Brainscape's Knowledge GenomeTM

Browse over 1 million classes created by top students, professors, publishers, and experts.


See full index

Systems Biology > Systems Biology Final exam > Flashcards

Systems Biology Final exam Flashcards

You may prefer our related Brainscape-certified flashcards:
AP® Biology flashcards Biology 101 flashcards
1
Q

Systems biology involves

A
  • collection of experimental data
  • mathematical models
  • computer simulations
  • validation with additional experimental data
    (all of the above)
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

Which of the simulations have emergent properties?

A

Conway’s game of life

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

Which of the following is true regarding systems biology?

A

Can study systems that have feedforward interactions

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

What is cybernetics?

A

The scientific study of control and communication in animals and machines

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

Why the properties of systems cannot be fully understood merely by drawing diagrams of their interactions?

A

You do not get the qualitative interactions or the details of the interactions

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

Which of the following is true regarding the deterministic models?

A
  • the same input and parameters always produce the same output
  • they can have complex dynamics
  • they can be hard to predict without simulations
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

Sensitivity analysis

A

studies how change in parameters change behavior

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

What advancements have permitted the recent success of systems biology?

A
  • increased computational power
  • advances on analysis of complex systems
  • development of quantitative biology techniques
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

What are S, I, and R?

A

variables

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

Which of the following properties is true in a scale free network?

A

Each node can be reached from any other node through a short path

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

Select the coherent feed forward loops

A

coherent feed loops have the same output (+/+ or + for example) no matter which path you take

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

What are network motifs?

A

Patterns that are seen in biological systems more often then in random networks

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

Double negative feedback loops have what basal level for a and b

A

Both high

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

What is a bistable system?

A

a system with two stable equilibrium states

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

In the context of biological systems what is robustness?

A

The ability to maintain biological functions despite perturbations

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

What are modular networks?

A

Networks that contain densely connected functional subunits sparsely connected between them

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
17
Q

Modularity can emerge as a result of

A

selective forces to maximize the performance and minimize the cost of interconnections in a network

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

What are the kinetic assumptions needed for applying the law of mass action?

A
  • fixed volume
  • reaction volume is well stirred
  • individual reaction events cause infinitesimal changes in concentration
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q

If you need to model spatial pattern in a developing embryo what would be the most appropriate mathematical formalism to use?

A

PDE

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
20
Q

In a dynamical system what is bifurcation?

A

A qualitative change in the behavior of the system due to a change in the parameters

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
21
Q

What type of systems are used for Turing’s reaction diffusion equation?

A

spatial patterns

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
22
Q

What do we need to discretize for solving PDEs numerically?

A

time and space

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
23
Q

Which of the following statements are true regarding parameter estimation with non linear regression?

A
  • multiple solutions are possible
  • heuristic methods are available for finding parameters close to the optimal
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
24
Q

Evolutionary algorithms can be used for parameter estimation and reverse engineering of models. What type of optimization algorithm is an evolutionary algorithm?

A

probabilistic search with multiple elements

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
25
Q

If we need to model a stochastic system with discrete number of molecule which of the following modeling approaches can we use?

A

Gillespie algorithm

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
26
Q

Is noise beneficial or detrimental

A

both

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
27
Q

Assuming the gene regulatory signals are not modeling but considered inputs of the systems where does the noise come from in the following system

A

extrinsic noise

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
28
Q

The following is a Lotka-Volterra predator prey system. What variables represent the number of predators in the population

A

y

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
29
Q

What does the population in an evolutionary algorithm contain?

A

a set of candidate models

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
30
Q

What does the fitness quantify in an evolutionary algorithm?

A

how close the simulation is to the experimental data

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
31
Q

What type of equations are used in the following model?

A

ODEs

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
32
Q

What is an emergent property?

A

a characteristic of a system that arises from complex interactions among its components rather than being directly attributable to any

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
33
Q

What other reason beyond high throughput data has allowed the application of systems biology?

A

increased computational power

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
34
Q

Why does clustering analysis not reveal causality of regulatory relationships?

A

because correlation does not imply causation

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
35
Q

What are some examples of abstraction levels in systems biology?

A
  • molecular scale
  • ecosystem scale
  • tissue scale
  • organism scale
  • cellular scale
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
36
Q

When does modeling become necessary?

A

when intuition reaches its limits

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
37
Q

Do simple systems have intuitive emergent properties?

A

no, they have non intuitive emergent properties

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
38
Q

What do transcription factors do?

A

proteins that regulate gene transcription

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
39
Q

What did Alan Turing suggest about patterns in nature?

A

certain patterns could be explained through interaction of reaction diffusion

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
40
Q

What 4 types of things do you need to create a model?

