10 papers that every bioinformatician should read

This list of top 10 papers in bioinformatics does not only consist of purely bioinformatic papers, but shows how gentle and simple bioinformatics can and should be:

1. Dudley JT, Butte AJ (2009) A Quick Guide for Developing Effective Bioinformatics Programming Skills. PLoS Computational Biology 5(12)
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"Consequently it is no surprise that many successful bioinformatics apps are written by biologists who lack formal computer science training, as they undoubtedly put scientific utility ahead of architectural elegance and completeness."

2. Kim TK, Hemberg M, Gray JM, Costa AM, Bear DM, Wu J, Harmin DA, Laptewicz M, Barbara-Haley K, Kuersten S, Markenscoff-Papadimitriou E, Kuhl D, Bito H, Worley PF, Kreiman G, Greenberg ME (2010) Widespread transcription at neuronal activity-regulated enhancers. Nature 465(7295)
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Simple and brilliant use of ChIP-seq and RNA-seq techniques.

3. Goecks J, Nekrutenko A, Taylor J, and The Galaxy Team (2010) Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences. Genome Biology 11(8)
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Bioinformatics for the masses.

4. Ameur A, Zaghlool A, Halvardson J, Wetterbom A, Gyllensten U, Cavelier L, Feuk L (2011) Total RNA sequencing reveals nascent transcription and widespread co-transcriptional splicing in the human brain. Nature Structural & Molecular Biology 18
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Great example of getting additional features from RNA-seq data.

5. Smedley D, Haider S, Ballester B, Holland R, London D, Thorisson G, Kasprzyk A (2009) BioMart – biological queries made easy. BMC Genomics 10
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Data mart for biologists.

6. Krzywinski M, Schein J, Birol I, Jones S, Marra M (2008) Circos - an information aesthetic for comparative genomics. Genome Informatics conference
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Beauty of data visualization.

7. Majewski J, Ott J (2004) Distribution and characterization of regulatory elements in the human genome. Genome Research 12
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One of the first successful attempts to analyze genomic features at genome scale.

8. Kent WJ, Zweig AS,  Barber G, Hinrichs AS, Karolchik D (2009) BigWig and BigBed: enabling browsing of large distributed datasets. Bioinformatics 26(17)
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Standard formats for storing NGS-data. Fast, simple.


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