Description
Bioinformatics Specialization When you complete this specialization, you will learn how to answer many of the questions in modern biology that have become inseparable from the computational approaches used to solve them. You will also receive a toolkit of existing software resources built on these computational approaches and which are used by thousands of biologists every day in one of the fastest growing fields of science. Although this specialization focuses on computational topics, you do not need to know how to program to complete it. If you are interested in programming, we feature an “Honors Track” (called the “Hacker Track” in previous versions of the course). The Honors Track allows you to implement the bioinformatics algorithms you will encounter in dozens of automatically graded coding challenges. By completing the Honors Track, you will become a bioinformatics software professional!
What you will learn
- Whole genome sequencing
- Viterbi Algorithm
- Suffix tree
- Python Programming
- Algorithms
- Unweighted pair group method with arithmetic mean (UPGMA)
- Bioinformatics
- Bioinformatics algorithms
- dynamic programming
- graph theory
Specificity of Bioinformatics specialization
- Publisher: Coursera
- Teacher: Pavel Pevzner
- language English
- Level: Beginner
- No. of Courses: 7
- Duration: 3 months 10 hours per week
Content of the Bioinformatics Expertise
Requirements
- No prior experience required.
Pictures
Sample clip
installation Guide
Extract files and watch with your favorite player
Subtitles: English
Quality: 720p
This specialization consists of 7 courses.
There are no changes in terms of duration and number of lessons in 2023/5 compared to the 2024/2 version. About 80 text files have been added. The final course has been added
Download links
Finding the Hidden Messages in DNA (Bioinformatics I)
Genome Sequencing (Bioinformatics II)
Comparing Genes, Proteins, and Genomes (Bioinformatics III)
Finding Mutations in DNA and Proteins (Bioinformatics VI)
Genomic Data Science and Clustering (Bioinformatics V)
Molecular Evolution (Bioinformatics IV)
Bioinformatics Capstone Big Data in Biology
Password File(s): free download software
file size
3.28 GB