Attack of the flies!

The 12 genomes are out!

Check out the relevant papers in Nature, Genome Research, PLoS Genetics, PLoS Biology, Genome Biology.

Elephant on a trampoline

I couldn't resist (doing reseach on elephants and all)... a great animation movie!

Webservers for detection of positively selected residues accounting for 3D protein structure

Three webservers so far that estimate ω (=Ka/Ks=dn/ds) taking into account the protein's tertiary structure (PDB ID):

- SELECTON by Tal Pupko's group at Tel Aviv University

- SWAKK by Laura Landweber's group at Princeton University

- Ka/Ks w/ 3D-windowing by David Liberles' group at the University of Wyoming

What's the impact factor got to do with paper quality?

Postma E. (2007) Inflated impact factors? The true impact of evolutionary papers in non-evolutionary journals. PLoS ONE 2(10):e999.

Too much ado about high impact factor journals. Evolutionary papers in lower-ranking non-specialized journals are undervalued. A call for a more elaborate journal classification system including field-oriented impact factors.

Intense sweetness surpasses cocaine reward

Lenoir et al. (2007) Intense sweetness surpasses cocaine reward. PLoS ONE 2(8):e698.

A cool experiment showed that rats prefer saccharin-sweetened water (calorie-free) to intravenous cocaine. The authors speculate that intense sweetness being a supernormal stimulus can override homeostatic and sel-control mechanisms and lead to addiction – greater than cocaine addiction! In most mammals sweet taste perception is primarily owed to the existence of two G-protein-coupled receptors (T1R2 & T1R3) that evolved in sugar-free ancestral environments not adapted to really sweet conditions.

RAxML black box

RAxML comes now in a new webserver flavor called RAxML Black Box. This is in addition to the RAxML webserver on the CIPRES Portal.

Accepts multiple outgroups (thanx, Alexis :-), does DNA and AA (not combined), accepts partitioned alignment (mixed models), emails a link to the results URL.

Brought to you by Alexandros Stamatakis & Jacques Rougemont.

Nature Editorial: ERC not disclosing the state-members distribution of its grants shortlist

Nature 448, 727-728 (16 August 2007)

Division of labour: The European Research Council shouldn't be coy about saying who will get its first set of grants.

The first Europe-wide research agency to distribute funding purely on the basis of scientific merit is working with commendable efficiency. Its officials have just ploughed through more than 9,000 first-stage applications for the inaugural programme of grants and asked 559 of them to submit a complete application. Around half of these shortlisted candidates will eventually win five-year grants worth up to euro dollar400,000 (US$550,000) per year.

The European Research Council (ERC) has done well to get so far within eight months of its official creation. But it is already facing criticism for its reluctance to reveal the exact distribution of nationalities on the shortlist. The ERC's decision to keep this information to itself for the time being can be read two ways: as a failure to be transparent or as a pragmatic response to a tricky political environment.

The ERC's mission is perhaps unprecedented in the brief history of the European Union (EU). It has to distribute large amounts of European money — building up to euro dollar1 billion a year within a few years — to the best research proposals, regardless of nationality or other political criteria. Both the EU member states and the European parliament have fully signed up to this mission.

Nonetheless, the young agency's leadership can expect to take some political heat if, as is likely, most of its grants go to those EU countries that are already most established scientifically. A comparable dilemma has been encountered in the past by the US National Science Foundation (NSF), an agency that, perhaps more than any other, the ERC seeks to emulate. NSF grants have always flowed disproportionately to certain states, such as Massachusetts and California, where US scientific excellence is most heavily concentrated. The agency has dealt with the political challenge that this presents by publishing reams of relevant data upfront, while developing programmes (at the prompting of Congress) that assist researchers in the states that do less well with their applications. It has done this without compromising its criteria for grant selection.

One of the council's top priorities is to make sure that it establishes a reputation for excellence in its processes. It must do this to win the solid support of European scientists ahead of its first formal evaluation by the EU authorities, which will take place in just two years' time. For now, the council is still negotiating the details of the final EU executive agency within which it will eventually operate. Evaluation of grant proposals, meanwhile, is being overseen by a modest number of staff, most of whom have been seconded from national research agencies.

It is in this fragile context that the ERC is eager to avoid rocking political boats by publishing a national breakdown of who is being considered for its first grants. Instead, it has broken down the shortlist into the groups of nations that joined the EU at different stages of its evolution.

So it has revealed that 45% of the applicants, and 53% of the winners, come from Belgium, Germany, France, Italy, Luxembourg and the Netherlands — the six original members of the European Economic Community, as it was then known. The nine countries that joined after 1973, but before the entry of the former communist states, account for 36% of applications and 27% of the winners. The 12 members who have joined since 2004 did not do so well, putting in 9% of the applications and winning 5%. (Nine 'associated countries', such as Russia and Israel, as well as participants from farther afield account for the rest of the applications.)

