Mais Challenges

São inúmeros os desafios com as novas tecnologias chegando... muitos já pensaram sobre isso...
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http://picasaweb.google.com/martinsnat/ChallengesOnBioinformatics
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Mais reflexões sobre desafios

Bioinformatics challenges of new sequencing technology.

Pop M, Salzberg SL.

Center for Bioinformatics and Computational Biology, University of Maryland, MD 20742, USA.

New DNA sequencing technologies can sequence up to one billion bases in a single day at low cost, putting large-scale sequencing within the reach of many scientists. Many researchers are forging ahead with projects to sequence a range of species using the new technologies. However, these new technologies produce read lengths as short as 35-40 nucleotides, posing challenges for genome assembly and annotation. Here we review the challenges and describe some of the bioinformatics systems that are being proposed to solve them. We specifically address issues arising from using these technologies in assembly projects, both de novo and for resequencing purposes, as well as efforts to improve genome annotation in the fragmented assemblies produced by short read lengths.

Desafios em Bioinformática

Caros leitores,

convido-os a refletir sobre desafios em bionformática. É sempre necessário ter desafios.... convido-os a pesquisar...imaginar... para começar o texto de Chris Burge.

The Top Bioinformatics Challenges according to Chris Burge at MIT and his colleagues are as follows...

1. Precise, predictive model of transcription initiation and termination: ability to predict where and when transcription will occur in a genome
2. Precise, predictive model of RNA splicing/alternative splicing: ability to predict the splicing pattern of any primary transcript
3. Precise, quantitative models of signal transduction pathways:ability to predict cellular response to external stimuli
4. Determining effective protein-DNA, protein-RNA and protein-protein recognition codes
5. Accurate ab initio structure prediction
6. Rational design of small molecule inhibitors of proteins
7. Mechanistic understanding of protein evolution: understanding exactly how new protein functions evolve
8. Mechanistic understanding of speciation: molecular details of how speciation occurs
9. Continued development of effective gene ontologies-systematic ways to describe the functions of any gene or protein
10. (Infrastructure and education challenge)
11. Education: development of appropriate bioinformatics curricula for secondary, undergraduate and graduate education