このコースについて
4.5
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15件のレビュー

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推奨:6-8 hours/week...

英語

字幕:英語

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約27時間で修了

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英語

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シラバス - 本コースの学習内容

1
2時間で修了

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件のビデオ (合計52分), 4 readings, 3 quizzes
3件のビデオ
Introduction to Cell Biology16 分
Introduction to Molecular Biology19 分
4件の学習用教材
Course Logistics10 分
Grading Policy10 分
Resources and Links to Additional Materials10 分
MATLAB License10 分
3の練習問題
Introduction to Complex Systems20 分
Introduction to Cell Biology18 分
Introduction to Molecular Biology20 分
2
2時間で修了

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件のビデオ (合計45分), 4 quizzes
4件のビデオ
Duplication-Divergence and Network Motifs8 分
Large Size Motifs and Complex Models of Network Evolution10 分
Network Properties of Biological Networks11 分
4の練習問題
Rich-Get-Richer14 分
Duplication-Divergence and Network Motifs16 分
Large Size Motifs16 分
Topological Properties of Biological Networks18 分
3
2時間で修了

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件のビデオ (合計58分), 4 quizzes
4件のビデオ
Genes2Networks and Network Visualization16 分
Sets2Networks - Creating Functional Association Networks14 分
Genes2FANs - Analyzing Gene Lists with Functional Association Networks14 分
4の練習問題
Types of Biological Networks16 分
Genes2Networks and Network Visualization14 分
Functional Association Networks with Sets2Networks16 分
Functional Association Networks with Genes2FANs16 分
4
1時間で修了

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件のビデオ (合計41分), 2 quizzes
5件のビデオ
Characteristic Direction Method - Part 18 分
Characteristic Direction Method - Part 27 分
Characteristic Direction Method - Part 310 分
Characteristic Direction Method - Part 45 分
2の練習問題
Data Normalization14 分
Characteristic Direction12 分
5
4時間で修了

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件のビデオ (合計139分), 1 reading, 8 quizzes
9件のビデオ
GEO2Enrichr: A Google Chrome Extension for Gene Set Extraction and Enrichment7 分
Gene Set Enrichment Analysis (GSEA) - Preliminaries13 分
Gene Set Enrichment Analysis (GSEA) - Part 28 分
Principal Angle Enrichment Analysis (PAEA)18 分
Network2Canvas (N2C) and Enrichment Analysis with N2C17 分
Expression2Kinases: Inferring Pathways from Differentially Expressed Genes24 分
DrugPairSeeker and the New CMAP17 分
Classifying Patients/Tumors from TCGA11 分
1件の学習用教材
GATE Desktop Software Tool10 分
8の練習問題
The Fisher Exact Test and Enrichr18 分
Gene Set Enrichment Analysis (GSEA) - Part 112 分
Gene Set Enrichment Analysis (GSEA) - Part 210 分
Principal Angle Enrichment Analysis (PAEA)10 分
GATE and Network2Canvas14 分
Expression2Kinases20 分
DrugPairSeeker and the New CMAP16 分
Classifying Patients from TCGA16 分
6
4時間で修了

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件のビデオ (合計125分), 7 quizzes
7件のビデオ
RNA-seq Analysis - Using TopHat and Cufflinks21 分
RNA-seq Analysis - R Basics23 分
RNA-seq Analysis - CummeRbund23 分
STAR: An Ultra-fast RNA-seq Aligner13 分
ChIP-seq Analysis - Part 113 分
ChIP-seq Analysis - Part 212 分
7の練習問題
RNA-seq and UNIX/Linux Commands16 分
RNA-seq Pipeline20 分
CummeRbund and R Programming20 分
CummeRbund - Demo18 分
RNA-seq STAR10 分
ChIP-seq Analysis - Part 118 分
ChIP-seq Analysis - Part 216 分
7
3時間で修了

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件のビデオ (合計90分), 1 reading, 6 quizzes
6件のビデオ
Principal Component Analysis (PCA) - Part 28 分
Principal Component Analyis (PCA) Plotting in MATLAB15 分
Clustergram in MATLAB14 分
Self-Organizing Maps14 分
Network-Based Clustering24 分
1件の学習用教材
MATLAB License10 分
6の練習問題
Principal Component Analysis (PCA) - Part 112 分
Principal Component Analysis (PCA) - Part 214 分
Principal Component Analysis (PCA) with MATLAB18 分
Hierarchical Clustering (HC) with MATLAB16 分
Self-Organizing Maps12 分
Network-Based Clustering10 分
8
1時間で修了

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件のビデオ (合計49分), 2 quizzes
5件のビデオ
Resources for Data Integration - Part 110 分
Resources for Data Integration - Part 212 分
Resources for Data Integration - Part 39 分
Resources for Data Integration - Part 410 分
2の練習問題
Big Data in Biology and Data Integration16 分
Resources for Data Integration24 分
9
1時間で修了

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件のビデオ (合計19分), 1 quiz
2件のビデオ
Crowdsourcing Tasks for this Course3 分
1の練習問題
Crowdsourcing: Microtasks and Megatasks16 分
10
2時間で修了

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 quiz
1の練習問題
Final Exam50 分
4.5
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人気のレビュー

by FPJun 3rd 2016

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

by CCApr 6th 2016

Its really a very interesting course ,and very informative

講師

Avatar

Avi Ma’ayan, PhD

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

マウントサイナイ医科大学(Icahn School of Medicine at Mount Sinai)について

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....

Systems Biology and Biotechnologyの専門講座について

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....
Systems Biology and Biotechnology

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