p3ll0n

In addition to Lincoln's thoughts I think one of the main reasons bioinformaticians are attracted to Perl is because it is forgiving. Biological data is often incomplete, fields can be missing, or a field that is expected to be present once occurs several times (because, for example, an experiment was run in duplicate), or the data was entered by hand and doesn't quite fit the expected format. Perl doesn't particularly mind if a value is empty or contains odd characters. Regular expressions can be written to pick up and correct a variety of common errors in data entry. Of course this flexibility can be also be a curse.

Some questions to ponder while we all continue to wait for the new NRC rankings:

Are the data that will be used in the rankings losing their analytical validity since they will be from the 2005-2006 academic year?

Why wasn't the NRC able to produce its rankings more quickly, using more up-to-date information?

How many faculty members have switched institutions and departments since the NRC first started collecting data in fall 2006? This is very important because faculty data are a key part of the NRC's analysis.

yeah the quality is going to be terrible and your going to hear a lot hissing but it will work!

Two more that come to my mind ...

1. Comparing local and remote files

$ ssh user@123.4.5.6 "cat /tmp/remotefile" | diff - /tmp/localfile

2. Outputting your microphone to a remote computer's speaker

dd if=/dev/dsp | ssh -c arcfour -C username@host dd of=/dev/dsp

Today was the first time I have visited SeatGeek and while I haven't used it to make a purchase yet I certainly made sure to add it to my bookmarks.

Great service that serves a real need (Craigslist/StubHub/etc are all a royal pain to navigate and utilize).

The site has a sophisticated, clean design, one which seems to assume that its visitors will plunge in and begin searching for seats with little hand-holding.

Reminds me of an academic project I ran across once that has had a mixed record of success ...

http://en.wikipedia.org/wiki/CubeSat

For a more humorous take on this issue check out

http://stuffwhitepeoplelike.com/2008/07/31/106-facebook/

A main problem for speaker independent automatic speech recognition systems is the variability of the speech signal - i.e. the same sequence of words uttered by different speakers or even uttered several times by one speaker never results in identical speech signals.

ROS (rate of speech) is one of the primary contributors to this variably and some recent research (http://www.ee.columbia.edu/~dpwe/papers/PfauR98-spkrate.pdf) has shown that good estimates of speaking rate can be obtained using vowel detection as vowels in general correspond to syllable nuclei.

I wonder if Sukhotin's algorithm could be modified to improve upon this work?

Interesting comment on related article by NYT that offers some insight into what type of behavior this bill may be aimed at curbing ...

http://cityroom.blogs.nytimes.com/2010/06/29/bill-could-make...

I like this model a lot but what if it was "pay what you can", not "pay what you want"? While subtle I think this change in the verb drastically changes the game. Not only is it much harder than you’d think to evaluate for yourself what you can pay but it requires a change in how we calculate value and turns payments into a mutual ethical obligation between producers and consumers. It goes well beyond our naive notion of "voting with your wallet".

The key/value model embraced by NoSQL databases (Scalaris, Voldemort, Tokyo Cabinet, etc) is the simplest and easiest to implement but inefficient when you are only interested in querying or updating part of a value.

This article (http://seattleweb.intel-research.net/people/lamarca/pubs/pap...) coming out of Intel argues that it is also difficult to implement more sophisticated structures on top of a distributed key/value. The author's main point is that a few specialized applications can and have been built on a plain distributed key/value store, but most applications have ended up having to customize the key/value store's internals to achieve their functional or performance goals.

From the little bit I have read about Membase it looks well positioned to bring simple distributed key/values stores to the next level and back into the lime light.

"Our culture celebrates the idea of the workaholic. We hear about people burning the midnight oil. They pull all-nighters and sleep at the office. It’s considered a badge of honor to kill yourself over a project. Workaholics wind up creating more problems than they solve. Workaholics miss the point, too. They try to fix problems by throwing sheer hours at them. They try to make up for intellectual laziness with brute force."

- Jason Fried & David Heinemeier Hansson, "Rework"

What I find most troubling about this 'dilemma' is that the reach of broadband nationwide is unknown. There is no comprehensive tracking of broadband service, including which neighborhoods, towns and cities have it and which don't. No federal agency or private group keeps track. To date we have relied on outreach efforts like the Pew Internet and American Life Project and the 2007 Census of Agriculture to measure rural broadband penetration. If we hope to fix America's Broadband Dilemma we need to know where to best target our efforts.

I thought Michael Lewis' "Liar’s Poker" was describing a world that was ending, not that a world was beginning. And what it was describing, it turns out, is a period in finance that went on for another 25 years or 20 years.

The incentives for people on Wall Street got so screwed up, that the people who worked there became blinded to their own long term interests because the short term interests were so overpowering. So they behaved in ways that were antithetical to their own long term interests.

Looking at these techniques I see them all leading towards a series of behaviors that we’ve learnt as kids, and that turn out to be quite useful in tapping into our "creative side". Behaviors like exploration, which is about going for quantity, building and thinking with our hands and role play, where acting it out helps us both have more empathy for the situations in which we’re designing, and to create services and experiences that are seamless and authentic.

Lisp is certainly great, and Clojure looks like a reasonable lisp. I wonder why the JVM attracts untyped languages while .NET attracts typed ones. Could it be that the Java language has damaged people’s ideas of what types are for?

It's great to see folks providing commercial consulting/hosting/support for CouchDB in the same vein as Cloudera (Hadoop/HBase), MongoHQ (MongoDB), etc!

CouchDB is great but don't get me wrong ORMs like ActiveRecord and DataMapper have done a lot to to ease the pain and abstract away the nastiness of SQL. It’s not enough though. It’s like treating the symptoms and not the underlying condition. You still have to worry about joins, normalization, and other artifacts from relational databases. These issues leak their way up into your models where they don’t belong, and obscure more important logic. All of this isn’t an issue with CouchDB, and that’s the biggest selling point for me.

