An Explicit Upper Bound for the Approximation Ratio of the Maximum Gene Regulatory Network Problem
One of the combinatorial models for the biological problem of inferring gene regulation networks is the Maximum Gene Regulatory Network Problem, shortly MGRN, proposed in . The problem is NP-hard , consequently the attention has shifted towards approximation algorithms, leading to a polynomial-time 1/2-approximation algorithm , while no upper bound on the possible approximation ratio was previously known.
In this paper we make a first step towards closing the gap between the best known and the best possible approximation factors, by showing that no polynomial-time approximation algorithm can have a factor better than 1 – (1/8) / (1+e2) unless RP=NP.
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- 1.Akutsu, T., Kuhara, S., Maruyama, O., Miyano, S.: Identification of gene regulatory networks by strategic gene disruptions and gene overexpressions. In: Proc. 9th Symp. on Discrete Algorithms (SODA), pp. 695–702 (1998)Google Scholar
- 5.Liang, S., Fuhrman, S., Somogyi, R.: Reveal, a general reverse engineering algorithm for inference of genetic network architectures. In: Proc. 5th Pacific Symposium on Biocomputing (PSB), pp. 18–29 (1998)Google Scholar
- 8.Trevisan, L.: Non-approximability results for optimization problems on bounded degree instances. In: Proc. 33rd Symp. Theory of Computing (STOC), pp. 453–461 (2001)Google Scholar