Informatics and Statistics for Metabolomics 2018 Module 6-Future of Metabolomics
Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, using pathway databases, performing pathway analysis, conducting univariate and multivariate statistics, working with metabolomics databases, and exploring chemical databases.
Informatics and Statistics for Metabolomics 2018 Module 6-Future of Metabolomics
https://bioinformaticsdotca.github.io/metabolomics_2018
http://tess.elixir-uk.org/materials/informatics-and-statistics-for-metabolomics-2018-module-6-future-of-metabolomics
Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, using pathway databases, performing pathway analysis, conducting univariate and multivariate statistics, working with metabolomics databases, and exploring chemical databases.
David Wishart
Researchers
Post-Doctoral Fellows
Graduate students
Biologists, Genomicists, Computer Scientists
Informatics and Statistics for Metabolomics 2018 Module 3-Databases for Chemical, Spectral, and Biological Data
Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, using pathway databases, performing pathway analysis, conducting univariate and multivariate statistics, working with metabolomics databases, and exploring chemical databases.
Informatics and Statistics for Metabolomics 2018 Module 3-Databases for Chemical, Spectral, and Biological Data
https://bioinformaticsdotca.github.io/metabolomics_2018
http://tess.elixir-uk.org/materials/informatics-and-statistics-for-metabolomics-2018-module-3-databases-for-chemical-spectral-and-biological-data
Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, using pathway databases, performing pathway analysis, conducting univariate and multivariate statistics, working with metabolomics databases, and exploring chemical databases.
David Wishart
Researchers
Post-Doctoral Fellows
Graduate Students
Biologists, Genomicists, Computer Scientists
Informatics and Statistics for Metabolomics 2018 Module 2-Metabolite Identification and Annotation
Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, using pathway databases, performing pathway analysis, conducting univariate and multivariate statistics, working with metabolomics databases, and exploring chemical databases.
Informatics and Statistics for Metabolomics 2018 Module 2-Metabolite Identification and Annotation
https://bioinformaticsdotca.github.io/metabolomics_2018
http://tess.elixir-uk.org/materials/informatics-and-statistics-for-metabolomics-2018-module-2-metabolite-identification-and-annotation
Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, using pathway databases, performing pathway analysis, conducting univariate and multivariate statistics, working with metabolomics databases, and exploring chemical databases.
David Wishart
Researchers
Graduate students
Post-Doctoral Fellows
Biologists, Genomicists, Computer Scientists
Informatics and Statistics for Metabolomics 2018 Module 1-Introduction to Metabolomics
Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, using pathway databases, performing pathway analysis, conducting univariate and multivariate statistics, working with metabolomics databases, and exploring chemical databases.
Informatics and Statistics for Metabolomics 2018 Module 1-Introduction to Metabolomics
https://bioinformaticsdotca.github.io/metabolomics_2018
http://tess.elixir-uk.org/materials/informatics-and-statistics-for-metabolomics-2018-module-1-introduction-to-metabolomics
Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, using pathway databases, performing pathway analysis, conducting univariate and multivariate statistics, working with metabolomics databases, and exploring chemical databases.
David Wishart
Researchers
Graduate Students
Post-Doctoral Fellows
Biologists, Genomicists, Computer Scientists
Informatics and Statistics for Metabolomics 2017 Module 6-Future of Metabolomics
Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, conducting univariate and multivariate statistics, working with metabolomic databases, and exploring chemical databases.
Informatics and Statistics for Metabolomics 2017 Module 6-Future of Metabolomics
https://bioinformaticsdotca.github.io/metabolomics_2017
http://tess.elixir-uk.org/materials/informatics-and-statistics-for-metabolomics-2017-module-6-future-of-metabolomics
Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, conducting univariate and multivariate statistics, working with metabolomic databases, and exploring chemical databases.
David Wishart
Researchers
Graduate students
Biologists, Genomicists, Computer Scientists
Post-Doctoral Fellows
Informatics and Statistics for Metabolomics 2017 Module 5-MetaboAnalyst
Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, conducting univariate and multivariate statistics, working with metabolomic databases, and exploring chemical databases.
Informatics and Statistics for Metabolomics 2017 Module 5-MetaboAnalyst
https://bioinformaticsdotca.github.io/metabolomics_2017
http://tess.elixir-uk.org/materials/informatics-and-statistics-for-metabolomics-2017-module-5-metaboanalyst
Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, conducting univariate and multivariate statistics, working with metabolomic databases, and exploring chemical databases.
David Wishart
Researchers
Graduate Students
Biologists, Genomicists, Computer Scientists
Post-Doctoral Fellows
Informatics and Statistics for Metabolomics 2017 Module 3-Databases for Chemical, Spectral, and Biological Data
Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, conducting univariate and multivariate statistics, working with metabolomic databases, and exploring chemical databases.
Informatics and Statistics for Metabolomics 2017 Module 3-Databases for Chemical, Spectral, and Biological Data
https://bioinformaticsdotca.github.io/metabolomics_2017
http://tess.elixir-uk.org/materials/informatics-and-statistics-for-metabolomics-2017-module-3-databases-for-chemical-spectral-and-biological-data
Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, conducting univariate and multivariate statistics, working with metabolomic databases, and exploring chemical databases.
David Wishart
Researchers
Graduate Students
Biologists, Genomicists, Computer Scientists
Post-Doctoral Fellows
Informatics and Statistics for Metabolomics 2017 Module 2-Metabolite Identification and Annotation
Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, conducting univariate and multivariate statistics, working with metabolomic databases, and exploring chemical databases.
