A somewhat belated happy birthday to Fight Aging!, an important resource for lifespan extension advocates that also has some of the best (and constantly improving) scientific coverage in the field. Fight Aging! (and its older companion effort The Longevity Meme) are two fine websites that this humble blog is proud to count as friends. We might not agree on everything, but then again, who does?

If you’re not reading Fight Aging!, you should be.

Congratulations to FA’s proprietor, Reason. Happy sixth blogiversary, and many (many, many…) happy returns!


Just to follow up on that last post asking you to help the SENS Foundation win $5000 — it worked! SENS came in first, and won the grand prize. The margins were pretty narrow — well below the number of people who visited the contest page from Ouroboros alone — so it can truly be said that every vote counted.

Thanks to the readers of Ouroboros and everyone else who helped SENS over the top.

The amount of money raised is, in the grand scheme, rather small, but it’s possible that the victory for SENS in what amounts to a popularity contest will help increase awareness of the life extension cause.

“I’m immensely grateful to 3banana for involving us in this great opportunity, and to all the SENSF supporters who took the time to leave comments at the site,” said SENS Foundation CSO, Dr Aubrey de Grey. “These supporters have recognised that a public and eloquent expression of broad-based support for our mission has the potential to raise the profile and perceived legitimacy of our work and thereby greatly amplify the impact of the competition itself.”

The SENS Foundation (which organizes the Strategies for Engineered Negligible Senescence conferences) is in the running for the $5000 grand prize in 3banana’s Share to Win event. The contest seeks to raise money “for causes serving unmet needs in health, education and environment.”

And you can help. It’s pretty simple: All you have to do is leave a comment on this page. (The award goes to the cause with the most comments.) You can sign on using a Google account if you already have one of those, or register for a free one-off account. It’s painless and takes about thirty seconds.

Your comment/vote makes a difference! Right now, SENS is neck-and-neck with the competition — as of this post, they’re 17 votes behind first place. (Well, sixteen, since I just commented.) So don’t just sit there — this is your opportunity to help send real money to a very important cause, at no cost to yourself.

Post your comment now.

There are only four days left in the contest, so time is of the essence.

(For all you social media users, feel free to spread the word via blogs and Twitter. If you’re interested in regular updates from the SENS Foundation, there’s a Facebook page as well.)

UPDATE: The push yesterday put SENS into the lead — thanks to all Ouroboros readers who took the time to comment! But the current lead is tenuous, and it could still be lost. If you haven’t commented yet: it doesn’t take much time, and with margins like these your vote really makes a difference. Would you really want to find out that SENS had lost by a single vote? Please consider taking a minute or so and leaving a comment on the contest page.

In collaboration with the estimable Vivan Siegel, I’m writing a series of op/ed articles on the future of scientific publishing. The first of these was about the challenges of filtering the scientific literature. The second piece, explores the prospect of using “Web 2.0” approaches to accelerate scientific progress. The article starts from the assumption that sharing is a good thing, and considers the ways in which social networking and other types of internet-powered tools might help scientists share more efficiently. We begin with a description of a long-term, somewhat pie-in-the-sky goal before returning to earth to evaluate the current state of the art (link):

This revolution will be digitized:
online tools for radical collaboration

But let us entertain the thought that the ideal size of the collaborative unit might be much larger than the average research group of today, and that we lived in a world in which scientific efforts were organized around this principle. How might evolving information technologies allow science to progress more rapidly? In such a world, we might choose to organize scientific efforts differently: not according to physical proximity in labs or departments, but rather by aptitude, expertise and availability. Rather than thinking of projects as the virtual property of small groups, we would simply broadcast ideas (or data) until they reached the right person(s) to take the next step. …

In other words, what if you could think a thought at the world and have the world think back? What if everyone in the world were in your lab – a ‘hive mind’ of sorts, but composed of countless creative intellects rather than mindless worker ants, and one in which resources, reagents and effort could be shared, along with ideas, in a manner not dictated by institutional and geographical constraints?

There’s another piece in the works, probably about the publication of results that fall below the threshold of a “publishable unit”. Others have written extensively on this subject, and there are a number of solutions to this problem out in the wild, so I’m currently absorbing all of that information and determining whether I have original thoughts on the subject.

ResearchBlogging.orgPatil, C., & Siegel, V. (2009). This revolution will be digitized: online tools for radical collaboration Disease Models and Mechanisms, 2 (5-6), 201-205 DOI: 10.1242/dmm.003285

A couple of months ago I lamented that scientific blogging would probably be unable to serve as an effective “filter” for the scientific literature. Scientists struggle to keep up with the literature in their own field (let alone related fields), and it would be nice if someone could pre-screen emerging papers in a way that would decrease the time and effort involved in keeping current. For a variety of reasons, I think it’s unlikely that science blogs will be able to serve this function.

