Ir al contenido principal

Dynamic Programming: Applications In Machine Learning and Genomics

Learn how dynamic programming and Hidden Markov Models can be used to compare genetic strings and uncover evolution.
Dynamic Programming: Applications In Machine Learning and Genomics

Hay una sesión disponible:

¡Ya se inscribieron 8,772! Una vez finalizada la sesión del curso, será archivado.
Comienza el 24 sept
4 semanas estimadas
8–10 horas por semana
A tu ritmo
Avanza a tu ritmo
Gratis
Cambio opcional de categoría disponible

Sobre este curso

Omitir Sobre este curso

If you look at two genes that serve the same purpose in two different species, how can you rigorously compare these genes in order to see how they have evolved away from each other?

In the first part of the course, part of the Algorithms and Data Structures MicroMasters program, we will see how the dynamic programming paradigm can be used to solve a variety of different questions related to pairwise and multiple string comparison in order to discover evolutionary histories.

In the second part of the course, we will see how a powerful machine learning approach, using a Hidden Markov Model, can dig deeper and find relationships between less obviously related sequences, such as areas of the rapidly mutating HIV genome.

De un vistazo

  • Institución: UCSanDiegoX
  • Tema: Informática
  • Nivel: Intermediate
  • Prerrequisitos:

    Basic knowledge of:

    • at least one programming language: loops, arrays, stacks, recursion.
    • mathematics: proof by induction, proof by contradiction.

Lo que aprenderás

Omitir Lo que aprenderás
  • Dynamic programming and how it applies to basic string comparison algorithms
  • Sequence alignment, including how to generalize dynamic programming algorithms to handle different cases
  • Hidden markov models
  • How to find the most likely sequence of events given a collection of outcomes and limited information
  • Machine learning in sequence alignment

Plan de estudios

Omitir Plan de estudios

Week 1: Pairwise Sequence Alignment
A review of dynamic programming, and applying it to basic string comparison algorithms.

Week 2: Advanced Sequence Alignment
Learn how to generalize your dynamic programming algorithm to handle a number of different cases, including the alignment of multiple strings.

Week 3: Introduction to Hidden Markov Models
Learn what a Hidden Markov model is and how to find the most likely sequence of events given a collection of outcomes and limited information.

Week 4: Machine Learning in Sequence Alignment
Formulate sequence alignment using a Hidden Markov model, and then generalize this model in order to obtain even more accurate alignments.

Testimonios de los estudiantes

Omitir Testimonios de los estudiantes
“This is an extraordinary course. It requires commitment and a fair amount of time, but this is what implies the approach of guiding students step-by-step to implement themselves the algorithms. In my opinion, this is the best way to fully understand how algorithms work.”
-- Previous Student

Acerca de los instructores

¿Quién puede hacer este curso?

Lamentablemente, las personas residentes en uno o más de los siguientes países o regiones no podrán registrarse para este curso: Irán, Cuba y la región de Crimea en Ucrania. Si bien edX consiguió licencias de la Oficina de Control de Activos Extranjeros de los EE. UU. (U.S. Office of Foreign Assets Control, OFAC) para ofrecer nuestros cursos a personas en estos países y regiones, las licencias que hemos recibido no son lo suficientemente amplias como para permitirnos dictar este curso en todas las ubicaciones. edX lamenta profundamente que las sanciones estadounidenses impidan que ofrezcamos todos nuestros cursos a cualquier persona, sin importar dónde viva.

¿Te interesa este curso para tu negocio o equipo?

Capacita a tus empleados en los temas más solicitados con edX para Negocios.