Modeling the Building Blocks of Life

eldavojohn writes "A new research paper is creating some buzz about the roles of computer engineering in biology. Historically, computational techniques in genome sequencing have proved useful in predicting which DNA sequence produces which amino acid and which amino acid sequence produces which protein. Now, this new research is leading towards a robust model of proteins and their messaging systems. This is one step further in understanding the basics of life and, consequently, pushes us closer to being able to emulate organisms entirely from the bottom up instead of our failed prior approaches of from the top down. A long way from perfect, but an opening into a wide field of study and maybe even a new division of biology."

Comments

Hmmm....

[Otter]

C. elegans has a completely predictable sequence of cell division, which is one of the main reasons (along with transparency, self-fertilization, survival in a freezer and some others) why it's so heavily studied.

This is a really nice piece of work, but they picked some really low-hanging fruit to try out their method. Which is one of the hallmarks of really nice work, of course.

Re:Hmmm....

[daniorerio]

you think so? How many animals are really studied do you think? I can give you the answer: C. elegans, fruitfly, zebrafish, bulfrog, chicken, mice and rats. The rest hardly counts. The reason why they choose C. elegans in this case you already stated, the principles of signal transduction apply just as much to human beings as to those worms. Your EGFR/RAS/MAPK pathway isn't that different...

Computer Science not Computer Engineering

[kramer2718]

This may be a bit picky, but the work being done here is not computer engineering but rather computer science. Computer engineering generally refers to engineering techniques for building computers and computer systems (including parts of electrical engineering, materials science, algorithms, etc.) whereas computer science is the study of algorithms. This work is not designing computing systems but rather using algorithms to model the building blocks of biology.