Clustering Biological Data (Bioinformatics V)

开始时间: 04/22/2022 持续时间: Unknown

所在平台: CourseraArchive 课程类别: 其他类别 大学或机构: University of California, San Diego （加州大学圣地亚哥分校）

课程主页: https://www.coursera.org/course/clustering

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课程详情

One of the first organisms to be domesticated by humans was yeast. Saccharomyces yeast is remarkable because it can not only convert the glucose in grapes into ethanol (which we then consume as wine), but it can also invert its own metabolism, consuming the ethanol it just produced in a process called the diauxic shift.  To find genes implicated in the diauxic shift, we will learn about clustering algorithms that will divide yeast genes into distinct groups based on their patterns of regulatory behavior.

A similar method can be applied to distinguish normal and tumor cells, an approach that led to diagnostic tests like MammaPrint for predicting the return of cancer after chemotherapy.

We can also apply clustering algorithms to identify the genetic foundation of human population structure and discover which populations have contributed to your own genome. To do so, we will need to power up the clustering algorithms we encounter using a powerful computational approach called principal component analysis.

课程大纲

How Did Yeast Become a Wine Maker? (Clustering Algorithms)

• An Evolutionary History of Wine Making
• Identifying Genes Responsible for the Diauxic Shift
• Introduction to Clustering
• k-Means Clustering
• The Lloyd Algorithm
• Clustering Genes Implicated in the Diauxic Shift
  
• Limitations of k-Means Clustering
• From Coin Flipping to k-Means Clustering
• Making Soft Decisions in Coin Flipping
• Soft k-Means Clustering
• Hierarchical Clustering
  
• Epilogue: Clustering Tumor Samples
  

What Genetic Characteristics Do Human Populations Share? (Principal Components Analysis)

• Specific Content TBA

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