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20 materials found

Keywords: computer-science  or Cells and Organisms 


Introducing Bivi.co

Introduction to the Bivi community presented as the introductory talk at the 1st Bivi Annual Meeting. Created at: 1st BiVi Annual Meeting.

Scientific topics: Phylogenetics, Pathway or network

Keywords: Anatomy Physiology and Atlases, Cells and Organisms, Genome, Molecular, Pathway, Phylogenetics, Populations

Resource type: Video

Introducing Bivi.co http://tess.elixir-uk.org/materials/introducing-bivi-co Introduction to the Bivi community presented as the introductory talk at the 1st Bivi Annual Meeting. Created at: 1st BiVi Annual Meeting. Prof. Jessie Kennedy Phylogenetics Pathway or network Anatomy Physiology and Atlases, Cells and Organisms, Genome, Molecular, Pathway, Phylogenetics, Populations 2016-12-08
Biological Networks

Scooter Morris (http://www.cgl.ucsf.edu/home/scooter/) talks about the opportunities and challenges in mapping biological networks and gives an brief overview of Cytoscape (http://www.cytoscape.org/), an open source bioinformatics software platform for visualizing molecular interaction...

Scientific topics: Pathway or network

Keywords: Cells and Organisms, Pathway

Resource type: Video

Biological Networks http://tess.elixir-uk.org/materials/biological-networks Scooter Morris (http://www.cgl.ucsf.edu/home/scooter/) talks about the opportunities and challenges in mapping biological networks and gives an brief overview of Cytoscape (http://www.cytoscape.org/), an open source bioinformatics software platform for visualizing molecular interaction networks.(PLEASE NOTE: There is a small formatting problem with the presentation slides for the first 2 min of the talk only). This video was filmed and distributed with permission under a Creative Commons license. Created at: VIZBI 2013. Dr. Scooter Morris Pathway or network Cells and Organisms, Pathway 2017-01-31
Cellular Image Data

Peter Sorger (http://sorger.med.harvard.edu/) and Bang Wong (http://bang.clearscience.info/) talk about the challenges of visualising large sets of multidimensional data (e.g. single cell imaging, dose-response assays, multiplex biochemistry etc.).This video was filmed and distributed with...

Keywords: Cells and Organisms

Resource type: Video

Cellular Image Data http://tess.elixir-uk.org/materials/cellular-image-data Peter Sorger (http://sorger.med.harvard.edu/) and Bang Wong (http://bang.clearscience.info/) talk about the challenges of visualising large sets of multidimensional data (e.g. single cell imaging, dose-response assays, multiplex biochemistry etc.).This video was filmed and distributed with permission under a Creative Commons license. Created at: VIZBI 2013. Bang Wong Cells and Organisms 2017-01-31
BBSRC: Data and Data Visualisation

Michael Ball from BBSRC's closing remarks on Data and Data Visualisation from 1st BiVi in 2014. Created at: 1st BiVi Annual Meeting.

Scientific topics: Phylogenetics, Pathway or network

Keywords: Anatomy Physiology and Atlases, Cells and Organisms, Genome, Molecular, Pathway, Phylogenetics, Populations, Information visualisation

Resource type: Video

BBSRC: Data and Data Visualisation http://tess.elixir-uk.org/materials/bbsrc-data-and-data-visualisation Michael Ball from BBSRC's closing remarks on Data and Data Visualisation from 1st BiVi in 2014. Created at: 1st BiVi Annual Meeting. Michael Ball Phylogenetics Pathway or network Anatomy Physiology and Atlases, Cells and Organisms, Genome, Molecular, Pathway, Phylogenetics, Populations, Information visualisation 2017-02-01
Cell lineage visualisation

Dr A J Pretorius discusses Cell-o-pane, a cell lineage visulaisation tool at 1st BiVi in 2014. As assoicated poster also presented a the meeting is included. Created at: 1st BiVi Annual Meeting.

