8251 modules
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BIOL6074 2029-30
Bioinformatics and Systems Biology
Large-scale approaches at the molecular, cellular, organismal and ecological level are revolutionizing biology by enabling systems-level questions to be addressed. In many cases, these approaches are driven by technologies that allow the components of biological systems to be surveyed en masse. For example, whole genome sequencing can rapidly profile complete human genomes and transcriptomic analyses provide quantitative surveys of 1000s of RNA molecules. In addition to changing fundamental biology, these techniques are a central component of personalized medicine by providing molecular readouts for individual patients to improve both diagnosis and therapy. Interpreting the outcome of these large-scale experiments requires an understanding of the experimental technologies themselves as well as the underlying biological processes. Bioinformatics techniques address many of the challenges of these experiments including how to process, analyse, visualize and ultimately interpret the data. This module will introduce students to large-scale ‘systems’ biology as well as equipping them with the practical, hands-on skills necessary to fully utilize data resulting from these techniques. -
BIOL3063 2031-32
Bioinformatics and Systems Biology
Large-scale approaches at the molecular, cellular, organismal and ecological level are revolutionizing biology by enabling systems-level questions to be addressed. In many cases, these approaches are driven by technologies that allow the components of biological systems to be surveyed en masse. For example, whole genome sequencing can rapidly profile complete human genomes and transcriptomic analyses provide quantitative surveys of 1000s of RNA molecules. In addition to changing fundamental biology, these techniques are a central component of personalized medicine by providing molecular readouts for individual patients to improve both diagnosis and therapy. Interpreting the outcome of these large-scale experiments requires an understanding of the experimental technologies themselves as well as the underlying biological processes. Bioinformatics techniques address many of the challenges of these experiments including how to process, analyse, visualize and ultimately interpret the data. This module will introduce students to large-scale 'systems' biology as well as equipping them with the practical, hands-on skills necessary to fully utilize data resulting from these techniques. -
BIOL3063 2027-28
Bioinformatics and Systems Biology
Large-scale approaches at the molecular, cellular, organismal and ecological level are revolutionizing biology by enabling systems-level questions to be addressed. In many cases, these approaches are driven by technologies that allow the components of biological systems to be surveyed en masse. For example, whole genome sequencing can rapidly profile complete human genomes and transcriptomic analyses provide quantitative surveys of 1000s of RNA molecules. In addition to changing fundamental biology, these techniques are a central component of personalized medicine by providing molecular readouts for individual patients to improve both diagnosis and therapy. Interpreting the outcome of these large-scale experiments requires an understanding of the experimental technologies themselves as well as the underlying biological processes. Bioinformatics techniques address many of the challenges of these experiments including how to process, analyse, visualize and ultimately interpret the data. This module will introduce students to large-scale 'systems' biology as well as equipping them with the practical, hands-on skills necessary to fully utilize data resulting from these techniques. -
BIOL6074 2026-27
Bioinformatics and Systems Biology
Large-scale approaches at the molecular, cellular, organismal and ecological level are revolutionizing biology by enabling systems-level questions to be addressed. In many cases, these approaches are driven by technologies that allow the components of biological systems to be surveyed en masse. For example, whole genome sequencing can rapidly profile complete human genomes and transcriptomic analyses provide quantitative surveys of 1000s of RNA molecules. In addition to changing fundamental biology, these techniques are a central component of personalized medicine by providing molecular readouts for individual patients to improve both diagnosis and therapy. Interpreting the outcome of these large-scale experiments requires an understanding of the experimental technologies themselves as well as the underlying biological processes. Bioinformatics techniques address many of the challenges of these experiments including how to process, analyse, visualize and ultimately interpret the data. This module will introduce students to large-scale ‘systems’ biology as well as equipping them with the practical, hands-on skills necessary to fully utilize data resulting from these techniques. -
BIOL3063 2028-29
Bioinformatics and Systems Biology
Large-scale approaches at the molecular, cellular, organismal and ecological level are revolutionizing biology by enabling systems-level questions to be addressed. In many cases, these approaches are driven by technologies that allow the components of biological systems to be surveyed en masse. For example, whole genome sequencing can rapidly profile complete human genomes and transcriptomic analyses provide quantitative surveys of 1000s of RNA molecules. In addition to changing fundamental biology, these techniques are a central component of personalized medicine by providing molecular readouts for individual patients to improve both diagnosis and therapy. Interpreting the outcome of these large-scale experiments requires an understanding of the experimental technologies themselves as well as the underlying biological processes. Bioinformatics techniques address many of the challenges of these experiments including how to process, analyse, visualize and ultimately interpret the data. This module will introduce students to large-scale 'systems' biology as well as equipping them with the practical, hands-on skills necessary to fully utilize data resulting from these techniques. -
SOES6092 2027-28
Biological Data Science in R
Biological data science is a rapidly evolving field at the intersection of biology, statistics, and computer science. There is a growing demand for professionals skilled in analysing and interpreting data as well as an expectation that students will be familiar with responsible use of Artificial Intelligence to achieve this goal. Upon successful completion of this course, you will have the skills and knowledge necessary to effectively analyse and interpret biological data using the versatile and freely available programming language R. -
SOES6092 2028-29
Biological Data Science in R
Biological data science is a rapidly evolving field at the intersection of biology, statistics, and computer science. There is a growing demand for professionals skilled in analysing and interpreting data as well as an expectation that students will be familiar with responsible use of Artificial Intelligence to achieve this goal. Upon successful completion of this course, students will have the skills and knowledge necessary to effectively analyse and interpret biological data using the versatile and freely available programming language R, empowering them to contribute to scientific and societal advancements. -
SOES6092 2026-27
Biological Data Science in R
Biological data science is a rapidly evolving field at the intersection of biology, statistics, and computer science. There is a growing demand for professionals skilled in analysing and interpreting data as well as an expectation that students will be familiar with responsible use of Artificial Intelligence to achieve this goal. Upon successful completion of this course, you will have the skills and knowledge necessary to effectively analyse and interpret biological data using the versatile and freely available programming language R. -
SOES6092 2030-31
Biological Data Science in R
Biological data science is a rapidly evolving field at the intersection of biology, statistics, and computer science. There is a growing demand for professionals skilled in analysing and interpreting data as well as an expectation that students will be familiar with responsible use of Artificial Intelligence to achieve this goal. Upon successful completion of this course, you will have the skills and knowledge necessary to effectively analyse and interpret biological data using the versatile and freely available programming language R. -
SOES6092 2025-26
Biological Data Science in R
Biological data science is a rapidly evolving field at the intersection of biology, statistics, and computer science. There is a growing demand for professionals skilled in analysing and interpreting data as well as an expectation that students will be familiar with responsible use of Artificial Intelligence to achieve this goal. Upon successful completion of this course, students will have the skills and knowledge necessary to effectively analyse and interpret biological data using the versatile and freely available programming language R, empowering them to contribute to scientific and societal advancements.