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大數(shù)據(jù)科學(xué)與BD2K-LINCS數(shù)據(jù)協(xié)調(diào)和集成中心培訓(xùn)

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.

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.

Serving Data with APIs

In this module we explain the concept of accessing data through

an application programming interface (API).

Bioinformatics Pipelines

This module describes the important concept of a Bioinformatics pipeline.

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/

Data Normalization

This module describes the mathematical concepts behind data normalization.

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.

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.

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.

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.

Benchmarking

This module discusses how Bioinformatics pipelines can be compared and evaluated.

Interactive Data Visualization

This module provides programming examples on how

to get started with creating interactive web-based data visualization elements/figures.

Crowdsourcing Projects

This final module describes opportunities to work on LINCS related projects that go beyond the course.

Final Exam

The Final Exam consists of 60 multiple choice questions which covers all of the modules

of the course. Some of the questions may require you to perform some analysis with

the methods you learned throughout the course on new datasets.