late March we released a survey on systems biology to a sampling of readers of Genome Technology and GenomeWeb Daily News. As you know, we’ve been trying to hash out a definition of the term for some time, but we wanted to know more than that. What’s the perception of systems biology among scientists? How long will it take to have a major impact on biology or in drug discovery? What segments of the genomics-based market are pieces of the systems biology puzzle? We’re all curious, but that’s information I haven’t seen anywhere else.

The quality of responses we received was impressive. I like to think we have our finger on the pulse of the field, but this time we hit a nerve. People who completed the survey often e-mailed me afterward, writing volumes about their experiences in systems biology and the challenges they see facing the nascent discipline. (For more on that, be sure to read our two-page special edition of Blunt End.) Have a look at the data from our survey — I think you’ll find, as I did, that it’s promising information that may very well help shape the way this field evolves.


Meredith W. Salisbury, Editor

What do you think of Genome Technology? Let me know how we’re doing by e-mailing me at [email protected] or by calling me at 212.651.5635.

The Scan

LINE-1 Linked to Premature Aging Conditions

Researchers report in Science Translational Medicine that the accumulation of LINE-1 RNA contributes to premature aging conditions and that symptoms can be improved by targeting them.

Team Presents Cattle Genotype-Tissue Expression Atlas

Using RNA sequences representing thousands of cattle samples, researchers looked at relationships between cattle genotype and tissue expression in Nature Genetics.

Researchers Map Recombination in Khoe-San Population

With whole-genome sequences for dozens of individuals from the Nama population, researchers saw in Genome Biology fine-scale recombination patterns that clustered outside of other populations.

Myotonic Dystrophy Repeat Detected in Family Genome Sequencing Analysis

While sequencing individuals from a multi-generation family, researchers identified a myotonic dystrophy type 2-related short tandem repeat in the European Journal of Human Genetics.