Mailund on the Internet

Ok, with the RSI I didn’t collect a list for last week, so here’s a list spanning the last two weeks instead…

Fun

• How Gay Marriage Causes Earthquakes (Green Gabbro)

Genetics

• MHC & Mating (Gene Expression)
• Richard Lewontin: “[T]oo rapid for genetic adaptation” (John Hawks)
• When whole genome sequencing becomes passe (bbgm)
• American Journal of Bioethics special issue on personal genomics (Genetic Future)

Geology

• Return of the Quaternary (All of My Faults are Stress Related)

Programming

• Short bioinformatics Hacks, ch. 1 (Byte Size Biology)
• Short bioinformatics hacks, ch. 2: chunk it. (Byte Size Biology)
• The 4 levels of making code work (Programming for Scientists)
• A short list of things I don’t like about Python (Jesse Noller)
• Using polymorphism with boost::shared_ptr (The Lone C++ Coder’s Blog)
• Plotting in Python: matplotlib vs. PyQwt (Eli Bendersky)

Public health

• One more time: Vaccine refusal endangers children (Respectful Insolence)

Research life

• The “Ida” fossil: on missing links and media circuses (Ars Technica)
• A few thoughts on “Uncovering Our Earliest Ancestor” (Laelaps)
• Top five annoying questions at scientific meetings (Byte Size Biology)
• EndNote maker’s lawsuit over open-source Zotero dismissed (Ars Technica)
• On the challenges of conference blogging (Genetic Future)

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A Blog Around the Clock has a list of links to blog posts about commenting on (scientific) papers.

There have been quite a few posts over the last few days about commenting, in particular about posting comments, notes and ratings on scientific papers. But this also related to commenting on blogs and social networks, commenting on newspaper online articles, the question of moderation vs. non-moderation, and the question of anonymity vs. pseudonymity vs. RL identity.

Read the post to get all the links.

I must admit that I have never left a comment on an online paper.  If I blog about a paper, I leave a traceback, but that is as far as it goes.

Since putting a review of a paper on my blog, just to add a comment, is a lot of work, I guess I should just get used to leaving comments instead.

Still, I am reluctant to comment on papers.  I don’t mind firing off a half thought through comment off at a blog, but I feel that for a scientific paper I should make sure I understand all the details of the paper before I start commenting on it.  I guess I just have to overcome that feeling.

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At AU they are trying to move all the various departments’ web pages to a common TYPO3 CMS with a uniform look’n'feel.  See examples below:

• Department of Computer Science
• Faculty of Science
• The iNano Center

We resisted a bit at BiRC, mainly because of the price the IT department at the Dept. of Computer Science wanted for hosting it.  We were quite happy with our own Skeletonz CMS and were hosting it for free.

Anyway, the Faculty of Science moved the web group from computer science to work directly under the faculty, and with that move made hosting free for all groups under the faculty, so we decided to try it out.

Yesterday I moved some of our existing pages to the new CMS.  I find TYPO3 a lot harder to work with than Skeletonz, but I’m sure I can get the hang of it eventually.  One thing I really like about it is that it is easy to duplicate web elements between pages so you only need to edit any particular element once and it will be updated on all the pages refering to it.  I use that extensively on the page describing our various projects.

Another selling point is that the CMS will soon be integrated with PU:RE, our publication management system.  We have to report all our publications – and various other activities – to that system, so being able to extract information from that database will reduce the work in maintaining the web pages significantly.  The plugin for that integration should be released shortly, and after that, I think we are ready for the move.

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RRResearch has some thoughts about keeping records of computer work:

When I do benchwork I consistently keep pretty good notes.  I write down everything I do as I do it, on numbered and dated sheets of paper that go into looseleaf binders, organized by experiment.

…

But I don’t seem to be able to apply these good record-keeping habits when I’m working with computers.  Instead everything I do feels ‘exploratory’, as if everything I do is just a preliminary check to see what effect a modification will have, before I do something worth writing down.

I recognise this all too well.

It is not so much a problem when I do some exploratory data analysis.  I will have my R log to see what I actually did, and if I find an interesting pattern I know what I found and I don’t really need the history of how I got there so much.

When writing programs I don’t have the problem either.  There I have source control and bug trackers to help me.

My problem is with scripts.

I write a small script to format my data into something I can analyse.  Run a program or two on the data. Write another script to re-format the data.  A small script to pull out relevant data.  Look at that.  Then I need to just check a few things, and that is easy as another little script.

Very soon I have ten to twenty small scripts of five to ten lines each. None of them are really worth putting in version control or cleaning up or anything, ’cause it was all just exploratory anyway, but if I come back to the data a few weeks later, I have no way of reproducing what I did.

It is really horrible.

Ideally, once I know what I want to do with the data, I should clean up the pipeline, put it under version control and document it, but by then I am already done with the data analysis so I rarely bother.

Until I have to do it all again a few weeks or month later on some new data.

At that point I should really clean up the pipeline, but most likely I need to do something slightly different.  Not drastically different, but a few of the steps should be modified anyway, and depending on the results I need a few more scripts and it just spirals out of control.

I don’t really know how to solve this, I only know that what I am doing is quite sub-optimal.

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Another week, another list…

Computing/programming

• HPC and abstractions (bbgm)
• Innovation or committee (bbgm)
• Does support for open source applications really suck? (Greg Laden)

Flu

• Swine flu: humans, a dangerous species (Effect Measure)
• How do we know how many people die from flu each year? (Effect Measure)
• H1N1/2009: where are we? (Effect Measure)

Genetics

• Human population structure, part n (Gene Expression)

Genomics

• Major themes from Biology of Genomes meeting (Genetic Future)
• Cold Spring Harbor Biology of Genomes meeting (Genetic Future)
• Why don’t we finish the human genome first? (Discovering Biology in a Digital World)

Paleontology

• Bone crushing super wolf went extinct during last ice age (Not Exactly Rocket Science)
• A curious skull from Calaveras County (Laelaps)

Research life

• What to do when your boss says: “Keep your head down” (Adventures in Ethics and Science)
• What? I need to find a post doc position a year in advance of my defense? (DrugMonkey)

Statistics

• “Buffett and Munger: Stay Away From Complex Math, Theories” . . . On the other hand, knowing some math can keep you from being fooled by silly formulas (Statistical Modeling)