digital biology, by ruediger trojok
Post on 18-Feb-2017
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BIOFLUX
presented at
Do It Together - Digital Biologya seminar organized byin January 2016, Berlin
Digital Biology
Dipl. Biol. Rüdiger TrojokBioflux, ITAS/KIT
Evolution
– 3,6 Bn. Years
> >
What is digital biology?
Or: can we program biology?
Shannon‘s information theory
Nachrichtenübertragung abhängig von:
• Signal-Noise-Ratio• bandwith / channel capacity• Available energy • Mutual Information of Sender / Receiver• Data compression
Can we apply information theroy on biology?
Landauer Information theory
Rolf Landauers:
“Information is not a disembodied abstract entity; it is always tied to a physical representation. It is represented by engraving on a stone tablet, a spin, a charge, a hole in a punched card, a mark on paper, or some other equivalent. This ties the handling of information to all the possibilities and restrictions of our real physical word, its laws of physics and its storehouse of available parts.”
The physical nature of information; Rolf Landauer; Physics Letters A 217 (1996) 188-193
Maxwell‘s Demon and Szilard‘s Machine
Landauer Principle:
• Information gain is entropy loss
• Work is an entropy-less energy source
• Heat is entropy carried by energy
observation:Information processing costs
energy
per bitdW = kBT ln2
work and heat exchange
Biosemiotik AGTC
Sequenz(digital)
Motif(analog)
Anabolism Katabolism
ProliferationDeath
„What we actually call information - the elementary unit of information - is a difference that makes a difference” Gregory Bateson
BioSyntaxJesper Hoffmeyer’s Theorie:• A monistic Code Duality: digital und analog• Code Memory of structural relations in space
and time
Creative Plasticity
AGTC
Digital:Sequence
Analog:Motif
Bio-Language AGTC
Biosphere
http://www.google.de/imgres?imgurl=http%3A%2F%2Fecotope.org%2Fanthromes%2Fbiodiversity%2Fplants%2Fmaps%2Fpng%2Fellis_2012_Olson_biomes.png&imgrefurl=http%3A%2F%2Fecotope.org%2Fanthromes%2Fbiodiversity%2Fplants%2Fmaps%2F&h=720&w=960&tbnid=rzbkGIJ_UVKZAM%3A&zoom=1&docid=nb8cF8yoWA4UDM&hl=de&ei=UQs9VKvFJIzY7AaCloFw&tbm=isch&iact=rc&uact=3&dur=902&page=3&start=52&ndsp=24&ved=0CNEBEK0DMDk
Read Write
Analog Biology
Digital Biology
Exponential growth of biological databases
http://www.kanehisa.jp/en/db_growth.html
14
Gaudilabs: Generic Lab Equipment
Physical principles used: light (optical sensors, filters, lenses), temperature (peltier), gravitiy (rotation), electricity (electrodes)
17
Prof. Blaney, Broad Institute http://www.youtube.com/watch?v=66Oc8fLKXlE
Historic Analogy: Printing pressmovable type inventions:
Korea: Choe Yun-ui 1377
Germany: Johannes Gutenberg 1436
Advantages of Digital Biology Technology
Efficiencylowest speed limit is cell growth rateSerial / parallel experimentationBrute force screeningMachine instead of manual standards
ReproducibilityPrecision of measurements vs. natural noiseReductionist vs. systems approachSingle cells vs. Population
Cost efficiencyWages for operation of equipmentService costsMaterial consumptionInfrastructure requirements
Architecture questions
Decentral vs. Central'Apple' vs. 'Sharp' modellow tech vs. High tech
open source vs. Closed sourceprogrammable vs. Application specificonline vs. Offline control
technology push and market pull:- what will be the killer app?- Who are the users?
Synthetic Biology
Systems approach(diverging)
Engineering approach(converging, iterative)
timetime
Systematic screening can be combined with
rational and iterative engineering.
22
Digital Biology Semiotics
DNA Extraction
DNA Amplification
DNA Insertion
Cell Transformation
Cell Incubation
Protein Expresion
DNA Sequencing
DNA Synthesis
DNA Extraction
DNA Amplification
DNA Insertion
Cell Transformation
Cell Incubation
Protein Expresion
DNA Sequencing
DNA Synthesis
DNA Extraction
DNA Amplification
DNA Insertion
Cell Transformation
Cell Incubation
Protein Expresion
DNA Sequencing
DNA Synthesis
Evironment and Agriculture
Health: Phage Therapy
• Well known since 100 years
• Programmable
• Highly specific
• Safe
Wetware
Software
Hardware 0
Biostrike
Citizens / NGOs / Academics
§§
Personalized Phages
0
Good
Environment
Human
Bad
Neutral
BSL 1
BSL 4
BSL3
BSL 2
Comments and suggestions welcome!
Thanks for listening.
Rüdiger Trojok
rt@openbioprojects.net
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