Introduction to Bioinformatics.

Introduction to bioinformatics

Elena Sügis elena.sugis@ut.ee

Bioinformatics Seminar MTAT.03.242, 2016

Questions we ask

Image credit:https://siteman.wustl.edu/glossary/cdr0000046470/

1014 cells in human body

23 000 genes

23 pairs of chromosomes

3 billion pairs

Cell size and scale

http://learn.genetics.utah.edu/content/cells/scale/

Central dogma

What is DNA?

What is the difference between DNA and RNA?

Image credit: Genome Research Limited

100 000 different proteins

23 000 genes

Technology

Image credit: Genome Research Limited

Mass spectrometry

Sequencing technologies

Measuring levels of gene expression

ON ON OFF

PROTEIN

G1 G2 G3 G4

Gene products carry out cellular

function

Gene expression profile

Gene Expression profile

Expression level

G1 OFF 0 G2 ON 30 G3 ON 20 G4 OFF 0

Each cell has its own gene expression profile

Expression level

G1 OFF 0 G2 ON 30 G3 ON 20 G4 OFF 0

Expression level

G1 OFF 0 G2 ON 30 G3 ON 20 G4 ON 20

HEALTHY CELL CANCER CELL

Single Nucleotide polymorphism •  variation in a single nucleotide that occurs at a specific position in the

genome, where each variation is present to some appreciable degree within a population (e.g. >1%)

•  underlie differences in our susceptibility to disease

Image credit: Wikipedia

Experiments

Good old times

Science

knowledge experiment hypothesis analysis v v v

How we do it now

lots of experiments

analysis

Science

knowledge

hypothesis

Bioinformatics is an interdisciplinary field that develops methods and software tools for understanding biological data

Bioinformatics is •  an interdisciplinary field •  that develops methods and software tools •  for understanding biological data

Moore’s law

Cost per genome

Why do we need bioinformaticians?

Because Excel can’t help anymore

Why do we need bioinformaticians?

•  Amount of generated biological data requires sophisticated data analysis and management

•  Programmers & statisticians lack biological knowledge

•  Biologists don’t program

•  These two don’t understand each other

Slide is inspired by from “How to be a bioinformatician” by Christian Frech

Biologist talks to statistician

http://www.youtube.com/watch?v=Hz1fyhVOjr4

What do bioinformaticians do?

Word cloud from manuscript titles published in Bioinformatics from Jan 2013 to April 2014

Slide credit: “How to be a bioinformatician” by Christian Frech

Machine learning

Algorithms

Proteomics

Black magic Sequences

Modeling

Bioinformatics is a broad field

What Does the Perfect Bioinformatician Look Like?

Computer Science

Biology

Computer Science

Biology

Statistics

Perfect bioinformatician

Computer Science

Biology

Statistics

Data comes in different forms

Slide credit: D.Fishman, Introduction to ML in bioinformatics

Data ≠ Knowledge

Slide credit: D.Fishman, Introduction to ML in bioinformatics

R. Matthiesen (ed.), Bioinformatics Methods in Clinical Research, Methods in Molecular Biology 593, DOI 10.1007/978-1-60327-194-3 2, © Humana Press, a part of Springer Science+Business Media, LLC 2010

Adopted from P.Vincent http://videolectures.net/deeplearning2015_vincent_machine_learning/

What is the main ingredient?

Adopted from P.Vincent http://videolectures.net/deeplearning2015_vincent_machine_learning/

Databases

Data management systems

Data source

Simple data analysis pipeline

Data Black Magic Result

high quality data machine learning method

awesome result

Simple data analysis pipeline

Data Black Magic Result

poor quality data machine learning method

not so awesome result

Data Preprocessing

Massage your data

Predictive modeling

Tools & Services

Understand the disease better

Make more precise diagnosis ML in Bioinformatics (part II)

Medical Imaging

Cancer Images credit: D.Fishman, Introduction to ML in bioinformatics

image by Krista Fisher et al.

Genetic risk assessment

Pharmacogenetics

Personalized medicine

http://www.pfizer.ie/personalized_med.cfm

Population genomics large-scale comparison of DNA sequences of populations

What do these books contain?

The Wellcome Human Genome Library in London (Left CC: Russ London, Right Source: Wellcome Collection)

This is a single human genome

The Wellcome Human Genome Library in London (Left CC: Russ London, Right Source: Wellcome Collection)

Moore’s law

Cost per genome

Big Data: Astronomical or Genomical?, Zachary et al, PlosOne Biology 2015

The Age Of Big Data

Labs that produce data

Research groups that can analyse data

Labs that produce data

Experts who can analyze data

Analyze that

Data analysis

Need to develop new: •  Preprocessing methods

•  Analysis pipelines

•  Methodology

•  Algorithmic solutions

•  Tools

IF YOU TORTURE THE DATA LONG ENOUGH

IT WILL CONFESS TO ANYTHING

Ronald Coase, Economist, Nobel Prize winner

http://baranzinilab.ucsf.edu/integration-large-scale-omics-data-sets

Data Integration

Data storage The amount of sequencing data created is growing at a faster rate than economically available storage

http://geschwindlab.neurology.ucla.edu/protocols/next-generation-sequencing

N Goldman et al. Nature 000, 1-4 (2013) doi:10.1038/nature11875

Using DNA as a digital archive media

store sequenced DNA information in … DNA

N Goldman et al. Nature 000, 1-4 (2013) doi:10.1038/nature11875

Scaling properties of DNA-based storage

If the cost of DNA synthesis falls by two orders of magnitude, it will become a sensible way to store data for the medium term

(below 50 years)

Challenges •  Need of new compression methods

•  Data integration methods

•  Lack of specialists

•  Need for new: –  Analysis pipelines

–  Methodology

–  Algorithmic solutions

–  Tools

Challenges of being bioinformatician

•  Biology is complex, not black and white –  As many exceptions as rules (e.g.: define “gene”)

–  No single optimal solution to a problem

–  Results interpretable in many ways (story telling, cherry picking)

•  Understanding the biological question

•  Field is moving incredibly fast –  Lack of standards, immature/abandoned software

–  Much time spent on collecting/cleaning-up data, troubleshooting errors

•  Hundreds of software tools and databases out there –  Easy to get lost

–  Important to understand their strengths and weaknesses

Genes are us…

and them.SOURCE:,JAVIER,HERRERO,,EUROPEAN,MOLECULAR,BIOLOGY,LABORATORY—EUROPEAN,BIOINFORMAT,ICS,INSTITUTE

Genes are us…

Introduction to Bioinformatics.

Education

Transcript of Introduction to Bioinformatics.

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