课程信息
5.0
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The Library of Integrative Network-based Cellular Signatures (LINCS) is an NIH Common Fund program. The idea is to perturb different types of human cells with many different types of perturbations such as: drugs and other small molecules; genetic manipulations such as knockdown or overexpression of single genes; manipulation of the extracellular microenvironment conditions, for example, growing cells on different surfaces, and more. These perturbations are applied to various types of human cells including induced pluripotent stem cells from patients, differentiated into various lineages such as neurons or cardiomyocytes. Then, to better understand the molecular networks that are affected by these perturbations, changes in level of many different variables are measured including: mRNAs, proteins, and metabolites, as well as cellular phenotypic changes such as changes in cell morphology. The BD2K-LINCS Data Coordination and Integration Center (DCIC) is commissioned to organize, analyze, visualize and integrate this data with other publicly available relevant resources. In this course we briefly introduce the DCIC and the various Centers that collect data for LINCS. We then cover metadata and how metadata is linked to ontologies. We then present data processing and normalization methods to clean and harmonize LINCS data. This follow discussions about how data is served as RESTful APIs. Most importantly, the course covers computational methods including: data clustering, gene-set enrichment analysis, interactive data visualization, and supervised learning. Finally, we introduce crowdsourcing/citizen-science projects where students can work together in teams to extract expression signatures from public databases and then query such collections of signatures against LINCS data for predicting small molecules as potential therapeutics....
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Intermediate Level

中级

Clock

Approx. 13 hours to complete

建议:4-5 hours/week...
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English

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Globe

100% 在线课程

立即开始,按照自己的计划学习。
Calendar

可灵活调整截止日期

根据您的日程表重置截止日期。
Intermediate Level

中级

Clock

Approx. 13 hours to complete

建议:4-5 hours/week...
Comment Dots

English

字幕:English...

教学大纲 - 您将从这门课程中学到什么

Week
1
Clock
完成时间为 2 小时

The Library of Integrated Network-based Cellular Signatures (LINCS) Program Overview

This module provides an overview of the concept behind the LINCS program; and tutorials on how to get started with using the LINCS L1000 dataset....
Reading
8 个视频(共 78 分钟), 2 个阅读材料
Video8 个视频
The Connectivity Map8分钟
Geometrical View of the Connectivity Map Concept3分钟
LINCS Data and Signature Generation Centers12分钟
BD2K-LINCS Data Coordination and Integration Center4分钟
Induced Pluripotent Stem Cells (iPSCs)4分钟
Introduction to LINCS L1000 Data22分钟
L1000 Characteristic Direction Signature Search Engine (L1000CDS2) Demo13分钟
Reading2 个阅读材料
Syllabus10分钟
Grading and Logistics10分钟
Clock
完成时间为 26 分钟

Metadata and Ontologies

This module includes a broad high level description of the concepts behind metadata and ontologies and how these are applied to LINCS datasets....
Reading
2 个视频(共 26 分钟)
Video2 个视频
Introduction to Metadata and Ontologies | Part 220分钟
Clock
完成时间为 24 分钟

Serving Data with APIs

In this module we explain the concept of accessing data through an application programming interface (API)....
Reading
2 个视频(共 19 分钟)
Video2 个视频
Accessing and Serving Data through RESTful APIs | Part 210分钟
Week
2
Clock
完成时间为 19 分钟

Bioinformatics Pipelines

This module describes the important concept of a Bioinformatics pipeline....
Reading
1 个视频(共 14 分钟)
Clock
完成时间为 1 小时

The Harmonizome

This module describes a project that integrates many resources that contain knowledge about genes and proteins. The project is called the Harmonizome, and it is implemented as a web-server application available at: http://amp.pharm.mssm.edu/Harmonizome/ ...
Reading
4 个视频(共 37 分钟)
Video4 个视频
Processing Datasets | Part 18分钟
Processing Datasets | Part 29分钟
Processing Datasets | Part 37分钟
Week
3
Clock
完成时间为 24 分钟

Data Normalization

This module describes the mathematical concepts behind data normalization....
Reading
2 个视频(共 19 分钟)
Video2 个视频
Data Normalization | Part 213分钟
Clock
完成时间为 1 小时

Data Clustering

This module describes the mathematical concepts behind data clustering, or in other words unsupervised learning - the identification of patterns within data without considering the labels associated with the data. ...
Reading
3 个视频(共 33 分钟)
Video3 个视频
Data Clustering | Part 2 | Distance Functions 12分钟
Data Clustering | Part 3 | Algorithms and Evaluation15分钟
Clock
完成时间为 2 小时

Midterm Exam

The Midterm Exam consists of 45 multiple choice questions which covers modules 1-7. Some of the questions may require you to perform some analysis with the methods you learned throughout the course on new datasets. ...
Reading
1 个测验
Quiz1 个练习
Midterm Exam30分钟
Week
4
Clock
完成时间为 29 分钟

Enrichment Analysis

This module introduces the important concept of performing gene set enrichment analyses. Enrichment analysis is the process of querying gene sets from genomics and proteomics studies against annotated gene sets collected from prior biological knowledge....
Reading
3 个视频(共 29 分钟)
Video3 个视频
Enrichment Analysis | Part 27分钟
Enrichr Demo9分钟
Clock
完成时间为 1 小时

Machine Learning

This module describes the mathematical concepts of supervised machine learning, the process of making predictions from examples that associate observations/features/attribute with one or more properties that we wish to learn/predict....
Reading
3 个视频(共 27 分钟)
Video3 个视频
Introduction to Machine Learning | Part 2 8分钟
Introduction to Machine Learning | Part 39分钟

讲师

Avi Ma’ayan, PhD

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

关于 Icahn School of Medicine at Mount Sinai

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....

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