Acerca de este Curso
4.2
102 calificaciones
28 revisiones
100 % en línea

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.
Nivel avanzado

Nivel avanzado

Horas para completar

Aprox. 23 horas para completar

Sugerido: 6 weeks of study, 3-5 hours per week...
Idiomas disponibles

Inglés (English)

Subtítulos: Inglés (English)

Habilidades que obtendrás

BioinformaticsData Clustering AlgorithmsBig DataR Programming
100 % en línea

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.
Fechas límite flexibles

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.
Nivel avanzado

Nivel avanzado

Horas para completar

Aprox. 23 horas para completar

Sugerido: 6 weeks of study, 3-5 hours per week...
Idiomas disponibles

Inglés (English)

Subtítulos: Inglés (English)

Programa - Qué aprenderás en este curso

Semana
1
Horas para completar
2 horas para completar

Genes and Data

After this module, you will be able to 1. Locate and download files for data analysis involving genes and medicine. 2. Open files and preprocess data using R language. 3. Write R scripts to replace missing values, normalize data, discretize data, and sample data. ...
Reading
11 videos (Total 59 minutos), 2 readings, 6 quizzes
Video11 videos
Introduction to Module1m
DNA and Genes9m
RNA and Proteins6m
Transcription Process4m
Transcription Animation1m
Translation Process5m
Translation Animation2m
Data, Variables, and Big Datasets6m
Working with cBioPortal - Genetic Data Analysis9m
Working with cBioPortal - Gene Networks9m
Reading2 lecturas
Module 1 cBioPortal Data Analytics10m
Module 1 Resources10m
Quiz6 ejercicios de práctica
DNA, RNA, Genes, and Proteins4m
Transcription and Translation Processes6m
Data, Variables, and Big Datasets4m
Working with cBioPortal6m
Module 1 Quiz20m
Module 1 cBioPortal Data Analytics8m
Semana
2
Horas para completar
5 horas para completar

Preparing Datasets for Analysis

After this module, you will be able to: 1. Locate and download files for data analysis involving genes and medicine. 2. Open files and preprocess data using R language. 3. Write R scripts to replace missing values, normalize data, discretize data, and sample data. ...
Reading
13 videos (Total 75 minutos), 4 readings, 8 quizzes
Video13 videos
Datasets and Files10m
Data Sources11m
Importance of Data Preprocessing4m
Data Preprocessing Tasks2m
Replacing Missing Values3m
Data Normalization9m
Data Discretization5m
Feature Selection3m
Data Sampling2m
Principles of R6m
R Language1m
Jupyter Notebooks 1017m
Reading4 lecturas
Jupyter Notebooks Essentials10m
Notebook Module 2 Tutorial10m
Module 2 R Data Preprocessing10m
Module 2 Resources10m
Quiz8 ejercicios de práctica
Datasets and Files4m
Data Preprocessing Tasks4m
Replacing Missing Values2m
Normalization and Discretization4m
Data Reduction4m
Working with R4m
Module 2 Quiz20m
Module 2 R Data Preprocessing10m
Semana
3
Horas para completar
4 horas para completar

Finding Differentially Expressed Genes

After this module, you will be able to 1. Select features from highly dimensional datasets. 2. Evaluate the performance of feature selection methods. 3. Write R scripts to select features from datasets involving gene expressions. ...
Reading
9 videos (Total 53 minutos), 4 readings, 6 quizzes
Video9 videos
Overview of Feature Selection Methods13m
Filter Methods4m
Wrapper Methods4m
Evaluation Schemes7m
Selecting Differentially Expressed Genes3m
Heatmaps6m
R Scripts for Feature Selection3m
Jupyter Notebooks 1017m
Reading4 lecturas
Notebook Module 3 Tutorial10m
Jupyter Notebooks Essentials10m
Module 3 R Finding Differentially Expressed Genes10m
Module 3 Resources10m
Quiz6 ejercicios de práctica
Feature Selection Methods4m
Evaluation Schemes2m
Differentially Expressed Genes4m
Heatmaps4m
Module 3 Quiz16m
Module 3 R Finding Differentially Expressed Genes10m
Semana
4
Horas para completar
4 horas para completar

Predicting Diseases from Genes

After this module, you will be able to 1. Build classification and prediction models. 2. Evaluate the performance of classification and prediction methods. 3. Write R scripts to classify and predict diseases from gene expressions....
Reading
12 videos (Total 85 minutos), 4 readings, 10 quizzes
Video12 videos
Overview of Classification and Prediction Methods8m
Classification Methods Based on Analogy12m
Classification Methods Based on Rules13m
Classification Methods Based on Neural Networks7m
Classification Methods Based on Statistics3m
Classification Methods Based on Probabilities7m
Prediction Methods4m
Evaluation Schemes13m
Prediction Workflow4m
R Scripts for Prediction1m
Jupyter Notebooks 1017m
Reading4 lecturas
Jupyter Notebooks Essentials10m
Notebook Module 4 Tutorial10m
Module 4 R Predicting Diseases from Genes10m
Module 4 Resources10m
Quiz10 ejercicios de práctica
Overview4m
Classification with Analogy2m
Classification based on Rules2m
Classification with Neural Networks2m
Classification based on Statistics2m
Classification based on Probabilities2m
Prediction Models2m
Evaluation Schemes2m
Module 4 Quiz20m
Module 4 R Predicting Diseases from Genes10m

Instructores

Avatar

Isabelle Bichindaritz

Associate Professor
Computer Science

Acerca de Universidad Estatal de Nueva York

The State University of New York, with 64 unique institutions, is the largest comprehensive system of higher education in the United States. Educating nearly 468,000 students in more than 7,500 degree and certificate programs both on campus and online, SUNY has nearly 3 million alumni around the globe....

Preguntas Frecuentes

  • Una vez que te inscribes para obtener un Certificado, tendrás acceso a todos los videos, cuestionarios y tareas de programación (si corresponde). Las tareas calificadas por compañeros solo pueden enviarse y revisarse una vez que haya comenzado tu sesión. Si eliges explorar el curso sin comprarlo, es posible que no puedas acceder a determinadas tareas.

  • Cuando compras un Certificado, obtienes acceso a todos los materiales del curso, incluidas las tareas calificadas. Una vez que completes el curso, se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes participar del curso como oyente sin costo.

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