A comparison of common programming languages used in bioinformatics

The electronic version of this article is the complete one and can be found online at:http://www.biomedcentral.com/1471-2105/9/82

Abstract

Background

The performance of different programming languages has previously been benchmarked using abstract mathematical algorithms, but not using standard bioinformatics algorithms. We compared the memory usage and speed of execution for three standard bioinformatics methods, implemented in programs using one of six different programming languages. Programs for the Sellers algorithm, the Neighbor-Joining tree construction algorithm and an algorithm for parsing BLAST file outputs were implemented in C, C++, C#, Java, Perl and Python.

Results

Implementations in C and C++ were fastest and used the least memory. Programs in these languages generally contained more lines of code. Java and C# appeared to be a compromise between the flexibility of Perl and Python and the fast performance of C and C++. The relative performance of the tested languages did not change from Windows to Linux and no clear evidence of a faster operating system was found.
Source code and additional information are available from http://www.bioinformatics.org/benchmark/webcite

Conclusion

This benchmark provides a comparison of six commonly used programming languages under two different operating systems. The overall comparison shows that a developer should choose an appropriate language carefully, taking into account the performance expected and the library availability for each language.

Share |

Comments

Popular posts from this blog

Sequence Analysis is still sexy:Dual Descriptor Method for Biological Sequence Analysis

Abbott Laboratories Buys Piramal Healthcare Limited Biz for $3.72B

List of Cheminformatics Companies & Institutions