Keywords: Cells and Organisms, Molecular

Resource type: Video

Cell lineage visualisation http://tess.elixir-uk.org/materials/cell-lineage-visualisation Dr A J Pretorius discusses Cell-o-pane, a cell lineage visulaisation tool at 1st BiVi in 2014. As assoicated poster also presented a the meeting is included. Created at: 1st BiVi Annual Meeting. Dr. A.J. Pretorius Cells and Organisms, Molecular 2017-02-01
BioLayout Express 3D

Derek Wright discusses the BioLayout Express visualisation tool at 1st BiVi in 2014. Created at: 1st BiVi Annual Meeting.

Scientific topics: Pathway or network

Keywords: Cells and Organisms, Genome, Pathway

Resource type: Video

BioLayout Express 3D http://tess.elixir-uk.org/materials/biolayout-express-3d Derek Wright discusses the BioLayout Express visualisation tool at 1st BiVi in 2014. Created at: 1st BiVi Annual Meeting. Derek Wright Pathway or network Cells and Organisms, Genome, Pathway 2017-02-02
Zegami: A tool for image data exploration

Stephen Taylor discusses the Zegami visualisation tool at 1st BiVi in 2014. An associated poster is also available. Created at: 1st BiVi Annual Meeting.

Keywords: Anatomy Physiology and Atlases, Cells and Organisms, Genome

Resource type: Poster, Video

Zegami: A tool for image data exploration http://tess.elixir-uk.org/materials/zegami-a-tool-for-image-data-exploration Stephen Taylor discusses the Zegami visualisation tool at 1st BiVi in 2014. An associated poster is also available. Created at: 1st BiVi Annual Meeting. Stephen Taylor Anatomy Physiology and Atlases, Cells and Organisms, Genome 2017-02-02
Zegami: Image visualisation, annotation and searching

Stephen Taylor describes and demonstrates Zegami at 2nd BiVi in 2015. Created at: 2nd BiVi Annual Meeting.

Keywords: Anatomy Physiology and Atlases, Cells and Organisms, Genome

Resource type: Slideshow

Zegami: Image visualisation, annotation and searching http://tess.elixir-uk.org/materials/zegami-image-visualisation-annotation-and-searching Stephen Taylor describes and demonstrates Zegami at 2nd BiVi in 2015. Created at: 2nd BiVi Annual Meeting. Stephen Taylor Anatomy Physiology and Atlases, Cells and Organisms, Genome 2017-02-03
Art and Science: A partnership catalyzing discovery in biomedicine

A 3rd BiVi 2017 Keynote Presentation by Bang Wong, Broad Institute of MIT & Harvard and Department of Art as Applied to Medicine, Johns Hopkins University School of MedicineChaired by: Geoff BartonThe data generated by the biomedical research community hold tremendous potential to inform our...

Scientific topics: Phylogenetics, Pathway or network

Keywords: Anatomy Physiology and Atlases, Cells and Organisms, Genome, Molecular, Pathway, Phylogenetics, Populations, Communication, Information visualisation

Resource type: Video

Art and Science: A partnership catalyzing discovery in biomedicine http://tess.elixir-uk.org/materials/art-and-science-a-partnership-catalyzing-discovery-in-biomedicine A 3rd BiVi 2017 Keynote Presentation by Bang Wong, Broad Institute of MIT & Harvard and Department of Art as Applied to Medicine, Johns Hopkins University School of MedicineChaired by: Geoff BartonThe data generated by the biomedical research community hold tremendous potential to inform our understanding and treatment of disease. The challenge is to ensure that technical and non-technical researchers can access, use and learn from this wealth of data and analytical resources. Bang will present examples of solutions developed at the Broad Institute that draw on art and design to enable scientific discovery.Bang Wong is the creative director of the Broad Institute of MIT & Harvard and an adjunct assistant professor in the Department of Art as Applied to Medicine at the Johns Hopkins University School of Medicine. His work focuses on the design and development of computation-visualization tools to meet the analytical challenges of research data. He leads the data visualization initiative at the Broad and is the founding author of Points of View published by Nature Methods, a series of articles that focus on the fundamental aspects of data presentation in science. Created at: 3rd BiVi Annual Meeting (2017). Bang Wong Phylogenetics Pathway or network Anatomy Physiology and Atlases, Cells and Organisms, Genome, Molecular, Pathway, Phylogenetics, Populations, Communication, Information visualisation 2017-05-12
Zegami: Digital Data Integration, Visualisation and Management

