introduction to computational and systems biology · y. lazebnik: can a biologist fix a radio?...

Introduction to computational and systems biology

Ion PetreComputer Science, Abo Akademi

http://users.abo.fi/ipetre/?n=Teaching.Intro-CompSysBioFall 2018

http://users.abo.fi/ipetre/?n=Teaching.Intro-CompSysBio


Goal

• To introduce a number of topics at the border between Biology, Mathematics and Computer Science

• explain the rationale and the benefits of the interactions• introduce a number of challenges and success stories in the area

• Run a student-driven, medicine-focused systems biology project• Start with a medical problem• Build a network model• Visualize, analyze the model• Interpret the conclusions

• Introductory course• does not go into deep details in any of the topics• advanced courses on some of the topics in the course exist

– algorithms in computational biology– Modeling – bioinformatics– molecular computing

September 4, 2018 Introduction to computational and systems biology 2

Y. Lazebnik: Can a biologist fix a radio?

• Y. Lazebnik: Can a biologist fix a radio? – Or what I learned while studying apoptosis Cancer Cell 3: 445-448, 2002

• the author (a well-established biologist at Cold Spring Harbor Laboratory, US) imagines how would a biologist attempt to understand the functioning of a radio and fix a broken one

• he abstracts in this way from the peculiarities of biological experiments

• uses plastic analogies to make a deep point about how computing is useful in biology



• Problem: fix a broken transistor radio• a radio is conceptually similar to a transduction pathway: both

convert a signal from one form to another• his radio has about 100 various components (resistors, capacitators,

transistors, etc), which is about the same as the number of molecules in a reasonable complex signal transduction network


• Y. Lazebnik: Can a biologist fix a radio? Biochemistry, vol. 69, No 12, 2004, pp 1403-1406


• The broken radio problem – the biological approach• secure funds to obtain a large supply of identical functioning radios• find out how to open the radios• describe and classify the objects inside a radio into families according

to their appearances– square metal objects– round brightly colored objects with two legs– round-shaped objects with three legs– …

• investigate whether changing the colors affects the radio’s performance

– for some trained ears there may be a difference sometimes– many publications, lively debate




• The broken radio problem – the biological approach

• remove components one at a time• eventually find a wire whose deficiency will stop the music completely: SRC (serendipitously recovered component)• the SRC wire is required because it is the only link between the radio and a long extendable object – call it MIC (most important component)

• flourishing field of research; structure of MIC, evolutionary explanation for why MIC is extendable

• later discovery that MIC is in fact not always required for the radio to work: another one could be used – RIC (really important component)

• scientific fight between the communities• later discovery of a switch that determines which of MIC and RIC is needed: U-MIC (undoubtedly most important component)

• a large-scale effort on the pull-it-out approach to establish the role of each and every component• similar effort on establishing the connections between the various components

• Y. Lazebnik: Can a biologist fix a radio? Biochemistry (Moscow), vol. 69, No 12, 2004, pp 1403-1406


• Eventually: • all components are catalogued, • connections between them described, • consequences of removing each components or their combination

documented

• Re-focus on the question of whether this information that everybody sought to collect can help fix the radio

• sometimes yes: if an object that is red in a working radio and black (and smells like burnt paint) in a non-working one is replaced, then the radio is fixed

• the pharmaceutical industry’s mantra: “give me a target””• sometimes no: e.g., with tunable components the radio may not work

because several components are not tuned properly


Biology needs computing

• Need for a formal language• needed for translating biological problems to computational ones• needed for reasoning about interactions, global effects• needed for representing knowledge, hypothesis• needed in the transition towards a quantitative science• needed as a communication standard

• Big data• Huge amounts of data, multiple sources, noise

• Computing needed in many different forms• data storage, retrieval, representation, analysis• algorithmics• modeling• abstract reasoning

• The view of life as computing• leads to biology as a science focused on reverse-engineering life• life processes as information-processing devices: inputs, output, internal

states, communication, concurrency, efficiency, robustness, etc.



Modern biology

Experimental

Theoretical

Mathematical

Computational Algorithmic

Executable

Systems

Synthetic


Biological neologisms

Network

Component

Robustness

Efficiency Control

Regulation

Synchronization

Concurrency

An example: shotgun genome sequencing


Eric D. Green, Strategies for the systematic sequencing of complex genomes. Nature Reviews Genetics 2, 578-583, 2001

Another example: whole cell models

September 4, 2018 Computational Biomodeling Laboratory http://combio.abo.fi/ 18

• Whole cell model of Mycoplasma genitalium (human urogenital parasite) whose genome contains 525 genes.

• 28 submodels integrated into a “super-model”; several math formalisms • Biggest computational challenges:

• Model fitting: based on 900 publications, 1900 parameter measurements• Integrate the 28 submodels into a unified model

High interest in building complex quantitative models in neuroscience

• The Human Brain Project (2013-2023) is a Future and Emerging Technologies (FET) Flagship project of the European Commission

• Aim: build and simulate complete model of the human brain to better understand its functions

• Total budget: 1.2 billion euros

• The BRAIN Activity Map Project (2013-2023) is a US initiative• Aim: map the activity of every neuron in the human brain• Seen as the next high-impact project after the human genome

project• Total budget: at least 3 billion dollars

September 4, 2018 Computational Biomodeling Laboratory http://combio.abo.fi/ 19

http://en.wikipedia.org/wiki/Human_Brain_Project

http://en.wikipedia.org/wiki/BRAIN_Initiative

Another example: synthetic biology


Source: http://www.snipview.com/

http://www.snipview.com/

Computer science needs biology

• Less talked about than the other direction of the interaction• The view of life as computing

• new definitions of what computing is• Many of the approaches in AI have a conceptual origin in biology• Parallelism and concurrency on a massive-scale

• A mainstream area in CS is the study of parallelism and concurrency• Biology is a rich reservoir of parallelism and concurrency problems,

on a massive scale, much larger than that seen in engineering• Tools developed in CS need to be refined, new ones needed

• Biology as hardware for computing• Computing with molecules• Nano-science and –engineering• Self-assembly• Functional materials• Personalized medicine• Faster computers



Modern comp. science

Computing with bio-molecules

Genetic algorithms

Evolutionary algorithms

Neural networks

Particle swarm

Ant computing

Self-assembly

New computing paradigms

Computing at the nano-scale


E Benson et al. Nature 523, 441-444 (2015) doi:10.1038/nature14586Scale bars: 50 nm

3D meshes rendered in DNA.

Content (tentative list)

§ Elements of molecular biology§ Elements of biotechnology§ Molecular programming§ Computational self-assembly§ Bioinformatics tools and databases§ Biological networks

§ Algorithms in computational biology

• Gene sequencing• Sequence alignment• Gene prediction• Genome rearrangements• Protein sequencing

40September 4, 2018 Introduction to computational and systems biology

Course schedule

• Course format: lectures, exercises, projects, final exam

• Lectures• Tuesdays 13.15-15.00: Agora 115A• Thursdays 13.15-15.00: Agora 115A

• Project discussions (when needed)• Wednesdays 15.15-17.00: Agora 115A

• Duration• Starts: September 4• Ends: October 23

• Exam: TBA

• Course webpage: http://users.abo.fi/ipetre/?n=Teaching.Intro-CompSysBio

• Lecturers: Ion Petre, Mikhail Barash

4104-09-2018 Introduction to computational and systems biology


introduction to computational and systems biology · y. lazebnik: can a biologist fix a radio?...

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