Quantcast

B.6 TOP BIOINFORMATICS CHALLENGES

B.6 TOP BIOINFORMATICS CHALLENGES (Chris Burge et al.)

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

C. Burge, “Bioinformaticists Will Be Busy Bees,” Genome Technology, No. 17, January, 2002. Available (by free subscription) at
http://www.genome-technology.com/articles/view-article.asp?Article=20021023161457.




The material in this press release comes from the originating research organization. Content may be edited for style and length. Want more? Sign up for our daily email.