Overview

Scientific computing is the field of study concerned with constructing mathematical models and quantitative analysis techniques and using computers to analyse and solve research problems. It is typically the application of computer simulation and other forms of computation to solve problems in various scientific disciplines. Scientific computing is relatively new field and it is distinct from computer science. So scientific computing involves developing computer programs and application software, that can model system being studied and this program can then be run using various set of input parameters.

As an end user of various scientific programs, I feel some basic knowledge about how these programs work is must. Learning to program is one of the first think you should do. Although there are many programming languages available today, I learned the basics of programming using python. To be frank, one reason I started using python is that most of the scientific programs that I used in my research was python based. However now if you ask me the same question I have one good reason.

“Python is an open-source object-oriented programming language that offers two to ten fold programmer productivity increases over languages like C, C++, Java, C#, Visual Basic (VB), and Perl”

What is Python?

Python is a remarkably powerful dynamic programming language that is used in a wide variety of general and research application. The Python core doesn’t have the basic data types and functions most needed for scientific programming. Many are available in an add-on module called Numerical Python (or NumPy). This in turn is part of a more comprehensive module called SciPy which includes NumPy plus much more.

What is Biopython?

The Biopython Project is an international association of developers of freely available Python tools for computational molecular biology, as well as bioinformatics.