Microbial Genomes Curator @ Computercraft Corporation--Maryland (US)

Microbial Genomes Curator @ Computercraft Corporation--Maryland (US). Submitted by Computercraft Corporation; posted on Saturday, March 17, 2012

RESPONSIBILITIES:
Computercraft seeks a microbiologist to work with a team of software developers and biologists on microbial genome analysis including pan-genome, protein clusters, phylogenetic tree and more. This is a technically challenging position requiring experience in genome sequencing and annotation. A background in comparative genome analysis such as alignments and tree building is a plus.

Our scientists work with genomic experts at the NIH's National Center for Biotechnology Information (NCBI) to create and enhance a suite of databases and tools available to researchers worldwide. Teamwork interaction and excellent organizational skills are essential for this detail-oriented position, as is scientific problem-solving with a results-oriented focus.

REQUIREMENTS:
* PhD in molecular biology, microbiology, or related field
* Experience in genome sequencing and annotation
* Familiarity with BLAST, genome browser, and genome assembly data
* Excellent verbal and written communication skills as well as organizational skills
* Strong interest in contributing to the development of public database resources

PREFERENCES:
Other Desirable Skills:
* Programming experience with LINUX/UNIX
* Scripting experience in PERL or related scripting languages

COMPENSATION:
Computercraft offers a competitive salary and an excellent benefits package including PPO health insurance with 100% company paid premiums, 401K program with matching, paid time off and holiday pay, life insurance, flexible spending and disability coverage. We offer an excellent work life balance with a standard 40 hour work week and the chance to work alongside accomplished scientists at NIH/NCBI.

HOW TO APPLY:
To apply for this position or learn about other Computercraft job opportunities, please visit the Careers section of our website: http://www.computercraft-usa.com/

POLICY:
Computercraft is an equal opportunity employer.

Bioinformatics Bacterial Identification Tool

BIBI automates DNA sequence analysis for bacterial identification in
the clinical field. BIBI relies on the use of BLAST and CLUSTAL W
programs applied to different subsets of sequences extracted from
GenBank. These sequences are filtered and stored in a new database,
which is adapted to bacterial identification.

For further details refer :http://umr5558-sud-str1.univ-lyon1.fr/ lebibi/lebibi.cgi

BioPuppy Linux

• It is more user friendly and easy to use for those new to Linux.
• Contains all the necessary Bioinformatics tools.
• BioPuppy contains extensive help files for ALL its programs and Bioinformatcis tools with screen shot.
•  Sequence Analysis tools such as: Genewise, Muscle, Sigma etc are already embedded.
•  Structure Prediction tools such as: Phylogibbs, Mfold, FastLink are present.
•  Protein Structure Analysis Tools like Rasmol and Phylogenetic Analysis Tools such as FastDNA and Philip are already embedded.
• Most Importantly Molecular Dynamics tools such as GROMACS,
• Statistical Analysis Tools such as R and BioConductor are pre-loaded.
• It also contains BLAST, EMBOSS, Biofox and other online tools also.

Install BioPuppy and experience all these features. Welcome to BioPuppy Linux

 

TS-AMIR: A Topology String Alignment Method for Intensive Rapid Protein Structure Comparison

In structural biology, similarity analysis of protein structure is a crucial step in studying the relationship between proteins. Despite the considerable number of techniques that have been explored within the past two decades, the development of new alternative methods is still an active research area due to the need for high performance tools. Results: In this paper, we present TS-AMIR, a Topology String Alignment Method for Intensive Rapid comparison of protein structures. The proposed method works in two stages: In the first stage, the method generates a topology string based on the geometric details of secondary structure elements, and then, utilizes an n-gram modelling technique over entropy concept to capture similarities in these strings. This initial correspondence map between secondary structure elements is submitted to the second stage in order to obtain the alignment at the residue level. Applying the Kabsch method, a heuristic step-by-step algorithm is adopted in the second stage to align the residues, resulting in an optimal rotation matrix and minimized RMSD. The performance of the method was assessed in different information retrieval tests and the results were compared with those of CE and TM-align, representing two geometrical tools, and YAKUSA, 3D-BLAST and SARST as three representatives of linear encoding schemes. It is shown that the method obtains a high running speed similar to that of the linear encoding schemes. In addition, the method runs about 800 and 7200 times faster than TM-align and CE respectively, while maintaining a competitive accuracy with TM-align and CE. Conclusions: The experimental results demonstrate that linear encoding techniques are capable of reaching the same high degree of accuracy as that achieved by geometrical methods, while generally running hundreds of times faster than conventional programs.

Do you wish to know more?

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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