Stephen Taylor discusses Zegami with examples and latest developments at 3rd BiVi in April 2017.Zegami has the potential to do for images what the spreadsheet did for number calculations. It provides a way of manipulating images and derived values (from the images themselves or annotated...

Keywords: Cells and Organisms, Databases

Resource type: Video

Zegami: Digital Data Integration, Visualisation and Management http://tess.elixir-uk.org/materials/zegami-digital-data-integration-visualisation-and-management Stephen Taylor discusses Zegami with examples and latest developments at 3rd BiVi in April 2017.Zegami has the potential to do for images what the spreadsheet did for number calculations. It provides a way of manipulating images and derived values (from the images themselves or annotated metadata) on a massive scale allowing querying and organisation of large image based collections. The talk will show various examples of its usage in biology and beyond, and will look at new features such as annotation to build training sets for machine learning. Created at: 3rd BiVi Annual Meeting (2017). Stephen Taylor Cells and Organisms, Databases 2017-05-12
Model organism analysis using Intermine

Poster presented at 3rd BiVi in April 2017.InterMine is an open source data warehouse based in the University of Cambridge. We integrate data from disparate sources and provide a single unified interface, allowing you to access your data via an easy-to-use webapp or API. InterMine has over 30...

Keywords: Cells and Organisms

Resource type: Poster

Model organism analysis using Intermine http://tess.elixir-uk.org/materials/model-organism-analysis-using-intermine Poster presented at 3rd BiVi in April 2017.InterMine is an open source data warehouse based in the University of Cambridge. We integrate data from disparate sources and provide a single unified interface, allowing you to access your data via an easy-to-use webapp or API. InterMine has over 30 different instances worldwide, covering model organisms, plants, mitochondrial DNA, drug targeting, and more.  Created at: 3rd BiVi Annual Meeting (2017). Ms. Yo Yehudi Cells and Organisms 2017-05-30
Big Data, Genes, and Medicine

This course distills for you expert knowledge and skills mastered by professionals in Health Big Data Science and Bioinformatics. You will learn exciting facts about the human body biology and chemistry, genetics, and medicine that will be intertwined with the science of Big Data and skills to...

Keywords: life-sciences, computer-science, bioinformatics, algorithms

Big Data, Genes, and Medicine http://tess.elixir-uk.org/materials/big-data-genes-and-medicine This course distills for you expert knowledge and skills mastered by professionals in Health Big Data Science and Bioinformatics. You will learn exciting facts about the human body biology and chemistry, genetics, and medicine that will be intertwined with the science of Big Data and skills to harness the avalanche of data openly available at your fingertips and which we are just starting to make sense of. We’ll investigate the different steps required to master Big Data analytics on real datasets, including Next Generation Sequencing data, in a healthcare and biological context, from preparing data for analysis to completing the analysis, interpreting the results, visualizing them, and sharing the results. Needless to say, when you master these high-demand skills, you will be well positioned to apply for or move to positions in biomedical data analytics and bioinformatics. No matter what your skill levels are in biomedical or technical areas, you will gain highly valuable new or sharpened skills that will make you stand-out as a professional and want to dive even deeper in biomedical Big Data. It is my hope that this course will spark your interest in the vast possibilities offered by publicly available Big Data to better understand, prevent, and treat diseases. life-sciences, computer-science, bioinformatics, algorithms 2017-03-24
Bioinformatics Capstone: Big Data in Biology

In this course, you will learn how to use the BaseSpace cloud platform developed by Illumina (our industry partner) to apply several standard bioinformatics software approaches to real biological data. In particular, in a series of Application Challenges will see how genome assembly can be used...

