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Bioinformatics Training

Bioinformatics course timetable

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Mon 24 Jun – Thu 31 Oct

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June 2019

Tue 25
Image Analysis for Biologists (2 of 3) In progress 09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

This course will focus on computational methods for analysing cellular images and extracting quantitative data from them. The aim of this course is to familiarise the participants with computational image analysis methodologies, and to provide hands-on training in running quantitative analysis pipelines.

On day 1 we will introduce principles of image processing and analysis, giving an overview of commonly used algorithms through a series of talks and practicals based on Fiji, an extensible open source software package.

On day 2, we will cover time series processing and cell tracking using TrackMate and advanced image segmentation using Ilastik. Additionally, in the afternoon we will run a study design and data clinic (sign up will be required) for participants that wish to discuss their experiments.

On day 3, we will describe the open Icy platform developed at the Institut Pasteur. Icy is a next-generation, user-friendly software offering powerful acquisition, visualisation, annotation and analysis algorithms for 5D bioimaging data, together with unique automation/scripting capabilities (notably via its graphical programming interface) and tight integration with existing software (e.g. ImageJ, Matlab, Micro-Manager).

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.

Wed 26
Image Analysis for Biologists (3 of 3) In progress 09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

This course will focus on computational methods for analysing cellular images and extracting quantitative data from them. The aim of this course is to familiarise the participants with computational image analysis methodologies, and to provide hands-on training in running quantitative analysis pipelines.

On day 1 we will introduce principles of image processing and analysis, giving an overview of commonly used algorithms through a series of talks and practicals based on Fiji, an extensible open source software package.

On day 2, we will cover time series processing and cell tracking using TrackMate and advanced image segmentation using Ilastik. Additionally, in the afternoon we will run a study design and data clinic (sign up will be required) for participants that wish to discuss their experiments.

On day 3, we will describe the open Icy platform developed at the Institut Pasteur. Icy is a next-generation, user-friendly software offering powerful acquisition, visualisation, annotation and analysis algorithms for 5D bioimaging data, together with unique automation/scripting capabilities (notably via its graphical programming interface) and tight integration with existing software (e.g. ImageJ, Matlab, Micro-Manager).

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.

Thu 27
An introduction to metabolomics and its application in life-sciences (1 of 2) [Places] 09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

The goal of metabolomics is to identify and quantify the complete biochemical composition of a biological sample. With the increase in genomic, transcriptomic and proteomic information there is a growing need to understand the metabolic phenotype that these genes and proteins ultimately control.

The aim of this course is to provide an overview of metabolomics and its applications in life sciences, clinical and environmental settings. Over 2 days we will introduce different techniques used to extract metabolites and analyse samples to collect metabolomic data (such as HPLC or GC-based MS and NMR), present how to analyse such data, how to identify metabolites using online databases and how to map the metabolomic data to metabolic pathways.

The course content will predominantly be based on analysing samples from model plant species such as Arabidopsis thaliana but the procedures are transferable to all other organisms, including clinical and environmental settings.

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here.

Fri 28
An introduction to metabolomics and its application in life-sciences (2 of 2) [Places] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

The goal of metabolomics is to identify and quantify the complete biochemical composition of a biological sample. With the increase in genomic, transcriptomic and proteomic information there is a growing need to understand the metabolic phenotype that these genes and proteins ultimately control.

The aim of this course is to provide an overview of metabolomics and its applications in life sciences, clinical and environmental settings. Over 2 days we will introduce different techniques used to extract metabolites and analyse samples to collect metabolomic data (such as HPLC or GC-based MS and NMR), present how to analyse such data, how to identify metabolites using online databases and how to map the metabolomic data to metabolic pathways.

The course content will predominantly be based on analysing samples from model plant species such as Arabidopsis thaliana but the procedures are transferable to all other organisms, including clinical and environmental settings.

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here.

July 2019

Mon 1
Summer School - Bioinformatics for Biologists: An introduction to Data Exploration, Statistics and Reproducibility charged (1 of 5) [Full] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

This 1-week course aims to provide an introduction to the best practices and tools needed to perform bioinformatics research effectively and reproducibly.

