Bioinformatics
Keywords |
Classification |
Keyword |
OFICIAL |
Molecular Biotechnology |
Instance: 2018/2019 - 1S
Cycles of Study/Courses
Acronym |
No. of Students |
Study Plan |
Curricular Years |
Credits UCN |
Credits ECTS |
Contact hours |
Total Time |
MIB |
20 |
Syllabus |
5 |
- |
6 |
42 |
162 |
Teaching language
Portuguese
Objectives
The course educates students in:
- what are and how can we access the majer Web resources in this area
- what are the key algorithms used by the fundamental tools, and what are the the corresponding algorithms,
- INtroduce students to data analysis
Learning outcomes and competences
The student should be able to successfully:
- program scripts on the access and manipulation of biological dsts.
-have critical understand of available tools
- be able to folow major developments in the area.
Working method
Presencial
Program
1. Molecular Evolution
Basic Concepts
Phylogenetics
Biiological Data Bases
Algorithms in:
Pairwise Alignment
Multiple Alignment
Phylogenetic Trees
Gene Expression.
Mandatory literature
ULL;
Computational statistics & data analysis
Teaching methods and learning activities
Classes include
a. form presentation
b. example basic discusssion
c, practical work, including a monography.
keywords
Natural sciences > Biological sciences > Biology > Computational biology
Evaluation Type
Distributed evaluation with final exam
Assessment Components
Designation |
Weight (%) |
Participação presencial |
25,00 |
Exame |
75,00 |
Total: |
100,00 |
Amount of time allocated to each course unit
Designation |
Time (hours) |
Estudo autónomo |
|
Frequência das aulas |
|
Total: |
0,00 |
Eligibility for exams
The students are required to attend classes, and participate in discussion of scientific work.
Calculation formula of final grade
P1 = EX (MAX 5V) + HOMEWORK (5V)
P2 = EX (MAX 10V)