Online Courses and Tutorials

Onlinecourses.tech provides you with the latest online courses information by assisting over 45,000 courses and 1 million students.

Learn programming, marketing, data science and more.

Get started today

Skip to main content

Featured Post

Machine Learning

Master machine learning fundamentals in four hands-on courses

About This Specialization This Specialization from leading researchers at the University of Washington introduces you to the exciting, high-demand field of Machine Learning. Through a series of practical case studies, you will gain applied experience in major areas of Machine Learning including Prediction, Classification, Clustering, and Information Retrieval. You will learn to analyze large and complex datasets, create systems that adapt and improve over time, and build intelligent applications that can make predictions from data. Created by: Industry Partners: 4 courses Follow the suggested order or choose your own. Projects Designed to help you practice and apply the skills you learn. Certificates Highlight your new skills on your resume or

Введение в биоинформатику (Introduction to Bioinformatics)

Введение в биоинформатику (Introduction to Bioinformatics)

About this course: Курс «Введение в биоинформатику» адресован тем, кто хочет получить расширенное представление о том, что такое биоинформатика и как она помогает биологам и медикам в их работе. The course is aimed at those who would like to have a better idea of what bioinformatics is and how it helps biologists and medical scientists in research and clinical work.

Created by:  Saint Petersburg State University

  • Alla L Lapidus
    Taught by:  Alla L Lapidus, Professor, Department of Cytology and Histology
    Centre For Algorithmic Biotechnology


  • Павел  Добрынин
    Taught by:  Павел Добрынин, Младший научный сотрудник
    Центр геномной биоинформатики им. Ф.Г.Добржанского

  • Михаил Райко
    Taught by:  Михаил Райко, Постдок
    Центр геномной биоинформатики им. Ф.Г.Добржанского