Focusing on solutions around handling biological data, we will cover introductory lessons in data manipulation and visualisation in R, statistical analyses, and reproducibility. The R component of the course will cover from basic steps in R to how to use some of the most popular R packages (dplyr and ggplot2) for data manipulation and visualisation. No prior R experience or previous knowledge of programming/coding is required. The course also includes introductory sessions in statistics and working examples on how to analyse biological data. At the end of the course we will address issues relating to reusability and reproducibility.

More information about the course can be found here.

This course is run in collaboration with the Institute of Continuing Education.

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.

Tue 2
Summer School - Bioinformatics for Biologists: An introduction to Data Exploration, Statistics and Reproducibility charged (2 of 5) [Full] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

This 1-week course aims to provide an introduction to the best practices and tools needed to perform bioinformatics research effectively and reproducibly.

Focusing on solutions around handling biological data, we will cover introductory lessons in data manipulation and visualisation in R, statistical analyses, and reproducibility. The R component of the course will cover from basic steps in R to how to use some of the most popular R packages (dplyr and ggplot2) for data manipulation and visualisation. No prior R experience or previous knowledge of programming/coding is required. The course also includes introductory sessions in statistics and working examples on how to analyse biological data. At the end of the course we will address issues relating to reusability and reproducibility.

More information about the course can be found here.

This course is run in collaboration with the Institute of Continuing Education.

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.

Wed 3
Summer School - Bioinformatics for Biologists: An introduction to Data Exploration, Statistics and Reproducibility charged (3 of 5) [Full] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

This 1-week course aims to provide an introduction to the best practices and tools needed to perform bioinformatics research effectively and reproducibly.

Focusing on solutions around handling biological data, we will cover introductory lessons in data manipulation and visualisation in R, statistical analyses, and reproducibility. The R component of the course will cover from basic steps in R to how to use some of the most popular R packages (dplyr and ggplot2) for data manipulation and visualisation. No prior R experience or previous knowledge of programming/coding is required. The course also includes introductory sessions in statistics and working examples on how to analyse biological data. At the end of the course we will address issues relating to reusability and reproducibility.

More information about the course can be found here.

This course is run in collaboration with the Institute of Continuing Education.

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.

Thu 4
Summer School - Bioinformatics for Biologists: An introduction to Data Exploration, Statistics and Reproducibility charged (4 of 5) [Full] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

This 1-week course aims to provide an introduction to the best practices and tools needed to perform bioinformatics research effectively and reproducibly.

Focusing on solutions around handling biological data, we will cover introductory lessons in data manipulation and visualisation in R, statistical analyses, and reproducibility. The R component of the course will cover from basic steps in R to how to use some of the most popular R packages (dplyr and ggplot2) for data manipulation and visualisation. No prior R experience or previous knowledge of programming/coding is required. The course also includes introductory sessions in statistics and working examples on how to analyse biological data. At the end of the course we will address issues relating to reusability and reproducibility.

More information about the course can be found here.

This course is run in collaboration with the Institute of Continuing Education.

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.

Fri 5
Summer School - Bioinformatics for Biologists: An introduction to Data Exploration, Statistics and Reproducibility charged (5 of 5) [Full] 09:30 - 17:15 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

This 1-week course aims to provide an introduction to the best practices and tools needed to perform bioinformatics research effectively and reproducibly.

Focusing on solutions around handling biological data, we will cover introductory lessons in data manipulation and visualisation in R, statistical analyses, and reproducibility. The R component of the course will cover from basic steps in R to how to use some of the most popular R packages (dplyr and ggplot2) for data manipulation and visualisation. No prior R experience or previous knowledge of programming/coding is required. The course also includes introductory sessions in statistics and working examples on how to analyse biological data. At the end of the course we will address issues relating to reusability and reproducibility.

More information about the course can be found here.

This course is run in collaboration with the Institute of Continuing Education.

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.

