The 4th Joint International Conference on Deep Learning, Big Data and Blockchain (DBB 2023). Joint International Conference on Deep Learning, Big Data and Blockchain (4th : 2023 : Marrakech, Morocco ; Online)最新文献

PENN: Phase Estimation Neural Network on Gene Expression Data. PENN：基因表达数据的相位估计神经网络。

The 4th Joint International Conference on Deep Learning, Big Data and Blockchain (DBB 2023). Joint International Conference on Deep Learning, Big Data and Blockchain (4th : 2023 : Marrakech, Morocco ; Online) Pub Date : 2023-08-01 Epub Date: 2023-08-31 DOI: 10.1007/978-3-031-42317-8_5

Aram Ansary Ogholbake, Qiang Cheng

{"title":"PENN: Phase Estimation Neural Network on Gene Expression Data.","authors":"Aram Ansary Ogholbake, Qiang Cheng","doi":"10.1007/978-3-031-42317-8_5","DOIUrl":"10.1007/978-3-031-42317-8_5","url":null,"abstract":"With the continuous expansion of available transcriptomic data like gene expression, deep learning techniques are becoming more and more valuable in analyzing and interpreting them. The National Center for Biotechnology Information Gene Expression Omnibus (GEO) encompasses approximately 5 million gene expression datasets from animal and human subjects. Unfortunately, the majority of them do not have a recorded timestamps, hindering the exploration of the behavior and patterns of circadian genes. Therefore, predicting the phases of these unordered gene expression measurements can help understand the behavior of the circadian genes, thus providing valuable insights into the physiology, behaviors, and diseases of humans and animals. In this paper, we propose a novel approach to predict the phases of the un-timed samples based on a deep neural network architecture. It incorporates the potential periodic oscillation information of the cyclic genes into the objective function to regulate the phase estimation. To validate our method, we use mouse heart, mouse liver and temporal cortex of human brain dataset. Through our experiments, we demonstrate the effectiveness of our proposed method in predicting phases and uncovering rhythmic pattern in circadian genes.","PeriodicalId":94283,"journal":{"name":"The 4th Joint International Conference on Deep Learning, Big Data and Blockchain (DBB 2023). Joint International Conference on Deep Learning, Big Data and Blockchain (4th : 2023 : Marrakech, Morocco ; Online)","volume":"768 ","pages":"59-67"},"PeriodicalIF":0.0,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10540272/pdf/nihms-1931232.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41125860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The 4th Joint International Conference on Deep Learning, Big Data and Blockchain (DBB 2023) 第四届深度学习、大数据与区块链国际联合会议(DBB 2023)

The 4th Joint International Conference on Deep Learning, Big Data and Blockchain (DBB 2023). Joint International Conference on Deep Learning, Big Data and Blockchain (4th : 2023 : Marrakech, Morocco ; Online) Pub Date : 2023-01-01 DOI: 10.1007/978-3-031-42317-8

引用次数: 0

Exploring the Link Between Brain Waves and Sleep Patterns with Deep Learning Manifold Alignment. 利用深度学习 Manifold Alignment 探索脑电波与睡眠模式之间的联系。

The 4th Joint International Conference on Deep Learning, Big Data and Blockchain (DBB 2023). Joint International Conference on Deep Learning, Big Data and Blockchain (4th : 2023 : Marrakech, Morocco ; Online) Pub Date : 2023-01-01 Epub Date: 2023-08-31 DOI: 10.1007/978-3-031-42317-8_7

Yosef Bernardus Wirian, Yang Jiang, Sylvia Cerel-Suhl, Jeremiah Suhl, Qiang Cheng

{"title":"Exploring the Link Between Brain Waves and Sleep Patterns with Deep Learning Manifold Alignment.","authors":"Yosef Bernardus Wirian, Yang Jiang, Sylvia Cerel-Suhl, Jeremiah Suhl, Qiang Cheng","doi":"10.1007/978-3-031-42317-8_7","DOIUrl":"https://doi.org/10.1007/978-3-031-42317-8_7","url":null,"abstract":"Medical data are often multi-modal, which are collected from different sources with different formats, such as text, images, and audio. They have some intrinsic connections in meaning and semantics while manifesting disparate appearances. Polysomnography (PSG) datasets are multi-modal data that include hypnogram, electrocardiogram (ECG), and electroencephalogram (EEG). It is hard to measure the associations between different modalities. Previous studies have used PSG datasets to study the relationship between sleep disorders and quality and sleep architecture. We leveraged a new method of deep learning manifold alignment to explore the relationship between sleep architecture and EEG features. Our analysis results agreed with the results of previous studies that used PSG datasets to diagnose different sleep disorders and monitor sleep quality in different populations. The method could effectively find the associations between sleep architecture and EEG datasets, which are important for understanding the changes in sleep stages and brain activity. On the other hand, the Spearman correlation method, which is a common statistical technique, could not find the correlations between these datasets.","PeriodicalId":94283,"journal":{"name":"The 4th Joint International Conference on Deep Learning, Big Data and Blockchain (DBB 2023). Joint International Conference on Deep Learning, Big Data and Blockchain (4th : 2023 : Marrakech, Morocco ; Online)","volume":"768 ","pages":"81-90"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11210370/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141474409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

CNN Architectures: An Evolution CNN架构:一个进化

The 4th Joint International Conference on Deep Learning, Big Data and Blockchain (DBB 2023). Joint International Conference on Deep Learning, Big Data and Blockchain (4th : 2023 : Marrakech, Morocco ; Online) Pub Date : 2021-12-10 DOI: 10.1201/9781003185635-6