Об этом курсе
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Рецензии: 15

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Прибл. 27 часа на выполнение

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Английский

Субтитры: Английский

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Английский

Субтитры: Английский

Программа курса: что вы изучите

Неделя
1
2 ч. на завершение

Course Overview and Introductions

The 'Introduction to Complex Systems' module discusses complex systems and leads to the idea that a cell can be considered a complex system or a complex agent living in a complex environment just like us. The 'Introduction to Biology for Engineers' module provides an introduction to some central topics in cell and molecular biology for those who do not have the background in the field. This is not a comprehensive coverage of cell and molecular biology. The goal is to provide an entry point to motivate those who are interested in this field, coming from other disciplines, to begin studying biology....
3 видео ((всего 52 мин.)), 4 материалов для самостоятельного изучения, 3 тестов
3 видео
Introduction to Cell Biology16мин
Introduction to Molecular Biology19мин
4 материала для самостоятельного изучения
Course Logistics10мин
Grading Policy10мин
Resources and Links to Additional Materials10мин
MATLAB License10мин
3 практического упражнения
Introduction to Complex Systems20мин
Introduction to Cell Biology18мин
Introduction to Molecular Biology20мин
Неделя
2
2 ч. на завершение

Topological and Network Evolution Models

In the 'Topological and Network Evolution Models' module, we provide several lectures about a historical perspective of network analysis in systems biology. The focus is on in-silico network evolution models. These are simple computational models that, based of few rules, can create networks that have a similar topology to the molecular networks observed in biological systems. ...
4 видео ((всего 45 мин.)), 4 тестов
4 видео
Duplication-Divergence and Network Motifs8мин
Large Size Motifs and Complex Models of Network Evolution10мин
Network Properties of Biological Networks11мин
4 практического упражнения
Rich-Get-Richer14мин
Duplication-Divergence and Network Motifs16мин
Large Size Motifs16мин
Topological Properties of Biological Networks18мин
Неделя
3
2 ч. на завершение

Types of Biological Networks

The 'Types of Biological Networks' module is about the various types of networks that are typically constructed and analyzed in systems biology and systems pharmacology. This lecture ends with the idea of functional association networks (FANs). Following this lecture are lectures that discuss how to construct FANs and how to use these networks for analyzing gene lists. ...
4 видео ((всего 58 мин.)), 4 тестов
4 видео
Genes2Networks and Network Visualization16мин
Sets2Networks - Creating Functional Association Networks14мин
Genes2FANs - Analyzing Gene Lists with Functional Association Networks14мин
4 практического упражнения
Types of Biological Networks16мин
Genes2Networks and Network Visualization14мин
Functional Association Networks with Sets2Networks16мин
Functional Association Networks with Genes2FANs16мин
Неделя
4
1 ч. на завершение

Data Processing and Identifying Differentially Expressed Genes

This set of lectures in the 'Data Processing and Identifying Differentially Expressed Genes' module first discusses data normalization methods, and then several lectures are devoted to explaining the problem of identifying differentially expressed genes with the focus on understanding the inner workings of a new method developed by the Ma'ayan Laboratory called the Characteristic Direction. ...
5 видео ((всего 41 мин.)), 2 тестов
5 видео
Characteristic Direction Method - Part 18мин
Characteristic Direction Method - Part 27мин
Characteristic Direction Method - Part 310мин
Characteristic Direction Method - Part 45мин
2 практического упражнения
Data Normalization14мин
Characteristic Direction12мин
Неделя
5
4 ч. на завершение

Gene Set Enrichment and Network Analyses

In the 'Gene Set Enrichment and Network Analyses' module the emphasis is on tools developed by the Ma'ayan Laboratory to analyze gene sets. Several tools will be discussed including: Enrichr, GEO2Enrichr, Expression2Kinases and DrugPairSeeker. In addition, one lecture will be devoted to a method we call enrichment vector clustering we developed, and two lectures will describe the popular gene set enrichment analysis (GSEA) method and an improved method we developed called principal angle enrichment analysis (PAEA)....
9 видео ((всего 139 мин.)), 1 материал для самостоятельного изучения, 8 тестов
9 видео
GEO2Enrichr: A Google Chrome Extension for Gene Set Extraction and Enrichment7мин
Gene Set Enrichment Analysis (GSEA) - Preliminaries13мин
Gene Set Enrichment Analysis (GSEA) - Part 28мин
Principal Angle Enrichment Analysis (PAEA)18мин
Network2Canvas (N2C) and Enrichment Analysis with N2C17мин
Expression2Kinases: Inferring Pathways from Differentially Expressed Genes24мин
DrugPairSeeker and the New CMAP17мин
Classifying Patients/Tumors from TCGA11мин
1 материал для самостоятельного изучения
GATE Desktop Software Tool10мин
8 практического упражнения
The Fisher Exact Test and Enrichr18мин
Gene Set Enrichment Analysis (GSEA) - Part 112мин
Gene Set Enrichment Analysis (GSEA) - Part 210мин
Principal Angle Enrichment Analysis (PAEA)10мин
GATE and Network2Canvas14мин
Expression2Kinases20мин
DrugPairSeeker and the New CMAP16мин
Classifying Patients from TCGA16мин
Неделя
6
4 ч. на завершение

