User:Ron Milo: Difference between revisions

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='''BioNumbers - the database of useful biological numbers'''=
[[Image:HomeP229.jpg|thumb|right|250px|Frame|]]


Current version of [http://spreadsheets.google.com/pub?key=pLEc8e_GzXWESQ8ZpQMXFYQ BioNumbers database].
'''I am a systems biology fellow at Harvard medical school.'''


== What is BioNumbers? ==


BioNumbers is a collaborative community effort to establish a database of useful biological numbers.  
e-mail: ron_milo@hms.harvard.edu


For example:
phone: 617-953-3247
*How many ribosomes or mRNAs are in a cell (e.coli, yeast, mammalian or any other) ?
*The volume of different cells and organelles
*Concentrations and absolute numbers of ions and metabolites
*Generation times of different organisms


and many many other useful but too often hard to find numbers. Each property/number includes a reference, and other relevant information.
We currently have a very rudimentary format based on the google documents collaboration tool (basically an excel-like sheet), but we hope to add graphical user interfaces with querying capabilities in the near future.


Please check out the current version of the [http://spreadsheets.google.com/pub?key=pLEc8e_GzXWESQ8ZpQMXFYQ BioNumbers database].


Some more explanation on what it is and where is it going to can be found below.
'''Research interests:'''


To join as a collaborator and contribute your favorite numbers to this effort please send an email to ron_milo@hms.harvard.edu or mike_springer@hms.harvard.edu or paul_jorgensen@hms.harvard.edu.


== Motivation ==
'''How physiological adaptations affect evolutionary adaptations'''


Numbers are absolute and immutable entities. Biology is built on adaptation and flexibility. It is thus no surprise that concrete values for many biological properties are hard to find. Most quantitative properties in biology depend on the context or the method of measurement, the organism and the cell type. Yet it is clear that characteristic numbers and ranges are very useful tools to have available. The aim of this database is to be a repository for useful biological numbers, that gives a concrete value while supplying the relevant reference and comments that depict its domain of validity. We hope that you and others will find it useful and help to expand it and make it more accurate.  
A central issue in understanding natural selection is the relationship between physiological adaptations and evolutionary adaptations. Though extensively discussed in qualitative terms, quantitative analysis has been lacking. Under the guidance of Marc Kirschner and Michael Brenner I am studying this relationship using hemoglobin as a model system, relying on extensive experimental data measured for various organisms and under varying conditions. In a related effort I am trying to experimentally map the adaptive environment-fitness landscape and its evolutionary dynamics using experimental evolution with e. coli.  


== Interesting examples from BioNumbers  ==
'''Dynamic proteomics'''


*Number of mRNAs in cell (total absolute number):
I am interested in studying the dynamics of protein levels at the single cell level. This promises to give us a deeper understanding into biological processes. In a research effort with Alex Sigal and other members of the Alon group at the Weizmann Institute I developed an experimental tool for dynamic proteomics in individual living human cells. This method enabled us to measure the variability and temporal memory in thousands of cells for several dozen proteins. Our approach uses a fluorescently tagged library under endogenous regulation analyzed using time lapse microscopy and custom written image analysis tools.
**Yeast - 15000 (BioNumbers index 339)
**Escherichia coli - 4000 (BioNumbers index 61)


*Number ATP to make 1 cell
'''Network motifs - building blocks of complex networks'''
**Escherichia coli - 55 billion (BioNumbers index 173)


*Minimal generation time:
To understand biological networks, together with Uri Alon and members of his lab, we have defined "network motifs": interaction patterns that appear in a network much more than expected in random. Network motifs help in finding functional building blocks of complex networks. Network motifs have been found to perform information processing tasks by studying their temporal dynamics in microorganisms. The approach was used to classify networks into superfamilies.
**Vibrio natriegens - 9.8 minutes (BioNumbers index 231)


*Mutation rate per genome per replication:
'''Plant and environmental systems biology'''
**Escherichia coli - 0.0025 (BioNumbers index 310)


I want to harness the tools and approaches employed in systems biology to bear on the grand challenges of sustainability. I am studying the efficiency of photosynthesis, trying to gain insight about the constraints that shape its properties and the limitations on the maximal productivity in plants and other photosynthetic organisms.
In the process of studying plants I developed a tool for the automatic measurement of hypocotyls (stems) and roots – [http://openwetware.org/wiki/HypocoTool HypocoTool].