Mon 8
Variant Discovery with GATK4 (1 of 4) [Places] 09:30 - 16:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

This workshop will focus on the core steps involved in calling germline short variants, somatic short variants, and copy number alterations with the Broad’s Genome Analysis Toolkit (GATK), using “Best Practices” developed by the GATK methods development team. A team of methods developers and instructors from the Data Sciences Platform at Broad will give talks explaining the rationale, theory, and real-world applications of the GATK Best Practices. You will learn why each step is essential to the variant-calling process, what key operations are performed on the data at each step, and how to use the GATK tools to get the most accurate and reliable results out of your dataset. If you are an experienced GATK user, you will gain a deeper understanding of how the GATK works under-the-hood and how to improve your results further, especially with respect to the latest innovations.

  • Day 1: Introductory and Overview. The first day of the workshop gives a high-level overview of various topics in the morning, and in the afternoon we show how these concepts apply to a case study. The case study is tailored based on the audience, as represented by their answers in our pre-workshop survey.
  • Day 2: Germline Short Variant Discovery. Today we dive deep into the tools that make up the GATK Best Practices Pipeline. In the morning we discuss variant discovery, and in the afternoon we look at refinement and filtering. You will have the opportunity both in the morning and in the afternoon to get hands-on with these tools and run them yourself.
  • Day 3: Somatic Variant Discovery. Today we will cover Somatic Variant Discovery in more depth. In the morning we primarily focus on calling short variants with Mutect2, and in the afternoon we look at copy number alterations. Both sections have a paired hands-on activity.
  • Day 4: Pipelining. Over the first three days, you would have learned a lot about different pipelines and tools that you can use in GATK. Today we will be learning all about how those pipelines are written in a language called WDL. In the afternoon we cover other useful topics to working on the cloud, including Docker and BigQuery.

Please note that this workshop is focused on human data analysis. The majority of the materials presented does apply equally to non-human data, and we will address some questions regarding adaptations that are needed for analysis of non-human data, but we will not go into much detail on those points.

The hands-on GATK tutorials in this workshop will be conducted on Terra, a new platform developed at Broad in collaboration with Verily Life Sciences for accessing data, running analysis tools and collaborating securely and seamlessly.

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to Book or register Interest by linking here.

Tue 9
Variant Discovery with GATK4 (2 of 4) [Places] 09:30 - 16:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

This workshop will focus on the core steps involved in calling germline short variants, somatic short variants, and copy number alterations with the Broad’s Genome Analysis Toolkit (GATK), using “Best Practices” developed by the GATK methods development team. A team of methods developers and instructors from the Data Sciences Platform at Broad will give talks explaining the rationale, theory, and real-world applications of the GATK Best Practices. You will learn why each step is essential to the variant-calling process, what key operations are performed on the data at each step, and how to use the GATK tools to get the most accurate and reliable results out of your dataset. If you are an experienced GATK user, you will gain a deeper understanding of how the GATK works under-the-hood and how to improve your results further, especially with respect to the latest innovations.

  • Day 1: Introductory and Overview. The first day of the workshop gives a high-level overview of various topics in the morning, and in the afternoon we show how these concepts apply to a case study. The case study is tailored based on the audience, as represented by their answers in our pre-workshop survey.
  • Day 2: Germline Short Variant Discovery. Today we dive deep into the tools that make up the GATK Best Practices Pipeline. In the morning we discuss variant discovery, and in the afternoon we look at refinement and filtering. You will have the opportunity both in the morning and in the afternoon to get hands-on with these tools and run them yourself.
  • Day 3: Somatic Variant Discovery. Today we will cover Somatic Variant Discovery in more depth. In the morning we primarily focus on calling short variants with Mutect2, and in the afternoon we look at copy number alterations. Both sections have a paired hands-on activity.
  • Day 4: Pipelining. Over the first three days, you would have learned a lot about different pipelines and tools that you can use in GATK. Today we will be learning all about how those pipelines are written in a language called WDL. In the afternoon we cover other useful topics to working on the cloud, including Docker and BigQuery.

Please note that this workshop is focused on human data analysis. The majority of the materials presented does apply equally to non-human data, and we will address some questions regarding adaptations that are needed for analysis of non-human data, but we will not go into much detail on those points.

