Question

Which of the following is untrue about PredictionUsing NeuralNetworks for Gene Prediction?

(a) A neural network   is a statistical model with a special architecture for pattern recognition and classification

(b) It is composed of a network of mathematical variables

(c) They resembles ab initio approaches

(d) The variables in NeuralNetworks resemble the biological nervous system, with variables or nodes connected by weighted functions that are analogous to synapses

This question was posed to me in class test.

The above asked question is from Gene Prediction in Eukaryotes topic in division Gene and Promoter Prediction of Bioinformatics

Answer 1

Correct answer is (c) They resembles ab initio approaches

Easy explanation: Aspect of the model that makes it look like a biological neural network is its ability to “learn” and then make predictions after being trained. The network is able to process information and modify parameters of the weight functions between variables during the training stage. Once it is trained, it is able to make automatic predictions about the unknown. This is quite different than the ab initio methods.