programming

bucket cross-validation? subject-wise k-fold cross-validation?

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Update: If you are looking for the Petition to ABC for Linux plug-in of online video streaming service "full episodes," please follow this link http://narnia.cs.ttu.edu/drupal/node/138 I updated my site and changed story numbers.

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by Forrest Sheng Bao http://fsbao.net

This is an article about machine learning and biomedical engineering. And you will need MATLAB and MATLAb Neural Network Toolbox to run my demo code.
An easier official example on using MATLAB NN Toolbox is here: http://www.mathworks.com/access/helpdesk/help/toolbox/nnet/radial_4.html#8370

Executing another executive in your C/C++ program

by Forrest Sheng Bao http://fsbao.net

Well, the trick is very easy, call system.

#include "stdio.h"
#include "assert.h"

int main ()
{
  char buffer [50];
  sprintf (buffer, "ls");
  printf (buffer);
  assert(system(buffer) >= 0);
  return 0;
}

Dumping Cross-Validation Result out from libsvm

by Forrest Sheng Bao http://fsbao.net

Libsvm (http://www.csie.ntu.edu.tw/~cjlin/libsvm/) is a great SVM implementation, made by a group in National Taiwan University, Taiwan.

But you can't see the cross-validation result, by default. Now I am gonna do a multi-source boosting and I am gonna compute the sensitivity and specificity. So I need the result of each weak classifier.

What to do? Well, libsvm is open sourced! You just need to simply modify the svm-train.c file. Following discussion is based on libsvm v. 2.88, released on Oct. 30, 2008

Let's make a Makefile

by Forrest Sheng Bao http://fsbao.net

Make is a great tool on Linux and Mac. I have never used it on Windows, coz I seldom use Windows, maybe once per two weeks. Windows sucks, flat suck, especially Windows Vista.

GUI programming made easy in LabVIEW on Linux

by Forrest Sheng Bao http://fsbao.net

Linux is a great platform for engineering and scientific research. But making GUI software on Linux is not as easy and fast as it's on Windows. Microsoft made the Windows and the APIs for Windows programming. And, they made an IDE, Visual Studio. On Linux, we have so many APIs to use, GNOME, KDE, and so many IDE's to use. Gee, I want to focus on my algorithm. Wanna build beautiful graphic interface for your algorithm on Linux in just few minutes? Try LabVIEW. It's just a few clicks away.

No EOF(), the Python way

by Forrest Sheng Bao http://fsbao.net

Today, I was writing a program and gonna to find a function to detect whether EOF, the end of file marker, was reached. But I failed. Not such function in file I/O of Python. Then I did some googling and realized we don't need an EOF detection function. Take a look at this: http://groups.google.com/group/comp.lang.python/browse_thread/thread/ed25388487b3ac7b

Searching phased siRNAs from mapping result over genomes in linear (O(n)) time complexity

by Forrest Sheng Bao http://fsbao.net

In bioinformatics, we prefer constant or linear algorithms. The reason is obvious. But, sometimes, something strange just happened in some papers.

In 2006, Ho-Ming Chen, Yi-Hang Li and Shu-Hsing Wu published a paper on PNAS, "Bioinformatic prediction and experimental validation of a microRNA-directed tandem trans-acting siRNA cascade in Arabidopsis", http://www.pnas.org/content/104/9/3318.abstract.

Truncating siRNAs by 5' and 3' adapters and categorizing them

by Forrest Sheng Bao http://fsbao.net

Some genes in DNA sequences are very short, for example 15 bases. They are too short to sequence. So, we can add some adapters at 5' and 3' to extend it to 34 bases. Besides, we have a huge pool of sequences from different sources and we mixed them up for sequencing. So we can also use the adapter as an indicator to mark the source of the gene.

PyWavelets and pywfdb library for biomedical time series analysis

by Forrest Sheng Bao http://fsbao.net

I am so excited today that I have found a very cool Python library for doing wavelet decomposition, the PyWavelets. It is developed by Filip Wasilewski

Plotting in matplotlib/pylab

by Forrest Sheng Bao http://fsbao.net

I like Python, the simple but elegant syntax. I can't love any other programming languages more than Python. So I prefer to do my scientific computing in Python. I am very happy to find Numpy/SciPy package. matplotlib/pylab makes it possible for me to visualize my results. Neat!

Here is my first plotting script using matplotlib/pylab:

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