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CS 583

Bioinformatics Algorithms

CS 583 treats biological sequences (DNA, RNA, protein) as strings and asks how you design algorithms that scale when the strings are billions of characters long and the questions, "are these related?", "where does this read come from?", "what does this fold into?", are inherently fuzzy. You'll work through the classical dynamic programming alignments (Needleman-Wunsch, Smith-Waterman) and then the indexing and k-mer machinery that makes real tools like BLAST, BWA-MEM, and minimap2 tractable, with homeworks, quizzes, and a midterm/final anchoring the load. It's a graduate algorithms course that assumes you're comfortable with complexity analysis and basic data structures; the payoff is being able to read and contribute to modern computational biology, where genome graphs and alignment-free methods are now where most of the research happens.

Kredi3ECTS5FakülteFaculty of EngineeringBölümComputer EngineeringKoordinatörCan Alkan

Haftalık müfredat 14 hafta

Hafta 114–20 Eyl
Computational complexity ve algoritma tasarımına giriş
A brief introduction to computational complexity and algorithm design techniques
computational complexityalgorithm design techniques
Hafta 221–27 Eyl
DNA mapping, motif search ve exact search
DNA mapping & motif search. Exact sequence search algorithms
DNA mappingmotif searchexact sequence search algorithms
Hafta 328 Eyl – 4 Eki
Exact string search algoritmaları
Exact string search algorithms.
exact string searchalgoritma
Hafta 45–11 Eki
Exact string search ve indexing
Exact string search (cont’d) and indexing.
exact string searchindexing
Hafta 512–18 Eki
Dynamic programming ve sequence alignment
Elements of dynamic programming, Manhattan tourist problem, introduction to sequence alignment. Global alignment.
dynamic programmingManhattan tourist problemsequence alignmentglobal alignment
Hafta 619–25 Eki
Local alignment ve bit-vector algoritması
Local alignment, linear space alignment. Bit-vector alignment algorithm.
local alignmentlinear space alignmentbit-vector alignment algorithm
Hafta 726 Eki – 1 Kas
Four-Russians tekniği ve çoklu dizi hizalama
Four-Russians trick. Multiple sequence alignment. Partial order alignments.
Four-Russians trickmultiple sequence alignmentpartial order alignment
Hafta 82–8 Kas
Heuristic sequence search ve BLAST
Heuristic sequence search. Short introduction to BLAST. Hash table indexes, minimizers and chaining.
BLASThash table indexminimizerchaining
Hafta 99–15 Kas
Hızlı dizi eşleme: MEM, MUM ve k-mer indeksleri
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).
MEMMUMBWA-MEMk-mer index
Hafta 1016–22 Kas
Alignment-free k-mer kompozisyon analizi
Alignment-free k-mer composition analysis. Minimum perfect hashing, MinHash, Jaccard Index.
k-merminimum perfect hashingMinHashJaccard Index
Hafta 1123–29 Kas
Phylogenetic Tree Oluşturma
Phylogenic tree construction.
phylogenetic treeağaç oluşturma
Hafta 1230 Kas – 6 Ara
Genom analizinde graph'lar
Graphs in genome analysis. OLC, de Bruijn, string graphs. Aligning reads to graphs.
OLCde Bruijn graphstring graphread alignment
Hafta 137–13 Ara
Genome sequencing: platformlar ve dosya formatları
Applications: short introduction to genome sequencing. Current platforms and data types. Standard file formats.
genome sequencingdata typesfile formats
Hafta 1414–20 Ara
Programming libraries ve uygulamaya özel diller
Applications: programming libraries, application-specific programming languages.
programming librariesapplication-specific programming languages

Önerilen kaynaklar 3 kitap

📖
Önerilen
An Introduction to Bioinformatics Algorithms
Neil Jones and Pavel Pevzner
2004 · MIT Press
📖
Önerilen
Algorithms on Strings
Trees, and Sequences: Computer Science and Computational Biology
Dan Gusfield · 1997
📖
Önerilen
Genome-Scale Algorithm Design
Veli Mäkinen, Djamal Belazzougui
Fabio Cunial · Alexandru I. Tomescu

🤖 GenAI politikası

Use of GenAI for homeworks is prohibited in this course.

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CS 583 için defter ekibi henüz not yazmadı.

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⚠️ FZ engelleyen şartlar

At least 30% average on homeworks, and 30% on quizzes required.

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