Policy-makers might benefit from fuller information about the geographical distribution of both those who apply and those who make the shortlist, if only as a snapshot of how excellence in European science is currently distributed.

Cell phone microwaves affect transcription and protein stability

Friedman et al. (2007) Mechanism of short-term ERK activation by electromagnetic fields at mobile phone frequencies. Biochemical Journal 405(3):559–568.

Abstract: The exposure to non-thermal microwave electromagnetic fields generated by mobile phones affects the expression of many proteins. This effect on transcription and protein stability can be mediated by the MAPK (mitogen-activated protein kinase) cascades, which serve as central signalling pathways and govern essentially all stimulated cellular processes. Indeed, long-term exposure of cells to mobile phone irradiation results in the activation of p38 as well as the ERK (extracellular-signal-regulated kinase) MAPKs. In the present study, we have studied the immediate effect of irradiation on the MAPK cascades, and found that ERKs, but not stress-related MAPKs, are rapidly activated in response to various frequencies and intensities. Using signalling inhibitors, we delineated the mechanism that is involved in this activation. We found that the first step is mediated in the plasma membrane by NADH oxidase, which rapidly generates ROS (reactive oxygen species). These ROS then directly stimulate MMPs (matrix metalloproteinases) and allow them to cleave and release Hb-EGF [heparin-binding EGF (epidermal growth factor)]. This secreted factor activates the EGF receptor, which in turn further activates the ERK cascade. Thus this study demonstrates for the first time a detailed molecular mechanism by which electromagnetic irradiation from mobile phones induces the activation of the ERK cascade and thereby induces transcription and other cellular processes.

rename it with a script

Although there are nice little programs for OSX that rename file names and extensions, like Renamer4Mac, NameChanger and FileSorter, it's always good to have something simple handy, like a script.

in AppleScript: Nem

in Perl: here and here (Linux)

my favorite is a loop in Unix to rename file extensions:

1) if you know what your extensions are:

#!/bin/bash

for i in *fasta
do
mv "$i" "`echo $i | sed -e 's/fasta/fas/'`"
done

for i in *fas
do
cat "$i" | sed -e 's/\.fasta\"/\.fas\"/g' > out
mv out "$i"
done

2) if you prefer an interactive script that will ask you what extension names you want to change from/to:

#!/bin/bash

echo -n "enter old: "
read old
echo -n "enter new: "
read new

for i in *.$old
do
mv "$i" "`echo $i | sed -e "s/$old/$new/"`"
done

The shell scripts were kindly written by my friend Ricardo Baratto

Automation and evaluation of NCPA

Following up on the previous posting on two programs that automate the inference process of Nested Clade Phylogeographic Analysis (NCPA), Panchal & Beaumont create a framework of automated NCPA. Their simulations show that NCPA has a high tendency for false positives. More research is needed, of course, on real-life data.

Panchal M, Beaumont MA. (2007) The automation and evaluation of Nested Clade Phylogeographic Analysis. Evolution 61(6):1466-1480.

Automating Nested Clade Analysis

TCS and GeoDis are the programs to use for NCA, but recently two programs came out that automate NC inference: AUTOINFER and ANeCA.

Addendum (30 Oct 2007)
Panchal & Beaumont (2007) of ANeCA report that Ai-bing Zhang of AUTOINFER has noted that there are some issues in the program that require resolution and that it has temporarily been withdrawn.

Trees: stop fighting!

Tree reconciliation in host-parasite coevolution or in gene-tree fitting has been a long-standing issue in evolutionary biology. Here's some programs that try to bring peace...

TreeMap: for cophylogeny mapping.

TreeFitter: for MP tree-fitting.

SoftParsMap: maps gene trees onto species trees using soft parsimony.

gtp: species tree reconciliation and gene tree parsimony.

UREC: for computing unrooted gene and rooted species tree reconciliation.

CopyCat: easy & fast access to co-phylogenetic analyses. has a wrapper for ParaFit that tests for the association of host and parasite phylogenies.

PriMETV: visualizes tree-within-tree phenomena.

bioinformatics dashboard widgets

Check out ~20 bioinformatics dashboard widgets for OSX Tiger. everything from genetic codes, aminoacid/nucleotide properties, to NCBI BLAST and Entrez. cool!

See the Tree?

Some programs I use to display trees in OSX. Some allow the user to modify trees.

TreeViewX: the industry standard for simple tree visualization.

TreeEdit: views and manipulates trees, re-roots, simulates trees.

FigTree: nice graphical tree viewer.

TreeIllustrator: not only it displays and fiddles with trees, but also has a built-in ToL browser/search engine.

TreeStat: calculates tree statistics (balance, shape, length, popgen).

Phylodendron: draws trees on a webserver or locally (Java app).

TreeJuxtaposer: displays and compares/compresses trees. needs GL4java.

ArboDraw: tree editing with sequence annotation functionality.

TreeMaker: builds taxonomies with species richness data.

TreeSetViz: visualizes tree sets in treespace as a Mesquite module.