A more humorous take on MySpace's slow demise ...

"For a brief period of time, MySpace was the site where everyone kept their profile and managed their friendships. But soon, the service began to attract fake profiles, the wrong kind of white people, and struggling musicians. In real world terms, these three developments would be equivalent to a check cashing store, a TGIFridays, and a housing project."

- Christian Lander, "Stuff White People Like" - #106 Facebook http://stuffwhitepeoplelike.com/2008/07/31/106-facebook/

Forbes had an interesting article

http://www.forbes.com/forbes/2010/0607/opinions-houston-immi...

recently that had a narrower focus (Houston) but touches on many of the same topics ... innovation, job growth and immigration ... and how they have helped Texas stay ahead of the curve during the recession.

I believe the author makes several interesting points about the aspects of Joost's business model and corporate culture that might of lead to its failure, however, one aspect not touched on is the user experience of the product itself.

When compared against its main rival Hulu (as in this post http://www.readwriteweb.com/archives/10_reasons_why_joost_fa...) it becomes clear why Joost's user experience also encumbered its own success.

Four rules that should be tattooed on the back of every technical writer’s hands so they can’t accidentally forget it.

1. Poor grammar and bad writing are often a sign of poor comprehension.

2. Good documentation takes time.

3. Deep expertise is not automatically a prerequisite for good documentation.

4. Don’t let working cultures that put too great a premium on knowing everything dominate - i.e. being 'in the know' should be a tool for helping others up rather than beating them down.

What really sets GitHub apart, is not that it uses Git, but how elegantly it pulls everything together (source control, new API discovery, networking, site hosting) around a set of core social networking ideas.

James Hamilton, VP at Amazon and author of the popular blog "Perspectives" has some interesting insights into and great things to say about the work SeaMicro and other new startups are doing to revolutionize the server industry.

http://perspectives.mvdirona.com/2010/06/14/SeaMicroReleases...

Padrino extends Sinatra with a wealth of extra features: namespaced route aliases, nested routes, controllers, i18n / internationalization, mailer system, django-esque admin interface and unified logging.

Most of these features can be added to Sinatra already, either manually or by selecting from a wide assortment of independent plugins. Padrino, on the other hand, provides a standard suite of functionality that, hopefully, will continue to be improved as a whole over time. It feels a lot like Ramaze (http://ramaze.net/) but with the similar functionality wrapped around Sinatra instead.

Benford's Law is a special case of Zipf's Law (http://en.wikipedia.org/wiki/Zipfs_law) as they both originate from the same scale invariant functional relation from stat mech.

Great Post!

While a lot of factors go into determining whether a language is readable I have always felt the most obvious is familiarity. The human mind is very good at adaptation, and often it’s astonishing what we will perceive as "normal." Familiarity only comes from constant exposure, though, which means that languages with relatively simple syntax become familiar more quickly. Lisp is at one extreme, with only one syntactic construct. It’s very easy to become familiar with Lisp, although grasping the large Common Lisp standard library is another matter. I tend to agree with the author that C++ is a language at the other extreme. Most C++ coders I have encountered use only a relatively small subset of the C++ language. Worse yet, everyone uses a slightly different subset.

Of course, the biggest impact on readability comes not from the language, but from the developer. A poor developer can write illegible code in any language. A good developer? I’ve even seen well-written, readable Visual Basic code (once).

At Baylor College of Medicine's Human Genome Sequencing Center where I work as a Software Engineer one of our biggest current needs (software-wise) is a working LIMS (Library Information Management System) that tracks the progress of DNA samples through our analysis pipeline (chemistry and software sides).

There is also a great need for Software Engineers/Mathematicians to improve the analysis software and the algorithms behind them (primarily string matching) to account for advances in the "chemistry" that companies like ABi and Illumina are making in regards to their sequencing technology.

These are both just on the "production" side of the process - i.e. the processes and people that produce the first round of analysis and statistics from the raw read data (sets of As, Gs, Ts and Cs). Further analysis that looks for SNPs (single nucleotide polymorphisms, what Wade calls 'variant DNA units'), carries out genome annotation and eventually attempts to statistical link both of those results and numerous others to disease traits is carried around by teams of programmers and biologists/geneticists. However, as the data becomes increasingly large and complex so too does the role programmers and clever software play.

One of the best time-management/productivity tips I ever came across was suggested by Jonathan Mead over at the blog Zen Habits.

He suggests creating a "to-stop" list - a list of all the things that are sucking away your energy and are wasting your time. He suggests figuring out which of those things is having the biggest negative impact on you doing the stuff you really want to do and tackling that thing head on each day.

in the last 3 or 4 years that the sequencing technology has exploded in terms of data volume, as well as modern computer hardware that can analyze that data in any reasonable time frame. That's whats enabled whole genome sequencing of disease patients to become something practical

As a computer scientist working at one of the major genome centers mentioned in the NYT I can attest to ben1040's claim.

In the last five years alone because of technological advances in sequencing technology we have moved from talking about genomic data in megabases (Mb) to gigabases (Gb). Illumina newest HighSeq sequencing technology is capable of 300 Gb per run, 10x more than there competitor ABi's SOLiD instruments which were released as little as 2 years ago!

I really like the approach you guys have taken to get fans involved (i.e. the partnership with NHL that gives discounts to 'active' fans).

Any talk of partnering with NHL, MLB, NBA, etc. to stream live audio/video of games?

With an increasing number of smart phones packing a powerful camera what about serving as a platform for fans to share their own media content from games - like photos?