Difference between revisions of "5/20 ask"
imported>S (Created page with "<p>실험의 목적 : 데이터 수집<br /> 최종 목적 : 생물 시스템 이해<br /> y2h<br /> scale free network ; 효율 vs 위험(one to one, one to many)</p> <p>archit...") |
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| − | <p> | + | <p>Bioprogramming</p> |
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| − | <p> | + | <p>why do we programming : to simulate (programming(architect) <=> coding(writing))</p> |
| − | <p> | + | <p>why do we do experiments : to collect the data</p> |
| − | <p>to | + | <p> - IP,Y2H -> experimental tech to study interaction</p> |
| − | <p> | + | <p>Final goal : understanding the biological system</p> |
| − | <p> | + | <p> - architecture (network) : data=>node & interaction</p> |
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| − | <p> | + | <p> - modeling = we can simplify and make the relationship clear by modeling the system. but careful not to lose too many data.</p> |
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| + | <p> - scale free network : 효율 vs 위험(one to one, one to many)</p> | ||
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| + | <p>(A <strong>scale-free network</strong> is a <a href="https://en.wikipedia.org/wiki/Complex_network" title="Complex network">network</a> whose <a href="https://en.wikipedia.org/wiki/Degree_distribution" title="Degree distribution">degree distribution</a> follows a <a href="https://en.wikipedia.org/wiki/Power_law" title="Power law">power law</a>, at least asymptotically. That is, the fraction <em>P</em>(<em>k</em>) of nodes in the network having <em>k</em> connections to other nodes goes for large values of <em>k</em> as</p> | ||
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| + | <p><img alt=" | ||
| + | P(k) \ \sim \ k^\boldsymbol{-\gamma} | ||
| + | " src="https://upload.wikimedia.org/math/f/7/9/f793f6d9a7fa1c45426ae53113c4c15e.png" /></p> | ||
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| + | <p>where <img alt="\gamma" src="https://upload.wikimedia.org/math/3/3/4/334de1ea38b615839e4ee6b65ee1b103.png" /> is a parameter whose value is typically in the range 2 < <img alt="\gamma" src="https://upload.wikimedia.org/math/3/3/4/334de1ea38b615839e4ee6b65ee1b103.png" /> < 3, although occasionally it may lie outside these bounds.<span style="font-size:10.8333px; line-height:17.3333px"> from wiki)</span></p> | ||
Latest revision as of 00:19, 30 May 2016
Bioprogramming
why do we programming : to simulate (programming(architect) <=> coding(writing))
why do we do experiments : to collect the data
- IP,Y2H -> experimental tech to study interaction
Final goal : understanding the biological system
- architecture (network) : data=>node & interaction
- modeling = we can simplify and make the relationship clear by modeling the system. but careful not to lose too many data.
- scale free network : 효율 vs 위험(one to one, one to many)
(A scale-free network is a network whose degree distribution follows a power law, at least asymptotically. That is, the fraction P(k) of nodes in the network having k connections to other nodes goes for large values of k as
where 
is a parameter whose value is typically in the range 2 < < 3, although occasionally it may lie outside these bounds. from wiki)
