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Bioinformatic Methods II
Coursera
Course
Unknown

Bioinformatic Methods II

University of Toronto

This course continues bioinformatic methods focusing on advanced data processing, visualization, cell biology analysis, and computational bioinformatics tools.

Unknown8 weeksEnglish37,632 enrolled

About this Course

Large-scale biology projects such as the sequencing of the human genome and gene expression surveys using RNA-seq, microarrays and other technologies have created a wealth of data for biologists. However, the challenge facing scientists is analyzing and even accessing these data to extract useful information pertaining to the system being studied. This course focuses on employing existing bioinformatic resources – mainly web-based programs and databases – to access the wealth of data to answer questions relevant to the average biologist, and is highly hands-on. Topics covered include multiple sequence alignments, phylogenetics, gene expression data analysis, and protein interaction networks, in two separate parts. The first part, Bioinformatic Methods I, dealt with databases, Blast, multiple sequence alignments, phylogenetics, selection analysis and metagenomics. This, the second part, Bioinformatic Methods II, will cover motif searching, protein-protein interactions, structural bioinformatics, gene expression data analysis, and cis-element predictions. This pair of courses is useful to any student considering graduate school in the biological sciences, as well as students considering molecular medicine. These courses are based on one taught at the University of Toronto to upper-level undergraduates who have some understanding of basic molecular biology. If you're not familiar with this, something like https://learn.saylor.org/course/view.php?id=889 might be helpful. No programming is required for this course although some command line work (though within a web browser) occurs in the 5th module. Bioinformatic Methods II is regularly updated, and was last updated for February 2026

What You'll Learn

  • Interpret biological data using advanced data processing techniques
  • Use data visualization software to explore biological relationships
  • Apply computational tools for cellular sample analysis
  • Utilize bioinformatics databases for applied research
  • Analyze biological results with bioinformatics methods

Prerequisites

  • Basic computer and internet skills
  • Ability to read and understand course instructions in English
  • Willingness to complete short practical exercises

Instructors

N

Nicholas James Provart

Professor

Topics

Health Informatics
Health
Data Processing
Informatics
Cell Biology
Data Visualization Software
Bioinformatics
Data Analysis
Biotechnology
Network Analysis

Course Info

PlatformCoursera
LevelUnknown
PacingUnknown
PriceFree

Skills

المعلوماتية الصحية
تحليل البيانات
معالجة البيانات الحيوية
البيولوجيا الخلوية
تصور البيانات
علم الأحياء الحاسوبي
علوم الحياة
برمجيات المعلوماتية الحيوية
Biotechnology
Network Analysis

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