Identification of Autistic Risk Genes Using Developmental Brain Gene Expression Data

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review

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Author(s)

  • Yu-An Huang
  • Zhu-Hong You
  • Shanwen Zhang
  • Chang-Qing Yu
  • Wenzhun Huang

Related Research Unit(s)

Detail(s)

Original languageEnglish
Title of host publicationIntelligent Computing Theories and Application - 16th International Conference, ICIC 2020, Proceedings
EditorsDe-Shuang Huang, Kang-Hyun Jo
PublisherSpringer Nature Switzerland AG
Pages326-338
VolumePart II
ISBN (Electronic)9783030608026
ISBN (Print)9783030608019
Publication statusPublished - Oct 2020

Publication series

NameLecture Notes in Computer Science
Volume12464
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Title16th International Conference on Intelligent Computing (ICIC 2020)
PlaceItaly
CityBari
Period2 - 5 October 2020

Abstract

Recently, the serious impairments of ASD cause a series of pending issues to increase a major burden of health and finance globally. In this work, we propose an effective convolutional neural network (CNN) - based model to identify the potential autistic risk genes based on the developmental brain gene expression profiles. Based on the 10-fold cross validations, the simulation experiments demonstrate that the proposed model shows supreme classification results as compared to the other state-of-the-art classifiers. In such an imbalanced dataset, the proposed CNN model achieves the F1-score of 63.07 ± 3.9 and the area under ROC curve of 0.6940. In case study, 70% out of the top-10 predicted risk genes have been confirmed to increase the risk of developing ASD via published literatures. The effectiveness enables our model to serve as a candidate tool for accelerating the identification of autistic genetic abnormalities.

Research Area(s)

  • Autism spectrum disorders (ASD), Autistic biomarkers, Developmental brain gene expression data, Gene prioritization

Citation Format(s)

Identification of Autistic Risk Genes Using Developmental Brain Gene Expression Data. / Huang, Zhi-An; Huang, Yu-An; You, Zhu-Hong; Zhang, Shanwen; Yu, Chang-Qing; Huang, Wenzhun.

Intelligent Computing Theories and Application - 16th International Conference, ICIC 2020, Proceedings. ed. / De-Shuang Huang; Kang-Hyun Jo. Vol. Part II Springer Nature Switzerland AG, 2020. p. 326-338 (Lecture Notes in Computer Science; Vol. 12464).

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review