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. Moreover, the emerging field of personalized medicine uses many search algorithms to find disease-causing mutations in the human genome.
Ce cours fait partie de la Spécialisation Structures de données et algorithmes
Offert par
Université de Californie à San Diego
Université nationale de recherche, École des hautes études en sciences économiques
Spécialisation Structures de données et algorithmesUniversité de Californie à San DiegoÀ propos de ce cours
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Niveau intermédiaire
Approx. 17 heures pour terminer
Anglais
Sous-titres : Anglais
Compétences que vous acquerrez
Suffix TreeSuffix ArrayKnuth–Morris–Pratt (KMP) AlgorithmAlgorithms On Strings
Résultats de carrière des étudiants
36%
ont commencé une nouvelle carrière après avoir terminé ce cours
29%
ont bénéficié d'un avantage concret dans leur carrières grâce à ce cours
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Cours 4 sur 6 dans le
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Niveau intermédiaire
Approx. 17 heures pour terminer
Anglais
Sous-titres : Anglais
Offert par
Université de Californie à San Diego
UC San Diego is an academic powerhouse and economic engine, recognized as one of the top 10 public universities by U.S. News and World Report. Innovation is central to who we are and what we do. Here, students learn that knowledge isn't just acquired in the classroom—life is their laboratory.
Université nationale de recherche, École des hautes études en sciences économiques
National Research University - Higher School of Economics (HSE) is one of the top research universities in Russia. Established in 1992 to promote new research and teaching in economics and related disciplines, it now offers programs at all levels of university education across an extraordinary range of fields of study including business, sociology, cultural studies, philosophy, political science, international relations, law, Asian studies, media and communicamathematics, engineering, and more.
Programme du cours : ce que vous apprendrez dans ce cours
4 heures pour terminer
Suffix Trees
How would you search for a longest repeat in a string in LINEAR time? In 1973, Peter Weiner came up with a surprising solution that was based on suffix trees, the key data structure in pattern matching. Computer scientists were so impressed with his algorithm that they called it the Algorithm of the Year. In this lesson, we will explore some key ideas for pattern matching that will - through a series of trials and errors - bring us to suffix trees.
4 heures pour terminer
5 vidéos (Total 27 min), 6 lectures, 1 quiz
5 vidéos
Brute Force Approach to Pattern Matching2 min
Herding Patterns into Trie5 min
Herding Text into Suffix Trie6 min
Suffix Trees4 min
6 lectures
Trie Construction - Pseudocode10 min
FAQ10 min
Slides and External References10 min
Available Programming Languages10 min
FAQ on Programming Assignments10 min
Rules on the academic integrity in the course10 min
4 heures pour terminer
Burrows-Wheeler Transform and Suffix Arrays
Although EXACT pattern matching with suffix trees is fast, it is not clear how to use suffix trees for APPROXIMATE pattern matching. In 1994, Michael Burrows and David Wheeler invented an ingenious algorithm for text compression that is now known as Burrows-Wheeler Transform. They knew nothing about genomics, and they could not have imagined that 15 years later their algorithm will become the workhorse of biologists searching for genomic mutations. But what text compression has to do with pattern matching??? In this lesson you will learn that the fate of an algorithm is often hard to predict – its applications may appear in a field that has nothing to do with the original plan of its inventors.
4 heures pour terminer
5 vidéos (Total 30 min), 4 lectures, 1 quiz
5 vidéos
Inverting Burrows-Wheeler Transform7 min
Using BWT for Pattern Matching6 min
Suffix Arrays5 min
Approximate Pattern Matching6 min
4 lectures
Using BWT for Pattern Matching10 min
Pattern Matching with Suffix Array10 min
FAQ10 min
Slides and External References10 min
3 heures pour terminer
Knuth–Morris–Pratt Algorithm
Congratulations, you have now learned the key pattern matching concepts: tries, suffix trees, suffix arrays and even the Burrows-Wheeler transform! However, some of the results Pavel mentioned remain mysterious: e.g., how can we perform exact pattern matching in O(|Text|) time rather than in O(|Text|*|Pattern|) time as in the naïve brute force algorithm? How can it be that matching a 1000-nucleotide pattern against the human genome is nearly as fast as matching a 3-nucleotide pattern??? Also, even though Pavel showed how to quickly construct the suffix array given the suffix tree, he has not revealed the magic behind the fast algorithms for the suffix tree construction!In this module, Miсhael will address some algorithmic challenges that Pavel tried to hide from you :) such as the Knuth-Morris-Pratt algorithm for exact pattern matching and more efficient algorithms for suffix tree and suffix array construction.
