Bioinformatics Lecture 1

Question 1

DNA sequencing machine

Answer 1

DNA comes out in random order

Question 2

meta genomics

Answer 2

data recovered directly form environmental sources

includes microbiome

Question 3

approach / goals of bioinformatics

Answer 3

store, process, analyse, model , predict

Question 4

biomarkers

Answer 4

measurable characteristics informative about a biological state

can be e.g. genes or metabolites

Question 5

Kaplan Meier curve

Answer 5

for progressive diseases
for incomplete observations
estimates / predicts survival

Question 6

sources of data in bioinformatics

Answer 6

clinical data
imaging
non-high throughput data
high throughput data

Question 7

high throughput profiling

Answer 7

automated process

outputs many different types of biological data

Question 8

Alzheimer’s progression

Answer 8

present one or two decades before symptom onset

treatment only effective if early

Question 9

FTD

Answer 9

frontal temporal dementia
more rare
little known about etiology
TAU and TDP proteins play a role

Question 10

mass spectronomy

Answer 10

identifies mass to charge ratio of ions

used to identify proteins

Question 11

gene networks

Answer 11

co-regulated / co-expressed genes

entire pathway goes up or down

Question 12

individual differences in protein expression

Answer 12

some are noise
some are natural variation unrelated to disease
some influenced by e.g. what people ate before

Question 13

gene set enrichment analysis

Answer 13

method to analyse genes or proteins that are overrepresented in a large dataset

identifying genes that are regulated together

often related to disease phenotypes

Question 14

finding out functions of proteins

Answer 14

either wikipedia
or a biobank
or BLAST

Question 15

BLAST

Answer 15

extremely widely used

output: homologous protein sequnces

aligned to the query (input) sequence

Question 16

homology search

Answer 16

are there proteins with similar sequences?

often evolutionary related

ancestral and children sequences

Question 17

ancestral sequences

Answer 17

from evolutionary ancestor

usually unknown

Question 18

phylogenetic tree

Answer 18

see where variants cluster and how far they are from the ancestor

Question 19

sequence alignment in evolution

Answer 19

shows which sequences are conserved in evolution

Question 20

blast parameters

Answer 20

e-value
substation matrix
gap penalties
word size

Question 21

defining similarity

Answer 21

scored by alignment score
matches and mismatches
in the end gap penalty is subtracted
= bit score

Question 22

e-value

Answer 22

converts bit score into statistical score

.01 means 1 in 100

Question 23

PSI blast

Answer 23

to find very distantly related homologies
first does a normal blast
then iteratively searches
hits come in and can be dropped out
creates an evolutionary conversation profile
in form of a position specific scoring matrix

Question 24

PSSM

Answer 24

position specific scoring matrix
made after every iteration in psi blast
used as the scoring function (instead of the substitution matrix)

Question 25

master-slave alignment

Answer 25

used in both blast and psi blast

not the same as multiple sequence alignment

Question 26

when does iteration stop

Answer 26

technically after no new sequences within e value threshold are found

in practice often capped to five to avoid spurious findings

Question 27

number of genes

Answer 27

20.000

only 1.5% code

Question 28

number of proteins

Answer 28

20.000

Question 29

number of amino acids

Answer 29

20

Question 30

cells in the body

Answer 30

37 trillion

Question 31

number of base pairs

Answer 31

3 billion

Question 32

number of chromosomes

Answer 32

23 pairs

Question 33

typical patient cohort size

Answer 33

20 to 500