Informações sobre o curso
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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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cursos 100% online

Comece imediatamente e aprenda em seu próprio cronograma.
Calendar

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.
Intermediate Level

Nível intermediário

Clock

Approx. 13 hours to complete

Sugerido: 4-5 hours/week...
Comment Dots

English

Legendas: English...
Globe

cursos 100% online

Comece imediatamente e aprenda em seu próprio cronograma.
Calendar

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.
Intermediate Level

Nível intermediário

Clock

Approx. 13 hours to complete

Sugerido: 4-5 hours/week...
Comment Dots

English

Legendas: English...

Programa - O que você aprenderá com este curso

Week
1
Clock
2 horas para concluir

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 vídeos (Total de 78 min), 2 leituras
Video8 videos
The Connectivity Map8min
Geometrical View of the Connectivity Map Concept3min
LINCS Data and Signature Generation Centers12min
BD2K-LINCS Data Coordination and Integration Center4min
Induced Pluripotent Stem Cells (iPSCs)4min
Introduction to LINCS L1000 Data22min
L1000 Characteristic Direction Signature Search Engine (L1000CDS2) Demo13min
Reading2 leituras
Syllabus10min
Grading and Logistics10min
Clock
26 minutos para concluir

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 vídeos (Total de 26 min)
Video2 videos
Introduction to Metadata and Ontologies | Part 220min
Clock
24 minutos para concluir

Serving Data with APIs

In this module we explain the concept of accessing data through an application programming interface (API)....
Reading
2 vídeos (Total de 19 min)
Video2 videos
Accessing and Serving Data through RESTful APIs | Part 210min
Week
2
Clock
19 minutos para concluir

Bioinformatics Pipelines

This module describes the important concept of a Bioinformatics pipeline....
Reading
1 vídeo (Total de 14 min)
Clock
1 hora para concluir

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 vídeos (Total de 37 min)
Video4 videos
Processing Datasets | Part 18min
Processing Datasets | Part 29min
Processing Datasets | Part 37min
Week
3
Clock
24 minutos para concluir

Data Normalization

This module describes the mathematical concepts behind data normalization....
Reading
2 vídeos (Total de 19 min)
Video2 videos
Data Normalization | Part 213min
Clock
1 hora para concluir

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 vídeos (Total de 33 min)
Video3 videos
Data Clustering | Part 2 | Distance Functions 12min
Data Clustering | Part 3 | Algorithms and Evaluation15min
Clock
2 horas para concluir

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 teste
Quiz1 exercício prático
Midterm Exam30min
Week
4
Clock
29 minutos para concluir

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 vídeos (Total de 29 min)
Video3 videos
Enrichment Analysis | Part 27min
Enrichr Demo9min
Clock
1 hora para concluir

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 vídeos (Total de 27 min)
Video3 videos
Introduction to Machine Learning | Part 2 8min
Introduction to Machine Learning | Part 39min

Instrutores

Avi Ma’ayan, PhD

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

Sobre 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....

Perguntas Frequentes – FAQ

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

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