Exploring Neural Networks and Related Visualization Techniques in Gene Expression Data.

Abstract:

:Over the past decade, neural networks have become one of the cutting-edge methods in various research fields, outshining specifically in complex classification problems. In this paper, we propose two main contributions: first, we conduct a methodological study of neural network modeling for classifying biological traits based on structured gene expression data. Then, we suggest an innovative approach for utilizing deep learning visualization techniques in order to reveal the specific genes important for the correct classification of each trait within the trained models. Our data suggests that this approach have great potential for becoming a standard feature importance tool used in complex medical research problems, and that it can further be generalized to various structured data classification problems outside the biological domain.

journal_name

Front Genet

journal_title

Frontiers in genetics

authors

Wilentzik Müller R,Gat-Viks I

doi

10.3389/fgene.2020.00402

subject

Has Abstract

pub_date

2020-05-15 00:00:00

pages

402

issn

1664-8021

journal_volume

11

pub_type

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