Search result for Courses taught by Pavel Pevzner
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Algorithms on Strings
by Alexander S. Kulikov , Michael Levin , Pavel Pevzner , Neil Rhodes- 4.5
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Approx. 18 hours to complete
World and internet is full of textual information. We search for information using textual queries, we read websites, books, e-mails. All those are strings from the point of view of computer science. To make sense of all that information and make search efficient, search engines use many string algorithms. Suffix Trees...
Genome Sequencing (Bioinformatics II)
by Pavel Pevzner , Phillip Compeau- 4.6
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Approx. 17 hours to complete
You may have heard a lot about genome sequencing and its potential to usher in an era of personalized medicine, but what does it mean to sequence a genome? Biologists still cannot read the nucleotides of an entire genome as you would read a book from beginning to end. However, they can read short pieces of DNA....
Comparing Genes, Proteins, and Genomes (Bioinformatics III)
by Pavel Pevzner , Phillip Compeau , Nikolay Vyahhi- 4.7
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Approx. 22 hours to complete
Once we have sequenced genomes in the previous course, we would like to compare them to determine how species have evolved and what makes them different. In the first half of the course, we will compare two short biological sequences, such as genes (i. e. , short sequences of DNA) or proteins....
Finding Mutations in DNA and Proteins (Bioinformatics VI)
by Pavel Pevzner , Phillip Compeau- 4.7
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Approx. 24 hours to complete
In previous courses in the Specialization, we have discussed how to sequence and compare genomes. This course will cover advanced topics in finding mutations lurking within DNA and proteins. In the first half of the course, we would like to ask how an individual's genome differs from the "reference genome" of the species....
Genomic Data Science and Clustering (Bioinformatics V)
by Pavel Pevzner , Phillip Compeau- 4.2
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Approx. 10 hours to complete
How do we infer which genes orchestrate various processes in the cell? How did humans migrate out of Africa and spread around the world? In this class, we will see that these two seemingly different questions can be addressed using similar algorithmic and machine learning techniques arising from the general problem of dividing data points into distinct clusters....
Bioinformatics Capstone: Big Data in Biology
by Phillip Compeau , Pavel Pevzner- 4.1
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Approx. 14 hours to complete
In this course, you will learn how to use the BaseSpace cloud platform developed by Illumina (our industry partner) to apply several standard bioinformatics software approaches to real biological data. whole exome sequencing for finding potentially harmful mutations in a human sample. Week 1: Identifying the Culprit in a Food Poisoning Outbreak...
Biology Meets Programming: Bioinformatics for Beginners
by Pavel Pevzner , Phillip Compeau- 4.3
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Approx. 19 hours to complete
Are you interested in learning how to program (in Python) within a scientific setting? This course will cover algorithms for solving various biological problems along with a handful of programming challenges helping you implement these algorithms in Python. It offers a gently-paced introduction to our Bioinformatics Specialization (https://www. coursera. coursera. org/learn/dna-analysis)....
Algorithmic Toolbox
by Alexander S. Kulikov , Michael Levin , Neil Rhodes , Pavel Pevzner , Daniel M Kane- 4.6
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Approx. 39 hours to complete
The course covers basic algorithmic techniques and ideas for computational problems arising frequently in practical applications: sorting and searching, divide and conquer, greedy algorithms, dynamic programming. You will practice solving computational problems, designing new algorithms, and implementing solutions efficiently (so that they run in less than a second). Programming Challenges Welcome!...
Finding Hidden Messages in DNA (Bioinformatics I)
by Pavel Pevzner , Phillip Compeau- 4.4
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Approx. 16 hours to complete
Named a top 50 MOOC of all time by Class Central! This course begins a series of classes illustrating the power of computing in modern biology. Please join us on the frontier of bioinformatics to look for hidden messages in DNA without ever needing to put on a lab coat. Week 1: Welcome!...
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