About this Programa de cursos integrados
cursos 100% online

cursos 100% online

Comece imediatamente e aprenda em seu próprio cronograma.
Cronograma flexível

Cronograma flexível

Definição e manutenção de prazos flexíveis.
Nível iniciante

Nível iniciante

Horas para completar

Aprox. 11 meses para completar

3 horas/semana sugeridas
Idiomas disponíveis

Inglês

Legendas: Inglês, Chinês (simplificado)...

Habilidades que você terá

Whole Genome SequencingViterbi AlgorithmSuffix TreePython ProgrammingAlgorithmsUnweighted Pair Group Method with Arithmetic Mean (UPGMA)Bioinformatics
cursos 100% online

cursos 100% online

Comece imediatamente e aprenda em seu próprio cronograma.
Cronograma flexível

Cronograma flexível

Definição e manutenção de prazos flexíveis.
Nível iniciante

Nível iniciante

Horas para completar

Aprox. 11 meses para completar

3 horas/semana sugeridas
Idiomas disponíveis

Inglês

Legendas: Inglês, Chinês (simplificado)...

How the Programa de cursos integrados Works

Fazer cursos

Um programa de cursos integrados do Coursera é uma série de cursos para ajudá-lo a dominar uma habilidade. Primeiramente, inscreva-se no programa de cursos integrados diretamente, ou avalie a lista de cursos e escolha por qual você gostaria de começar. Ao se inscrever em um curso que faz parte de um programa de cursos integrados, você é automaticamente inscrito em todo o programa de cursos integrados. É possível concluir apenas um curso — você pode pausar a sua aprendizagem ou cancelar a sua assinatura a qualquer momento. Visite o seu painel de aprendiz para controlar suas inscrições em cursos e progresso.

Projeto prático

Todos os programas de cursos integrados incluem um projeto prático. Você precisará completar com êxito o(s) projeto(s) para concluir o programa de cursos integrados e obter o seu certificado. Se o programa de cursos integrados incluir um curso separado para o projeto prático, você precisará completar todos os outros cursos antes de iniciá-lo.

Obtenha um certificado

Ao concluir todos os cursos e completar o projeto prático, você obterá um certificado que pode ser compartilhado com potenciais empregadores e com sua rede profissional.

how it works

Este Programa de cursos integrados contém 7 cursos

Curso1

Finding Hidden Messages in DNA (Bioinformatics I)

4.7
367 classificações
81 avaliações
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....
Curso2

Genome Sequencing (Bioinformatics II)

4.8
158 classificações
34 avaliações
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....
Curso3

Comparing Genes, Proteins, and Genomes (Bioinformatics III)

4.7
72 classificações
16 avaliações
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....
Curso4

Molecular Evolution (Bioinformatics IV)

4.5
39 classificações
11 avaliações
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....

Instrutores

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Pavel Pevzner

Professor
Department of Computer Science and Engineering
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Phillip Compeau

Visiting Researcher
Department of Computer Science & Engineering
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Nikolay Vyahhi

Visiting Scholar
Department of Computer Science and Engineering

Sobre University of California San Diego

UC San Diego is an academic powerhouse and economic engine, recognized as one of the top 10 public universities by U.S. News and World Report. Innovation is central to who we are and what we do. Here, students learn that knowledge isn't just acquired in the classroom—life is their laboratory....

Perguntas Frequentes – FAQ

  • Sim! Para começar, clique na carta de curso que lhe interessa e se inscreva. Você pode se inscrever e concluir o curso para ganhar um certificado compartilhável ou você pode auditar para ver os materiais do curso de graça. Quando você se inscrever em um curso que faz parte de uma especialização, você está automaticamente inscrito para a especialização completa. Visite o seu painel de aluno para acompanhar o seu progresso.

  • Este curso é totalmente on-line, então não existe necessidade de aparecer em uma sala de aula pessoalmente. Você pode acessar suas palestras, leituras e atribuições a qualquer hora e qualquer lugar, via web ou dispositivo móvel.

  • Esta Especialização não carrega créditos universitários, mas algumas universidades podem optar por aceitar certificados de especialização como crédito. Verifique com sua instituição para saber mais.

  • The print companion accompanying the Specialization is Bioinformatics Algorithms: An Active Learning Approach (Vols. 1 and 2).

  • Time to completion can vary based on your schedule, but most learners are able to complete the Specialization in 4-6 months.

  • We require only a basic knowledge of high school-level biology and the ability to think technically.

  • We recommend taking the courses in the order presented, as each subsequent course will build on material from previous courses.

  • You will understand the ideas behind many different software tools that are used every day by biotech researchers, and you will know how to apply these tools to real datasets.

Mais dúvidas? Visite o Central de Ajuda ao Aprendiz.