Sentence examples for go functions in from inspiring English sources

The most enriched GO functions in the genes correlating with CT are: DNA metabolic process (GO: 0006259), antigenic variation (GO: 0020033), protein amino acid dephosphorylation (GO: 0006470) and cell-cell adhesion and cytoadherence to microvasculature (GO: 0016337).

Although experimentally proven functional residues are scarce, we show here that Evolutionary Trace (ET) rankings of residue importance are sufficient to build 3D templates, match them, and then assign Gene Ontology (GO) functions in enzymes and non-enzymes alike.

GO functions in BP differ greatly among species groups (Table 5).

Lge genes were enriched (p<0.01) for GO functions in cell cycle processes, including DNA replication and repair, chromatin structure, and the cytoskeleton.

Whi genes were enriched (p<0.01) for GO functions in growth related processes, including cytosolic or mitochondrial ribosome assembly and function, mitochondrial function, and metabolism.

Several terms have defined: A: set of annotated GO functions (in test set) P: set of predicted GO functions F: GO functions in train set So, we can establish: (1) (2) (3) (4) then, define: (5) (6) The variance of the reconstructed annotation was computed in order to see if it is affected by the random split choice.

The only enriched GO function in the olfactory bulb is "regulation of cell cycle", which could be affected by processes that modulate the rate or extent of progression through the cell cycle.

A novel framework for the online estimation of cost-to-go functions in wireless networks was proposed.

We propose a novel approach for the online learning of cost-to-go functions in networks modeled via large finite state machines (FSM).

We now present an algorithm for the online learning of cost-to-go functions in wireless networks from the observation of a state-cost trajectory of the associated FSM.

In fact, the estimation of cost-to-go functions in traditional online learning (e.g., Q-learning and Reinforcement learning[10 12]) requires sufficient observation of a sample-path such that it hits all the states of the FSM a large number of times.