The hands-on GATK tutorials in this workshop will be conducted on Terra, a new platform developed at Broad in collaboration with Verily Life Sciences for accessing data, running analysis tools and collaborating securely and seamlessly.

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to Book or register Interest by linking here.

Wed 10
Variant Discovery with GATK4 (3 of 4) [Places] 09:30 - 16:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

This workshop will focus on the core steps involved in calling germline short variants, somatic short variants, and copy number alterations with the Broad’s Genome Analysis Toolkit (GATK), using “Best Practices” developed by the GATK methods development team. A team of methods developers and instructors from the Data Sciences Platform at Broad will give talks explaining the rationale, theory, and real-world applications of the GATK Best Practices. You will learn why each step is essential to the variant-calling process, what key operations are performed on the data at each step, and how to use the GATK tools to get the most accurate and reliable results out of your dataset. If you are an experienced GATK user, you will gain a deeper understanding of how the GATK works under-the-hood and how to improve your results further, especially with respect to the latest innovations.

  • Day 1: Introductory and Overview. The first day of the workshop gives a high-level overview of various topics in the morning, and in the afternoon we show how these concepts apply to a case study. The case study is tailored based on the audience, as represented by their answers in our pre-workshop survey.
  • Day 2: Germline Short Variant Discovery. Today we dive deep into the tools that make up the GATK Best Practices Pipeline. In the morning we discuss variant discovery, and in the afternoon we look at refinement and filtering. You will have the opportunity both in the morning and in the afternoon to get hands-on with these tools and run them yourself.
  • Day 3: Somatic Variant Discovery. Today we will cover Somatic Variant Discovery in more depth. In the morning we primarily focus on calling short variants with Mutect2, and in the afternoon we look at copy number alterations. Both sections have a paired hands-on activity.
  • Day 4: Pipelining. Over the first three days, you would have learned a lot about different pipelines and tools that you can use in GATK. Today we will be learning all about how those pipelines are written in a language called WDL. In the afternoon we cover other useful topics to working on the cloud, including Docker and BigQuery.

Please note that this workshop is focused on human data analysis. The majority of the materials presented does apply equally to non-human data, and we will address some questions regarding adaptations that are needed for analysis of non-human data, but we will not go into much detail on those points.

The hands-on GATK tutorials in this workshop will be conducted on Terra, a new platform developed at Broad in collaboration with Verily Life Sciences for accessing data, running analysis tools and collaborating securely and seamlessly.

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to Book or register Interest by linking here.

Thu 11
Variant Discovery with GATK4 (4 of 4) [Places] 09:30 - 16:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

This workshop will focus on the core steps involved in calling germline short variants, somatic short variants, and copy number alterations with the Broad’s Genome Analysis Toolkit (GATK), using “Best Practices” developed by the GATK methods development team. A team of methods developers and instructors from the Data Sciences Platform at Broad will give talks explaining the rationale, theory, and real-world applications of the GATK Best Practices. You will learn why each step is essential to the variant-calling process, what key operations are performed on the data at each step, and how to use the GATK tools to get the most accurate and reliable results out of your dataset. If you are an experienced GATK user, you will gain a deeper understanding of how the GATK works under-the-hood and how to improve your results further, especially with respect to the latest innovations.

  • Day 1: Introductory and Overview. The first day of the workshop gives a high-level overview of various topics in the morning, and in the afternoon we show how these concepts apply to a case study. The case study is tailored based on the audience, as represented by their answers in our pre-workshop survey.
  • Day 2: Germline Short Variant Discovery. Today we dive deep into the tools that make up the GATK Best Practices Pipeline. In the morning we discuss variant discovery, and in the afternoon we look at refinement and filtering. You will have the opportunity both in the morning and in the afternoon to get hands-on with these tools and run them yourself.
  • Day 3: Somatic Variant Discovery. Today we will cover Somatic Variant Discovery in more depth. In the morning we primarily focus on calling short variants with Mutect2, and in the afternoon we look at copy number alterations. Both sections have a paired hands-on activity.
  • Day 4: Pipelining. Over the first three days, you would have learned a lot about different pipelines and tools that you can use in GATK. Today we will be learning all about how those pipelines are written in a language called WDL. In the afternoon we cover other useful topics to working on the cloud, including Docker and BigQuery.