But filtering isn’t the only justification for the existence of science blogs, as is made clear by a recent bumper crop of blog posts and articles about science blogging. Blogging can help an individual scientist share ideas with colleagues and spread the word about one’s own work. Some see blogs as increasingly essential to the process of self-promotion, whereas others see an opportunity to fill growing holes in the fabric of conventional science journalism. There is a consensus that blogging is less prestigious than other kinds of scientific publishing, but as participation grows, this may change.

In rough order of the ideas presented in the previous paragraph, I present these pieces here for your delectation:

Continuing with my current fascination with cool ways to enhance the experience of searching and engaging the literature online…

Deepak Singh at business|bytes|genes|molecules tells us about Reflect, a new tool for adding value to online articles:

Essentially, Reflect is an entity extraction engine with a specific purpose, recognizing molecular entities, both compounds and proteins. I have spoken at length about the value of entity extraction, and the availability of a service like Reflect just shows you how useful something like this can be. Using either the Reflect website where you can enter a URL, or the Firefox plugin, you can use extract molecular entities on a webpage quite easily. The service highlights recognized entities, and using your mouse you can get additional details as shown in the screenshot below.

Reflect identifies the names of proteins/genes or small molecules that appear in a body of text and generates a live link to a floating window containing informations (and further linkage) about that entity.

You can check it out at the Reflect website.

I had a lot of fun plugging in blog posts from Ouroboros and seeing what Reflect thought of them. It did a great job with genes and a fairly good job with small molecules, though the higher false positive rate in the latter case was a little disappointing (identifying words as small molecules that weren’t, and linking to things that aren’t small molecules at all, like the word “reset” that appears in a graph about something else).

(P.S.: By the way, Reflect was the winner of the Elsevier Grand Challenge, and its development may have been motivated by the incentive of the prize. In light of that, I just want to clarify that I still think Elsevier is the devil.)

Update: The developers of Reflect have a preprint up at Nature Precedings. Thanks to Hilary Spencer for the heads-up.

You know by now that I love literature search tools (check out the small but growing “Links: Search” category in the right-hand column on the main page). I am strongly motivated by a desire to filter the huge and growing biological literature so that I can find the most relevant papers with the least amount of effort. Therefore, I’m always curious when I hear of a tool that purports to do an old task (searching Medline) in a new and unusual way.

A company called Cognition (“Giving technologies new meaning”) claims to enable the user to use semantic natural language processing to search the literature. Here’s their elevator pitch:

Cognition’s Semantic Natural Language Processing (NLP) technologies add word and phrase meaning and understanding to computer applications, providing a technology and/or end-user with actionable content based upon semantic knowledge. This understanding results in simultaneously much higher precision and recall of salient data within the universe of possible results. Cognition’s Semantic NLPTM makes technologies and applications more human-like in their understanding of language, thereby resulting in more robust applications, greater user satisfaction and new capabilities available for exploitation. On the Web in particular, powering applications with Cognition’s semantic understanding technology drives these applications ever closer to Web 3.0 (the semantic Web).

They have various commercial applications for sale but their semantic MEDLINE product is freely available on the web.

I’m not going to lie to you — it’s pretty great. You can ask the interface a real English question, like “Which genes are expressed in senescent fibroblasts?” and get real answers. (OK, to be fair, it’s fine with just “genes expressed senescent fibroblasts”, but I enjoy being able to use my native language when I talk to a computer.) I encourage you to play around with it; it’s fun.

One feature that seemed promising at first didn’t seem to work well at all. On the right-hand side of the search results screen are a series of dropdown menus; each menu contains several different meanings for keywords within the query. The idea is that one could refine a search by choosing the specific meaning of an ambiguous term, rather than having to slog through a search result that allows all meanings of the term in question. Unfortunately, this feature doesn’t deliver. Allow me to illustrate.

In the query example mentioned above, the dropdowns allowed for six meanings for the word “express”. The results had initially come back with one of these meanings (“6. to make a protein in bacteria or cells in culture”) already selected (I assume because this meaning gave the largest number of hits: ~12 papers, a totally manageable number, all of which were good answers to the question).

That definition is OK but I felt like another meaning (“5. to make a protein from a gene”) was slightly closer to the original intent, so I chose that definition and resubmitted. This culled the list down to only 1 paper, which wasn’t a very good match, and eliminated all the excellent answers from the earlier version of the search.

I can’t even begin to guess how the “sense” of a word is determined algorithmically by the Cognition software, but I do know that the outcome of my twiddling didn’t conform to my intuitive understanding of the words involved — which, after all, is the whole point of natural language processing. So I have to list this under “room for improvement”.

Which is all just to say that this search engine isn’t perfect yet — but please don’t let that stop you from checking it out. I like a lot of things about Cognition semantic Medline, and I’m going to be using it a lot.

What do you think? I’d love to hear about other people’s experience with the software.

(Hat tip to Code-Itch. Yes, I’ve had that post bookmarked since September.)

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