Q1. Is this course right for me?

This is right for you if you are interested in modern day Biology and Computers. Professionals need skills that will help them to excel. They should be passionate and curious about research and development. They must be motivated, patient and analytical as they continuously learn, persevere and solve problems.

Q2. Is this a practical course?

This course is a practical based course with hands-on activity, projects, activity based learning materials and much more.

Q3. Is there any pre-requisite?

There are no such prerequisites required for this course. But, having basic knowledge about Chemistry, Biology and Physics will be an added advantage.

Q4. I am a fresher, is this course hard for me to learn?

Our courses are designed in a way that caters to different age groups and different types of learners.

Algorithm For DNA Sequencing Course- Henry Harvin®

Module 1: DNA sequencing, strings and matching
In this unit we will learn about DNA sequencing, strings and matching, Manipulating DNA strings , Downloading and parsing a genome , Working with sequencing reads, Naive exact matching and matching artificial reads
- Introduction
- Importance of DNA sequencing, strings and matching
- LDNA sequencing past and present
- Genomes as strings, reads as substrings
- String definitions and Python examples
- Manipulating DNA strings
- Downloading and parsing a genome
- How DNA gets copied
- How second-generation sequencers work
- Sequencing errors and base qualities
- Sequencing reads in FASTQ format
- Working with sequencing reads
- Analyzing reads by position
- Sequencers give pieces to genomic puzzles
- Read alignment and why it's hard
- Naive exact matching
- Matching artificial reads
Module 2: Preprocessing, indexing and approximate matching
In this unit we will learn about Boyer-Moore basics, Indexing and the k-mer index, Preprocessing, indexing and approximate matching and Approximate matching, Hamming and edit distance
- Introduction
- Boyer-Moore basics
- Boyer-Moore: putting it all together
- Diversion: Repetitive elements
- Implementing Boyer-Moore
- Preprocessing
- Indexing and the k-mer index
- Ordered structures for indexing
- Hash tables for indexing
- Implementing a k-mer index
- Variations on k-mer indexes
- Genome indexes used in research
- Approximate matching, Hamming and edit distance
- Pigeonhole principle
- Implementing the pigeonhole principle
Module 3: Edit distance, assembly, overlaps
In this unit we will learn about using dynamic programming for edit distance, reading alignment in the field, first and second laws of assembly, Prac Overlaps between pairs of reads
- Introduction
- Solving the edit distance problem
- Using dynamic programming for edit distance
- Implementing dynamic programming for edit distance
- A new solution to approximate matching
- Meet the family: global and local alignment
- Implementing global alignment
- Read alignment in the field
- Assembly: working from scratch
- First and second laws of assembly
- Overlap graphs
- PracOverlaps between pairs of reads
- Finding and representing all overlaps
Module 4: Algorithms for assembly
In this unit we will learn about Algorithms for assembly, implementing shortest common superstring and assemblers in practice
- Introduction
- The shortest common superstring problem
- Implementing shortest common superstring
- Greedy shortest common superstring
- Implementing greedy shortest common superstring
- Third law of assembly: repeats are bad
- De Bruijn graphs and Eulerian walks
- Building a De Bruijn graph
- When Eulerian walks go wrong
- Assemblers in practice
- Computer science and life science