RNA Biology provides incentives to review

The full text of the email from Renee Schroeder and Eva Riedmann from RNA Biology is below. The gist of it is that researchers get free subscriptions and discounts on publication costs in exchange for reviewing. This is a clever move by them (in my completely biased opinion). The journal, Nucleic Acids Research, is the only other journal I know of that offers incentives for reviews. They offer a few pounds towards books or CDs from their preferred suppliers in exchange for reviewing. This is nice, but frankly the selection from those sources is very limited. I'd much rather have full access to the journals I review for (actually, I'd rather everyone had full access, that's another battle). All too often I've wanted to look at the published version of a manuscript that I've reviewed and not had access to it. This is ridiculous.



Dear Research Community –

We are writing to you now because you have either served as a reviewer or have submitted a manuscript to the journal RNA Biology in the past.

RNA Biology will be instituting a reviewer incentive program offering free subscriptions and discounts on publication costs in exchange for timely reviews. To guarantee the success of this program we need to update our database and are requesting a few moments of your time.

Please login to the RNA Biology submission and peer-review website here:

http://rnabiol.msubmit.net/

and click on the link “Modify Profile/Password.”

If you could please ensure that your institutional affiliation, address, and email address are up to date AND please select up to five ‘Areas of Expertise’, we would greatly appreciate this. (For your convenience, we have listed the areas of expertise below.)

This will ensure that we are able to notify you of new developments with the journal. Additionally, this information will help ensure that we have a robust database from which to quickly identify appropriate peer-reviewers.

If you have any questions or concern please contact us at rna@landesbioscience.com

Thank you very much for your help.

Sincerely,

Renee Schroeder
Editor-in-Chief
University of Vienna

Eva Riedmann, Ph.D.
Acquisitions Editor
Landes Bioscience

Areas of Expertise

Apatamers
biogenesis
bioinformatics
cancer
cell biology
chromatin
developmental biology
epigenetics
mechanism of translation
methods
miRNA
mRNA transport/localization
natural antisense
neurobiology/neurological disease
prokaryotes
protein-RNA interactions
regulation of stability/degradation
regulation of translation
ribonucleases
ribosome
riboswitches
ribozymes
RNA binding proteins
RNA damage/repair
RNA in disease
RNA stability/degradation
RNA viruses
RNomics
siRNA
small and large non-coding RNAs
splicing/pre-mRNA processing
therapeutics
transcriptome
TRNA

Fetching sequences from EMBL/ENA using wget/curl

Every time I want to download several EMBL files (eg. all the bacterial genomes) I spend at least an hour trying to find the right URL syntax. This post is a public note to self that will help me next time and perhaps help others who are also receiving a few lines of HTML when all they want is a verdammt plain-text EMBL formatted file.

There is actual documentation on the right syntax here, which again takes a while to find, searching for wget, curl, EMBL and various related combinations doesn't get you there quickly. However, the main issue I have is, if I go to the recommended sequence record eg. here, none of the links work with a simple "wget URL" or "curl -G URL".

So, if I want to fetch the Roseobacter denitrificans genome sequence with EMBL accession CP000362. I use:
wget http://www.ebi.ac.uk/Tools/dbfetch/dbfetch/embl/CP000362
or if you're into curl:
curl -G http://www.ebi.ac.uk/Tools/dbfetch/dbfetch/embl/CP000362 > CP000362.embl

Simple!

Excited about eQTLs

During my time at the Sanger Institute I heard many talks from people in Manolis Dermitzakis' group on expressed quantitative trait loci (eQTLs). For practical purposes these eQTLs are SNPs that are strongly correlated with expression level eg. a population's genotypes at one site might be AA, AG and GG, a nearby gene might have corresponding median expression levels of 2, 4 and 6 (arbitrary units) across multiple genotyped individuals. Something I've always thought would be very interesting to look at was the functional characterisation of the sites these SNPs lie in. A recent paper by Gaffney et al entitled "Dissecting the regulatory architecture of gene expression QTLs" has made some inroads into this problem. It looks like they've focussed on the promoter regions and found that ~40% are in open chromatin structures and are enriched in transcription factor binding sites. My interests are of course more on the putative cis-regulatory elements such as structured UTR elements (eg. IREs) and microRNA binding sites that the eQTLs can presumably influence. So it looks like there are still many fun projects that these datasets can spawn.

Interesting articles

This week I've been setting up a new laptop. Shifting from a MacBook back to my beloved Lenovo ThinkPad running Ubuntu. Things have really moved along in the last 4 years (glipper/klipper - how I've missed you!).

Consequently I haven't done anything terribly useful this week other than give a brief talk for the monthly NZ Bioinformatics VC (I don't know what VC stands for yet - must find out). Also, later today I'll give a talk at the BIC Symposium. Fortunately I can reuse one or two slides.

In the absence of anything really useful to say I've spotted a couple of articles this week that have made it to my "I really must read these on the bus to work one day" pile. The first [1] describes some experimental work that shows that Hfq binds to the rho independent terminator of the sRNA SgrS. Since I've recently developed quite an interest in terminators I think I'd better take a look at this result. The second [2] is pulled from Sean Eddy's preprint server. This describes some of his and Diana Kolbe's work on applying HMMER3-like speedups to covariance models. The results appear to be both promising and disappointing. They definitely speed up CMs but to come at a cost to sensitivity, however merging the accelerated CM results with an HMM-filter appears to bring the sensitivity back up to the level of a raw CM, the combined filters appear to be much faster than running a raw CM. So all in all a very promising result. Hopefully this work will be added to the main trunk of Infernal soon.

[1] Otaka H, Ishikawa H, Morita T, Aiba H. (2011) PolyU tail of rho-independent terminator of bacterial small RNAs is essential for Hfq action. Proc Natl Acad Sci U S A.

[2] D. L. Kolbe, S. R. Eddy. (2011) Fast Filtering for RNA Homology Search. In press.

First post

I hope to make this a fairly active blog. Including a weekly roundup of links and articles in the RNA bioinformatics field, an edited diary of my research activities, comments on other research areas, thoughts on bioinformatics and research in New Zealand and anything else roughly professional that seems blog-worthy.