The International Conference on Intelligent Biology and Medicine 2019 (ICIBM 2019): computational methods and applications in medical genomics-Reference-Cited by-同舟云学术

The International Conference on Intelligent Biology and Medicine 2019 (ICIBM 2019): computational methods and applications in medical genomics

Published:2020-04 Issue:S5 Volume:13 Page:
ISSN:1755-8794
Container-title:BMC Medical Genomics
language:en
Short-container-title:BMC Med Genomics

Author:

Zhang Chi,Mathé Ewy,Ning Xia,Zhao Zhongming,Wang Kai,Li Lang,Guo Yan

Abstract

AbstractIn this editorial, we briefly summarized the International Conference on Intelligent Biology and Medicine 2019 (ICIBM 2019) that was held on June 9–11, 2019 at Columbus, Ohio, USA. We further introduced the 19 research articles included in this supplement issue, covering four major areas, namely computational method development, genomics analysis, network-based analysis and biomarker prediction. The selected papers perform cutting edge computational research applied to a broad range of human diseases such as cancer, neural degenerative and chronic inflammatory disease. They also proposed solutions for fundamental medical genomics problems range from basic data processing and quality control to functional interpretation, biomarker and drug prediction, and database releasing.

Publisher

Springer Science and Business Media LLC

Subject

Genetics (clinical),Genetics

Link

http://link.springer.com/content/pdf/10.1186/s12920-020-0678-1.pdf

Reference20 articles.

1. Mathé E, Zhang C, Wang K, Ning X, Guo Y, Zhao Z. The International Conference on Intelligent Biology and Medicine 2019 (ICIBM 2019): conference summary and innovations in genomics. BMC Med Genomics. 2020;13(Suppl 5). https://doi.org/10.1186/s12920-020-0678-1.

2. Li M, Liu M, Bin Y, Xia J. Prediction of circRNA-disease associations based on inductive matrix completion. BMC Med Genomics. 2020;13(Suppl 5). https://doi.org/10.1186/s12920-020-0679-0.

3. Li Y, Wang G, Tan X, Ouyang J, Zhang M, Song X, Liu Q, Leng Q, Chen L, Xie L. ProGeo-neo: a Customized Proteogenomic Workflow for Neoantigen Prediction and Selection. BMC Med Genomics. 2020;13(Suppl 5). https://doi.org/10.1186/s12920-020-0683-4.

4. Mostavi M, Chiu Y-C, Huang Y, Chen Y. Convolutional neural network models for cancer type prediction based on gene expression. BMC Med Genomics. 2020;13(Suppl 5). https://doi.org/10.1186/s12920-020-0677-2.

5. Cai X, Chang L-B, Potter J, Song C. Adaptive Fisher method detects dense and sparse signals in association analysis of SNV sets. BMC Med Genomics. 2020;13(Suppl 5). https://doi.org/10.1186/s12920-020-0684-3.

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