Biomolecular sequence analysis, Needleman/Wunsch and Smith/Waterman alignment algorithms. Pattern matching algorithms and sequence similarity search. Phylogenetic trees, distance based hierarchical clustering and protein and genome sequence database search. RNA secondary structure prediction problem. Exact and approximation algorithms, heuristics, stochastic context-free grammars, k-mer indexes.
İlk dosyayı sen ekleyebilirsin — notlar, geçmiş finaller, çözümler, cheat-sheet, ne varsa. Drive linki / PDF / ZIP / fotoğraf, hepsi olur.
Şu an: mail at, ben düzenleyip yayına alayım. Form/upload UX yakında geliyor (Kimya tasarlıyor).
At least 30% average on homeworks, and 30% on quizzes required.
Use of GenAI for homeworks is prohibited in this course.
A brief introduction to computational complexity and algorithm design techniques DNA mapping & motif search. Exact sequence search algorithms Exact string search algorithms. Exact string search (cont’d) and indexing. Elements of dynamic programming, Manhattan tourist problem, introduction to sequence alignment. Global alignment. Local alignment, linear space alignment. Bit-vector alignment algorithm. Four-Russians trick. Multiple sequence alignment. Partial order alignments. Heuristic sequence search. Short introduction to BLAST. Hash table indexes, minimizers and chaining. Maximal exact matches (MEMs), maximal unique matches (MUMs) to speed up search. Mapping tools such as BWA-MEM and minimap2. K-mer index structures (hash tables, minimizers, CQF). K-mer “containers” (Bloom filters, SBTs, BSTs). Alignment-free k-mer composition analysis. Minimum perfect hashing, MinHash, Jaccard Index. Phylogenic tree construction. Graphs in genome analysis. OLC, de Bruijn, string graphs. Aligning reads to graphs. Applications: short introduction to genome sequencing. Current platforms and data types. Standard file formats. Applications: programming libraries, application-specific programming languages. ECTS - Workload Table: Activities Number Hours Workload Final exam 1 2,5 2.5 Preparation for Midterm exam 1 20 20 Course hours 14 3 42 Quiz 6 1 6 Individual or group work 14 2 28 Preparation for Final exam 1 25 25 Homework 5 5 25 Midterm exam 1 2 2 Total Workload: 150.5 Total Workload / 30: 150.5 / 30 5.02 ECTS Credits of the Course: 5 Type of Course: Lecture Course Material: Slides - Written - Lecture Notes Teaching Methods: Assignment - Lecturing