Keywords: life-sciences, computer-science, health-informatics, algorithms

Bioinformatics Capstone: Big Data in Biology http://tess.elixir-uk.org/materials/bioinformatics-capstone-big-data-in-biology In this course, you will learn how to use the BaseSpace cloud platform developed by Illumina (our industry partner) to apply several standard bioinformatics software approaches to real biological data. In particular, in a series of Application Challenges will see how genome assembly can be used to track the source of a food poisoning outbreak, how RNA-Sequencing can help us analyze gene expression data on the tissue level, and compare the pros and cons of whole genome vs. whole exome sequencing for finding potentially harmful mutations in a human sample. Plus, hacker track students will have the option to build their own genome assembler and apply it to real data! life-sciences, computer-science, health-informatics, algorithms 2017-03-25
Finding Hidden Messages in DNA (Bioinformatics I)

Named a top 50 MOOC of all time by Class Central! This course begins a series of classes illustrating the power of computing in modern biology. Please join us on the frontier of bioinformatics to look for hidden messages in DNA without ever needing to put on a lab coat. In the first half of the...

Keywords: life-sciences, computer-science, health-informatics, algorithms

Finding Hidden Messages in DNA (Bioinformatics I) http://tess.elixir-uk.org/materials/finding-hidden-messages-in-dna-bioinformatics-i Named a top 50 MOOC of all time by Class Central! This course begins a series of classes illustrating the power of computing in modern biology. Please join us on the frontier of bioinformatics to look for hidden messages in DNA without ever needing to put on a lab coat. In the first half of the course, we investigate DNA replication, and ask the question, where in the genome does DNA replication begin? We will see that we can answer this question for many bacteria using only some straightforward algorithms to look for hidden messages in the genome. In the second half of the course, we examine a different biological question, when we ask which DNA patterns play the role of molecular clocks. The cells in your body manage to maintain a circadian rhythm, but how is this achieved on the level of DNA? Once again, we will see that by knowing which hidden messages to look for, we can start to understand the amazingly complex language of DNA. Perhaps surprisingly, we will apply randomized algorithms, which roll dice and flip coins in order to solve problems. Finally, you will get your hands dirty and apply existing software tools to find recurring biological motifs within genes that are responsible for helping Mycobacterium tuberculosis go "dormant" within a host for many years before causing an active infection. life-sciences, computer-science, health-informatics, algorithms 2017-10-09
Finding Mutations in DNA and Proteins (Bioinformatics VI)

In previous courses in the Specialization, we have discussed how to sequence and compare genomes. This course will cover advanced topics in finding mutations lurking within DNA and proteins. In the first half of the course, we would like to ask how an individual's genome differs from the...

Keywords: life-sciences, computer-science, health-informatics, algorithms

Finding Mutations in DNA and Proteins (Bioinformatics VI) http://tess.elixir-uk.org/materials/finding-mutations-in-dna-and-proteins-bioinformatics-vi In previous courses in the Specialization, we have discussed how to sequence and compare genomes. This course will cover advanced topics in finding mutations lurking within DNA and proteins. In the first half of the course, we would like to ask how an individual's genome differs from the "reference genome" of the species. Our goal is to take small fragments of DNA from the individual and "map" them to the reference genome. We will see that the combinatorial pattern matching algorithms solving this problem are elegant and extremely efficient, requiring a surprisingly small amount of runtime and memory. In the second half of the course, we will learn how to identify the function of a protein even if it has been bombarded by so many mutations compared to similar proteins with known functions that it has become barely recognizable. This is the case, for example, in HIV studies, since the virus often mutates so quickly that researchers can struggle to study it. The approach we will use is based on a powerful machine learning tool called a hidden Markov model. Finally, you will learn how to apply popular bioinformatics software tools applying hidden Markov models to compare a protein against a related family of proteins. life-sciences, computer-science, health-informatics, algorithms 2017-10-09
Genome Sequencing (Bioinformatics II)

You may have heard a lot about genome sequencing and its potential to usher in an era of personalized medicine, but what does it mean to sequence a genome? Biologists still cannot read the nucleotides of an entire genome as you would read a book from beginning to end. However, they can read...

