Sebastian Pokutta's Blog

As promised roughly half a year ago, here is my opinion on Mendeley. I was reminded of writing my review two days ago after I downloaded the latest version of Mendeley. After the update I fired up Mendeley and I was shocked (at first) – ALL MY DATA WAS GONE. Although I started out to test Mendeley only, I got so used to it that I couldn’t believe that my data was gone. The desktop client just asked me to log in but all the categories, groups etc were gone. More or less out of desperation I logged in (again) and the software immediately synchronized with the web service which has a backup of all the references (I chose to just save the references and not the pdfs). After less than a minute all the references were transferred back to my machine and even the links to the files on my hard drive worked. I was quite impressed with this backup/synchronization feature so that I decided that it was time to keep my promise and write a few lines about it.

So first of all, what is Mendeley? From the FAQ:

Mendeley is a combination of a desktop application and a website which helps you manage, share and discover both content and contacts in research.

Our software, Mendeley Desktop, offers you:

• Automatic extraction of document details (authors, title, journal etc.) from academic papers into a library database, which saves you a lot of manual typing! As more people use Mendeley, the quality of the data extraction improves.
• Super-efficient management of your papers: “Live” full-text search across all your papers – the results start to appear as you type! Mendeley Desktop also lets you filter your library by authors, journals or keywords. You can also use document groups, notes and tags to organize your knowledge, and export the document details in different citation styles.
• Sharing and synchronisation of your library (or parts of it) with selected colleagues. This is perfect for jointly managing all the papers in your lab!
• More great features: A plug-in for citing your articles in Microsoft Word, OCR (image-to-text conversion, so you can full-text search all your scanned PDFs) and lots more new features being worked upon.

Our website, Mendeley Web, complements Mendeley Desktop by offering you these features:

• An online back up of your library: Store your documents in your account and access them from anywhere through your browser.
• Detailed statistics of all things interesting: You can upload your own publications to your research profiles, then track the evolution of your readership. How often are your papers downloaded? How often are they read? From which academic disciplines and geographic regions do your readers come from? Additionally, there are detailed statistics for each academic discipline and research topic. Who are the up-and-coming authors in your discipline? Is the interest in a research topic growing or declining? What are the most widely read papers on a specific subject?
• A research network that allows you to keep track of your colleagues’ publications, conference participations, awards etc., and helps you discover people with research interests similar to yours.
• A recommendation engine for papers that might interest you, but are not yet in your library! Based on what you know already, what should you read next? Coming soon

To be honest, in the beginning when I first started to use Mendeley in Jan 2009 it did not quite convince me. The interface of the desktop software was slow, the meta-data extraction was quite crappy, etc. For short, I just didn’t like the user experience. I knew Papers from before but it didn’t convince me either and so I stuck with the one that was free – Mendeley. Then, over time more and more updates for Mendeley were released. The user interface got better and also the meta-data extraction improved significantly – nobody wants to enter all the meta-data by hand… The current version of Mendeley is 0.9.xx. It is still beta but the latest version is really a great piece of software. Some of the features:

1. Grouping and categorizing of your papers – you can slice and dice it in almost any way.
2. Shared groups – you are collaborating with somebody and you want to share your papers. Mendeley can do that for you. One guy adds a new paper, the other guy gets it automatically the next time (s)he uses Mendeley.
3. Full text search – search within all your papers. fast.
4. Integrated pdf viewer that allows annotation, notes, etc.
5. DOI / arxiv support – Add the corresponding references and Mendeley updates meta-data automatically. No need to enter anything.
6. Statistics functions (via the web service) – you can get detailed statistics about the papers in your library. Most-read journals, more-read authors, etc.
7. Every entry can have one or more pdfs (or other formats) attached to it – One click opens the paper in the built-in pdf viewer.
8. It is free – according to the faq, the current service level will remain free. There might be some premium features coming up at some point that will be charged for extra.
9. Backup/synchronization with the online service – all our references and notes are synchronized with the web service so that you can use your library on different machines and you always have a backup.
10. You can log-in to your Mendeley account from all over the world and access your references on the web (part of the synchronization feature).
11. Meta-data extraction – The extraction works quite well, conditional on the pdfs being somewhat reasonably tagged.

So if you are still looking for a great software for organizing your papers with a great overall concept then you should definitely give it a try!!

Protein structure prediction is an important problem in order to develop new treatments against diseases. The structure determines how the protein works to a large extent and thus being able to predict the structure is essential in order to develop new drugs (see fold.it):

Protein structure prediction: As described above, knowing the structure of a protein is key to understanding how it works and to targeting it with drugs. A small proteins can consist of 100 amino acids, while some human proteins can be huge (1000 amino acids). The number of different ways even a small protein can fold is astronomical because there are so many degrees of freedom. Figuring out which of the many, many possible structures is the best one is regarded as one of the hardest problems in biology today and current methods take a lot of money and time, even for computers. Foldit attempts to predict the structure of a protein by taking advantage of humans’ puzzle-solving intuitions and having people play competitively to fold the best proteins.

Unfortunately, from a computational point of view, structure prediction is a tough problem. The problem has a significant 3D geometrical component which makes it accessible for humans though. Exploiting this fact is what fold.it aims for. It is a game that has humans fold proteins presented as puzzles. The goals of fold.it are:

For protein structure prediction, the eventual goal is to have human folders work on proteins that do not have a known structure. This would require first attracting the attention of scientists and biotech companies and convincing them that the process is effective. Another goal is to take folding strategies that  human players have come up with while playing the game, and automate these strategies to make protein-prediction software more effective. These two goals are more or less independent and either or both may happen.

The more interesting goal for Foldit, perhaps, is not in protein prediction but protein design. Designing new proteins may be more directly practical than protein prediction, as the problem you must solve as a protein designer is basically an engineering problem (protein engineering), whether you are trying to disable a virus or scrub carbon dioxide from the atmosphere. It’s also a relatively new field compared to protein prediction. There aren’t a lot of automated approaches to protein design, so Foldit’s human folders will have less competition from the machines.

Wired run an interesting article a few weeks ago about fold.it and its performance in the CASP (Critical Assessment of Techniques for Protein Structure Prediction) competition where the rankings of the human folded proteins were pretty competitive. Exploiting human intelligence for certain computations is not completely new. Captchas were probably one of the first applications that exploited the human pattern recognition capabilities in order to differentiate between humans and machines. Amazon is running a whole service “MTurk” which provides an infrastructure to utilize “idling Internet users”. The new aspect here might be the design problem mentioned above which aims for constructing proteins with specific properties by leveraging not only human pattern recognition capabilities but also creativity.

Wolfram|Alpha, the computational search engine, is online now. Check it out yourself –  it is definitely worth it.

A few examples that I tried:

• 3-cross polytope or the n-cross polytope
• another polytope example
• you can also solve equation
• or calculate recurrence relations

More examples are available here.