Bioinformatics

Algorithms and Pseudocode

Bioinformatics

Formulating Problems


Clarify input and output elements


Requires
modeling

the problem in
some concise form


Example: Given n cities and distances
between cities, find the shortest tour


More concise description of input: integer
N, distances d[i,j], 1<=i<=N, 1<=j<=N.
What about output?

Traveling Salesman Problem


Input:

Integer N



Distances d[i,j],




1<=i<=N, 1<=j<=N


Output:

Permutation p
1

p
2

… p
N

of the



integers 1…N such that




1<=i<N
d[p
i
,p
i+1
] is the



smallest possible

String Search Problem


Input:

Strings s[1…m] and t[1…n]


Output:

The (smallest) position p



such that for all i, 1 <= i <= m,



s[i] = t[p+i
-
1];



p = 0, if no such p exists

Algorithm

String_Search(s[1…m], t[1…n])


for p = 1 to n
-
m+1 do


found = true


for i = 1 to m do



if s[i]


瑛瀫p
-
ㅝ⁴桥1


†††
景畮搠㴠晡f獥


if found then



break

if not found then


return 0

else


return p

Algorithm Specification


Pseudocode: not tied to a particular
programming language syntax


Data


Variables


Arrays


Statements


Assignments and computation


Decisions, conditions, and loops


Break and return