Keywords: life-sciences, computer-science, health-informatics, algorithms

Genome Sequencing (Bioinformatics II) http://tess.elixir-uk.org/materials/genome-sequencing-bioinformatics-ii You may have heard a lot about genome sequencing and its potential to usher in an era of personalized medicine, but what does it mean to sequence a genome? Biologists still cannot read the nucleotides of an entire genome as you would read a book from beginning to end. However, they can read short pieces of DNA. In this course, we will see how graph theory can be used to assemble genomes from these short pieces. We will further learn about brute force algorithms and apply them to sequencing mini-proteins called antibiotics. In the first half of the course, we will see that biologists cannot read the 3 billion nucleotides of a human genome as you would read a book from beginning to end. However, they can read shorter fragments of DNA. In this course, we will see how graph theory can be used to assemble genomes from these short pieces in what amounts to the largest jigsaw puzzle ever put together. In the second half of the course, we will discuss antibiotics, a topic of great relevance as antimicrobial-resistant bacteria like MRSA are on the rise. You know antibiotics as drugs, but on the molecular level they are short mini-proteins that have been engineered by bacteria to kill their enemies. Determining the sequence of amino acids making up one of these antibiotics is an important research problem, and one that is similar to that of sequencing a genome by assembling tiny fragments of DNA. We will see how brute force algorithms that try every possible solution are able to identify naturally occurring antibiotics so that they can be synthesized in a lab. Finally, you will learn how to apply popular bioinformatics software tools to sequence the genome of a deadly Staphylococcus bacterium that has acquired antibiotics resistance. life-sciences, computer-science, health-informatics, algorithms 2017-10-09
Biology Meets Programming: Bioinformatics for Beginners

Are you interested in learning how to program (in Python) within a scientific setting? This course will cover algorithms for solving various biological problems along with a handful of programming challenges helping you implement these algorithms in Python. It offers a gently-paced introduction...

Keywords: life-sciences, computer-science, health-informatics, software-development

Biology Meets Programming: Bioinformatics for Beginners http://tess.elixir-uk.org/materials/biology-meets-programming-bioinformatics-for-beginners Are you interested in learning how to program (in Python) within a scientific setting? This course will cover algorithms for solving various biological problems along with a handful of programming challenges helping you implement these algorithms in Python. It offers a gently-paced introduction to our Bioinformatics Specialization (https://www.coursera.org/specializations/bioinformatics), preparing learners to take the first course in the Specialization, "Finding Hidden Messages in DNA" (https://www.coursera.org/learn/dna-analysis). Each of the four weeks in the course will consist of two required components. First, an interactive textbook provides Python programming challenges that arise from real biological problems. If you haven't programmed in Python before, not to worry! We provide "Just-in-Time" exercises from the Codecademy Python track (https://www.codecademy.com/learn/python). And each page in our interactive textbook has its own discussion forum, where you can interact with other learners. Second, each week will culminate in a summary quiz. Lecture videos are also provided that accompany the material, but these videos are optional. life-sciences, computer-science, health-informatics, software-development 2017-05-04
Genomic Data Science and Clustering (Bioinformatics V)

How do we infer which genes orchestrate various processes in the cell? How did humans migrate out of Africa and spread around the world? In this class, we will see that these two seemingly different questions can be addressed using similar algorithmic and machine learning techniques arising from...

