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An Order Independent Algorithm for Inferring Gene Regulatory Network Using Quantile Value for Conditional Independent Tests
| Content Provider | Semantic Scholar |
|---|---|
| Author | Mahmoudi, Sayyed Hadi Aghdam, Rosa Eslahchi, Changiz |
| Copyright Year | 2020 |
| Abstract | Background: In recent years, due to the difficulty and inefficiency of experimental methods, numerous computational methods have been introduced for inferring structure of Gene Regulatory Networks (GRNs). Bayesian network is one of the popular methods in this field, however, still has many drawbacks and there is still a great space to be improved. For example, the Path Consistency (PC)-based algorithms as Bayesian network methods are still sensitive to the ordering of nodes i.e. different node orders results in different network structures. The second is that the networks inferred by these methods are highly dependent on the threshold used for independence testing. Also, it is still a challenge to select the set of conditional genes in an optimal way, which affects the performance and computation complexity of the PC-based algorithm. |
| File Format | PDF HTM / HTML |
| DOI | 10.21203/rs.2.21700/v1 |
| Alternate Webpage(s) | https://assets.researchsquare.com/files/62613a3c-e4b6-4fa0-8dc0-27d760f6206f/v1/Manuscript.pdf |
| Alternate Webpage(s) | https://doi.org/10.21203/rs.2.21700%2Fv1 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
