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.

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India's First Symposium on Synthetic Biology

Centre for Systems and Synthetic Biology & Centre for Bioinformatics University of Kerala, Thiruvananthapuram, Kerala
Welcome to India's First Symposium on Synthetic Biology                       The event will address several strategic issues: 1. How to design organisms from scratch ? 2. Are we ready for the Computer Aided Design of organisms ? 3. Can we design stable genetic circuits for useful applications ? 4. Have we entered the era of ordering genomes by email ? 5. Is the emergence of biohacking, the next big thing in biology ? Invite you to this first synthetic biology meeting in India. The evolving synthetic biology community in our country needs to discuss unique ideas, interest groups, synergies, funding avenues and useful applications. The key goal will be to identify areas where India has potential to take global leadership.
		Welcome to BIODESIGN INDIA 1.0

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The unknown future rolls toward us 23andMe, The story continues

The tables turn, it's 23andMe's turn to send a letter to FDA... Continuing the story Reading Between Lines slapped with cease and desist letters.

Direct-to-consumer genomics firm 23andMe has sent a letter to the heads of the US Food and Drug Administration and National Institutes of Health asking for a collaborative effort to develop guidelines for genetic testing.

The firm posted the letter that it sent to FDA Commissioner Margaret Hamburg and NIH Director Francis Collins on its blog, The Spittoon, last night.

23andMe is one of several companies to be targeted recently by FDA, which sent letters to several firms saying that it believes the firms are selling unapproved diagnostic devices. The other firms that received letters were Knome, 23andMe, Decode Genetics, Navigenics, and Illumina, the last of which was cited for providing the tools that are used to provide genetic information to certain of the DTC genomics' customers.

In the letter sent to FDA and NIH, 23andMe noted that there have been reports of inconsistencies in the results provided by DTC genetic test providers. Specifically, it pointed to a paper published in October 2009 in the journal Nature, in which the authors cited inconsistencies in the results provided by 23andMe and Navigenics.

Though Nature did not publish a joint response from 23andMe and Navigenics to that paper, the firms made it publicly available. In that response, they took exception to some of the methods used, but they also said they agreed with most of the recommendations made by the authors, who were from the J. Craig Venter Institute and the Scripps Translational Science Institute.

"We believe that it is important to emphasize that different genetic testing companies can report inconsistent results even when based on tests with proven analytical validity," 23andMe wrote this week in its letter to FDA and NIH. It added that such inconsistent results may be confusing to physicians and consumers alike.

The firm asked FDA and NIH for help in developing broadly applicable standards and guidelines for providing genetic test results and risk estimates. For example, the firm said such a collaborative effort could develop guidelines for acceptable analytical validity; standards for the positive and negative predictive value of tests; and best practices for companies that could lead to results being readily compared across companies.

"We note that any framework developed for genetic testing companies must consider the multiple high throughput technologies on the horizon, including genome, exome and transcriptome sequencing," it said in the letter. "For this reason, the set of ideas we present above does not include having an organization define a specific set of markers as an acceptable genetic test."