A
  • scope
  • data
  • qualitative information
  • feasibility of model
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
41
Q

What is a correlative model?

A

given x values, model predicts y values, but doesn’t explain why

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
42
Q

What is an explanatory model?

A

shows correlation between groups

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
43
Q

What is a static model?

A

no changes over time

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
44
Q

What is a dynamic model?

A

changes over time

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
45
Q

What is a deterministic model?

A
  • no random variables
  • same input
  • parameters produce same output
  • hard to predict
  • complex dynamics
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
46
Q

What is a stochastic model?

A
  • random variables
  • same input
  • parameters produce different outputs
  • results make sense
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
47
Q

What are 4 things used to design a model?

A
  • variables
  • parameters
  • constants
  • interactions
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
48
Q

What do model diagnostics help with?

A

showing what is wrong with the model

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
49
Q

What does model analysis do?

A

explains model behaviors

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
50
Q

What does stability on a graph represent?

A

reaching a steady state

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
51
Q

What does sensitivity on a graph represent?

A

how parameter changes can change behavior

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
52
Q

Explain the paradox that the more facts we learn the less we understand the process

A

the more info you have on a topic, the more difficult it is to understand its complexity

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
53
Q

What are characteristics of the languages used by engineers in comparison with the languages usually used by biologists?

A

engineering languages are standard and quantitative

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
54
Q

What are randomized networks?

A

the nodes in networks with random links are connected with equal probability

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
55
Q

What are biological networks?

A

nodes are not connected with equal probability

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
56
Q

What are properties of biological networks?

A
  • connection sparsity
  • distribution of connections
  • hubs
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
57
Q

What is a network motif

A

a recurring structural feature of a network or system that is found more often than one would expect in a corresponding randomly composed system

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
58
Q

Where are network motifs found

A
  • internet networks
  • biochemical networks
  • ecological networks
  • electronic circuits
  • neural networks
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
59
Q

What could be the bi-parallel motif indicate in food webs

A

two species that are predators to the same prey, have the same predator

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
60
Q

What is bistability

A

when there are 2 stable steady states in a system

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
61
Q

Steady state

A

system does not change

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
62
Q

Stable steady state

A

system returns after small perturbation

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
63
Q

Insatiable steady state

A

system diverges after a small perturbation

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
64
Q

Is a feedback loop necessary or sufficient for bi stability or memory

A
  • bi stability - necessary but not sufficient
  • memory - necessary and sufficient
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
65
Q

Is positive autoregulation bistable

A

it can be

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
66
Q

Linear autoregulation

A

one instable steady state

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
67
Q

Sensitive autoregulation

A

one stable steady state, one instable steady state

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
68
Q

Ultrasensitive autoregulation

A

two stable steady states, one instable steady state

69
Q

What can biological switches do

A

provide memory

70
Q

In the absence of regulation, how do RNA and proteins react vs genes

A

RNA/proteins - decay
genes - high basal levels

71
Q

Randomized network

A

nodes in network with random links are connected with equal probability

72
Q

Biological netwokr

A

nodes in biological interactions that are not connected with equal probability

73
Q

Connection sparsity

A

only a very small portion of all possible edges are formed

74
Q

Distribution of biological networks

A

power law distribution of connections or scale free network

75
Q

Hubs

A

nodes with a high number of connections

76
Q

Scale free network have

A

small world behavior

77
Q

Negative auto regulation

A

stronger promoter -> fast response, controlled steady state

78
Q

Bistability and memory

A
  • switches can provide memory
  • response is history dependent
79
Q

Design principles that are prevalent in dynamic biological systems

A
  • network motifs
  • modularity
  • robustness
  • redundancy
80
Q

Components in chemical reaction

A
  • molecular species
  • ions
81
Q

Interactions

A
  • chemical binding and unbinding
  • reaction catalysis
  • regulation of activity
82
Q

Rates of interactions depend of

A
  • concentration of reactants
  • physio chemical conditions
83
Q

Kinetic modeling assumptions

A
  • spatial homogeneity
  • continuum hypothesis
  • Law of mass action
84
Q

Equations in kinetic modeling

A

ODEs

85
Q

intrinsic noise

A
  • from probabilistic character
  • particularly important with low numbers of reacting molecules
  • inherent to the dynamics of any genetic or biochemical system
86
Q

Extrinsic noise

A

from random fluctuations in environmental parameters

87
Q

Modeling of stochastic systems

A
  • Langevin approach
  • Gillespie algorithm
88
Q

Parameter estimation for linear systems

A

the exact solution can be calculated analytically by linear regression

89
Q

Parameter estimation for non linear systems

A

linear regression can also be used for some nonlinear functions if they permit a mathematical transformation to make them

90
Q

Parameter in linear regression

A
  • one function gits best the data
  • analytical methods for finding the optimal parameters
  • solution is unique
91
Q

Parameter estimation in non linear regression

A
  • infinite function data perfectly
  • no simple methods for finding the optimal parameters
  • multiple solutions possible
92
Q

Steady state

A

a state in which the system does not change

93
Q

Stable steady state

A

a steady state in which the system returns after a small perturbation

94
Q

Instable steady state

A

a steady state in which the system diverges after a small perturbation

95
Q

Are there design principles that are prevalent in dynamic biological systems?