  • Екатерина Черняева
    Taught by:  Екатерина Черняева, Постдок
    Центр геномной биоинформатики им. Ф.Г.Добржанского
LevelBeginner
Language
Russian
How To PassPass all graded assignments to complete the course.
User Ratings
Average User Rating 4.5See what learners said
Syllabus
WEEK 1
Неделя 1 - Введение (Week 1 - Introducton)
Первая неделя нашего курса посвящена основным концепциям геномной биоинформатики. Вы узнаете об истории этой дисциплины, основных методах и алгоритмах. Также вас ждет знакомство с реальной лабораторной работой - мы расскажем, как выделяется ДНК и откуда берутся данные, с которыми нам предстоит работать в дальнейшем. <br>The first week of our course covers the basic concepts of genome bioinformatics. You will learn about the history of this discipline, the main methods and algorithms. Also you will familiarize yourself with actual laboratory work - we will explain how DNA is extracted and where the sequencing data comes from.
8 videos
  1. Video: Введение в биоинформатику (Introduction to Bioinformatics)
  2. Video: Сиквенсные проекты (Sequencing Projects)
  3. Video: Алгоритмы сборки (Assembly Algorithms)
  4. Video: Подходы к анализу данных (Data Analysis Approaches)
  5. Video: Знакомство с методами выделения геномной ДНК (Genomic DNA Isolation techniques overview) (13:49)
  6. Video: Определение количества и качества ДНК (DNA quality and quantity control) (07:37)
  7. Video: Подготовка ДНК-библиотек для секвенатора Illumina MiSeq (DNA-library preparation for Illumina MiSeq platform) (13:21)
  8. Video: Запуск секвенатора Illumina MiSeq (Illumina MiSeq sequencer running) (03:25)
Graded: Тест 1 (Quiz 1)
WEEK 2
Неделя 2 - Технологии секвенирования (Sequencing Technologies)
Добро пожаловать на вторую неделю нашего курса! Эта неделя будет посвящена обзору методов секвенирования ДНК. Вы узнаете об истории развития этих технологий и принципах, на которых они основаны. <br>Welcome to the second week of the course! This week will be dedicated to Next Generation DNA Sequencing technologies. You will learn about the new methods development and main approaches that gave base to NGS.
4 videos
  1. Video: Основные понятия. Секвенирование по Сэнгеру (Basic concepts. Sanger sequencing.)
  2. Video: Обзор технологий нового поколения (NGS Technologies Overview)
  3. Video: 454, Ion Torrent, SOLiD, Illumina
  4. Video: Synthetic Long Reads, PacBio, Oxford Nanopore
Graded: Тест 2 (Quiz 2)
WEEK 3
Неделя 3 - Контроль качества (Quality Control)
На этой неделе вы уже можете приступить к работе над геномным проектом. В лекциях мы поговорим о формате представления исходных данных и контроле качества. Также мы подготовили для вас небольшое введение в операционную систему Linux, так как большинство необходимых нам программ разработаны именно для нее. <br>This week your can start working on the real genome project. This week lectures will cover raw data formats and aspects of quality control. Also we offer you a brief introduction to the Linux, because the majority of bioinformatics tools developed for this operation system.
6 videos
  1. Video: Проблемы качества (Quality Issues)
  2. Video: Форматы данных, шкала Phred (Data Formats, Phred Scale)
  3. Video: Проверка качества. FastQC (Quality Check. FastQC)
  4. Video: Пример - часть 1 (Case Study - part 1)
  5. Video: Пример - часть 2 (Case Study - part 2)
  6. Video: Введение в Linux (Introduction to Linux)
Graded: Тест 3 (Quiz 3)
WEEK 4
Неделя 4 - Сборка ДНК de novo (De novo DNA assembly)
Добро пожаловать на четвертую неделю нашего курса. Она будет посвящена сборке геномов de novo. Вы узнаете о различных подходах к секвенированию малоизученных организмов, и о проблемах, которые при этом возникают. Также мы расскажем о работе алгоримов, используемых при сборке новых геномов. Оставайтесь с нами! <br>Welcome to the fourth week of our course. It will be dedicated to de novo genome assembly. You will hear about different sequencing approaches of unknown organisms, and the problems associated with this task. We will also talk about algorithms used for the assembly of new genomes. Stay tuned!
7 videos
  1. Video: Сборка ДНК de novo - часть 1 (De novo DNA assembly - part 1)
  2. Video: Сборка ДНК de novo - часть 2 (De novo DNA assembly - part 2)
  3. Video: Алгоритмы (Algorithms)
  4. Video: Сложность алгоритмов (Algorithms Complexity)
  5. Video: Overlap Layout Concensus
  6. Video: Графы де Брюйна (De Bruijn Graphs)
  7. Video: Алгоритмы сборки геномов (Genome Assembly Algorithms)
Graded: Тест 4 (Quiz 4)
WEEK 5
Неделя 5 - Выравнивание коротких фрагментов (Short read alignment)
Пятая неделя нашего курса посвящена выравниванию коротких фрагментов на референс - подходу, который используется при работе с уже изученными геномами. В лекциях разбираются наиболее популярные программы для решения таких задач, а также основные алгоритмы для работы со строками. <br>Fifth week of our course is devoted to short read alignment to the reference genome, which is used when we work with the already studied organisms. In lectures we will talk about the most popular software for solving such problems, as well as basic algorithms for working with strings.
8 videos
  1. Video: Подходы к выравниванию ( Alignment approaches)
  2. Video: Построение индекса (Building index)
  3. Video: Выравнивание с помощью Bowtie (Bowtie Alignment)
  4. Video: Форматы SAM, BAM. Сортировка. (SAM, BAM Alignment Format. Sorting.)
  5. Video: Поиск вариантов (Variant Calling)
  6. Video: Строковые алгоритмы. Хэш-функция. (String Algorithms. Hash.)
  7. Video: Поиск подстроки с ошибками (String Searching with Errors)
  8. Video: Суффиксные деревья (Suffix Trees)
Graded: Тест 5 (Quiz 5)
WEEK 6
Неделя 6 - Поиск и аннотация генов (Gene Finding and Annotation)
В завершающей неделе курса мы разберем методы поиска генов в собранных последовательностях и их аннотации.<br> In the final week of the course we will examine methods of gene finding and annotation in assembled sequences. 
4 videos
  1. Video: Подходы к аннотации генов (Gene Finding Approaches)
  2. Video: Скрытые марковские модели (Hidden Markov Models)
  3. Video: Аннотация генов в бактериальном геноме (Bacterial Genome Annotation)
  4. Video: Анализ вариантов (Variant Analysis)
Graded: Тест 6 (Quiz 6)
WEEK 7
Геномный проект (Genome Project)
В этом практическом задании вам предстоит собрать и проаннотировать бактериальный геном, проинтерпретировать результаты и найти причину ужасной эпидемии, охватившей Европу в 2011 году. <br>In this practice challenge you will have to assemble and annotate bacterial genome, interpret the results and find the cause of the terrible epidemic in Europe in 2011.
5 items
  1. Discussion Prompt: Впечатления о курсе
Graded: Часть 1: исходные данные (Part 1: Raw Data)
Graded: Часть 2: сборка de novo (Part 2: De Novo Assembly)
Graded: Часть 3: выравнивание по референсу (Part 3: Alignment to Reference)
Graded: Часть 4: аннотация (Part 4: Annotation)
How It Works
Coursework
Coursework
Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.
Help from Your Peers
Help from Your Peers
Connect with thousands of other learners and debate ideas, discuss course material, and get help mastering concepts.
Certificates
Certificates
Earn official recognition for your work, and share your success with friends, colleagues, and employers.
Creators
Saint Petersburg State University
The Saint-Petersburg University (SPbU) is a state university, located in Saint-Petersburg, Russia. Founded in 1724, SPbU is the oldest institution of higher education in Russia. At present, there are more than 25 000 students in SPbU studying over 200 programmes.
Learn more about this course