Keywords: life-sciences, computer-science, health-informatics, algorithms

Genomic Data Science and Clustering (Bioinformatics V) http://tess.elixir-uk.org/materials/genomic-data-science-and-clustering-bioinformatics-v How do we infer which genes orchestrate various processes in the cell? How did humans migrate out of Africa and spread around the world? In this class, we will see that these two seemingly different questions can be addressed using similar algorithmic and machine learning techniques arising from the general problem of dividing data points into distinct clusters. In the first half of the course, we will introduce algorithms for clustering a group of objects into a collection of clusters based on their similarity, a classic problem in data science, and see how these algorithms can be applied to gene expression data. In the second half of the course, we will introduce another classic tool in data science called principal components analysis that can be used to preprocess multidimensional data before clustering in an effort to greatly reduce the number dimensions without losing much of the "signal" in the data. Finally, you will learn how to apply popular bioinformatics software tools to solve a real problem in clustering. life-sciences, computer-science, health-informatics, algorithms 2017-10-09
Comparing Genes, Proteins, and Genomes (Bioinformatics III)

Once we have sequenced genomes in the previous course, we would like to compare them to determine how species have evolved and what makes them different. In the first half of the course, we will compare two short biological sequences, such as genes (i.e., short sequences of DNA) or proteins. We...

Keywords: life-sciences, computer-science, health-informatics, algorithms

Comparing Genes, Proteins, and Genomes (Bioinformatics III) http://tess.elixir-uk.org/materials/comparing-genes-proteins-and-genomes-bioinformatics-iii Once we have sequenced genomes in the previous course, we would like to compare them to determine how species have evolved and what makes them different. In the first half of the course, we will compare two short biological sequences, such as genes (i.e., short sequences of DNA) or proteins. We will encounter a powerful algorithmic tool called dynamic programming that will help us determine the number of mutations that have separated the two genes/proteins. In the second half of the course, we will "zoom out" to compare entire genomes, where we see large scale mutations called genome rearrangements, seismic events that have heaved around large blocks of DNA over millions of years of evolution. Looking at the human and mouse genomes, we will ask ourselves: just as earthquakes are much more likely to occur along fault lines, are there locations in our genome that are "fragile" and more susceptible to be broken as part of genome rearrangements? We will see how combinatorial algorithms will help us answer this question. Finally, you will learn how to apply popular bioinformatics software tools to solve problems in sequence alignment, including BLAST. life-sciences, computer-science, health-informatics, algorithms 2017-10-09
Molecular Evolution (Bioinformatics IV)

In the previous course in the Specialization, we learned how to compare genes, proteins, and genomes. One way we can use these methods is in order to construct a "Tree of Life" showing how a large collection of related organisms have evolved over time. In the first half of the course, we will...

Keywords: life-sciences, computer-science, health-informatics, algorithms

Molecular Evolution (Bioinformatics IV) http://tess.elixir-uk.org/materials/molecular-evolution-bioinformatics-iv In the previous course in the Specialization, we learned how to compare genes, proteins, and genomes. One way we can use these methods is in order to construct a "Tree of Life" showing how a large collection of related organisms have evolved over time. In the first half of the course, we will discuss approaches for evolutionary tree construction that have been the subject of some of the most cited scientific papers of all time, and show how they can resolve quandaries from finding the origin of a deadly virus to locating the birthplace of modern humans. In the second half of the course, we will shift gears and examine the old claim that birds evolved from dinosaurs. How can we prove this? In particular, we will examine a result that claimed that peptides harvested from a T. rex fossil closely matched peptides found in chickens. In particular, we will use methods from computational proteomics to ask how we could assess whether this result is valid or due to some form of contamination. Finally, you will learn how to apply popular bioinformatics software tools to reconstruct an evolutionary tree of ebolaviruses and identify the source of the recent Ebola epidemic that caused global headlines. life-sciences, computer-science, health-informatics, algorithms 2017-10-09