A
  • network motifs
  • modularity
  • robustness
  • redundancy
96
Q

Robustness

A

the ability to maintain biological function despite perturbations

97
Q

modeling chemical reaction networks

A
  • components
  • interactions
  • rates of interactions
98
Q

Spatial homogeneity

A
  • reaction is well stirred
  • reactants equally distributed
  • rates independent of position in space
99
Q

Continuum hypothesis

A
  • many molecules of each species present
  • concentration varies continuously
  • individual reaction events cause infinitesimal changes in concentration
100
Q

Law of mass action

A

reaction is proportional to probability of a collision of the reactants

101
Q

Enzymatic reactions can be described in general as

A

binding and catalysis

102
Q

Spatial chemical reaction networks

A

dynamic behavior that is spatially distributed and modeled with PDEs

103
Q

Intrinsic noise

A

from the probabilistic character of the biochemical reactions

104
Q

Extrinsic noise

A

from random fluctuations in environmental parameters

105
Q

The Langevin approach

A
  • stochastic differential equation
  • variables are continuous
106
Q

The Gillespie algorithm

A
  • direct simulation of the master equation
  • variables are discrete
107
Q

What term did Norbert Wiener define

A

cybernetics

108
Q

What does cybernetics mean

A

the scientific study of control and communication in the animal and the machine

109
Q

Why the properties of a system cannot be fully understood by drawing diagrams of their interconnections

A
  • because the behavior of the system depends on the specifics of the interconnections
  • because changing the strength of an interconnection can change the behavior of the system
110
Q

Why clustering analysis does not reveal the causality of regulatory relationships

A

because correlation does not imply causation

111
Q

What are network motifs?

A

overrepresented patterns of network interconnections as compared to a corresponding random network

112
Q

What could the bi parallel motif indicate in food webs?

A

two species that are predators to the same prey have the same predator

113
Q

Is the cell too complex to use engineering approaches?

A

no because the properties of electric things have levels of complexity just as a cell does

114
Q

What is a bistable system?

A

a dynamical system with two stable states

115
Q

Is feedback necessary or sufficient ingredient for biostability?

A

necessary

116
Q

What is hysteresis?

A

the dependence of the system state on its past history

117
Q

What is evolvability?

A

the capacity of a population to adapt in evolutionary time to novel environments

118
Q

What are modular networks?

A

networks that contain highly connected clusters of nodes that are sparsely connected to nodes in other clusters

119
Q

What are modularly varying goals environments?

A

rapidly changing environments that have common subproblems but different overall problems

120
Q

What is one of the main advantages of using modeling based on differential equations compared to pother approaches based on statistics?

A

models based on differential equations can make predictions beyond the observations gathered

121
Q

In a dynamical system model of a set of mixed chemical species what are the components of the system?

A

the chemical species

122
Q

In a dynamical system model of a set of mixed chemical species what are the rules of the system?

A

the chemical reactions and rates at which they occur

123
Q

In a dynamical system model of a set of mixed chemical species what are the states of the system?

A

the concentrations of the chemical species over time

124
Q

What is the difference between models based on difference equations and models based on differential equations?

A

models based on difference equations treat time as evolving in discrete steps
models based on differential equations treat time steps becoming infinitely small

125
Q

What premise must be true in a biological system for modeling it with ordinary differential equation?

A

the system components must be well mixed so their concentrations are spatially homogenous
each of the system components must have sufficiently many elements to be treated as continuous quantities

126
Q

How can we model systems with spatial structures using ODEs?

A

dividing the system into well mixed compartments

127
Q

What is the appropriate mathematical formalism to model systems where continuous aspects of geometry are important of the well mixed assumption does not hold?

A

partial differential equations

128
Q

What is the process of model calibration?

A

the process of finding the parameters so that the model simulations recapitulate the observed data

129
Q

Where can the stochasticity in gene expression arise from?

A
  • splicing of mRNA
  • binding of DNA polymerase
  • binding of transcription factors
  • post translational changes of protein
  • protein degradation
130
Q

Why transcription initiation is inherently stochastic?

A

because binding events are the result of random encounters between molecules some present in small numbers

131
Q

What is the difference between deterministic and stochastic simulation?