Comments

Popular posts from this blog

Hands-on Text Mining and Analytics by Yonsei University

About this course: This course provides an unique opportunity for you to learn key components of text mining and analytics aided by the real world datasets and the text mining toolkit written in Java. Hands-on experience in core text mining techniques including text preprocessing, sentiment analysis, and topic modeling help learners be trained to be a competent data scientists. Empowered by bringing lecture notes together with lab sessions based on the y-TextMiner toolkit developed for the class, learners will be able to develop interesting text mining applications.



LevelIntermediateLanguage English, Subtitles: Chinese (Simplified) How To PassPass all graded assignments to complete the course.
Syllabus

Big Data Hadoop Certification Training

Big Data Hadoop training will make you an expert in HDFS, MapReduce, Hbase, Hive, Pig, Yarn, Oozie, Flume and Sqoop using real-time use cases on Retail, Social Media, Aviation, Tourism, Finance domain. You will get Hadoop certification at the end of the course

About the Training
This Hadoop training is designed to make you a certified Big Data practitioner by providing you rich hands-on training on Hadoop ecosystem and best practices about HDFS, MapReduce, HBase, Hive, Pig, Oozie, Sqoop. This course is stepping stone to your Big Data journey and you will get the opportunity to work on a Big data Analytics project after selecting a data-set of your choice. You will get Hadoop certification after the project completion.

Training Objectives
The hadoop training is designed to help you become a top Hadoop developer. During this course, our expert instructors will train you to: Master the concepts of HDFS and MapReduce frameworkUnderstand Hadoop 2.x ArchitectureSetup Hadoop Cluster and write Co…

Learn to Program and Analyze Data with Python

About This Specialization This Specialization builds on the success of the Python for Everybody course and will introduce fundamental programming concepts including data structures, networked application program interfaces, and databases, using the Python programming language. In the Capstone Project, you’ll use the technologies learned throughout the Specialization to design and create your own applications for data retrieval, processing, and visualization. Created by: 5 courses Follow the suggested order or choose your own. Projects Designed to help you practice and apply the skills you learn. Certificates Highlight your new skills on your resume or LinkedIn. Courses

An Introduction to Interactive Programming in Python (Part 1)

About this course: This two-part course is designed to help students with very little or no computing background learn the basics of building simple interactive applications. Our language of choice, Python, is an easy-to learn, high-level computer language that is used in many of the computational courses offered on Coursera. To make learning Python easy, we have developed a new browser-based programming environment that makes developing interactive applications in Python simple. These applications will involve windows whose contents are graphical and respond to buttons, the keyboard and the mouse. In part 1 of this course, we will introduce the basic elements of programming (such as expressions, conditionals, and functions) and then use these elements to create simple interactive applications such as a digital stopwatch. Part 1 of this class will culminate in building a version of the classic arcade game "Pong".
Who is this class for: Recommended Background - A knowledge o…