== What qualifies as a good BioNumber? ==
'''BioNumbers database'''


It is hard to define precisely. We think about them as the “model organisms” of numbers. A good BioNumber is one that will be useful for other people in the community. Examples of what we thought will be useful can be seen by browsing the database. If in doubt, you can always ask us or just add the number, we are sure it wouldn’t do any harm…
This is a collaborative effort to establish a database of useful biological numbers such as the number of ribosomes in the cell, the volume of the nucleus, the rate of translation and transcription and many many other useful but too often hard to find biological numbers. You can learn more about it and check out the current version at the [http://openwetware.org/wiki/bioNumbers BioNumbers database].
High throughput data on mRNA levels, life times, protein-protein interactions or similar properties are better stored in a database of their own that we can happily point to from our section on “other databases of useful biological numbers”.
In properties where the value is known for many organisms (say number of chromosomes), we are interested in the values for the model organisms and the extreme cases that teach about the limits (say largest number of chromosomes in any animal).


== Ideas in the pipeline ==
'''Top 20 places for short hikes in and around Boston'''


*The comparative tables builder: you will be able to choose your properties and and organisms of interest and get a table comparing the values. We hope this will make comparative studies much easier, and will lead to new insights into quantitative design principles. Blanks will denote where we need more data.
[http://maps.google.com/maps/ms?f=q&hl=en&geocode=&ie=UTF8&om=1&msa=0&msid=100468890176738841334.0004384ab492807b4e551&ll=42.271212,-71.173553&spn=0.431878,0.933838&z=10/ my recommendations]
*The comperaVisulaizer: a graphical interface that will visualize values for different organisms and different properties that share the same units. Kind of like the scale of lengths showing the progression from molecules to galaxies
*Vote for the ten BioNumbers every high school biology graduate should know.
*Vote for the one hundred BioNumbers every college biology graduate should know.


== Contribute a BioNumber ==
'''Selected Publications:'''


It is really easy. You can send us an email to be able to edit the source database. Alternatively you can just go [http://openwetware.org/wiki/User:Ronmilo_AddBioNumberForm here] and we will put it in the database with an acknowledgment of your contribution.
You can download any of the publications below and my CV at my [http://www.weizmann.ac.il/mcb/UriAlon/people/RonMilo/Ron_Milo_HomePage.htm/ Weizmann website]


== How did it get started? ==
    - A. Sigal*, R. Milo*, A. Cohen*, N. Geva-Zatorsky, Y. Klein, Y. Liron, N. Rosenfeld, T. Danon, N. Pertzov & U. Alon,
      Variability and memory of protein levels in human cells.
      Nature 444(7119) 643-6 (2006).
      * these authors contributed equally to this work


The BioNumbers database started as a joint effort by Ron Milo, Paul Jorgensen and Mike Springer at the systems biology department in Harvard. The effort was inspired by a comparison of values of key properties in bacteria, yeast and a mammalian cell in Uri Alon’s book – “Introduction to systems biology”. It is our hope that the database will facilitate quantitative analysis and reasoning in a field of research where numbers tend to be “soft” and difficult to vouch for.
    - A. Sigal*, R. Milo*, A. Cohen, N. Geva-Zatorsky, Y. Klein, I. Alaluf, N. Swerdlin, N. Perzov, T. Danon,
      Y. Liron, T. Raveh, A. E. Carpenter, G. Lahav & U. Alon,
      Dynamic proteomics in individual human cells uncovers widespread cell-cycle dependence of nuclear proteins.
      Nature Methods 3, 525 - 531 (2006).
      * these authors contributed equally to this work


== Other databases dedicated to certain types of biological numbers ==
    - R. Milo, S. Itzkovitz, N. Kashtan, R. Levitt, S. Shen-Orr, I. Ayzenshtat, M. Sheffer & U. Alon,
      Superfamilies of designed and evolved networks
      Science, 303:1538-42 (2004).


*[http://redpoll.pharmacy.ualberta.ca/CCDB/cgi-bin/STAT_NEW.cgi CyberCell Project] - statistics on the bacteria E.coli
    - R. Milo, S. Shen-Orr, S. Itzkovitz, N. Kashtan, D. Chklovskii & U. Alon,
*[http://www.brenda.uni-koeln.de/ BRENDA] - a database of enzyme properties
      Network Motifs: Simple Building Blocks of Complex Networks
*[http://www.genomesize.com/ Animal Genome Size Database] - a database of animal genome sizes, chromosomes numbers etc.
      Science, 298:824-827 (2002).


== Our "wish list" of BioNumbers (can you help find them?)  ==
    - S. Shen-Orr, R. Milo, S. Mangan & U. Alon,
 
      Network motifs in the transcriptional regulation network of Escherichia coli
* Minimal known generation time of a photosynthetic organism
      Nature Genetics, 31:64-68 (2002).
* Concentration of NADP and NADPH in chloroplasts and in cyanobacteria under normal illumination
* Concentration of ADP and ATP in chloroplasts and in cyanobacteria under normal illumination
* Number of ribosomes in a Hela Cell or other mammalian cell
* Number of ATP molecules consumed in making a yeast
* Number of ATP molecules consumed in making a Hela cell
 
== A number you would like to see on BioNumbers?  ==
 
Do you have a secret "wish list" of biological numbers you would like to know? Please tell them to us and we would try to find them and incorporate them as soon as possible. Go to [http://openwetware.org/wiki/User:Ronmilo_AddWishfulBioNumber add wishful number].
 
