Temporal convolutional network for a Fast DNA mutation detection in breast cancer data.

ABSTRACT: Early detection of breast cancer can be achieved through mutation detection in DNA sequences, which can be acquired through patient blood samples. Mutation detection can be performed using alignment and machine learning techniques. However, alignment techniques require reference sequences, and machine learning techniques still cannot predict index mutation and require supporting tools. Therefore, in this research, a Temporal Convolutional Network (TCN) model was proposed to detect the type and index mutation faster and without reference sequences and supporting tools. The architecture of the proposed TCN model is specifically designed for sequential labeling tasks on DNA sequence data. This allows for the detection of the mutation type of each nucleotide in the sequence, and if the nucleot

SUBMITTER: Wisesty UN 

PROVIDER: S-EPMC10212167 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature