Report title: Disease gene prediction based on complex network seabet crypto casino and deep learning
Report seabet crypto casino: 3:00 pm on April 12, 2019
Reporting location: Conference Room 308, Computer seabet crypto casino, School Headquarters
Reporter: Dr. Luo Ping
Abstract: Complex diseases are often caused by variations in a group of genes，We call these genes disease genes。Identifying disease genes can help us understand the principles of disease formation，This is very helpful for early diagnosis of diseases and drug development。Because using biological experiments to identify disease genes requires a lot of time and money，So scientific researchers have proposed many algorithms，I hope to use computers to predict disease genes。The predictions from these algorithms can help biochemists optimize their experiments，Thus accelerating the identification of disease genes。Currently，A variety of biological data can be used to predict disease genes，How to better integrate these data is the key to accurately predicting disease genes。In our research group，Network seabet crypto casino methods and deep learning are combined，Complete the fusion of different types of data，Thus achieving accurate prediction of disease genes。In this report，I will introduce several studies on disease gene prediction during my Ph.D.。Part of the research focuses on data fusion based on deep learning，Another part of the research focuses on the seabet crypto casino of clinical gene expression data。
Personal profile: Graduated from Hunan University in 2010, majoring in computer science and technology，Received a master’s degree in biomedical engineering from Beijing Institute of Technology in 2015，Currently studying for a PhD at the University of Saskatchewan, Canada。His main research areas are: disease gene prediction、Application of deep learning in bioinformatics、Complex network seabet crypto casino、seabet crypto casino of multi-omics data。
Academic part-seabet crypto casino job:IEEETNNNLS，Neurocomputingetc.
Title: Disease gene prediction based on complex network seabet crypto casino and deep learning
seabet crypto casino: Apr 12, 2019, 3 pm
Location: Room 308, Computer seabet crypto casino
Speaker: Dr. Ping Luo
Abstract:Complexdiseases are caused by the malfunction of a group of genes (known as disease genes) and identifying them can help us understand the mechanism of diseases, which has many applications such as early diagnosis and drug development. Since experimental techniques for identifying disease genes are time-consuming and expensive, many computational algorithms have been developed to help scientists optimize the in-depth experimental validation and accelerate the identification of true disease genes.Currently, various types of data can be used to predict disease genes, and properly integrating them is the key issue for accurate prediction. In our group, network seabet crypto casino algorithms and deep learning models are combined to fuse different types of data and enhance the prediction. In this talk, I will present a few studies of my Ph.D. program in disease genes prediction. Some of them use deep learning models to fuse the data, while others focus on clinical expression data and achieve the prediction by classic machine learning models.
About the speaker: Hereceived his bachelor's degree in Computer Science and Technology from Hunan University in 2010 and master's degree in Biomedical Engineering from Beijing Institute of Technology in 2015. Currently, he is working toward the Ph.D. degree in the Division of Biomedical Engineering at the University of Saskatchewan, Saskatoon, Canada. His research interests include disease gene prediction, seabet crypto casino learning in Bioinformatics, biomolecular network analytics, and multi-omics data analytics.
Academic job:reviewer ofIEEE TNNLS,Neurocomputingetc.
