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17 materials found

Authors: Jared Simpson  or Gary Bader  or Morris Riedel 


Pathways and Network Analysis of -Omics data 2018 Module 3-Network Visualization and Analysis with Cytoscape

Course covers the bioinformatics concepts and tools available for interpreting a gene list using pathway and network information.

Pathways and Network Analysis of -Omics data 2018 Module 3-Network Visualization and Analysis with Cytoscape https://tess.elixir-europe.org/materials/pathways-and-network-analysis-of-omics-data-2018-module-3-network-visualization-and-analysis-with-cytoscape Course covers the bioinformatics concepts and tools available for interpreting a gene list using pathway and network information. Researchers Graduate students Post-Doctoral Fellows Biologists, Genomicists, Computer Scientists
Pathways and Network Analysis of -Omics Data 2018 Module 1-Introduction to Pathway and Network Analysis

Course covers the bioinformatics concepts and tools available for interpreting a gene list using pathway and network information.

Pathways and Network Analysis of -Omics Data 2018 Module 1-Introduction to Pathway and Network Analysis https://tess.elixir-europe.org/materials/pathways-and-network-analysis-of-omics-data-2018-module-1-introduction-to-pathway-and-network-analysis Course covers the bioinformatics concepts and tools available for interpreting a gene list using pathway and network information. Researchers Post-Doctoral Fellows Biologists, Genomicists, Computer Scientists Graduate Students
Informatics on High-Throughput Sequencing Data 2018 Module 6-De Novo Assmebly

Course covers the bioinformatics tools available for managing and interpreting high-throughput sequencing data, where the focus is on Illumina reads although information is applicable to all sequencer reads.

Informatics on High-Throughput Sequencing Data 2018 Module 6-De Novo Assmebly https://tess.elixir-europe.org/materials/informatics-on-high-throughput-sequencing-data-2018-module-6-de-novo-assmebly Course covers the bioinformatics tools available for managing and interpreting high-throughput sequencing data, where the focus is on Illumina reads although information is applicable to all sequencer reads. Researchers Post-Doctoral Fellows Biologists, Genomicists, Computer Scientists Graduate students
Informatics on High-Throughput Sequencing Data 2018 Module 1-Introduction to High-Throughput Sequencing

Course covers the bioinformatics tools available for managing and interpreting high-throughput sequencing data, where the focus is on Illumina reads although information is applicable to all sequencer reads.

Informatics on High-Throughput Sequencing Data 2018 Module 1-Introduction to High-Throughput Sequencing https://tess.elixir-europe.org/materials/informatics-on-high-throughput-sequencing-data-2018-module-1-introduction-to-high-throughput-sequencing Course covers the bioinformatics tools available for managing and interpreting high-throughput sequencing data, where the focus is on Illumina reads although information is applicable to all sequencer reads. Researchers Graduate students Post-Doctoral Fellows Biologists, Genomicists, Computer Scientists
Bioinformatics for Cancer Genomics 2018 Module 5-Genome Assembly

Course covers the key bioinformatics concepts and tools required to analyze cancer genomic data sets and access and work with data sets in the cloud.

Bioinformatics for Cancer Genomics 2018 Module 5-Genome Assembly https://tess.elixir-europe.org/materials/bioinformatics-for-cancer-genomics-2018-module-5-genome-assembly Course covers the key bioinformatics concepts and tools required to analyze cancer genomic data sets and access and work with data sets in the cloud. Researchers Graduate students Biologists, Genomicists, Computer Scientists Post-Doctoral Fellows
Bioinformatics for Cancer Genomics 2018 Module 4-Genome Alignment

Course covers the key bioinformatics concepts and tools required to analyze cancer genomic data sets and access and work with data sets in the cloud.

Bioinformatics for Cancer Genomics 2018 Module 4-Genome Alignment https://tess.elixir-europe.org/materials/bioinformatics-for-cancer-genomics-2018-module-4-genome-alignment Course covers the key bioinformatics concepts and tools required to analyze cancer genomic data sets and access and work with data sets in the cloud. Researchers Graduate students Biologists, Genomicists, Computer Scientists Post-Doctoral Fellows
Pathways and Network Analysis of -Omics Data 2017 Module 3-Network Visualization and Analysis with Cytoscape

Course covers the bioinformatics tools available for analyzing and conducting pathway and network analysis on a gene list.

Pathways and Network Analysis of -Omics Data 2017 Module 3-Network Visualization and Analysis with Cytoscape https://tess.elixir-europe.org/materials/pathways-and-network-analysis-of-omics-data-2017-module-3-network-visualization-and-analysis-with-cytoscape Course covers the bioinformatics tools available for analyzing and conducting pathway and network analysis on a gene list.
Pathways and Network Analysis 2017 Module 2-Finding Over-Represented Pathways

Course covers the bioinformatics tools available for analyzing and conducting pathway and network analysis on a gene list.

Pathways and Network Analysis 2017 Module 2-Finding Over-Represented Pathways https://tess.elixir-europe.org/materials/pathways-and-network-analysis-2017-module-2-finding-over-represented-pathways Course covers the bioinformatics tools available for analyzing and conducting pathway and network analysis on a gene list.
Pathways and Network Analysis of -Omics Data 2017 Module 1-Introduction to Pathway and Network Analysis

Course covers the bioinformatics tools available for analyzing and conducting pathway and network analysis on a gene list.

Pathways and Network Analysis of -Omics Data 2017 Module 1-Introduction to Pathway and Network Analysis https://tess.elixir-europe.org/materials/pathways-and-network-analysis-of-omics-data-2017-module-1-introduction-to-pathway-and-network-analysis Course covers the bioinformatics tools available for analyzing and conducting pathway and network analysis on a gene list. Researchers Biologists, Genomicists, Computer Scientists Graduate Students Post-Doctoral Fellows
Bioinformatics for Cancer Genomics 2017 Module 3-Genome Alignment and Assembly

Course covers the bioinformatics tools required to analyze genomic data sets.

Bioinformatics for Cancer Genomics 2017 Module 3-Genome Alignment and Assembly https://tess.elixir-europe.org/materials/bioinformatics-for-cancer-genomics-2017-module-3-genome-alignment-and-assembly Course covers the bioinformatics tools required to analyze genomic data sets. Researchers Graduate students Biologists, Genomicists, Computer Scientists Post-Doctoral Fellows
Informatics on High-Throughput Sequencing Data 2017 Module 6-De Novo Assembly

Course covers the bioinformatics tools available for managing and interpreting high-throughput sequencing data with a focus on Illumina reads.

Informatics on High-Throughput Sequencing Data 2017 Module 6-De Novo Assembly https://tess.elixir-europe.org/materials/informatics-on-high-throughput-sequencing-data-2017-module-6-de-novo-assembly Course covers the bioinformatics tools available for managing and interpreting high-throughput sequencing data with a focus on Illumina reads. Researchers Graduate Students Post-Doctoral Fellows Biologists, Genomicists, Computer Scientists
Informatics on High-Throughput Sequencing Data 2017 Module 1-Introduction to High-Throughput Sequencing

Course covers the bioinformatics tools available for managing and interpreting high-throughput sequencing data with a focus on Illumina reads.

Informatics on High-Throughput Sequencing Data 2017 Module 1-Introduction to High-Throughput Sequencing https://tess.elixir-europe.org/materials/informatics-on-high-throughput-sequencing-data-module-1-introduction-to-high-throughput-sequencing Course covers the bioinformatics tools available for managing and interpreting high-throughput sequencing data with a focus on Illumina reads. Researchers Graduate students Biologists, Genomicists, Computer Scientists Post-Doctoral Fellows
High-Throughput Biology 2017 Module 6-De Novo Assembly

Course covers the key bioinformatics concepts and tools required to analyze DNA- and RNA- sequence reads using a reference genome.

High-Throughput Biology 2017 Module 6-De Novo Assembly https://tess.elixir-europe.org/materials/high-throughput-biology-2017-module-6-de-novo-assembly Course covers the key bioinformatics concepts and tools required to analyze DNA- and RNA- sequence reads using a reference genome. Researchers Graduate students Biologists, Genomicists, Computer Scientists Post-Doctoral Fellows
High-Throughput Biology 2017 Module 1-Introduction to High-Throughput Sequencing

Course covers the key bioinformatics concepts and tools required to analyze DNA- and RNA- sequence reads using a reference genome.

High-Throughput Biology 2017 Module 1-Introduction to High-Throughput Sequencing https://tess.elixir-europe.org/materials/high-throughput-biology-2017-module-1-introduction-to-high-throughput-sequencing Course covers the key bioinformatics concepts and tools required to analyze DNA- and RNA- sequence reads using a reference genome. Graduate students Post-Doctoral Fellows Researchers Biologists, Genomicists, Computer Scientists
Deep Learning using a Convolutional Neural Network

This course part focuses on a recent machine learning method known as deep learning that emerged as a promising disruptive approach, allowing knowledge discovery from large datasets in an unprecedented effectiveness and efficiency. It is particularly relevant in research areas, which are not...

Scientific topics: Machine learning

Resource type: Video

Deep Learning using a Convolutional Neural Network https://tess.elixir-europe.org/materials/deep-learning-using-a-convolutional-neural-network This course part focuses on a recent machine learning method known as deep learning that emerged as a promising disruptive approach, allowing knowledge discovery from large datasets in an unprecedented effectiveness and efficiency. It is particularly relevant in research areas, which are not accessible through modelling and simulation often performed in HPC. Traditional learning, which was introduced in the 1950s and became a data-driven paradigm in the 90s, is usually based on an iterative process of feature engineering, learning, and modelling. Although successful on many tasks, the resulting models are often hard to transfer to other datasets and research areas. Machine learning PhD students Post Docs
Introduction to Machine Learning Algorithms

This course offers basics of analysing datasets with machine learning algorithms and data mining techniques in order to understand foundations of learning from large quantities of data.

Scientific topics: Machine learning

Resource type: Video

Introduction to Machine Learning Algorithms https://tess.elixir-europe.org/materials/introduction-to-machine-learning-algorithms-b1434ce7-b934-4b48-af7c-0274e2c37815 This course offers basics of analysing datasets with machine learning algorithms and data mining techniques in order to understand foundations of learning from large quantities of data. Machine learning PhD students Post Docs
Introduction to Machine Learning Algorithms

This course offers basics of analysing datasets with machine learning algorithms and data mining techniques in order to understand foundations of learning from large quantities of data.

Scientific topics: Machine learning

Resource type: PDF

Introduction to Machine Learning Algorithms https://tess.elixir-europe.org/materials/introduction-to-machine-learning-algorithms This course offers basics of analysing datasets with machine learning algorithms and data mining techniques in order to understand foundations of learning from large quantities of data. Machine learning PhD students Post Docs