Please note that this workshop is focused on human data analysis. The majority of the materials presented does apply equally to non-human data, and we will address some questions regarding adaptations that are needed for analysis of non-human data, but we will not go into much detail on those points.

The hands-on GATK tutorials in this workshop will be conducted on Terra, a new platform developed at Broad in collaboration with Verily Life Sciences for accessing data, running analysis tools and collaborating securely and seamlessly.

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to Book or register Interest by linking here.

Fri 12
Statistical Analysis using R [Full] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

Statistics are an important part of most modern studies and being able to effectively use a statistical package will help you to understand your results.

This course provides an introduction to some statistical techniques through the use of the R language. Topics covered include: Chi2 and Fisher tests, descriptive statistics, t-test, analysis of variance and regression.

Students will run analyses using statistical and graphical skills taught during the session.

The course manual can be found here.

This event is supported by the BBSRC Strategic Training Awards for Research Skills (STARS) grant (BB/P022766/1).

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here.

September 2019

Thu 5
An Introduction to Solving Biological Problems with Python (1 of 2) [Places] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

This course provides a practical introduction to the writing of Python programs for the complete novice. Participants are lead through the core aspects of Python illustrated by a series of example programs. Upon completion of the course, attentive participants will be able to write simple Python programs and customize more complex code to fit their needs.

Course materials are available here.

Please note that the content of this course has recently been updated. This course now mostly focuses on core concepts including Python syntax, data structures and reading/writing files. Concepts and strategies for working more effectively with Python are now the focus of a new 2-days course, Data Science in Python.

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here.

Fri 6
An Introduction to Solving Biological Problems with Python (2 of 2) [Places] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

This course provides a practical introduction to the writing of Python programs for the complete novice. Participants are lead through the core aspects of Python illustrated by a series of example programs. Upon completion of the course, attentive participants will be able to write simple Python programs and customize more complex code to fit their needs.

Course materials are available here.

Please note that the content of this course has recently been updated. This course now mostly focuses on core concepts including Python syntax, data structures and reading/writing files. Concepts and strategies for working more effectively with Python are now the focus of a new 2-days course, Data Science in Python.

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here.

Thu 19
Statistics for Biologists in R (1 of 2) [Places] 09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

This course is intended to provide a strong foundation in practical statistics and data analysis using the R software environment. The underlying philosophy of the course is to treat statistics as a practical skill rather than as a theoretical subject and as such the course focuses on methods for addressing real-life issues in the biological sciences using the R software package.

In this course we explore classical statistical analysis techniques starting with simple hypothesis testing and building up to multiple linear regression. The focus of the course is on practical implementation of these techniques and developing robust statistical analysis skills rather than on the underlying statistical theory.

After the course you should feel confident to be able to select and implement common statistical techniques using R and moreover know when, and when not, to apply these techniques.

This event is supported by the BBSRC Strategic Training Awards for Research Skills (STARS) grant (BB/P022766/1).

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.

Fri 20
Statistics for Biologists in R (2 of 2) [Places] 09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

This course is intended to provide a strong foundation in practical statistics and data analysis using the R software environment. The underlying philosophy of the course is to treat statistics as a practical skill rather than as a theoretical subject and as such the course focuses on methods for addressing real-life issues in the biological sciences using the R software package.

In this course we explore classical statistical analysis techniques starting with simple hypothesis testing and building up to multiple linear regression. The focus of the course is on practical implementation of these techniques and developing robust statistical analysis skills rather than on the underlying statistical theory.

After the course you should feel confident to be able to select and implement common statistical techniques using R and moreover know when, and when not, to apply these techniques.

This event is supported by the BBSRC Strategic Training Awards for Research Skills (STARS) grant (BB/P022766/1).

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.

October 2019

Wed 2
An Introduction to Machine Learning (1 of 3) [Full] 09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

Machine learning gives computers the ability to learn without being explicitly programmed. It encompasses a broad range of approaches to data analysis with applicability across the biological sciences. Lectures will introduce commonly used algorithms and provide insight into their theoretical underpinnings. In the practicals students will apply these algorithms to real biological data-sets using the R language and environment.