3 heures pour terminer
5 vidéos (Total 35 min), 2 lectures, 1 quiz
5 vidéos
Safe Shift3 min
Prefix Function7 min
Computing Prefix Function9 min
Knuth-Morris-Pratt Algorithm5 min
2 lectures
Programming Assignment 3 lasts for two weeks2 h
Slides and External References10 min
1 exercice pour s'entraîner
Exact Pattern Matching30 min
5 heures pour terminer
Constructing Suffix Arrays and Suffix Trees
In this module we continue studying algorithmic challenges of the string algorithms. You will learn an O(n log n) algorithm for suffix array construction and a linear time algorithm for construction of suffix tree from a suffix array. You will also implement these algorithms and the Knuth-Morris-Pratt algorithm in the last Programming Assignment in this course.
5 heures pour terminer
11 vidéos (Total 76 min), 5 lectures, 2 quiz
11 vidéos
Suffix Array6 min
General Strategy6 min
Initialization9 min
Sort Doubled Cyclic Shifts8 min
SortDouble Implementation6 min
Updating Classes8 min
Full Algorithm3 min
Suffix Array and Suffix Tree8 min
LCP Array5 min
Computing the LCP Array6 min
Construct Suffix Tree from Suffix Array and LCP Array6 min
5 lectures
Counting Sort10 min
Slides and External References2 min
Computing the LCP Array - Additional Slides10 min
Suffix Tree Construction - Pseudocode10 min
Slides and External References2 min
1 exercice pour s'entraîner
Suffix Array Construction30 min
Avis
Meilleurs avis pour ALGORITHMES SUR LES CHAÎNES
par CS7 juil. 2019
Very good course. String algorithms are very important in day today life and one should really know how to solve command problems related to it. This course have described everything so well.
par PA12 mai 2020
course content was great but i personally feels some difficulties in the implementation part so the course is meant to be more implementation oriented . thank you for the wondorful course
par NR18 oct. 2019
Very well put together course. Challenging but understandable. I highly recommend you stick out. If you get stuck check the forums there's lots of helpful things there. Time well spent!
par AB20 oct. 2017
Its a very good course overall. Just felt that towards the end the material got too much to digest, might be a good idea to split the contents of weeks 3 and 4 into 3 or 4 weeks.
À propos du Spécialisation Structures de données et algorithmes
This specialization is a mix of theory and practice: you will learn algorithmic techniques for solving various computational problems and will implement about 100 algorithmic coding problems in a programming language of your choice. No other online course in Algorithms even comes close to offering you a wealth of programming challenges that you may face at your next job interview. To prepare you, we invested over 3000 hours into designing our challenges as an alternative to multiple choice questions that you usually find in MOOCs. Sorry, we do not believe in multiple choice questions when it comes to learning algorithms...or anything else in computer science! For each algorithm you develop and implement, we designed multiple tests to check its correctness and running time — you will have to debug your programs without even knowing what these tests are! It may sound difficult, but we believe it is the only way to truly understand how the algorithms work and to master the art of programming. The specialization contains two real-world projects: Big Networks and Genome Assembly. You will analyze both road networks and social networks and will learn how to compute the shortest route between New York and San Francisco (1000 times faster than the standard shortest path algorithms!) Afterwards, you will learn how to assemble genomes from millions of short fragments of DNA and how assembly algorithms fuel recent developments in personalized medicine.
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