A

stochastic simulation includes random processes such as noise while deterministic simulation does not

132
Q

What conditions are necessary for deterministic and stochastic simulations to produce similar results?

A

large number of molecules and fast promoter kinetics

133
Q

What is the difference between intrinsic and extrinsic noise?

A

intrinsic noise comes from factors within the system and extrinsic noise comes from factors outside of the system

134
Q

Why differential equations are ideal for modeling dynamic biological mechanisms?

A

they can predict precise behaviors under perturbations

135
Q

What do X and Y represent in the original Turing system?

A

the interactions of the system

136
Q

What method was used for numerically solving the Turing system?

A

Euler

137
Q

What does the population in an evolutionary algorithm contain?

A

a set of fitness values

138
Q

What does the fitness quantify in an evolutionary algorithm?

A

how close a model simulation is to the experimental data

138
Q

What are GRN sub circuits?

A

they are a part of the network that performs individual regulatory tasks

139
Q

What operation is not part of the main loop in an evolutionary algorithm?

A

creating an initial population of random models

140
Q

Why is the view that the location of the target gene expression is determined solely by the quantitative value of a morphogen gradient overly simplistic?

A

the pattern and signal strength are network properties as opposed to a property of individual cis regulatory models

141
Q

Generally how is the topology of embryonic genetic regulatory networks?

A

they are hierarchal and they are deep

142
Q

What type of genes are found in differentiation drivers?

A

genes encoding for transcription factors

143
Q

What type of genes are found in differentiation gene batteries?

A

genes encoding for transcription factors

144
Q

What types of mathematical models are frequently used for GRNs?

A

differential equations and boolean networks

145
Q

How dynamic are protein levels during development?

A

most protein levels do not change much

146
Q

Which proteins are most dynamic during development?

A

proteins that are in low abundance

147
Q

What is an example of low dynamic proteins with high abundance during development?

A

metabolic enzymes

148
Q

What is an example of high dynamic proteins during development?

A

tissue specific proteins

149
Q

In addition to concentration levels what is another highly dynamic property of some proteins during development?

A

post translational modifications

150
Q

Did the dynamics of protein and RNA levels correlate?

A

some protein levels correlated with their mRNA levels but many did not

151
Q

What are some examples of qualitative modeling approaches?

A
  • logical modeling
  • graph models
  • petri nets
152
Q

What type of information needed for quantitative models are not needed for qualitative models?

A
  • parameters
  • mechanistic descriptions of biochemical processes
  • quantitative data
153
Q

Regarding the number and type of edges when is a feedback loop positive and when is it negative?

A

a feedback loop is positive when it contains zero or an even number of negative edges
it is negative when it contains an odd number of negative edges

154
Q

What is the difference between a graph and a hypergraph?

A

the edges in a graph connects only two nodes
the edges in a hypergraph can connect more than two nodes

155
Q

What are minimal intervention sets in logical models?

A

they area the minimum sets of deactivators or constitutive activations that achieve a desires behavior in the system

156
Q

What are the two critical factors hindering the construction of comprehensive computational models??

A
  • there are no single computational method that can explain all complex phenotypes from molecules and their interactions
  • we do not know enough about all the molecules and their interactions in any one organism
157
Q

The full global model is

A

stochastic and dynamic

158
Q

What term and process regarding developmental biology did Turing postulate in 1952?

A

morphogen and reaction diffusion

159
Q

What type of mathematical model did Turing use?

A

partial differential equations

160
Q

What can the Turing system explain?

A

how periodic patterns form

161
Q

Why are Turing systems non intuitive?

A

because it is based on diffusion which by itself destroys spatial patterns

162
Q

What can Wolpert’s concept of positional information explain?

A

how cells can form spatial patterns using gradient signal

163
Q

What is an example of developmental process that follows Wolpert’s concept of positional information?

A

the gap genes pattern in drosophila

164
Q

Why Wolpert’s concept of positional information cannot be called a self organizing system?

A

because it depends on an external signal producing the morphogen gradient

165
Q

Why Wolpert’s concept of positional information became initially more accepted than Turing’s reaction diffusion system

A
  • because developing one pattern into another was seen as more plausible than patterns from nothing
  • because positional information is conceptually simper and easier to explain than reaction diffusion
166
Q

What was the main reason for the revival of Turings reaction diffusion system?

A

because scientists started to find specific genes that implemented turing systems

167
Q

What is one reason for which understanding metabolism remains a challenge?

A

metabolic fluxes cannot be measured directly

Systems Biology (1 decks)

Brainscape helps you reach your goals faster, through stronger study habits.
© 2024 Bold Learning Solutions. Terms and Conditions