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Content provider: GOBLET 

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Keywords: Exploratory-analysis  or metagenomics  or Chip-seq  or Systems  or Sequence alignment  or Flow cytometry data 


Using Bioinformatics to Understand Genetic Diseases: A Practical Guide

This Practical Guide in the Bringing Bioinformatics into the Classroom series outlines a number of basic bioinformatics approaches that can be used to understand the molecular basis of genetic diseases. A rare variation in the insulin gene is discussed, and the impact of the variation on the gene...

Keywords: Basic bioinformatics, Bioinformatics schools, Gene finding, Genetic mutation, Insulin structure, Sequence alignment, Sequence database searching, Training material

Using Bioinformatics to Understand Genetic Diseases: A Practical Guide https://tess.elixir-europe.org/materials/using-bioinformatics-to-understand-genetic-diseases-a-practical-guide This Practical Guide in the Bringing Bioinformatics into the Classroom series outlines a number of basic bioinformatics approaches that can be used to understand the molecular basis of genetic diseases. A rare variation in the insulin gene is discussed, and the impact of the variation on the gene product, and how this results in disease, is explored. Specifically, this Guide introduces a range of commonly used bioinformatics tools and databases with which to analyse both DNA and protein sequences, and protein structures. On reading the Guide and completing the exercises, users will be able to: i) investigate the locations of genes on the human genome using a genome browser; ii) compare DNA sequences using an alignment tool; iii) translate a DNA sequence into its protein product; iv) search a protein structure database, and visualise the 3D structure of insulin; and v) infer whether insulin is specific to humans by using protein sequence database search tools. Basic bioinformatics, Bioinformatics schools, Gene finding, Genetic mutation, Insulin structure, Sequence alignment, Sequence database searching, Training material 2019-03-18
EMBL-EBI Train Online

If you work in the life sciences, you may find that you’re spending less time doing experiments and more time analysing huge amounts of biological data. Train online is here to help you do this quickly and efficiently.

Scientific topics: Bioinformatics

Keywords: Bioinformatics, Chemical biology, Cross domain, Dna rna, Gene expression, Literature, Ontologies, Proteins, Structures, Systems

EMBL-EBI Train Online https://tess.elixir-europe.org/materials/embl-ebi-train-online If you work in the life sciences, you may find that you’re spending less time doing experiments and more time analysing huge amounts of biological data. Train online is here to help you do this quickly and efficiently. Bioinformatics Bioinformatics, Chemical biology, Cross domain, Dna rna, Gene expression, Literature, Ontologies, Proteins, Structures, Systems Beginner informatics Life sciences 2018-05-11
Introduction to Multiple Sequence Alignments (MSAs) and Phylogenies

Slides used for teaching an introduction to phylogenies and MSAs in the context of phylogenies for the first day of a two-day course on MSAs at Cambridge University, in the UK, in December 2013. Course taught together with Holger Dinkel and Terri Attwood.

Keywords: Molecular evolution, Multiple sequence alignment, Phylogenetics, Protein sequence analysis, Sequence alignment

Introduction to Multiple Sequence Alignments (MSAs) and Phylogenies https://tess.elixir-europe.org/materials/introduction-to-multiple-sequence-alignments-msas-and-phylogenies Slides used for teaching an introduction to phylogenies and MSAs in the context of phylogenies for the first day of a two-day course on MSAs at Cambridge University, in the UK, in December 2013. Course taught together with Holger Dinkel and Terri Attwood. Molecular evolution, Multiple sequence alignment, Phylogenetics, Protein sequence analysis, Sequence alignment Bench biologists Post-Doctoral Fellows Postgraduate students principle investigators 2013-12-19 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://tess.elixir-europe.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. Dotmatrix plots, Scoring matrices, Sequence alignment Undergraduate students 2013-11-12 2017-10-09
Flow Cytometry 2013 Module 4 - 1D Static gating

How to create a constant gate for the whole data set for one channel by first creating a sample representative of the whole data set How to apply a static gate to all samples and count the proportions of cells lying on either side of the gate Visualizing the proportions using a density...

