title: Discovering essential domains in essential genes.
abstract: Genes with indispensable functions are identified as essential; however, the traditional gene-level perspective of essentiality has several limitations. We hypothesized that protein domains, the independent structural or functional units of a polypeptide chain, are responsible for gene essentiality. If the essentiality of domains is known, the essential genes could be identified. To find such essential domains, we have developed an EM algorithm-based Essential Domain Prediction (EDP) Model. With simulated datasets, the model provided convergent results given different initial values and offered accurate predictions even with noise. We then applied the EDP model to six microbes and predicted 3,450 domains to be essential in at least one species, ranging 8-24 % in each species.
authors: State Key Laboratory of Genetic Engineering, Institute of Biostatistics, School of Life Science, Fudan University, 220 Handan Road, Shanghai, 200433, People's Republic of China.
authors: Yulan
authors: Y
authors: Lu
authors: Yao
authors: Y
authors: Lu
authors: Jingyuan
authors: J
authors: Deng
authors: Hui
authors: H
authors: Lu
authors: Long Jason
authors: LJ
authors: Lu
mesh_terms: D001419:Bacteria / Q000235:genetics; D003198:Computer Simulation; D030541:Databases, Genetic; D005658:Fungi / Q000235:genetics; D005798:Genes, Bacterial; D020043:Genes, Essential; D005800:Genes, Fungal; D023281:Genomics / Q000379:methods*; D008962:Models, Theoretical