Deep Sequencing Data Processing and Analysis

A set of lectures in the 'Deep Sequencing Data Processing and Analysis' module will cover the basic steps and popular pipelines to analyze RNA-seq and ChIP-seq data going from the raw data to gene lists to figures. These lectures also cover UNIX/Linux commands and some programming elements of R, a popular freely available statistical software. Note that since these lectures were developed and recorded during the Fall of 2013, it is possible that there are better tools that should be used now since the field is rapidly advancing. ...
7 видео ((всего 125 мин.)), 7 тестов
7 видео
RNA-seq Analysis - Using TopHat and Cufflinks21мин
RNA-seq Analysis - R Basics23мин
RNA-seq Analysis - CummeRbund23мин
STAR: An Ultra-fast RNA-seq Aligner13мин
ChIP-seq Analysis - Part 113мин
ChIP-seq Analysis - Part 212мин
7 практического упражнения
RNA-seq and UNIX/Linux Commands16мин
RNA-seq Pipeline20мин
CummeRbund and R Programming20мин
CummeRbund - Demo18мин
RNA-seq STAR10мин
ChIP-seq Analysis - Part 118мин
ChIP-seq Analysis - Part 216мин
Неделя
7
3 ч. на завершение

Principal Component Analysis, Self-Organizing Maps, Network-Based Clustering and Hierarchical Clustering

This module is devoted to various method of clustering: principal component analysis, self-organizing maps, network-based clustering and hierarchical clustering. The theory behind these methods of analysis are covered in detail, and this is followed by some practical demonstration of the methods for applications using R and MATLAB....
6 видео ((всего 90 мин.)), 1 материал для самостоятельного изучения, 6 тестов
6 видео
Principal Component Analysis (PCA) - Part 28мин
Principal Component Analyis (PCA) Plotting in MATLAB15мин
Clustergram in MATLAB14мин
Self-Organizing Maps14мин
Network-Based Clustering24мин
1 материал для самостоятельного изучения
MATLAB License10мин
6 практического упражнения
Principal Component Analysis (PCA) - Part 112мин
Principal Component Analysis (PCA) - Part 214мин
Principal Component Analysis (PCA) with MATLAB18мин
Hierarchical Clustering (HC) with MATLAB16мин
Self-Organizing Maps12мин
Network-Based Clustering10мин
Неделя
8
1 ч. на завершение

Resources for Data Integration

The lectures in the 'Resources for Data Integration' module are about the various types of networks that are typically constructed and analyzed in systems biology and systems pharmacology. These lectures start with the idea of functional association networks (FANs). Following this lecture are several lectures that discuss how to construct FANs from various resources and how to use these networks for analyzing gene lists as well as to construct a puzzle that can be used to connect genomic data with phenotypic data. ...
5 видео ((всего 49 мин.)), 2 тестов
5 видео
Resources for Data Integration - Part 110мин
Resources for Data Integration - Part 212мин
Resources for Data Integration - Part 39мин
Resources for Data Integration - Part 410мин
2 практического упражнения
Big Data in Biology and Data Integration16мин
Resources for Data Integration24мин
Неделя
9
1 ч. на завершение

Crowdsourcing: Microtasks and Megatasks

The final set of lectures presents the idea of crowdsourcing. MOOCs provide the opportunity to work together on projects that are difficult to complete alone (microtasks) or compete for implementing the best algorithms to solve hard problems (megatasks). You will have the opportunity to participate in various crowdsourcing projects: microtasks and megatasks. These projects are designed specifically for this course....
2 видео ((всего 19 мин.)), 1 тест
2 видео
Crowdsourcing Tasks for this Course3мин
1 практическое упражнение
Crowdsourcing: Microtasks and Megatasks16мин
Неделя
10
2 ч. на завершение

Final Exam

The final exam consists of multiple choice questions from topics covered in all of modules of the course. Some of the questions may require you to perform some of the analysis methods you learned throughout the course on new datasets. ...
1 тест
1 практическое упражнение
Final Exam50мин
4.5
Рецензии: 15Chevron Right

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Лучшие рецензии

автор: FPJun 3rd 2016

Excellent course to get deep into the data analysis of system biology experimentation.

автор: CCApr 6th 2016

Its really a very interesting course ,and very informative

Преподаватели

Avatar

Avi Ma’ayan, PhD

Director, Mount Sinai Center for Bioinformatics
Professor, Department of Pharmacological Sciences

О Школа Медицины Икан на горе Синай

The Icahn School of Medicine at Mount Sinai, in New York City is a leader in medical and scientific training and education, biomedical research and patient care....

О специализации ''Системная биология и биотехнологии'

Design systems-level experiments using appropriate cutting edge techniques, collect big data, and analyze and interpret small and big data sets quantitatively. The Systems Biology Specialization covers the concepts and methodologies used in systems-level analysis of biomedical systems. Successful participants will learn how to use experimental, computational and mathematical methods in systems biology and how to design practical systems-level frameworks to address questions in a variety of biomedical fields. In the final Capstone Project, students will apply the methods they learned in five courses of specialization to work on a research project....
Системная биология и биотехнологии

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