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100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.

Nivel intermedio

Aprox. 14 horas para completar

Sugerido: 4-5 hours/week...

Inglés (English)

Subtítulos: Inglés (English)

Programa - Qué aprenderás en este curso

Semana
1
2 horas para completar

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.

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8 videos (Total 78 minutos), 2 readings
8 videos
The Connectivity Map8m
Geometrical View of the Connectivity Map Concept3m
LINCS Data and Signature Generation Centers12m
BD2K-LINCS Data Coordination and Integration Center4m
Induced Pluripotent Stem Cells (iPSCs)4m
Introduction to LINCS L1000 Data22m
L1000 Characteristic Direction Signature Search Engine (L1000CDS2) Demo13m
2 lecturas
Syllabus10m
Grading and Logistics10m
26 minutos para completar

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.

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2 videos (Total 26 minutos)
2 videos
Introduction to Metadata and Ontologies | Part 220m
24 minutos para completar

Serving Data with APIs

In this module we explain the concept of accessing data through an application programming interface (API).

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2 videos (Total 19 minutos)
2 videos
Accessing and Serving Data through RESTful APIs | Part 210m
Semana
2
19 minutos para completar

Bioinformatics Pipelines

This module describes the important concept of a Bioinformatics pipeline.

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1 video (Total 14 minutos)
1 hora para completar

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/

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4 videos (Total 37 minutos)
4 videos
Processing Datasets | Part 18m
Processing Datasets | Part 29m
Processing Datasets | Part 37m
Semana
3
24 minutos para completar

Data Normalization

This module describes the mathematical concepts behind data normalization.

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2 videos (Total 19 minutos)
2 videos
Data Normalization | Part 213m
1 hora para completar

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.

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3 videos (Total 33 minutos)
3 videos
Data Clustering | Part 2 | Distance Functions 12m
Data Clustering | Part 3 | Algorithms and Evaluation15m
2 horas para completar

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.

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1 quiz
1 ejercicio de práctica
Midterm Exam1h 30m
Semana
4
29 minutos para completar

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.

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3 videos (Total 29 minutos)
3 videos
Enrichment Analysis | Part 27m
Enrichr Demo9m
1 hora para completar

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.

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3 videos (Total 27 minutos)
3 videos
Introduction to Machine Learning | Part 2 8m
Introduction to Machine Learning | Part 39m
4.9
4 revisionesChevron Right

Principales revisiones sobre Big Data Science with the BD2K-LINCS Data Coordination and Integration Center

por MSJan 21st 2017

A very practical courses. Very good introduction to Big Data sources and Computational Analysis tool.

por HHSep 19th 2018

excellent oppurtunity for the data science learners

Instructor

Avatar

Avi Ma’ayan, PhD

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

Acerca de Escuela Icahn de Medicina del Monte Sinaí

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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