1999
DOI: 10.1162/evco.1999.7.4.377
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Linkage Identification by Non-monotonicity Detection for Overlapping Functions

Abstract: This paper presents the linkage identification by non-monotonicity detection (LIMD) procedure and its extension for overlapping functions by introducing the tightness detection (TD) procedure. The LIMD identifies linkage groups directly by performing order-2 simultaneous perturbations on a pair of loci to detect monotonicity/non-monotonicity of fitness changes. The LIMD can identify linkage groups with at most order of k when it is applied to O(2k) strings. The TD procedure calculates tightness of linkage betw… Show more

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Cited by 95 publications
(71 citation statements)
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“…Strictly speaking, these results do not apply to the LINC algorithm of [MG99b] since the above analysis assumes that the backgrounds of probes are chosen independently, and this is not the case for the LINC algorithm. However, our empirical results show that these formulas are quite accurate when the backgrounds are chosen from a population.…”
Section: Corollary 2 If M Is a Hyperedge Of The Hypergraph And If Amentioning
confidence: 99%
See 4 more Smart Citations
“…Strictly speaking, these results do not apply to the LINC algorithm of [MG99b] since the above analysis assumes that the backgrounds of probes are chosen independently, and this is not the case for the LINC algorithm. However, our empirical results show that these formulas are quite accurate when the backgrounds are chosen from a population.…”
Section: Corollary 2 If M Is a Hyperedge Of The Hypergraph And If Amentioning
confidence: 99%
“…The order-2 version of this algorithm is similar to the LINC algorithm of [MG99b]. However, they start with a population of strings.…”
Section: Corollary 2 If M Is a Hyperedge Of The Hypergraph And If Amentioning
confidence: 99%
See 3 more Smart Citations