Keywords: 1d static gating, Flow cytometry data

Flow Cytometry 2013 Module 4 - 1D Static gating https://tess.elixir-europe.org/materials/flow-cytometry-2013-module-4-1d-static-gating How to create a constant gate for the whole data set for one channel by first creating a sample representative of the whole data set How to apply a static gate to all samples and count the proportions of cells lying on either side of the gate Visualizing the proportions using a density plot, histogram, bean/violin plot Automating a sequential gating strategy in R to obtain cell proportions for a desired phenotype 1d static gating, Flow cytometry data 2013-06-26 2017-10-09
Flow Cytometry 2013 Module 6 - Clustering and Additional FCM Tools

Lecture on FlowCAP (Flow Cytometry: Critical Assessment of Population Identification Methods) project K-means explained flowMeans: smart k-means for FCM data flowClust3.0, SPADE, flowBin, flowFP, SamSPECTRAL clustering Biomarker discovery: flowType and RchyOptimyx, advanced tools used...

Keywords: Biomarker discovery, Flow cytometry data, Flowcap

Flow Cytometry 2013 Module 6 - Clustering and Additional FCM Tools https://tess.elixir-europe.org/materials/flow-cytometry-2013-module-6-clustering-and-additional-fcm-tools Lecture on FlowCAP (Flow Cytometry: Critical Assessment of Population Identification Methods) project K-means explained flowMeans: smart k-means for FCM data flowClust3.0, SPADE, flowBin, flowFP, SamSPECTRAL clustering Biomarker discovery: flowType and RchyOptimyx, advanced tools used to explore novel phenotypes and find ones which correlate with a clinical diagnosis More R: Bioconductor.org, an open source software project full of bioinformatics packages created for R, including sample work flows GenePattern.org: web-interface for running analysis modules such as sample deidentication, extracting specic keywords, quality control, normalization, clustering, classification FlowRepository.org: online FCM data repository to share public or private data sets with collaborators while providing detailed descriptions of the experiment set up and each FCS file Biomarker discovery, Flow cytometry data, Flowcap 2013-06-26 2017-10-09
Flow Cytometry 2013 Module 5 - 1D Dynamic gating

Using quantiles to set a gate based on a negative control Using median and standard deviation to set a gate based on a negative control Exploring rangeGate: an automated way to set a 1D gate for each sample individually Recording proportions of cells in subpopulations of interest by...

Keywords: 1d dynamic gating, Flow cytometry data

Flow Cytometry 2013 Module 5 - 1D Dynamic gating https://tess.elixir-europe.org/materials/flow-cytometry-2013-module-5-1d-dynamic-gating Using quantiles to set a gate based on a negative control Using median and standard deviation to set a gate based on a negative control Exploring rangeGate: an automated way to set a 1D gate for each sample individually Recording proportions of cells in subpopulations of interest by creating a spreadsheet file Recording a visual record of the gating results by creating JPEG image files 1d dynamic gating, Flow cytometry data 2013-06-26 2017-10-09
Flow Cytometry 2013 Module 3 - Preprocessing and Quality Assurance of FCM Data

Preprocessing Removing margin events Data transformation: log vs. biexponential Data normalization Quality Assurance Overview of quality assurance concepts: total raw/viable cell count, margin event count, outlier detection based on density of common...

Keywords: Flow cytometry data, Preprocessing, Quality assurance

Flow Cytometry 2013 Module 3 - Preprocessing and Quality Assurance of FCM Data https://tess.elixir-europe.org/materials/flow-cytometry-2013-module-3-preprocessing-and-quality-assurance-of-fcm-data Preprocessing Removing margin events Data transformation: log vs. biexponential Data normalization Quality Assurance Overview of quality assurance concepts: total raw/viable cell count, margin event count, outlier detection based on density of common parameters Building quality assurance objects using flowQ and generating summary HTML reports Flow cytometry data, Preprocessing, Quality assurance 2013-06-26 2017-10-09