Ask MetaFilter questions tagged with bioinformatics

Compare two podcast episodes for similarity?

pwnguin — Tue, 13 Oct 2009 14:15:23 -0800

How can I generate a dotplot of general files? On a few occasions I've seen some graphics that apply bioinformatics dotplots (aka recurrence plots) to general files, to demonstrate things like beat detection in music, or relationships between .dlls. I'd like to use it to identify strongly conserved portions of an audio stream are between two files.

Is there an open source program that takes two files A and B and generates a dotplot visualization of them? Or even better, one that takes two compressed audio files? I can find plenty of genetics related tools, but I'm looking for a more generalized tool, or at least one specialized for audio or video.

Best language for highschool bioinformatics course?

bergeycm — Thu, 25 Jun 2009 11:22:31 -0800

I'm teaching a course on bioinformatic programming for high schoolers. Which language should I teach it in? And do you have any nifty ideas for easy projects that fall under the bioinformatics header? It's a six-week, twice-weekly internship for highschoolers with absolutely no programming experience. The catch is, it has to be a bioinformatics course. What language would be best? I think the two contenders are Perl and Python, though I'm open to other options.

Possible Perl Advantages:

- I know Perl, so I won't need to pick up another language and I'd be better at debugging it.
- If the kids go on to AP Comp Sci or a 101 course in college, the language is often Java. Both Perl and Java use C-style syntax.
- The bioinformatics online support for Perl seems better than for Python.
- Long-string manipulation and speed seem much better in Perl.
- Though complex Perl is scary-looking, well-writen basic perl doesn't seem that intimidating.

Possible Python Advantages:

- Less steep learning curve.
- Possibly more resources for beginner programmers.
- The whitespace-is-important thing and there-is-only-one-best-way-of-doing-something thing may be better for teaching good programming techniques.

Also, any basic bioinformatics projects you can think of are much appreciated. The goal is really to teach programming, but the internship requires that it be done through bioinformatic applications.

Bioinformatics basics and beyond

Sublimity — Thu, 25 Sep 2008 12:37:30 -0800

Bioinformatics filter: Suggestions for resources to get up to speed on current approaches in genomics and bioinformatics? I have a graduate-level biochemistry background, but in a different area, and am interested in getting up-to-date on where this part of the field is developing. I'm hoping there are others in the Hive Mind who are much closer to this cutting edge and can point me to some good resources for an "advanced beginner".

I would appreciate reviews, tutorials, or textbook suggestions on in vitro and in vivo experimental methods, as well as computational/bioinformatics methods and tools to try to make sense of the great flood of information.

I've already got a few easy-to-find resouces to start: this bioinformatics tutorial page, the NCBI Tools for Data Mining page, and the NCBI Science Primers, such as this microarray page.

Any and all other suggestions (journal articles? user groups or listservs? more?) are welcome. Thanks so much!

Clustering techniques

Blazecock Pileon — Wed, 11 Jun 2008 14:04:02 -0800

What clustering technique to use? I have a set of roughly 500 curves, each curve representing the numerical representation of the behavior of a transcription factor (represented by its binding motif) along a set of genomic coordinates.

In addition, I have six pre-ordained structural classifications. Each of the 500 transcription factor types is a member of one classification.

Presently, I have performed hierarchical clustering of the distances between the curves. I then color the leaves with the according classification, in order to see how the factors organize.

Is there a way to incorporate information from the structural classifications to help assist clustering? What techniques would be better suited for that?

I looked into k-means clustering, but I'm uncertain how I merge the curve information with, say, a six-dimensional unit vector (each axis being the structural classification) that represents membership to a class.

Thanks for your advice.

SVM, HMM, and wavelets in bioinformatics

Blazecock Pileon — Sat, 24 Nov 2007 08:49:25 -0800

I'd like to learn about SVM, HMM and wavelet algorithms in their usage in bioinformatics. I have a somewhat rudimentary understanding of the underlying mathematics from Wikipedia and a couple other sources, but I find that a concrete demonstration of their application fleshes it out. Are there texts, software packages (preferably free) or papers you'd recommend that: 1) includes good starter problem sets, or; 2) demonstrates how these techniques are used in research applications (beyond "we used xyz here"). Thanks!

What are the top bioinformatics graduate universities in the US?

lpctstr; — Thu, 24 May 2007 13:44:19 -0800

What are the top bioinformatics graduate universities in the US? I tried US news, but only got the top 3 without a subscription. Otherwise, I've searched on the web for about 5 hours with no luck besides individual universities tooting themselves.

cell?

delmoi — Wed, 13 Jul 2005 21:50:16 -0800

How do cells form various shapes? A lot of cells are just round blobs, but some of them have pretty complicated shapes (like nerve cells) how to cells build structures like axons and dendrites, or flagella or whatever?

Bonus question: how is gene expression regulated by chemicals in the cell. I get the idea that hormones, and other chemicals alter gene expression inside a cell How does this work? (I mean I realize its probably different for all different kind of chemicals, but is there a sort of general mechanism?)

I have an idea for a genetic cellular simulator based on some simple rules that sort of approximate real world phenomena, but I'd like to know how those two process work.

CompSci PhD

azazello — Sun, 07 Nov 2004 10:00:30 -0800

I'm looking for a good computer science Ph.D. program to apply to, with strong research groups in both bioinformatics and AI. I'm graduating from a leading US university with a triple degree in CS, applied math, and statistics. My research background is fairly strong (a few joint published papers in my research concentrations, recommendations, etc.), my GREs are/should be very decent, but what's holding me back is my GPA, which really sucks except for the past two semesters. Because of this, the top-tier schools (Stanford, MIT, Princeton, Berkeley, probably CMU) are out.
Therefore I'm looking mainly for schools just below that level. I can apply as either CS or Applied Math (I can probably collaborate with the right people from either position), but I'd rather get into CS. My requirements are:

Strong research groups in both of my research concentrations - bioinformatics (comparative genomics) and AI (machine vision, computational cogsci).
Decent location (I don't want to be stuck in Idaho or the rural Eastern US, for instance. I'd rather visit them on hiking trips.) A large northern coastal metro area would be ideal.

Can't think of anything else right now...
I will consider Canadian, UK, and other English-speaking schools, but I'm told they don't have nearly as much money to assist students financially as the US schools. Is that correct?
I have a list of about 40 schools, but that's too many (I'd like to narrow it down to at most 25) and I don't know how comprehensive my initial list was.
I'm told the proper way to select schools in this situation is to read the current publications and identify which places the strong research groups come from. I'm in the process of doing that, but wanted to ask for more advice regardless.