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Keywords: computer-science  or Python biologists 


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
Python programming primer

The purpose of this training is to teach general programming concepts using Python as an instruction tool. Topics: Introduction to Python: basic principles. Python data structures: strings, tuples, lists, dictionaries, sets. Object-oriented programming: how to model coffee machines in Python...

Scientific topics: Software engineering

Keywords: Python biologists

Python programming primer http://tess.elixir-uk.org/materials/python-programming-primer The purpose of this training is to teach general programming concepts using Python as an instruction tool. Topics: Introduction to Python: basic principles. Python data structures: strings, tuples, lists, dictionaries, sets. Object-oriented programming: how to model coffee machines in Python :-). Inheritance (base and derived classes), polymorphism. Write your own script to convert BED files to GFF. Command-line option processing, file I/O, error handling. Software engineering Python biologists 2016-04-21 2017-10-09
Introduction to Biopython

This is a module from the "Python for Biologists" course. The module presents an introduction to Biopython. It shows how to deal with sequences and sequence records, how to download records from NCBI databases, how to run Blast and how to parse XML Blast outputs.

Keywords: Bioinformatics, Biopython, Programming, Python, Python biologists

Introduction to Biopython http://tess.elixir-uk.org/materials/introduction-to-biopython This is a module from the "Python for Biologists" course. The module presents an introduction to Biopython. It shows how to deal with sequences and sequence records, how to download records from NCBI databases, how to run Blast and how to parse XML Blast outputs. Bioinformatics, Biopython, Programming, Python, Python biologists Biologists Biologists, Genomicists, Computer Scientists bioinformaticians 2013-11-04 2017-10-09
Python @ TGAC - Python for Life Scientists: Managing biological data with Python

Python is an object-oriented programming language that is ideal for biological data analysis. The course will start with very basic language concepts and instructions and will cover all the main language aspects, including variables, types, modules, functions, exceptions, control of flux, input,...

Keywords: Biopython, Python, Python biologists

Python @ TGAC - Python for Life Scientists: Managing biological data with Python http://tess.elixir-uk.org/materials/python-tgac-python-for-life-scientists-managing-biological-data-with-python Python is an object-oriented programming language that is ideal for biological data analysis. The course will start with very basic language concepts and instructions and will cover all the main language aspects, including variables, types, modules, functions, exceptions, control of flux, input, output, and classes. All the examples and practical sessions will focus on solving particular biological problems. In particular, examples and practical sessions will cover: Working with DNA and protein sequences Data retrieval from files and their manipulation Running applications, such as BLAST, locally and from a script Finding motifs in sequences Parsing Swiss-Prot files, PDB files, ENSEMBL records, blast output files, etc. Biopython will be also introduced and applied to some of the mentioned examples. The course is meant to be highly interactive and the students will continuously put theory into practice while learning. By the end of the course, the students will have a good understanding of Python basics and will have acquired the skills to manage any type of bioinformatics record and to run applications from scripts. Unix/Linux basic skills will be provided at the beginning of the course. Biopython, Python, Python biologists PhD post-docs 2015-07-14 2017-10-09
Using R with Python

This is a module from the "Python for Biologists" course. It describes the Python module interfacing the R package for statistics. The module shows how to calculate mean, standard deviation, z-score and p-value of a set of numbers, and how to generate plots. Input files for the scripts presented...

Keywords: Programming, Python, Python biologists

Using R with Python http://tess.elixir-uk.org/materials/using-r-with-python This is a module from the "Python for Biologists" course. It describes the Python module interfacing the R package for statistics. The module shows how to calculate mean, standard deviation, z-score and p-value of a set of numbers, and how to generate plots. Input files for the scripts presented are also provided. Programming, Python, Python biologists Biologists Biologists, Genomicists, Computer Scientists beginner bioinformaticians bioinformaticians 2013-11-04 2017-10-09
Searching data using Python

This is a module from the "Python for Biologists" course. It describes how to use Python dictionary and set data structures to search your data. In particular, how to use a dictionary to represent the genetic code table and use it to translate a nucleotide sequence into a protein sequence, and...

