Scientific Computing: Mapping the Human Genome

Computing technology is rapidly advancing and recent scientific discoveries could not have been accomplished without the help of this computational power.  Different from traditional scientific data collection, the field of Scientific Computing (or Computational Science) uses a mathematical approach ran on computers to understand a situation or environment.  Whether it is predicting this week's weather or mapping out the DNA structure of humans, Scientific Computing is giving us the tools to advance the knowledge of our existence. My favorite example of the use of Scientific Computing is that of the Human Genome Project.

The Human Genome Project was an international effort aimed at mapping and understanding all the genes of human beings. It was a three billion dollar project which took 13 years to complete and required massive amounts of computing power in order to accomplish its goal.  This project found there are about 20,500 human genes and offered the world the details about the structure, organization and function of these genes. Essentially it created a blueprint map of our selves.

The benefits this project provided to the world is astonishing. It was reported that for every $1 spent by the federal government a return of $141 was returned back to the U.S. economy. Medical advances in the diagnosis of cancer as well as many other genetic diseases have also benefited from the results of this project.

Computer Graphics: Bitmap and Vector Imaging

In the world of Computer Graphics there are two major two-dimensional types: bitmap and vector images. The more common of the two is the bitmap image (also referred to a raster image). Bitmap images consist of many tiny dots of color called pixels. All of these pixels together form an image. Common bitmap images are icons on your desktop which are typically 32 by 32 pixels. On the left is an example of a paintbrush icon. It consists of 32 dots of color going in each direction. When enlarged, one can see the individual pixels. Bitmap images are resolution dependent. This means when resizing a bitmap image to be smaller, the resize command on your imaging software must throw away pixels to make the image smaller. When enlarging the image the software must create new pixels and estimate the color of the new pixels using a process called interpolation. Bitmap images are also restricted to be a rectangular shape.

Some common bitmap formats are:

• BMP
• GIF
• JPEG or JPG
• PNG
• PSD (Adobe Photoshop)

The other major type of Computer imaging is Vector images. Vector images are made up of many scalable objects which are defined by mathematical equations. This is quite different than the bitmap's pixels in that these objects are lines, curves and shapes which can be modified without destroying the object itself instead of a defined dot of color. Vector images are resolution independent because they are scalable. Increasing or decreasing the size of a vector image will not affect the sharpness of the image. Another advantage of vector images is that they are not restricted to be a rectangular shape.

Vector images are usually made up of solid shapes of color or gradient instead of pixels and tend to have a cartoon-like appearance. For this reason a vector image is not a good choice for producing a photo-realistic image. On the other hand, vector graphics are continually becoming more advanced. There are tools which apply a bitmapped textures to vector objects giving them a photo-realistic appearance. Here is an article with additional information about converting between these two types of image formats as well as scanning and keeping transparency.

Common vector formats are:

• AI (Adobe Illustrator)
• CDR (CorelDRAW)
• CMX (Corel Exchange)
• DXF AutoCAD
• WMF Windows Metafile