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We describe Bioconductor infrastructure for representing and computing on annotated genomic ranges and integrating genomic data with the statistical computing features of R and its extensions. At the core of the infrastructure are three packages: IRanges, GenomicRanges, and GenomicFeatures. These packages provide scalable data structures for representing annotated ranges on the genome, with special support for transcript structures, read alignments and coverage vectors. Computational facilities include efficient algorithms for overlap and nearest neighbor detection, coverage calculation and other range operations. This infrastructure directly supports more than 80 other Bioconductor packages, including those for sequence analysis, differential expression analysis and visualization.

Feng JQ, Huang H, Lu Y, Ye L, Xie Y, et al. (2003) The Dentin matrix protein 1 (Dmp1) is specifically expressed in mineralized, but not soft, tissues during development. Journal of dental research 82: 776–780. doi: 10.1177/154405910308201003. CrossRef PubMed/NCBI Google Scholar 10. Lu Y, Xie Y, Zhang S, Dusevich V, Bonewald LF, et al. (200

Cultures or bone chips were homogenized in Trizol solution using a polytron (Ika) for approximately 40 seconds. RNA was extracted and converted into cDNA utilizing Improm-II™ Reverse Transcription System (Promega). Real-time PCR was performed using TaqMan® Gene Expression Assays specific for Gapdh (Mm99999915_g1), dentin matrix protein 1 (Dmp1, Mm00803833­­_g1), bone sialoprotein (Bsp, Mm00492555_m1), Sost (Mm00470479_m1), adipsin (Mm00442664_m1) and adiponectin (Mm00456425_m1). Data obtained were normalized to Gapdh expression levels. Differences in expression between selected groups were compared using Student’s t-tests.

Cell sorting of BOC cultures derived from Dmp1Cre/Ai9 mice. BOC from Dmp1Cre/Ai9 mice were cultured for before FACS sorting. Nontransgenic cells were utilized as controls to preset the sorting gates (A). The proportion of Dmp1Cre/Ai9+ and Dmp1Cre/Ai9− cells is indicated (B). Reanalysis of the sorted population purity is shown for Dmp1Cre/Ai9− (C) and Dmp1Cre/Ai9+ (D) cells. Data is representative of five different sorting experiments. RNA from digested bone chips (n = 2), and from 10 day Dmp1Cre/Ai9+ and Dmp1Cre/Ai9− cultured cells immediately post sorting (n = 3) was used to assess expression of osteocyte marker genes Dmp1 (E) and Sost (F). Expression levels are presented as mean±SEM and are normalized to Gapdh expression. Changes in Dmp1 expression were not statistically significant. ND, not detectable; SSC, side scatter. doi:10.1371/journal.pone.0075204.s002

Some specific points Use the 'active' voice: don’t write “I was able to see…” when you could write “I saw…” or "the cells were incubated" when you could write "I incubated the cells". Use first names rather than titles to help personalise the research. Only include important and relevant information. Readers are restless and will stop reading if you include information that is important only to fellow scientists. Always bear in mind what is interesting to your reader. Avoid acronyms if at all possible — even if a protein is known as ABC2D among scientists, it is more appropriate and understandable to use a different name for a public audience. If you use any technical terms, do so sparingly and consistently and provide explanations if necessary. Be careful with grammar, especially punctuation and especially commas and semi-colons. Don’t use a semi-colon unless you are sure it is appropriate. Double check your use of commas too — don't pepper the text with them at random but use them when you need them. Break up your paragraphs. It is hard work to read paragraphs of more than, say, 100 words. There’s no hard and fast rule for word count in paragraphs (or sentences) but if in doubt, put in a break. Don’t berate the media for not covering your disease area or research interest in the past — not only is this undiplomatic, as you are potentially being featured in the Times Higher Education, it is irrelevant: your reader is reading about it now.

Where the proposal involves collaboration with one or more industrial partners the applicant will need to submit a MICA form and Heads of Terms, at the full stage, if invited forward.

The £180 million Biomedical Catalyst is an integrated translational funding programme jointly operated by the Medical Research Council and the Technology Strategy Board providing responsive and effective support for the best life science opportunities arising in the UK.