Keywords: Programming, Python, Python biologists

Searching data using Python http://tess.elixir-uk.org/materials/searching-data-using-python This is a module from the "Python for Biologists" course. It describes how to use Python dictionary and set data structures to search your data. In particular, how to use a dictionary to represent the genetic code table and use it to translate a nucleotide sequence into a protein sequence, and how to use sets to find unique records in two datasets and remove redundancy.  Programming, Python, Python biologists Biologists Biologists, Genomicists, Computer Scientists beginner bioinformaticians 2013-11-04 2017-10-09
Pattern Matching

This is a module from the "Python for Biologists" course. It teaches how to do pattern matching in Python, i.e. how to find a substring (or a set of substrings) in a string. To this aim, it introduces the regular expression syntax, and the tools needed to search regular expressions in biological...

Keywords: Pattern matching, Programming, Python, Python biologists

Pattern Matching http://tess.elixir-uk.org/materials/pattern-matching This is a module from the "Python for Biologists" course. It teaches how to do pattern matching in Python, i.e. how to find a substring (or a set of substrings) in a string. To this aim, it introduces the regular expression syntax, and the tools needed to search regular expressions in biological sequences and in regular text, such as PubMed abstracts. Exercises and suggested solutions are presented in a separate file. Pattern matching, Programming, Python, Python biologists Biologists Biologists, Genomicists, Computer Scientists beginner bioinformaticians 2013-11-04 2017-10-09
Writing functions in Python programming

This is a module from the "Python for Biologists" course. It deals with functions and how to write and use them. It also introduces namespaces and the tuple data structure. The module contains several exercises and suggested solutions. The text of exercises is also provided in a separate file. 

Scientific topics: Bioinformatics

Keywords: Programming, Python, Python biologists

Writing functions in Python programming http://tess.elixir-uk.org/materials/writing-functions-in-python-programming This is a module from the "Python for Biologists" course. It deals with functions and how to write and use them. It also introduces namespaces and the tuple data structure. The module contains several exercises and suggested solutions. The text of exercises is also provided in a separate file.  Bioinformatics Programming, Python, Python biologists Biologists Biologists, Genomicists, Computer Scientists beginner bioinformaticians 2013-11-04 2017-10-09
Python Programs

This is a module from the "Python for Biologists" course. It deals with Python programs, how to write and run them, and how to provide input and generate output. The module also contains exercises and suggested solutions. 

Keywords: Programming, Python, Python biologists

Python Programs http://tess.elixir-uk.org/materials/python-programs This is a module from the "Python for Biologists" course. It deals with Python programs, how to write and run them, and how to provide input and generate output. The module also contains exercises and suggested solutions.  Programming, Python, Python biologists Biologists Biologists, Genomicists, Computer Scientists beginner bioinformaticians 2013-11-04 2017-10-09
Parsing data records using Python programming

This is a module from the "Python for Biologists" course. One typical problem in bioinformatics is parsing data files. This module explains how to parse FASTA files and GenBank records. It also introduces the if/elif/else construct to make choice in programming and the list  data structure. The...

Keywords: Bioinformatics, Programming, Python, Python biologists, Record parsing

Parsing data records using Python programming http://tess.elixir-uk.org/materials/parsing-data-records-using-python-programming This is a module from the "Python for Biologists" course. One typical problem in bioinformatics is parsing data files. This module explains how to parse FASTA files and GenBank records. It also introduces the if/elif/else construct to make choice in programming and the list  data structure. The text of exercises is provided in a separate file.  Bioinformatics, Programming, Python, Python biologists, Record parsing Biologists beginner bioinformaticians bioinformaticians programmers 2013-07-05 2017-10-09