Advanced Computing Approaches

Introduction, History of Bioinformatics-I (Till 2000), History of Bioinformatics-II (After 2000), Applications of Bioinformatics-I, Applications of Bioinformatics-II, Cell organelles-I, Cell organelles-II, Central Dogma, DNA Structure, Replication of DNA, Structure of RNA, DNA Transcription, Protein Translation, First Algorithm-Multiplication of integers, Karatsuba Algorithm, Recursive Algorithm-Theory, Recursive Algorithm-Application, Sorting Algorithms-Classification, Sorting Algorithms-Example, Introduction to Bioinformatics Algorithm, Bioinformatics algorithm-Example, Simple algorithms operations-I, Simple algorithms operations-II, Pseudocode with simple example, Biological Algorithms versus Computer, algorithms-I, Biological Algorithms versus Computer algorithms-II, Algorithm and complexity-The Change Problem-I, The Change Problem-II, Better Change Problem, Correct versus incorrect algorithm, Brute Force change, Tower of Hanoi, Selection Sort, Big O notation, Algorithm Design Techniques I, Algorithm Design Techniques II, Restriction Mapping I, Restriction Mapping II, Dynamic Programming I Partial Digest Problem, Dynamic Programming II, Algorithm for Dynamic Programming, Partial Digest Problem, Practical Restriction Mapping Algorithm, Partial Digest Algorithm I, Partial Digest Algorithm II, Regulatory Motifs, Profiles I, Profiles II, Profiles III, Motif Finding Problem I, Motif Finding Problem II, Search Trees-Introduction, Search Trees-Best Alternative, Algorithm for Search Trees I, Algorithm for Search Trees II, Next Vertex Algorithm, Bypass Algorithm , Finding Motifs, Simple Motif Search Algorithm, Branch and bound Algorithm, Brute Force Median Search, Genome Rearrangements, Sorting by reversals, Reversal Distance Problem, Simple Reversal Sort Algorithm, Approximation Algorithms , Breakpoint Reversal Sort Algorithm, Theorem – Permutation, A greedy approach to motif finding, The Power of DNA Sequence Comparison, The Change Problem Revisited, Recursive Change Algorithm, Dynamic Programming Algorithm, Manhattan Tourist Problem I, Brute Force vs Greedy Algorithm, Weight of the paths, 85. Calculation of weights, Manhattan Tourist Algorithm, Directed Acyclic Graphs, Directed Acyclic Graphs, DAG in daily life

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