BioNumbers: Difference between revisions
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*Number of mRNAs in cell (total absolute number): | *Number of mRNAs in cell (total absolute number): | ||
**Yeast - 15000 ( | **Yeast - 15000 ([http://bionumbers.hms.harvard.edu/bionumber-drill-down.aspx?s=y&id=100273&ver=0 BioNumber index 100273]) | ||
**Escherichia coli - 4000 (BioNumbers index 61) | **Escherichia coli - 4000 (BioNumbers index 61) | ||
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*Mutation rate per genome per replication: | *Mutation rate per genome per replication: | ||
**Escherichia coli - 0.0025 (BioNumbers index 310) | **Escherichia coli - 0.0025 (BioNumbers index 310) | ||
== What qualifies as a good BioNumber? == | == What qualifies as a good BioNumber? == | ||
Revision as of 09:24, 15 April 2008
BioNumbers - the database of useful biological numbers
Please follow this link to the BioNumbers database. Below is a short introduction.
BioNumbers (bioNumbers.org) enables you to find in one minute any common biological number that can be important for your research, such as the rate of translation of the ribosome or the number of bacteria in your gut. You will find full reference, comments and related numbers that are useful.
Here is our clip on youtube
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What is BioNumbers?
Bionumbers is a collaborative community effort to establish a database of useful biological numbers.
For example:
- 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.
Some more explanation on what it is and where is it going to can be found below.
To join as a collaborator and contribute your favorite numbers please visit BioNumbers.
Motivation
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.
Interesting examples from BioNumbers
- Number of mRNAs in cell (total absolute number):
- Yeast - 15000 (BioNumber index 100273)
- Escherichia coli - 4000 (BioNumbers index 61)
- Number ATP to make 1 cell
- Escherichia coli - 55 billion (BioNumbers index 173)
- Minimal generation time:
- Vibrio natriegens - 9.8 minutes (BioNumbers index 231)
- Mutation rate per genome per replication:
- Escherichia coli - 0.0025 (BioNumbers index 310)
What qualifies as a good BioNumber?
It is hard to define precisely. Feel free to enter BioNumbers that you want to keep track of and help others on the way. As an easily searchable and permanent database, BioNumbers is superior to napkins, post-its, and notebooks. Your colleagues will benefit from your numbers and you from theirs. 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…
There is a subset of bioNumbers that can be thought of as the “model organisms” of numbers. We will try to engage the community in an effort to define this subset and think of how to disseminate the knowledge of these precious values.
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 with a pointer bioNumber. In this way bioNumbers serves as a portal to other databases and high throughput data repositories. 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
- 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.
- 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
It is really easy. You can send log in and create an account at bioNumbers website, or if you are too busy just choose Quick Submit and we will enter the number for you based on a reference you provide.
How did it get started?
The BioNumbers database started as a joint effort by Ron Milo, Paul Jorgensen and Mike Springer at the systems biology department in Harvard and Griffin Weber of information technology at Harvard medical school. 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.
Other databases dedicated to certain types of biological numbers
- CyberCell Project - statistics on the bacteria E.coli
- BRENDA - a database of enzyme properties
- Animal Genome Size Database - a database of animal genome sizes, chromosomes numbers etc.
- yeastgfp - a database of protein abundance in yeast
Our "wish list" of BioNumbers (can you help find them?)
- Minimal known generation time of a photosynthetic organism
- 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. Send us an email at bionumbers@gmail.com or use the Quick Submit form.
Features to be added to BioNumbers
We wish to continue to improve bioNumbers. To expedite this we welcome all comments/ideas large or small. Feel free to comment on posted ideas also (e.g. this sounds good or useless)
Minor additions
- After login show the results of the last search (this is not needed given that the previous point is covered)
- Add a text explanation of how to enter big/small numbers using scientific notation. Also maybe allow notation like 10^11
- Show the total number of bioNumbers, users and searches since release
- BioNumber of the day/week/month
- Wish lists of desired BioNumbers (open a request page).
