“You’re free to speculate as you wish about the philosophical and allegorical meaning of the film — and such speculation is one indication that it has succeeded in gripping the audience at a deep level — but I don’t want to spell out a verbal road map for 2001 that every viewer will feel obligated to pursue or else fear he’s missed the point.” – Stanley Kubrick

I just finished watching 2001 A Space Odyssey, and as always the first thing I do after seeing a movie is to visit its wikipedia page to read the plot and interpretations of the movie. Even for movies that weren’t meant to be particularly deep, I always read up. The quote by Kubrick was given when asked for an interpretation of 2001. By and large, I totally agree. Since we are all different, we all pursue our own intellectual thoughts.

So the question on my mind is what was this monolithic block? One of the reasons I always read up on a movie is because I’m afraid I missed the point, which Kubrick pointed out. I’m afraid to make connections, which differ from the director/author’s intentions. But just like how Tarantino has his interpretations on the song “Like a virgin” (which perhaps wasn’t the song writer’s original intentions), shouldn’t we all have our interpretations on things? Maybe this is why 2001 is highly acclaimed.

As for what I got out of the movie, I guess it was the special effects. For a film made in 1968, it is pretty spectacular. The “Dawn of man” was particularly boring for me (and I kept thinking back at The Simpsons awesome parody of it) and the lack of dialogue and prolonged cinematic effects didn’t do it for me. I loved the HAL 9000 portion of the movie, and finally understood all The Simpsons references made to it. The only thing gripping about the movie was the monolithic block, and trying to figure out what it is. I’m truly a mystery fan boy, with favourites such as The Maltese Falcon and Chinatown.

The block will remain an enigma, just like the intentions of the movie. My overall interpretation of the movie? Computers will eventually get smart enough and take over us (which it has probably achieved already on my part, since I spend a crazy amount of time in front of a computer).

Saturday night 11:30pm. What better way to spend time than writing random facts about cancer.

Q. What is the relationship between telomeres and cancer?
A. Increased telomerase activity can increase longevity of cells, but it is also implicated in cancer formation. Almost 90% of cancer cells have been found to have enhanced activity, and a cancer cell usually divides about 80 times before a tumour mass becomes large enough to be detected In contrast, normal human cells usually divide 30 to 50 times before telomeres become too short and doubling stops.

Q. Who was the first individual to find the gene for breast cancer?
A. Mary Claire King (1946-) determined that in 5 to 10% of those women with breast cancer, the cancer is the result of a mutation of a gene on chromosome 17, the BRCA1 (Breast Cancer 1). The BRCA1 gene is a tumour suppressor gene and is also linked to ovarian cancer. Subsequently, other researchers were able to clone the gene and pinpoint its exact location on chromosome 17.

Q. What is an example of a drug developed through pharmacogenomics that is associated with cancer?
A. Gleevec (approved by the FDA in 2001) is a drug developed for a rare type of genetically caused chronic myeloid leukemia. In this type of leukemia, pieces of two different chromosomes break off and reattach on the opposite chromosome, causing a chromosome translocation. This abnormality causes a gene for a blood cell enzyme to continually manufacture the enzyme, resulting in high levels of white blood cells in the bone marrow and blood. Gleevec was specifically engineered to inhibit the enzyme created by the translocation mutation and to thus block the rapid growth of white blood cells.

Recently I posted a question to the Perl beginner mailing list about Perl and bioinformatics. My question was asking why Perl is better than other scripting languages when it comes to working with text. And as a final note in my email, I made a remark towards to how parsing text is useful to biology since a lot of biological data is stored in text files.

I had an abundance of answers (some that I am still slowly digesting), and there were several reasons towards Perl’s superiority in text processing. In no particular order, here were some answers to why Perl is good/great at text parsing:

1. Regexes are first class citizens in Perl, in other languages you must use a library that feels out of place
2. Perl tends to innovate in regexes, adding features (the most popular non-Perl regex library is PCRE, PCRE stands for Perl Compatible Regular Expressions)
3. Perl is weakly typed, which reduces the amount of code you must write. In strongly typed languages you spend a lot of time casting variables into the desired type.
4. Many of the operators like the readline operator (<>) are setup to do what you want with a minimum level of effort, such as a bare readline operator creating the default UNIX filter style (read from stdin if no files are specified on the commandline, otherwise open each file passed on the commandline and read from each of them in turn).
5. The, much maligned, set of special variables also makes this easy (for instance, $ARGV is set to the file currently being read by the construct in the last point).
6. Perl’s regexes are still better and faster than the compatible libraries. There are many things Perl can do that they can’t even come close to (my favourite is the /e modifier on s///!).
7. CPAN is another major reason for Perl’s strength in text processing. There are hundreds if not thousands of modules that parse, mung, generate text in all sorts of forms. just consider how many templaters there are alone.
8. Perl’s scalar values are designed from the start to be powerful text storage items. they have no fixed limit on size, you can add, cut, shrink, extract, etc directly with operators instead of long winded function calls. the Perl ops and functions are designed to work well together generating concise (a better word and more accurate than terse) code. Perl’s guts have been optimized over many years and are very fast when doing text munging.

So from what I have gathered Perl’s regexes give the user power to create complex text parsing abilities and since Perl’s scalar values can be limitless in size, large chucks of text can be stored and operated upon. It also seems that the special variables and operators available to Perl make it easier to work with text and pattern matching.

And after some further discussion with a Perl guru, I understood the concept of type casting and how Perl’s many operators assist with writing less code for casting variables. They also mentioned about strongly typed languages like C++ where 10.0 + 5 would result in an error due to addition between a floating point type vs integer type. This was also touched on briefly in the “How Perl Saved The Human Genome Project” and how weak casting can be a problem if a variable changes from a number to a character. This often happens as a lot of data is manually handled and human errors do occur.

And just today I corresponded with a fellow bioinformatician who has used Perl for almost 10 years. They wanted to point out that biological data isn’t just huge genomic files (which makes Perl extremely useful) and as such other scripting languages are just as competent as Perl, which was also a note made by another Perl guru. Apparently Ruby is extremely popular in Japan, and was developed by the Japanese. There is even a BioRuby! But the point is really that for many bioinformatic tasks such as parsing XML files, Perl holds no advantage over other scripting languages. Perl is just popular in bioinformatics because it was there first.

It has been a very insightful thread and I did get a lot out of it. It helped me understand the history of Perl and biology and bioinformatics, and explain why Perl is very suitable in parsing large text files. However I have heard that Perl’s syntax is hard to read and ugly. I guess when you’re developing software, readability plays a large part. Besides Perl is known to be quick and dirty and considered to be the Swiss army chainsaw. But hopefully when I get my python bioinformatics book, I can get a better perspective.