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Content provider: GOBLET 

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Keywords: Exploratory-analysis  or metagenomics  or Flow cytometry data  or Expression-estimation  or E learning 


BLAST and multiple sequence alignment (MSA) programs

Background The rapid identification of pathogens infecting livestock is essential to appropriately respond to the threat. The number and the variety of pathogen sequenced genomes have been growing more dramatically these recent years, because of the new sequencing technologies. This wealth of...

Keywords: Blast, E learning, Multiple sequence alignment

BLAST and multiple sequence alignment (MSA) programs https://tess.elixir-europe.org/materials/blast-and-multiple-sequence-alignment-msa-programs Background The rapid identification of pathogens infecting livestock is essential to appropriately respond to the threat. The number and the variety of pathogen sequenced genomes have been growing more dramatically these recent years, because of the new sequencing technologies. This wealth of new data is very useful to the research field through the development of bioinformatics tools and databases that deal with large amount of sequences. Among them, BLAST (Basic Local Alignment Search Tool) and MSA () programs are very efficient for protein or nucleotide sequence similarity search. The present course introduces the main biological databases, alignment tool BLAST and Multiple sequence alignments (MSA) programs, and interpretation of results. Goal The ultimate aim is the better management of animal diseases by preparing laboratory technicians, veterinarians and molecular epidemiologists from diagnostic and research laboratories of developing FAO and IAEA member states, to be self-sufficient in the data analysis by interpreting the phylogenetic trees and their relationships. Target audience Researchers, Laboratory technicians, veterinarians, epidemiologists from diagnostic and research laboratories of member states of IAEA and FAO. The concepts are explained in generalized way to help all academicians, researchers, students from all countries working in the field of molecular genetics and epidemiology. AuthorsViral-zone, Swiss-Prot group at the SIB Swiss Institute of Bioinformatics   Blast, E learning, Multiple sequence alignment Bench biologists Biologists Laboratory technicians Researchers Veterinarians 2014-04-28 2017-10-09
Phylogenetics of animal viral pathogens

Background The vast diversity of the pathogens affecting livestock demands a very specific diagnostic procedure in identification and characterization of each pathogen. In this context, the enormous amount of sequence and genotype data is being generated on animal pathogens, which is further...

Keywords: Animal pathogens, E learning, Phylogenetics

Phylogenetics of animal viral pathogens https://tess.elixir-europe.org/materials/phylogenetics-of-animal-viral-pathogens Background The vast diversity of the pathogens affecting livestock demands a very specific diagnostic procedure in identification and characterization of each pathogen. In this context, the enormous amount of sequence and genotype data is being generated on animal pathogens, which is further useful in understanding their pathogenicity and molecular epidemiology. The usage of this data in developing efficient molecular diagnostic tools needs basic understanding of the phylogenetic analysis. Phylogenetic classification, construction of trees, interpretation unveils the geographical distribution and migration of pathogens which helps in better management of animal diseases. The present course is designed with introduction to phylogenetics, tools, building and interpreting trees and finally its application to veterinary diagnostics. Though the course is driven in veterinary aspects, the same implicates to the human and plant pathogen study. Goal The ultimate aim is the better management of animal diseases by preparing laboratory technicians, veterinarians and molecular epidemiologists from diagnostic and research laboratories of developing FAO and IAEA member states, to be self-sufficient in the data analysis by interpreting the phylogenetic trees and their relationships. Target audience Researchers, Laboratory technicians, veterinarians, epidemiologists from diagnostic and research laboratories of member states of IAEA and FAO. The concepts are explained in generalized way to help all academicians, researchers, students from all countries working in the field of molecular genetics and epidemiology. AuthorsViral-Zone, Swiss-Prot Group at SIB Swiss Institute of Bioinformatics   Animal pathogens, E learning, Phylogenetics Bench biologists Biologists Laboratory technicians Researchers Veterinarians 2014-04-28 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