We give advanced courses on many different aspects of computer science, mathematics, and computational systems biology. Here is the list of our latest courses, including lecture notes, exercises, and student projects.
Teaching
2018 – Computability and computational complexity
Description: Computability is the area of computer science that investigates computation as its main subject of interest: what is computation, how can a computation be carried out, why some problems are impossible to solve by computers, why some problems are difficult to solve, what degrees of difficulty are there. This field that was virtually inexistent some …
2018 – Advanced Text Algorithms
Description Text algorithms are essential in many areas of science and information processing. Very often the information is represented as a written text in the form of, e.g., newspapers, books, computer hard-drives, optical disks, the genetic information of living organisms, etc. Specific text algorithms are needed when processing the information, whether in text editors or …
2017 – Graph Algorithms
Description In mathematics and computer science, graph theory is the study of graphs, which are mathematical structures used to model pairwise relations between objects. One can “observe graphs” everywhere. Virtually, any field of science, industry, commerce, politics, social life, etc. contains numerous cases of relations and processes that could be naturally represented in terms of …
2017 – Cryptography and Network Security
SPRING 2017 Description We cover in this course principles and practice of cryptography and network security: classical systems, symmetric block ciphers (DES, AES, other contemporary symmetric ciphers), linear and differential cryptanalysis, perfect secrecy, public-key cryptography (RSA, discrete logarithms), algorithms for factoring and discrete logarithms, cryptographic protocols, hash functions, authentication, key management, key exchange, signature schemes, …
2016 – Stochastic Biomodelling
Lecturer: Andrzej Mizera Content Introduction Stochasticity in biological processes Prerequisite Crash course on probability theory Stochastic modelling of chemical kinetics The chemical master equation (CME) Stochastic simulation of the CME Gillespie’s direct method algorithm Practicals Implementing the Gillespie’s algorithm in Matlab and demonstrating its characteristics on various biochemical systems; comparing the obtained simulation results with the solutions in …
2015 – Special course in Computer Science: Molecular Computing
Fall, Period 1, 2015 Description During this course we will discuss a novel fast developing interdisciplinary area called Molecular Computing and will consider both its theoretical and experimental aspects. In this area biological systems and living organisms are regarded from the Computer Science perspective, molecular-scale biological processes are considered as computations, manipulations with biologically derived materials …
2015 – Introduction to Natural Computing
Grenoble, France, November 2015 Major objective of the course is to present an overview of a novel fast developing interdisciplinary area called “Natural Computing”. The aim is to introduce to the students new computational paradigms and methods inspired by Nature as well as to demonstrate how Mathematics, Computers Science, Information Technologies can be used to …
2015 – Introduction to computational and systems biology
Period 1, 2015-2016 (456511.0) Description This course aims to give an introduction to the broad field of computational and systems biology. The course takes a computer science perspective on the field, focusing on the algorithmic and computational challengens and opportunities in this area. We discuss in the course four main topics: Algorithms in computational biology …
2014 – Computational modeling techniques
Period 1, 2014-2015 (456402.0) Description This course aims to provide an introduction to the entire computational modeling process, from the formulation of a qualitative model, to its quantitative formulation, to model fitting and validation, model analysis, and model predictions. We focus on the various computational methods that can be employed for modeling and especially on …
2014 – Advanced computational modeling
Period 2, 2014-2015 (456513.0) NEW: The course booklet, containing the reports from all teams, is now available here. Description: This course builds onto the introductory Computational modeling techniques course. It aims to provide a deeper view into several computational modeling techniques. We discuss in the course modeling with stochastic processes, with Petri nets and with rule-based systems. We …
2010 – Computational processes in living cells
Spring term 2010 (456507.0) Description Viewed as information processing systems, biological organisms possess amazing capabilities to perform information-handling tasks such as: control, pattern recognition, adaptability, information-storage, etc. Thus, the functioning of biological organisms as information-processing systems is of great interest to computer scientists, and we are witnessing now a fast growing research in this field. …
2004 – Introduction to Biocomputing
(M537, G637) (This course is listed also in the Department of Information Technology and Bioinformatics Laboratory, University of Turku, under the name “Fundamentals of Bioinformatics – Sequence analysis”) Description Research at the border of Molecular Biology and Information Technology has witnessed in recent years an exciting development, with remarkable benefits for both areas. On one hand, biological data is …