EN: I think I am not the only one who would like see that Connotea makes use Nature Precedings meta-data during the tagging procedure. So far not even the title is fetched automatically.

EN: Well, I think it is nothing completely unexpected but interesting to see research going on about this: Lesser et al. showed that nutrition studies are biased by the sources of their funding.

For interventional studies, the proportion with unfavorable conclusions was 0% for all industry funding versus 37% for no industry funding (p = 0.009). The odds ratio of a favorable versus unfavorable conclusion was 7.61 (95% confidence interval 1.27 to 45.73), comparing articles with all industry funding to no industry funding.

A similar study regarding financial biases in clinical studies was published already some years ago [2].

[1] Relationship between Funding Source and Conclusion among Nutrition-Related Scientific Articles. Lesser LI, Ebbeling CB, Goozner M, Wypij D, Ludwig DS PLoS Med. 2007 Jan 9; 4(1): e5

[2] Association between competing interests and authors’ conclusions: epidemiological study of randomised clinical trials published in the BMJ. Kjaergard LL, Als-Nielsen B BMJ. 2002 Aug 3; 325(7358): 249

EN: DRIVER (Digital Repository Infrastructure Vision for European Research) recently launched a wiki to aggregate knowledge regarding open access with focus on Europe. It intends to offer e.g. country specific information about fundings, events and organizations.

[via open-access.net]

EN: As announced on Nasecent the preprint-server Nature Preceedings is officially launched now:

Nature Precedings is a place for researchers to share pre-publication research, unpublished manuscripts, presentations, posters, white papers, technical papers, supplementary findings, and other scientific documents. Submissions are screened by our professional curation team for relevance and quality, but are not subjected to peer review.

Pedro who tested it already for some month as a beta user reported some days ago about it. His earlier post regarding policies of journals regarding preprint-server might take some fears away. Some of the usual suspects have already added documents.

EN: The ENCODE-project presents the results of the functional analysis of 1% of the human genome [1]. I have not have the time to read it completely so far but listened to a talk by Ewan Birney at EMBL on Tuesday. The approach might be the prototype of how some of the big questions in biology have to be solved - in huge consortia (308 authors contributed to this publication). 30 Mbp (1%) of the human genome were analyzed using different wet-lab techniques and intra- and inter-species sequence comparisons. One result of the integration of all this is that there is much more (10fold) transcription going on than reported before, but not all of the transcripts contain genes. The plan to extent the analysis to the full genome is currently reviewed.

[1] Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project, Nature 447, 799-816 (14 June 2007)

Privacy International published an analysis [1] in which 23 (! ;)) web companies are ranked by their treatment of the users’ privacy. As described before (and here again) Google’s huge collection of personal data that is havested by the toolbox of services can be seen as a harm for privacy. The authors of the study think that Google’s behaviour regarding privacy is the worst one of all companies in the analysis. Although the study is highly criticized e.g. at Search Engine Land I really like to see the topic discussed in the media and getting more awareness.

Part of the privacy problem is the communication of the policies of the web services. The language of the general terms and conditions is in rare cases well understandable by usual people. There was recently a podcast (german) on netzpolitik.org with Matthias Mehldau. Matthias developed similar to Creative Commons an icon set for data privacy (PDF but SVG should be available soon). It is created to communicate in an easy way the privacy policies of a web service. So far is it in an early development phase and Matthias invited everbody to contribute with ideas and improved icons.

[1] “A Race to the Bottom - Privacy Ranking of Internet Service Companies”, 09/06/2007

… at least not in Science or Nature (also other journal from the Nature family e.g. EMBO journal) as Undernews reported. These publisher cannot handle the new format (docx). Hopefully this issue stimulates to rethink the current pipelines. Having a work flow based on a proprietary format (and despite its name Microsofts new Office Open XML format is also not really open) is in my opinion a bad idea as it forces possible authors to use a distinct software to create the publication. Not everybody can effort the Microsoft products or wants to use them. Sure, LaTeX would be a cool solution (and is used e.g. by some mathematical journals) but for many people it is just too nerdy. But how about ODF? It is a file format that is open, ISO-accepted, XML-based, and used by many (mostly open source) office suits like OpenOffice.

