The effects of knocking out (deleting) one gene (from weakly to strongly
connected) in a 10 gene random Boolean network.
Note: The new network with 9 genes is renumbered to close the gap.
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key to network definition
__gene number n to 0
/ __number of inputs, k
/ / __input genes
/ / / __rule in hex
/ / / /
7. 4, - 5 0 1 1, ed1a
| network graph
Nodes are scaled according to their number of inputs.
| the basin of attraction field
showing attractor patterns.
| the meta-graph and jump-table
showing the probability of jumps between attractors(link thickness)
resulting from 1 bit purturbations to attractor states.
Note: short stubs are self jumps, a measure of stability.
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Original 10 gene network
9. 1, - - - - 5, 01
8. 2, - - - 7 2, 0a
7. 4, - 5 0 1 1, ed1a
6. 1, - - - - 1, 02
5. 2, - - - 4 0, 04
4. 1, - - - - 1, 01
3. 1, - - - - 8, 01
2. 1, - - - - 1, fe
1. 3, - - 1 0 0, 72
0. 5, 3 7 2 0 2, 56ca15b6
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1 2 3 P J Volume Self
1: 9 . 1 1 10 564=55.08% 90.00%
2: 4 6 . 1 10 268=26.17% 60.00%
3: 2 2 6 1 10 192=18.75% 60.00%
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Knockout gene 9
one input, no output
8. 2, - - - 7 2, 0a
7. 4, - 5 0 1 1, ed1a
6. 1, - - - - 1, 02
5. 2, - - - 4 0, 04
4. 1, - - - - 1, 01
3. 1, - - - - 8, 01
2. 1, - - - - 1, fe
1. 3, - - 1 0 0, 72
0. 5, 3 7 2 0 2, 56ca15b6
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1 2 3 P J Volume Self
1: 8 . 1 1 9 282=55.08% 88.89%
2: 4 5 . 1 9 134=26.17% 55.56%
3: 2 2 5 1 9 96=18.75% 55.56%
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Knockout gene 4
1 input, 1 output
8. 1, - - - - 4, 01
7. 2, - - - 6 2, 0a
6. 4, - 4 0 1 1, ed1a
5. 1, - - - - 1, 02
4. 1, - - - - 0, 00
3. 1, - - - - 7, 01
2. 1, - - - - 1, fe
1. 3, - - 1 0 0, 72
0. 5, 3 6 2 0 2, 56ca15b6
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1 2 P J Volume Self
1: 8 1 1 9 416=81.25% 88.89%
2: 4 5 1 9 96=18.75% 55.56%
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Knockout gene 0
strongly linked
8. 1, - - - - 4, 01
7. 2, - - - 6 1, 0a
6. 3, - - 4 0 0, c7
5. 1, - - - - 0, 02
4. 1, - - - - 3, 03
3. 1, - - - - 0, 01
2. 1, - - - - 7, 01
1. 1, - - - - 0, fe
0. 2, - - - 0 0, 01
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