Index slides en cursus bio-informatica

Hoofdstuk Onderwerpen Slides Boek pagina's
H1: Intro 7- 28
H2: Background in  Database organisation  6  29-30
computer sciences  Relational databases  7-8  31
 Algorithms  9-14  32-37
 Classification problems  33  38
 Confusion matrix  35-39  39-42
 ROC  40-41  42
 Graph theory  43- 58  42-51
 Different types of graphs  44--51  42-45
 Adjacency matrix  46  46
 Adjacency list  47  46
 Brute force algorithm  63  51-52
 Big-O-notation  65-68  53
 Complexity classes  69-72  53-54
 Exhaustive vs. heuristic  73  54-55
 Search, decision and optimization  74-91  55-59
problems/algorithms
 Iterative improvement  82-87  58-59
H3: Pairwise  Match/mismatch/hamming distance  7  64-67
alignment  Substitution matrix and alignment score  17-22  67-72
o Gap penalties  23-25  72-73
 Global vs. local pairwise alignment  32  75
 Definitions: similarity/identity/conservation  35-39  77
 /Homologs/orthologs/paralogs/xenologs/
analogs
 Dot matrix of dotplot  44-50  78-81
o EMBOSS dotplot  50-54  81
 Global alignment  55-80  81-93
o Needleman-Wunsch  59-80  84-93
 Local alignment  82-91  93-96
o Smith-Waterman
 Advanced penalties  92-93  97
 Substitution matrices  97-114  98-101
o PAM  115-141  102-106
o Blosum  142-150  106-108
o PAM vs. Blosum  151-154  108
H4: Multiple  Use MSA  6-15  111
alignment (MSA)  MSA as a graph  20-24
 Dynamic methods (exhaustive)  25-37  115-120
o Lipman MSA algorithm  29-30  117-118
o Scoring multiple alignment  31-37  118-120
 Progressive methods (heuristic)  39-49  121-125
o Feng-Doolittle algorithm  41-45  121-122
o Clustal W  46-49  122-125
 Iterative methods  51-58  125-130
o MAFFT  57  126-127
o MUSLE  53-56  127-128
o SAGA  58  128-130
 Consistency-based methods  60-67  130-132
o ProbCons  61  130-131