[via O'Reilly Radar]

EN: It is again the beginning of a month so time for a new issue of Bio::Blogs. The 11th edition is hosted on nodalpoint (pdf-version) and has the usual best-of-bioinformatics-blogs of the previous month (thanks Pedro!). Additionally a collection of tips with focus on best practice in bioinformatics can be found on Bioinformatics Zen (pdf). Michael Barton did a great job as an editor of this nicely designed collection. I contributed some recommendations, too and post below my raw version as it contain the links. Michael did some modification/cleaning to fit it into the style of the collection so there might be some small differences.

Here are some of my lifehack tips for computational biologists based on my personal experience. Please keep in mind that my main task is the data analysis itself, not the general tool development. Some of the points are not so relevant for people mainly developing software.

Maybe you are already inspired by general classical literature such as “Getting things done“, “Seven habits of highly effective people” and the new kid on the block “The-4-hour-work-week” and are following blogs such as lifehacker.

Set up a proper tool box containing …

• … a programming language (or several) that suits your needs and lets you write functional and readable code quickly, e.g. Python
• … the knowledge of the most important/used Unix commands
• … a powerful editor (hot tips here: syntax-highlighting and completion)
• … a reference management system like Connotea/citeulike or JabRef
• … a browser equipped with handy extentsions
• … a proper version control system for your code and documents - CVS or Subversion might be the options that come to your mind first, but if you would ask Linus Torvalds, he would recommend git.

The habit of proper documentation

• Think about your future ego that will thank you for the possibility to travel back in time.
• Write a lab journal/book
• I highly recommend a blog or wiki based system, but for sure flat files or even a hand written notebook *cough*no*couch*way!!!*cough* might do the job.
• Write down what you did, how you did it, why you did it, and where the input and output are stored. Also some of your key graphics, article summaries, and overviews of the results should be placed in there.
• By articulating the thoughts in your head you define aims and become aware of them (”Begin with the end in mind” as Stephen R. Covey says).
• Document your code
• A short description at the beginning of the program is the minimal documentation.
• Give meaningful names to functions and variables. If you cannot find a proper name, you don’t know what the thing really does.
• Use clear file names, file headers and folder structures to find things easily
• I do this by putting the date in the beginning of folders where I organise my analyses e.g. 2007-05-28-foo_analysis_in_bar_data.
• I put a master shell script into these folders which contains all the calls and sometimes, as a comment, the names of the resulting files.
• The output files of my programs have a short header that tells by which program they were created, at which time and with which parameters the program was called (I use a little library for that).

Empathy and compassion

• Think about which information in your head could be needed by other people in your lab or in your scientific community. A wiki for example can be an excellent tool for organizing generally needed knowledge and avoiding the drain of it if somebody leaves the lab.

Other small tips:

• Be aware that demands will change so program from the beginning on in a way that make it easy to extend/adapt the program.
• As soon as there is the smallest possibility that a function might be used twice write a proper library.
• Often flat files are a handy format for data, and grep and others are good companions. If data sets are constantly changing and built of many components a proper database might be a better solution. For many purposes you don’t need a client-server-based database like MySQL but a simple library based one e.g. SQLite that does the job without server set up and user management.
• Code your graphics, as this will give you more control. Especially if you have graphics that consist of different panels, it will save you a lot of time if changes will be needed (and this will be the case). I personally create primarily SVG files and convert them to other formats if needed.
• If you set up a web-server think not only about functionality but also about security. Make the internet a safer place and don’t feed the spam/botnet industry with your server.
• Regarding sustainability: We are not evolved to work for hours in the same position in front of a computer. Know when to take breaks, stretch, and try to focus as often as possible at distant objects. Hopefully this will help to maintain proper eyesight long enough until neuronal interfaces are on the market.

EN: The next step to the personal genome: Yesterday James Watson, one of the discoverers of the DNA structure, got the sequence of his genome. It was sequenced by 454 in two month and cost less than $1 Million. Watson will make parts of his genome public soon.

More information can be found in the press release.

[via Technology Review]