== People contributing numbers to BioNumbers  ==
 
*[http://openwetware.org/wiki/User:Ronmilo_PersonalWebsite Ron Milo]
*[http://kirschner.med.harvard.edu/files/html/people.shtml Michael Springer]
*[http://kirschner.med.harvard.edu/files/html/people.shtml Paul Jorgensen]
*[http://www.sfc.keio.ac.jp/~tom  Tom Shimizu]
*[http://www.yanaiweb.com/itai.html Itai Yanai]
*[http://wormsense.stanford.edu/people.html Daniel Ramot]

Revision as of 18:53, 29 August 2007

I am a systems biology fellow at Harvard medical school.


e-mail: ron_milo@hms.harvard.edu

phone: 617-953-3247


Research interests:


How physiological adaptations affect evolutionary adaptations

A central issue in understanding natural selection is the relationship between physiological adaptations and evolutionary adaptations. Though extensively discussed in qualitative terms, quantitative analysis has been lacking. Under the guidance of Marc Kirschner and Michael Brenner I am studying this relationship using hemoglobin as a model system, relying on extensive experimental data measured for various organisms and under varying conditions. In a related effort I am trying to experimentally map the adaptive environment-fitness landscape and its evolutionary dynamics using experimental evolution with e. coli.

Dynamic proteomics

I am interested in studying the dynamics of protein levels at the single cell level. This promises to give us a deeper understanding into biological processes. In a research effort with Alex Sigal and other members of the Alon group at the Weizmann Institute I developed an experimental tool for dynamic proteomics in individual living human cells. This method enabled us to measure the variability and temporal memory in thousands of cells for several dozen proteins. Our approach uses a fluorescently tagged library under endogenous regulation analyzed using time lapse microscopy and custom written image analysis tools.

Network motifs - building blocks of complex networks

To understand biological networks, together with Uri Alon and members of his lab, we have defined "network motifs": interaction patterns that appear in a network much more than expected in random. Network motifs help in finding functional building blocks of complex networks. Network motifs have been found to perform information processing tasks by studying their temporal dynamics in microorganisms. The approach was used to classify networks into superfamilies.

Plant and environmental systems biology

I want to harness the tools and approaches employed in systems biology to bear on the grand challenges of sustainability. I am studying the efficiency of photosynthesis, trying to gain insight about the constraints that shape its properties and the limitations on the maximal productivity in plants and other photosynthetic organisms. In the process of studying plants I developed a tool for the automatic measurement of hypocotyls (stems) and roots – HypocoTool.

BioNumbers database

This is a collaborative effort to establish a database of useful biological numbers such as the number of ribosomes in the cell, the volume of the nucleus, the rate of translation and transcription and many many other useful but too often hard to find biological numbers. You can learn more about it and check out the current version at the BioNumbers database.

Top 20 places for short hikes in and around Boston

my recommendations


Selected Publications:

You can download any of the publications below and my CV at my Weizmann website 

   - A. Sigal*, R. Milo*, A. Cohen*, N. Geva-Zatorsky, Y. Klein, Y. Liron, N. Rosenfeld, T. Danon, N. Pertzov & U. Alon,
     Variability and memory of protein levels in human cells.
     Nature 444(7119) 643-6 (2006). 
     * these authors contributed equally to this work

   - A. Sigal*, R. Milo*, A. Cohen, N. Geva-Zatorsky, Y. Klein, I. Alaluf, N. Swerdlin, N. Perzov, T. Danon, 
     Y. Liron, T. Raveh, A. E. Carpenter, G. Lahav & U. Alon,
     Dynamic proteomics in individual human cells uncovers widespread cell-cycle dependence of nuclear proteins.
     Nature Methods 3, 525 - 531 (2006).
     * these authors contributed equally to this work

   - R. Milo, S. Itzkovitz, N. Kashtan, R. Levitt, S. Shen-Orr, I. Ayzenshtat, M. Sheffer & U. Alon,
     Superfamilies of designed and evolved networks
     Science, 303:1538-42 (2004).

   - R. Milo, S. Shen-Orr, S. Itzkovitz, N. Kashtan, D. Chklovskii & U. Alon,
     Network Motifs: Simple Building Blocks of Complex Networks
     Science, 298:824-827 (2002).

   - S. Shen-Orr, R. Milo, S. Mangan & U. Alon,
     Network motifs in the transcriptional regulation network of Escherichia coli
     Nature Genetics, 31:64-68 (2002).
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