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The Morris Lab

We use machine learning to understand biology. We reconstruct the evolutionary history of tumors to understand how different populations of cells evolve over time. We develop computational methods to understand the regulatory mechanisms of RNA-binding proteins, 3'-end mRNA processing, and alternative splicing. We explore mutant phenotypes of single-deletion strains of. By applying novel machine learning approaches. The human splicing code reveals new insights into the genetic determinants of disease.

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The Morris Lab | profiledemixing.org Reviews
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We use machine learning to understand biology. We reconstruct the evolutionary history of tumors to understand how different populations of cells evolve over time. We develop computational methods to understand the regulatory mechanisms of RNA-binding proteins, 3'-end mRNA processing, and alternative splicing. We explore mutant phenotypes of single-deletion strains of. By applying novel machine learning approaches. The human splicing code reveals new insights into the genetic determinants of disease.
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2 projects
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4 publications
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6 cancer genomics
7 post transcriptional regulation
8 genotype to phenotype
9 s cerevisiae
10 precision medicine
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The Morris Lab | profiledemixing.org Reviews

https://profiledemixing.org

We use machine learning to understand biology. We reconstruct the evolutionary history of tumors to understand how different populations of cells evolve over time. We develop computational methods to understand the regulatory mechanisms of RNA-binding proteins, 3'-end mRNA processing, and alternative splicing. We explore mutant phenotypes of single-deletion strains of. By applying novel machine learning approaches. The human splicing code reveals new insights into the genetic determinants of disease.

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The Morris Lab

We use machine learning to understand biology. We reconstruct the evolutionary history of tumors to understand how different populations of cells evolve over time. We develop computational methods to understand the regulatory mechanisms of RNA-binding proteins, 3'-end mRNA processing, and alternative splicing. We explore mutant phenotypes of single-deletion strains of. By applying novel machine learning approaches. The human splicing code reveals new insights into the genetic determinants of disease.

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