Mendeley sharing papers across computers

Goal: Organize all your papers and being able to use Mendeley from home and at work for this task.

First Problem: Since I’ve being using different computers for saving my articles I first had to find duplicated articles and delete them.

Solution: Use FSLINT for finding duplicated files on your computer. DONE

Now I have all my article in a folder inside Dropbox!


Next Goal: Integrate Mendeley with Dropbox!

And how do I access my collection of papers on my Tablet ?

I can use Scholar on my tablet everytime I want to read a paper as long I syncronized the paper with the mendeley web.

So on this way it’s easy to transfer the files that I’m reading to Mendeley.


How to install broadcom 4321 on Ubuntu 12.04

Driver from lspci: Broadcom Corporation BCM4321 802.11a/b/g/n (rev 03)

On Ubuntu, you will need headers and tools. Try these commands:
sudo apt-get install build-essential linux-headers-generic
sudo apt-get build-dep linux

sudo apt-get update
sudo apt-get –reinstall install bcmwl-kernel-source

Reboot and try it out!


Links da Semana

How to partition your computer for windows and linux?

This kind of partition configuration let me always have windows and linux at the same time and I can format linux at any time without changing anything on my /home

Device Boot      Start         End      Blocks   Id  System

/dev/sda1   *        2048      409599      203776    7  HPFS/NTFS/exFAT
/dev/sda2          409600   226192803   112891602    7  HPFS/NTFS/exFAT
/dev/sda3       616818688   625140399     4160856    c  W95 FAT32 (LBA)
/dev/sda4       226193406   616818687   195312641    5  Extended
/dev/sda5       226193408   265253954    19530273+  83  Linux
/dev/sda6       265256960   275019775     4881408   82  Linux swap / Solaris
/dev/sda7       275021824   616818687   170898432   83  Linux


Broad releases FASTG reference format that contains variation

The FASTG Format Specification Working Group is pleased to announce version 1.0 of the FASTG specification

FASTG is a format for faithfully representing genome assemblies in the face of allelic polymorphism and assembly uncertainty. Currently genome assemblies are represented linearly, as sequences of bases, recorded in FASTA files. Since chromosomes are in fact linear or circular, this makes sense, so long as one has complete knowledge of the genome. However, many genomes contain polymorphisms that cannot be represented in a simple linear sequence, and almost all assemblies contain errors and omissions, which can result in incorrect biological inferences. The FASTG format aims to address this problem using a flexible graph-based approach to encode any variability in the sequence, along with metadata to score and annotate the source of those variations. Assembly graphs in FASTG can be easily translated into linear FASTA sequences to support current analysis tools for reading mapping, annotation, visualization, etc, but our hope is to develop a next generation of assembly and genome analysis algorithms that can work with the graph structure directly. For the complete specification and additional information on FASTG, please visit:

If you are interested to discuss this further, please subscribe to the assemblathon-file-format mailing list:

The immediate plans are to enlist help to develop a reference library and command line suite for parsing, transforming, and querying assemblies in FASTG format, similar to the widely used SAM/SAMTools suite.


Your Genome? Which One?

One thing is clear at this stage: the assumption that each individual has a unique genome has been overthrown to some extent. Think how this might impact common evolutionary studies. For years, evolutionists have claimed small differences between human and chimpanzee genomes. What if the percent difference is a function of the source cells used? Remember, the Yale team found differences between cells in the same organ — human skin. If the percent difference grows or shrinks depending on the source, any conclusions about human-chimp similarities would prove unreliable.


It’s also not clear yet whether geneticists will be able to mask the differences between cells to establish an individual’s genome (to say nothing of a species’s genome) as a useful concept. Results would appear to be a function of investigator choice. Say, for instance, that an evolutionist chooses to compare genes of a particular kind of blood cell between species. If the CNV’s and SNP’s vary significantly from blood cell to blood cell within the individual, the results will be skewed. Mixing or averaging the maps of numerous cells, though, risks creating a theoretical construct that does not correspond to reality. Which cells should be averaged? Will the averages converge or diverge, depending on which cells are selected? Philosophers of science can have fun with this one.

Claims about evolutionary similarities and differences based on genetics must be taken with a grain of salt from now on. Perhaps the feared “profound implications” will prove inconsequential. If nothing else, though, the Yale study provides an example of conceptual superstructures built on shaky assumptions and “prevailing wisdom.” As those of us in the intelligent design community know, what prevails at a given moment is not necessarily wise.