Lessons for article recommendation services

Today someone proposed the creation of a sub-reddit where scientists could recommend papers to each other. While it’s a nice thought, I can almost guarantee that it’s going to be a failed effort. There are already sites like Faculty of 1000, which try to use panels of experts to recommend good papers. In my experience, they mostly fail at listing things that I want to read.

The main reason such sites are useless is that we scientists are uber-specialized, so what you think is the greatest paper ever will likely have very litle interest for me. It’s not that I don’t want to read about cool discoveries in other fields, it’s just that I don’t have time to. Until they invent the matrix-esque brain-jack for rapid learning, I have to prioritize my time, and my field and my work will always come first.

There are only two systems I’ve found that work well. The first are recommendation systems based on what you’ve read in the past, and what your colleagues are reading. CiteULike, for example, recommends users that have bookmarked similar papers to you, and perusing through their libraries gives me an excellent source of material. The other quality source of recommendations is FriendFeed, where I can subscribe to the feeds of other bioinformaticians with similar interests, and we can swap links to papers and comments about those papers.

Both of these systems are all about building micro-communities, with a focus that you can’t achieve in larger communities like Reddit. In this way, it’s sort of like a decentralized version of departmental journal clubs, or specialized scientific conferences. Any site that ignores the value of creating this type of community is pretty much doomed to failure from the start.

Published Again

The second paper to go out with my name on it has just been published online:

A sequence-level map of chromosomal breakpoints in the MCF-7 breast cancer cell line yields insights into the evolution of a cancer genome. doi:10.1101/gr.080259.108

That’s me, listed as “Christian A Miller”. Yeah, we’re working on getting that fixed…

As an added bonus, this one is open access!

Published!

The first paper to go out with my name on it has been officially published in this week’s Nature:

Comprehensive genomic characterization defines human glioblastoma genes and core pathways.

Sure, I’m one of about 200 people credited on the paper, but I was happy with my contribution to the group effort. Unfortunately, it’s not in an open-access journal, so I can’t link to anything but the abstract.

Our lab has another paper in submission that I’m an author on, and the plan is for me to clean up some data over the next few months to get a solid first-author paper out the door. That sounds great and all, but the hard work is really just beginning.

Published!

My first paper hit online publication today:

Comprehensive genomic characterization defines human glioblastoma genes and core pathways. The Cancer Genome Atlas Research Network. doi:10.1038/nature07385

Big Data

Nice to see bioinformatics and computational infrastructure getting some love in today’s issue of Nature:

Above all, data on today’s scales require scientific and computational intelligence. Google may now have its critics, but no one can deny its impact, which ultimately stems from the cleverness of its informatics. The future of science depends in part on such cleverness again being applied to data for their own sake, complementing scientific hypotheses as a basis for exploring today’s information cornucopia.

Hopefully, funding agencies and universities will take note and begin funding infrastructure projects, and the scientific community will begin recognizing the value they add. A good computational project can enable thousands of discoveries, and the biological community needs to give appropriate credit (and pay) to bioinformaticians.

There are several other good articles in this issue, including one about biocuration. Link (free access for two weeks, as I understand it)