This is a summary which includes an overview of the (online) lecture material, papers provided and all chapters from the course manual which were discussed.
It even includes drawings and some extra definiton list.
Week 1 Introduction to Systems Biology – Introduction 3
Practical 3
Week 2 3
Practical Top-down Systems Biology 3
Lecture Big Data 5
Week 3 + 4 6
Practical Cellular composition and time scales 6
Lecture Molecular processing in cells 8
Week 5 + 6 9
Practical Kinetics of biochemical reactions 9
Lecture State analysis 10
Week 7 13
Practical Chapter 4: Signal Transduction 13
Lecture Signalling 15
Exercise class quiz content 17
, Lectures + Chapters + Papers
Week 1 Introduction to Systems Biology – Introduction
Practical
Dynamics: set of elements actions/interactions that give change or movement to a system.
Dynamics: change with respect to something.
So a dynamical model is a model that represents these interactions.
Network structure: explanation of which exact molecules have what kind of interactions. Their
number and nature also give extra information.
Parameter: a property of a certain component of a system. So for an enzyme a parameter is
molecular rate for example. E.g. the initial concentration of glucose is the parameter. The
concentration at a certain timepoint is a variable
Variable: something you can measure and change (like cell size, volume etc.)
Metabolic network: network of interconversions between different molecules.
What problems can systems biology solve? Systems approaches allows you to solve more than only
the specific problem you work on.
Week 2
Practical Top-down Systems Biology
Principle component analysis: calculating interesting projections based on variance maximization in
a system of perpendicular axes. Start with a first principal component, an axis along which the data
has the highest variance, then go on to as many axis (perpendicular to the previous one) as variables.
t-SNE is a non-deterministic alternative for PCA. This method derives distance from the distribution
of the data.
Statistical learning
Supervised learning: learning from data by using additional knowledge about the data, with the aim
of making predictions about samples collected in the future having unknown properties. A second
goal is finding these variables either alone or in combination.
Common techniques are: principal component analysis, hierarchical- and k-means clustering.
Un-supervised learning: learning from data without using any additional knowledge about the
samples to which the data apply.
There are different ‘distances’ used in clustering or finding structures.
- Euclidian distance: the distance measured along a straight line between objects.
In 2D the Euclidian distance 𝐷𝑒 (𝑥, 𝑦) between two points 𝑥 = (𝑥1 , 𝑥2 ) and 𝑦 = (𝑦1 , 𝑦2 ) is
calculated as: 𝐷𝑒 (𝑥, 𝑦) = √(𝑥1 − 𝑦1 )2 + (𝑥2 − 𝑦2 )2
- Base pair difference: the number of differences in homologous sequences of DNA.
Hamming distance: number of differences in strings of characters in general.
Jukes-Cantor distance: a metric to quantify DNA differences.
- Distance between communities of species: often used when interested in causes and effects
of differences in distribution of species in an ecosystem. Two ways to calculate the distance
between distributions:
Voordelen van het kopen van samenvattingen bij Stuvia op een rij:
Verzekerd van kwaliteit door reviews
Stuvia-klanten hebben meer dan 700.000 samenvattingen beoordeeld. Zo weet je zeker dat je de beste documenten koopt!
Snel en makkelijk kopen
Je betaalt supersnel en eenmalig met iDeal, creditcard of Stuvia-tegoed voor de samenvatting. Zonder lidmaatschap.
Focus op de essentie
Samenvattingen worden geschreven voor en door anderen. Daarom zijn de samenvattingen altijd betrouwbaar en actueel. Zo kom je snel tot de kern!
Veelgestelde vragen
Wat krijg ik als ik dit document koop?
Je krijgt een PDF, die direct beschikbaar is na je aankoop. Het gekochte document is altijd, overal en oneindig toegankelijk via je profiel.
Tevredenheidsgarantie: hoe werkt dat?
Onze tevredenheidsgarantie zorgt ervoor dat je altijd een studiedocument vindt dat goed bij je past. Je vult een formulier in en onze klantenservice regelt de rest.
Van wie koop ik deze samenvatting?
Stuvia is een marktplaats, je koop dit document dus niet van ons, maar van verkoper lenie22. Stuvia faciliteert de betaling aan de verkoper.
Zit ik meteen vast aan een abonnement?
Nee, je koopt alleen deze samenvatting voor €7,74. Je zit daarna nergens aan vast.
