Cancelled Classes (tentative):
March 13-14;...
Note that some of these classes may be covered by Guest Lectures.
Topic of Modules 1 & 2
Biology, Genomics, Algorithms and Data Structures. By the end of this module, the students will have familiarity with basic concepts of biology in terms genomics, transcriptomics and proteomics and how they are used in formulating combinatorial problems leading to data science algorithms and their complexity. The students will also have a historical perspectives. [Reading 1] https://en.wikipedia.org/wiki/Algorithm; https://en.wikipedia.org/wiki/Muhammad_ibn_Musa_al-Khwarizmi [Reading 2] https://en.wikipedia.org/wiki/Genomics; https://en.wikipedia.org/wiki/Human_Genome_Project
Topic of Module 3, 4, 5 & 6
Objective(s) By the end of this module, the students will have familiarity with basic concepts of Graph Theory and ability to devise new graph algorithms for bioinformatics applications. Topic of interest: Graph Representation, Trees, DeBruijn Graph, DFS and BFS, Shortest Paths, Eulerian Paths, Hamiltonian Paths, Applications to Genomics [Reading 1] Cormen et al. Chapters 23 and 25. [Reading 2] https://en.wikipedia.org/wiki/Hamiltonian_path; https://en.wikipedia.org/wiki/Eulerian_path
Topic of Module 7, 8 & 9.
Strings & Stringology. By the end of this module, the students will have familiarity with basic concepts of sequence analysis and will be able to devise new string theoretic algorithms to manipulate data structures involving strings over finite alphabets. Topics of interest: Suffix Trees and Suffix Arrays, String Matching, Edit Distance, Alignment, BLAST, BLAT. [Reading 1] Cormen et al. Chapter 34 [Reading 2] https://en.wikipedia.org/wiki/BLAST
Topic of Module 10, 11 & 12
Sorting and Searching By the end of this module, the students will have familiarity with basic concepts of representation of bioinformatics statistics and data and will be able to devise algorithms to search, organize and analyze data using efficient algorithms. Topics of interest: Order Statistics, Sorting, Binary Search, Merge Sort, Heap Sort, Quick Sort, Selection and Median. [Reading 1] Cormen et al., Chapters 7, 8, 9, & 10. [Reading 2] https://en.wikipedia.org/wiki/Sorting_algorithm; https://en.wikipedia.org/wiki/Search_algorithm
Topic of Module 13
Computational Complexity Analysis By the end of this module, the students will have familiarity with basic concepts of complexity theory and will be able to understand, devise and solve recurrence equations for expressing the time complexity of an algorithm. Problem. [Reading 1] Cormen et al. Chapters 2, 3 and 4. [Reading 2] https://en.wikipedia.org/wiki/Recurrence_relation
Topic of Model 14
Future!