Front-End JavaScript Frameworks: Angular

About this course: This course concentrates mainly on Javascript based front-end frameworks, and in particular the Angular framework (Currently Ver. 4.x). This course will use Typescript for developing Angular application. Typescript features will be introduced in the context of Angular as part of the exercises. You will also get an introduction to the use of Angular Material and Angular Flex-Layout for responsive UI design. You will be introduced to various aspects of Angular including components, directives and services. You will learn about data binding, Angular router and its use for developing single-page applications. You will also learn about designing both template-driven forms and reactive forms. A quick introduction to Observables, reactive programming and RxJS in the context of Angular is included. You will then learn about Angular support for client-server communication and the use of REST API on the server side. You will use Restangular for communicating with a server sup…

Launch Your Career in Data Science

A nine-course introduction to data science, developed and taught by leading professors.
About This Specialization Ask the right questions, manipulate data sets, and create visualizations to communicate results. This Specialization covers the concepts and tools you'll need throughout the entire data science pipeline, from asking the right kinds of questions to making inferences and publishing results. In the final Capstone Project, you’ll apply the skills learned by building a data product using real-world data. At completion, students will have a portfolio demonstrating their mastery of the material. Created by: Industry Partners: 10 courses Follow the suggested order or choose your own. Projects Designed to help you practice and apply the skills you learn.

Программирование на Python

About this course: Python – простой, гибкий и невероятно популярный язык, который используется практически во всех областях современной разработки. С его помощью можно создавать веб-приложения, писать игры, заниматься анализом данных, автоматизировать задачи системного администрирования и многое другое. “Программирование на Python” читают разработчики, применяющие Python в проектах, которыми ежедневно пользуются миллионы людей. Курс покрывает все необходимые для ежедневной работы программиста темы, а также рассказывает про многие особенности языка, которые часто опускают при его изучении. В ходе курса вы изучите конструкции языка, типы и структуры данных, функции, научитесь применять объектно-ориентированное и функциональное программирование, узнаете про особенности реализации Python, научитесь писать асинхронный и многопоточный код. Помимо теории вас ждут практические задания, которые помогут проверить полученные знания и отточить навыки программирования на Python. После успешного о…

Master of Computer Science in Data Science

A flexible and affordable degree from one of the top Computer Science programs in the world, focused on one of the hottest fields of the new millennium

Enroll in the Master of Computer Science in Data Science (MCS-DS) and gain access to the computational and statistical knowledge needed to turn big data into meaningful insights. Build expertise in four core areas of computer science—data visualization, machine learning, data mining, and cloud computing—while learning key skills in statistics and information science. This completely online degree is an affordable gateway to one of the most lucrative and fastest growing careers of the new millennium. The MCS-DS is offered by CS @ ILLINOIS, a U.S. News & World Report top five CS graduate program, in collaboration with the University’s Statistics Department and top-ranked iSchool. Join our alumni network of entrepreneurs, educators, and technical visionaries, who have revolutionized the way people communicate, shop, conduct business,…

Machine Learning

Master machine learning fundamentals in four hands-on courses

About This Specialization This Specialization from leading researchers at the University of Washington introduces you to the exciting, high-demand field of Machine Learning. Through a series of practical case studies, you will gain applied experience in major areas of Machine Learning including Prediction, Classification, Clustering, and Information Retrieval. You will learn to analyze large and complex datasets, create systems that adapt and improve over time, and build intelligent applications that can make predictions from data. Created by: Industry Partners: 4 courses Follow the suggested order or choose your own. Projects Designed to help you practice and apply the skills you learn. Certificates Highlight your new skills on your resume or

Introduction to Data Science in Python

About this course: This course will introduce the learner to the basics of the python programming environment, including how to download and install python, expected fundamental python programming techniques, and how to find help with python programming questions. The course will also introduce data manipulation and cleaning techniques using the popular python pandas data science library and introduce the abstraction of the DataFrame as the central data structure for data analysis. The course will end with a statistics primer, showing how various statistical measures can be applied to pandas DataFrames. By the end of the course, students will be able to take tabular data, clean it,  manipulate it, and run basic inferential statistical analyses. This course should be taken before any of the other Applied Data Science with Python courses: Applied Plotting, Charting & Data Representation in Python, Applied Machine Learning in Python, Applied Text Mining in Python, Applied Social Ne…

Archive