Computational Biology exam 1
Exhaustive algorithm
accurate, A LOT of time and memory
looks at every possibility
greedy algorithm
follows problem solving heuristic of making optimal choices at each stage. Hopefully
finds the global optimum.
not as thorough, uses shortcut
recursion
calls itself
Dynamic Programming
break problem into sub problems
ex. NW, SW, BLAST
Randomization
uses random number to make decision
stochastic
randomness affects either runtime or output
heuristic
decision may not be optimal but is fast enough or close enough to optimal
greedy algorithm
exact vs approximate
BLAST = approximiate
deterministic vs stochastic
Deterministic - same decision at every step, always same output given input
Stochastic - depends on random but informed choices, can have different results from
different runs
NW
global, exhaustive, pairwise
SW
local exhaustive pairwise
