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Aantekeningen hoorcollege 1: Introduction + homology searching . Introduction to Bioinformatics

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The notes from lecture 1 about Introduction + homology searching for the course introduction to bioinformatics. The document contains clear images. Furthermore, it is organized and clearly marked.

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Uploaded on
February 14, 2024
Number of pages
7
Written in
2023/2024
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Class notes
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Evert bosdriesz
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Hoorcollege 1

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Introduction to bioinformatics
Hoorcollege 1 – 8 januari 2024
Introduction + homology searching
Human genome:
- 23 pairs of chromosomes (DNA)
o DNA codes for genes
- 20,000 genes on DNA and 20,000 proteins
o 1.5% of DNA is protein/gene coding
- 3 billion base pairs
- 37 trillion cells
Measure cells  measure a lot of things


What is bioinformatics used for?
- DNA sequencing
We can sequence the whole human DNA
We get lots of data
Identify pinpoint mutations / changes
Bioinformatics is used ‘to find the needle in the haystack’ = naald in hooiberg
 But what does the needle do is more important
- What does the mutation mean
- What is the effect of the mutation? Is it related to the disease?


DNA sequencing analysis
Images  translated to letters  reads (short DNA sequences)  aligned reads 
mutations
Each step contains bioinformatics


Bioinformatics develop methods, create workflows, and analyze large datasets to answer
biological questions
- For example, develop new algorithm to align proteins
- Typically, many computational methods need to be combined in a workflow to
process all data


“Omics” analysis in biomedicine
= Data science in the field of molecular biology
Omics data = extensive molecular profiling data of biological sample

, Do this for all / many proteins in the cell
- Measure (levels of) molecules/variant in cells
- Huge number of measurements per sample (>1000)
o Important
- For example
o All bases of the DNA
o mRNA abundances of all genes
o abundances of many/all proteins



What can we measure, and how?
Some examples, are much more
Genomics (DNA)
- point mutations (1 letter) / small variants
- structural variant (bigger changes – cancer)
- methylation
- DNAseq
- chemical marks … eppi/???
Transcription (mRNA)
- single cell RNAseq
- micro arrays (becoming obsolete)
proteomics (proteins)
- measure proteins
- immunohistochemistry
o empty body’s
- mass spectrometry (MS)
o high throughput

metabolomics (metabolites / small molecules)
- NMR / mass spectrometry


Can now measure individual cells ?
Personalized medicine = which patient should (not) get drug based on (molecular) profiling
of patient


Biomarkers are indicators of some biological state or condition
Omics data is often used to find biomarkers
Examples of biomarkers:
- A metabolite or protein present in blood/urine/stool
- Mutation found in blood or a tumor sample
- Overexpression of specific gene or set of genes in diseased tissue (from RNAseq)

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