- When scrolling down the page, keep the search etc buttons visible (bottom or top)
- Add a list of recent bioNumbers contributers
- Add explanation about how to add units, usage of ^ and (), e.g. sec^(-1).
Some work
- Enable contributing numbers in "batch" mode, either through an excel table or some other format. Enable to enter a new number based on the fields of a previous number. Add an option of add a similar number to the one just searched, that will keep the fields values and will only require the updates to be made.
- Automatically add keywords based on synonymous names and in general a semantic web
- Email corresponding author of referenced papers when a number is added and ask her/him to verify accuracy (done by automatic script, for example based on pubmed id).
- Wild card searches and google style fill in suggestions to help in finding entries
- A babel to help different communities who use different words to describe the same processes to find each others entries
- Option to change all values into scientific notation.
- Options to customize display (add remove fields from browse view)
Advanced features
- Make sure that each property will be google searchable. This will increase our exposure significantly. Maybe by creating a webpage for every record that will contain the data and will be searched by google's robots. We can possibly start with a "flat file" that will be robot accessible. Current flat file is at: bioNumbers flat file.
- Each entry will contain a link to a wiki page for discussion of the number (e.g. validity of the number, measurement method etc.). There will also be pages for discussion of larger but related topics (comments on class of entries). Following the example of wikipedia we would like to have discussions on editing, having tags etc.
- Enable automatic units conversion
- Automatically create comparison table between species for several user selected properties.
- a visualization tool for showing order of magnitude differences for properties with same units.
- Suggestions based on the query, "people searching for this number also searched for this number..." or "other numbers you might be interested in..."
- Vote for interesting numbers (and then interesting numbers list), each number would get a score between 1 and 10 for example
- Community score for reliability of number (receives non anonymous score of 1-10)
- Make the reference entries link to the articles. Furthermore have search for the entry when initially entered to help increase the reliability of the entered primary references.
New content or assignments to be done
- History pages with a story about some BioNumber: how it was "discovered" and what was its significance.
- Add link to bioNumbers from department website
- Publicize bioNumbers existence via short press releases in leading journal, announcements in conferences, large circulation web groups and list servers.
- create "Journal of BioNumbers" where authors could send short reports on numbers they measured, with details on the method and how it relates to previous measurements. Will be a peer reviewed journal published in electronic format and automatically linked to BioNumbers database.
Please add your suggestion....
Open issues regarding policy for discussion
- Use real name when adding entries (no anonymous submission of data). Will we need to confirm identity ? Will there be a restriction to people from scientific background (university/industry).?
- Will the database be curated mostly by the community or by dedicated BioNumbers people? probably a combination of both but where will the emphasis be?
- Do we want to allow people to edit numbers added by other people or just comment on them? How do you define the name of the contributer in that case?
- How reliable would a community voting on the reliability of a bioN be? we don't want to strengthen misconceptions
People contributing to BioNumbers
- Ron Milo - Harvard, sys. bio.
- Paul Jorgensen - Harvard, sys. bio.
- Michael Springer - Harvard, sys. bio.
- Tom Shimizu - Harvard, MCB
- Itai Yanai - Harvard, MCB
- Daniel Ramot - Stanford
- Lea Goentoro - Harvard, sys. bio.
- Griffin Weber - Harvard, HMS IT
- Alex Loewer - Harvard, sys. bio.
- Ricardo Vidal - University of Algarve, Portugal
- Austin Che - MIT
- Zeev Waks - Harvard, sys. bio.
- Alex Sigal - Caltech
- Ronen Zaidel-Bar - U. Wisconsin
- Ian Swinburne - Harvard, sys. bio.
- Cellina Cohen-Saidon - Weizmann Institute, Israel
- Sudhakaran Prabhakaran - Harvard, sys. bio.