Please be aware that the course syllabus is currently being updated following feedback from the last event; therefore the agenda below will be subjected to changes.

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here.

Thu 3
An Introduction to Machine Learning (2 of 3) [Full] 09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

Machine learning gives computers the ability to learn without being explicitly programmed. It encompasses a broad range of approaches to data analysis with applicability across the biological sciences. Lectures will introduce commonly used algorithms and provide insight into their theoretical underpinnings. In the practicals students will apply these algorithms to real biological data-sets using the R language and environment.

Please be aware that the course syllabus is currently being updated following feedback from the last event; therefore the agenda below will be subjected to changes.

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here.

Fri 4
An Introduction to Machine Learning (3 of 3) [Full] 09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

Machine learning gives computers the ability to learn without being explicitly programmed. It encompasses a broad range of approaches to data analysis with applicability across the biological sciences. Lectures will introduce commonly used algorithms and provide insight into their theoretical underpinnings. In the practicals students will apply these algorithms to real biological data-sets using the R language and environment.

Please be aware that the course syllabus is currently being updated following feedback from the last event; therefore the agenda below will be subjected to changes.

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here.

Wed 23
ChIP-seq and ATAC-seq analysis (1 of 2) [Places] 09:30 - 17:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

The primary aim of this course is to familiarise participants with the analysis of ChIP-seq and ATAC-seq data and provide hands-on training on the latest analytical approaches.

The course starts with an introduction to ChIP-seq experiments for the detection of genome-wide DNA binding sites of transcription factors and other proteins. We first show data quality control and basic analytical steps such as alignment, peak calling and motif analysis, followed by practical examples on how to work with biological replicates and fundamental quality metrics for ChIP-seq datasets. On the second day, we then focus on the analysis of differential binding, comparing between different samples. We will also give an introduction to ATAC-seq data analysis for the detection of regions of open chromatin.

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.

Thu 24
ChIP-seq and ATAC-seq analysis (2 of 2) [Places] 09:30 - 17:00 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

The primary aim of this course is to familiarise participants with the analysis of ChIP-seq and ATAC-seq data and provide hands-on training on the latest analytical approaches.

The course starts with an introduction to ChIP-seq experiments for the detection of genome-wide DNA binding sites of transcription factors and other proteins. We first show data quality control and basic analytical steps such as alignment, peak calling and motif analysis, followed by practical examples on how to work with biological replicates and fundamental quality metrics for ChIP-seq datasets. On the second day, we then focus on the analysis of differential binding, comparing between different samples. We will also give an introduction to ATAC-seq data analysis for the detection of regions of open chromatin.

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book or register your interest by linking here.

Wed 30
Data Science in Python (1 of 2) [Places] 09:30 - 16:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

This course covers concepts and strategies for working more effectively with Python with the aim of writing reusable code, using function and libraries. Participants will acquire a working knowledge of key concepts which are prerequisites for advanced programming in Python e.g. writing modules and classes.

Note: this course is the continuation of the Introduction to Solving Biological Problems with Python; participants are expected to have attended the introductory Python course and/or have acquired some working knowledge of Python. This course is also open to Python beginners who are already fluent in other programming languages as this will help them to quickly get started in Python.

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here.

Thu 31
Data Science in Python (2 of 2) [Places] 09:30 - 16:30 Bioinformatics Training Room, Craik-Marshall Building, Downing Site

This course covers concepts and strategies for working more effectively with Python with the aim of writing reusable code, using function and libraries. Participants will acquire a working knowledge of key concepts which are prerequisites for advanced programming in Python e.g. writing modules and classes.

Note: this course is the continuation of the Introduction to Solving Biological Problems with Python; participants are expected to have attended the introductory Python course and/or have acquired some working knowledge of Python. This course is also open to Python beginners who are already fluent in other programming languages as this will help them to quickly get started in Python.

The training room is located on the first floor and there is currently no wheelchair or level access available to this level.

Please note that if you are not eligible for a University of Cambridge Raven account you will need to book by linking here.