Informatics and Statistics for Metabolomics 2017 Module 2-Metabolite Identification and Annotation
https://bioinformaticsdotca.github.io/metabolomics_2017
http://tess.elixir-uk.org/materials/informatics-and-statistics-for-metabolomics-2017-module-2-metabolite-identification-and-annotation
Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, conducting univariate and multivariate statistics, working with metabolomic databases, and exploring chemical databases.
David Wishart
Researchers
Graduate students
Post-Doctoral Fellows
Biologists, Genomicists, Computer Scientists
Informatics and Statistics for Metabolomics 2017 Module 1-Introduction to Metabolomics
Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, conducting univariate and multivariate statistics, working with metabolomic databases, and exploring chemical databases.
Informatics and Statistics for Metabolomics 2017 Module 1-Introduction to Metabolomics
https://bioinformaticsdotca.github.io/metabolomics_2017
http://tess.elixir-uk.org/materials/informatics-and-statistics-for-metabolomics-2017-module-1-introduction-to-metabolomics
Course covers many topics ranging from understanding metabolomics technologies, data collection and analysis, conducting univariate and multivariate statistics, working with metabolomic databases, and exploring chemical databases.
David Wishart
Researchers
Graduate students
Biologists, Genomicists, Computer Scientists
Post-Doctoral Fellows
Similarity searching, multiple sequence alignment and protein families - undergraduate lab
Lab 3 in a series of labs given as part of a "bioinformatics for biologists" course targeted at 2nd/3rd year undergraduates and focusing on informed use of tools. Some instructions are specific to our local computer lab setup but overall the content should be adaptable. Note that because some of...
Keywords: Blast, Hmmer, Interpro, Multiple sequence alignment, Similarity searching
Similarity searching, multiple sequence alignment and protein families - undergraduate lab
https://www.mygoblet.org/training-portal/materials/similarity-searching-multiple-sequence-alignment-and-protein-families
http://tess.elixir-uk.org/materials/similarity-searching-multiple-sequence-alignment-and-protein-families-undergraduate-lab
Lab 3 in a series of labs given as part of a "bioinformatics for biologists" course targeted at 2nd/3rd year undergraduates and focusing on informed use of tools. Some instructions are specific to our local computer lab setup but overall the content should be adaptable. Note that because some of the exercises make use of public databases they need to be checked and in some cases updated every time the lab is run. The lab is meant to be easily assessed using an online quiz (I use moodle). I provides a hands on introduction to NCBI BLAST, Interproscan, Clustal, MUSCLE and T-COFFEE, and HMMER.
Bruno Gaeta
Blast, Hmmer, Interpro, Multiple sequence alignment, Similarity searching
biology and bioinformatics sophomore undergraduates
2013-11-12
2017-10-09
Multiple sequence alignment and phylogeny - undergraduate lab
This is lab 4 in a series of labs given as part of an undergraduate "Bioinformatics for biologists" course delivered to 2nd and 3rd year biology and bioinformatics undergraduate students, as part of a course focusing on using bioinformatics tools. Some instructions in it are specific to our lab...
Keywords: Clustalw, Multiple sequence alignment, Phylip, Phylogeny
Multiple sequence alignment and phylogeny - undergraduate lab
https://www.mygoblet.org/training-portal/materials/multiple-sequence-alignment-and-phylogeny-undergraduate-lab
http://tess.elixir-uk.org/materials/multiple-sequence-alignment-and-phylogeny-undergraduate-lab
This is lab 4 in a series of labs given as part of an undergraduate "Bioinformatics for biologists" course delivered to 2nd and 3rd year biology and bioinformatics undergraduate students, as part of a course focusing on using bioinformatics tools. Some instructions in it are specific to our lab environment - including some not so current programs (clustalw, treetool, seaview, phylip) as that's what we have installed at the moment and they're stable, but the content can easily be adapted to other environments and programs. The lab is meant to be easily assessed and I get the students to answer the question in a moodle quiz which makes marking easier. The lab follows some lectures on multiple sequence alignment and molecular phylogeny.
Bruno Gaeta
Clustalw, Multiple sequence alignment, Phylip, Phylogeny
biology and bioinformatics sophomore undergraduates
2013-11-12
2017-10-09
Sequence comparison - undergraduate lab
This is lab 2 in a series of labs developed as part of a "bioinformatics for biology undergraduates" course and targeted at 2nd and 3rd year undergraduates. It is meant to be easily assessible. The lab includes some instructions that are specific to our computer lab environment but the content of...
Keywords: Dotmatrix plots, Scoring matrices, Sequence alignment
Sequence comparison - undergraduate lab
https://www.mygoblet.org/training-portal/materials/sequence-comparison-undergraduate-lab
http://tess.elixir-uk.org/materials/sequence-comparison-undergraduate-lab
This is lab 2 in a series of labs developed as part of a "bioinformatics for biology undergraduates" course and targeted at 2nd and 3rd year undergraduates. It is meant to be easily assessible. The lab includes some instructions that are specific to our computer lab environment but the content of the lab should be easy to adapt to other environments. This lab makes use of EMBOSS programs, prss in the FASTA package, as well as the NCBI BLAST website. I usually deliver this lab after a series of lectures discussing dotmatrix plots and sequence alignment. Students enter their answers to the questions into a quiz set up within moodle which allows for easier marking.
Bruno Gaeta
Dotmatrix plots, Scoring matrices, Sequence alignment
Undergraduate students
2013-11-12
2017-10-09