Ab initio gene prediction for protein-coding regions

ABSTRACT: Abstract

Motivation

Ab initio gene prediction in nonmodel organisms is a difficult task. While many ab initio methods have been developed, their average accuracy over long segments of a genome, and especially when assessed over a wide range of species, generally yields results with sensitivity and specificity levels in the low 60% range. A common weakness of most methods is the tendency to learn patterns that are species-specific to varying degrees. The need exists for methods to extract genetic features that can distinguish coding and noncoding regions that are not sensitive to specific organism characteristics.

Results

A new method based on a neural network (NN) that uses a collection of sensors to create input features is presented. It is shown that accurate prediction

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PROVIDER: S-EPMC10448985 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature