Proceedings of the 2022 6th International Conference on Computational Biology and Bioinformatics最新文献

Cross-Disease Bioinformatics Analysis to Elucidate Roles of Astrocytic Pathways Regulating Neuroinflammation in Autism Spectrum Disorder 跨疾病生物信息学分析阐明星形细胞通路在自闭症谱系障碍中调节神经炎症的作用

Proceedings of the 2022 6th International Conference on Computational Biology and Bioinformatics Pub Date : 2022-12-26 DOI: 10.1145/3589437.3589441

Valentina Zhang

{"title":"Cross-Disease Bioinformatics Analysis to Elucidate Roles of Astrocytic Pathways Regulating Neuroinflammation in Autism Spectrum Disorder","authors":"Valentina Zhang","doi":"10.1145/3589437.3589441","DOIUrl":"https://doi.org/10.1145/3589437.3589441","url":null,"abstract":"While neuroinflammation has been implicated as a significant component in autism spectrum disorder (ASD) and its etiology [5], the molecular mechanism in the disease is not well understood. Astrocytes are the most abundant glial cell type in the central nervous system (CNS). They respond to inflammatory signals and can themselves promote inflammation, which makes them important players in neurologic diseases [19]. Advances in single-cell genomics and transcriptomics have fueled the identification of novel pathways that control astrocyte functions associated with chronic neuroinflammatory disorders such as multiple sclerosis (MS) [2]. These advances present an opportunity to study the common molecular mechanisms underlying neuroinflammation in both ASD and MS. In this paper, we analyze and characterize the common astrocytes subpopulations shared in both ASD and MS using the large-scale single-cell RNA-seq expression data collected from postmortem brain samples of subjects diagnosed with ASD (PRJNA434002) and MS (PRJNA544731). Batch correction [11] was implemented using Harmony [10] to strengthen the unbiased analysis. Seurat and SC3 were used for the identification of common astrocyte clusters and their marker genes; DESeq2 for disease-specific differentially expressed gene (DEG) analysis; Monocle and Enrichr for trajectory, enrichment, and ingenuity pathway analysis (IPA) of DEGs. Finally, GSEA was performed on IPSC bulk-RNA sequencing data to further characterize the common pro-inflammatory astrocytes subpopulations using transcriptional signatures of secondary progressive MS. This research revealed that oxidative stress-induced ferroptosis plays a pronounced role in the pathological astrocyte subpopulations common to both diseases. The discovery enables us to hypothesize that FTH1, SLC7A11, SAT1, CP, FTL and MAPK signaling are potentially involved in ASD pathophysiology, which could be further explored as novel targets for disease intervention.","PeriodicalId":119590,"journal":{"name":"Proceedings of the 2022 6th International Conference on Computational Biology and Bioinformatics","volume":"278 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121036126","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Customized SEIR Mathematical Model to Predict the trends of Vaccination for Spread of COVID-19 自定义SEIR数学模型预测COVID-19疫苗接种趋势

Proceedings of the 2022 6th International Conference on Computational Biology and Bioinformatics Pub Date : 2022-12-26 DOI: 10.1145/3589437.3589450

A. Alluhaidan, R. C. Poonia, P. P, Marwan Alluhaidan

引用次数: 0

Wavelet-Based Microbiome Correlations of Host Traits 基于小波的宿主性状微生物组相关性研究

Proceedings of the 2022 6th International Conference on Computational Biology and Bioinformatics Pub Date : 2022-12-26 DOI: 10.1145/3589437.3589440

Adeethyia Shankar, Stephanie Chang, Yongzhong Zhao, Xiaodi Wang, Tong Liu

{"title":"Wavelet-Based Microbiome Correlations of Host Traits","authors":"Adeethyia Shankar, Stephanie Chang, Yongzhong Zhao, Xiaodi Wang, Tong Liu","doi":"10.1145/3589437.3589440","DOIUrl":"https://doi.org/10.1145/3589437.3589440","url":null,"abstract":"The gut microbiome is composed of a plethora of microorganisms, and these microbes contribute to overall human health. It has been shown that dysbiosis of the microbiome is associated with certain diseases, including colorectal cancer and diabetes, yet the role of the microbiome is still little-known. Here, we aim to develop a novel wavelet-based framework to dissect the microbiome correlations of host traits. Due to the clinical nature of the biological dataset, we utilize the discrete wavelet transform (DWT)—enabling us to impute sparse matrices and decompose the data into different frequency components. We further carry out regressions of host traits with the microbiome relative abundances followed by computing correlations between the regression-predicted trait values. Moreover, we visualize these microbiome correlations of host traits with heat maps and build microbiome correlations of host traits network. As a result, our results revealed that microbiome correlations of host traits are prevalent. Our wavelet-based microbiome correlations of host traits analytic framework aims to lay the foundation for further causality analysis of the complex interplays between the microbiome and host traits.","PeriodicalId":119590,"journal":{"name":"Proceedings of the 2022 6th International Conference on Computational Biology and Bioinformatics","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128837185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Utilizing Data Clustering for Hypotheses Discovery in Multimodal Exercise and Health Interventions with Limited Sample Size 利用数据聚类在有限样本量的多模式运动和健康干预中发现假设

Proceedings of the 2022 6th International Conference on Computational Biology and Bioinformatics Pub Date : 2022-12-26 DOI: 10.1145/3589437.3589446

Mckay Russell, Guanrong Cai, Steven Merino, Clemente Rodriguez, Zachary Scholefield, J. Moore, George Salem, Chengwei Lei

引用次数: 0

Application of Convolutional Neural Network in Raman Spectral Recognition of Covid-19 卷积神经网络在新型冠状病毒拉曼光谱识别中的应用

Proceedings of the 2022 6th International Conference on Computational Biology and Bioinformatics Pub Date : 2022-12-26 DOI: 10.1145/3589437.3589448

Wandan Zeng, Mangmang Hang

{"title":"Application of Convolutional Neural Network in Raman Spectral Recognition of Covid-19","authors":"Wandan Zeng, Mangmang Hang","doi":"10.1145/3589437.3589448","DOIUrl":"https://doi.org/10.1145/3589437.3589448","url":null,"abstract":"The outbreak of COVID-19 has lasted for two years. The rapid spread and fatal variability of COVID-19 pose a great threat to human survival. Today, the existing high-tech medical technology has not found a direct specific drug. Therefore, efficient diagnostic techniques and methods play a key role in controlling the spread of COVID-19 and managing patients' conditions. Deep learning technology can learn implicit samples of data. This paper mainly studies the nonlinear relationship between the serum Raman spectrum data of new crown and healthy people by using convolutional neural network, effectively expand the samples of training set by using data enhancement method, standardize the spectral data, smooth denoising by savitzky Golay method, and construct the prediction model based on convolutional neural network after principal component analysis. Compared with other traditional machine learning algorithms, the features extracted by convolution neural network through convolution layer, batch standardization layer and pooling layer are more comprehensive, which can effectively improve the accuracy and speed of COVID-19 recognition and classification. The experimental results show that convolution neural network has a higher screening accuracy for COVID-19, and the accuracy rate is 98.39%, It is proved that Raman spectroscopy combined with deep learning is effective and feasible in screening COVID-19.","PeriodicalId":119590,"journal":{"name":"Proceedings of the 2022 6th International Conference on Computational Biology and Bioinformatics","volume":"15 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115497785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Research on Cell Aging Based on Reprogramming Senescent Cells by Inhibiting Pro-Inflammatory TNF/Edn1 Pathway as a Potential Treatment of Age-Related Diseases 抑制促炎因子TNF/Edn1通路对衰老细胞重编程的细胞衰老研究

Proceedings of the 2022 6th International Conference on Computational Biology and Bioinformatics Pub Date : 2022-12-26 DOI: 10.1145/3589437.3589442

Siwen Cui, Virgia Wang

{"title":"Research on Cell Aging Based on Reprogramming Senescent Cells by Inhibiting Pro-Inflammatory TNF/Edn1 Pathway as a Potential Treatment of Age-Related Diseases","authors":"Siwen Cui, Virgia Wang","doi":"10.1145/3589437.3589442","DOIUrl":"https://doi.org/10.1145/3589437.3589442","url":null,"abstract":"Aging is the process of progressive cellular senescence and tissue degeneration that eventually leads to organismal death. This degeneration manifests itself in the forms of various age-related diseases, such as neurodegenerative disorders, diabetes, and chronic inflammation. Although initially believed to be the inevitable final fate of human life, mounting evidence demonstrate the possibility to extend lifespan and decelerate the process of aging. From these observations, the question of whether aging can be reversed through cellular rejuvenation inspires further research. In humans, germline cells activate a natural program of rejuvenation in fertilization events, suggesting the possibility of cellular age reversal. While the nuance of the underlying mechanism is unclear, reprogramming the epigenome during aging seems to play central role.This project aims to identify candidate age reprogramming genes as alternatives to OSKM through directly comparing senescent and young cells (with gene expression data from human bone marrow-derived stromal cells, mouse retinal ganglion cells, and mouse fibroblasts).","PeriodicalId":119590,"journal":{"name":"Proceedings of the 2022 6th International Conference on Computational Biology and Bioinformatics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128815979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Augmented Pre-Segmentation Method for Medical Image Dataset Based on Machine Vision 基于机器视觉的医学图像数据集增强预分割方法

Proceedings of the 2022 6th International Conference on Computational Biology and Bioinformatics Pub Date : 2022-12-26 DOI: 10.1145/3589437.3589444

Xuan Huang, Zhi-yun Yang, Jiawei Yang, Dapeng Zou, Han Sun

引用次数: 0

Decoded Visual Stimulus Studies Using Functional Magnetic Resonance Imaging 使用功能性磁共振成像解码视觉刺激研究

Proceedings of the 2022 6th International Conference on Computational Biology and Bioinformatics Pub Date : 2022-12-26 DOI: 10.1145/3589437.3589445

Junzhu Ma, Yiming Zhu

引用次数: 0

Interpreting Arrhythmia Classification Using Deep Neural Network and CAM-Based Approach 利用深度神经网络和基于cam的方法解释心律失常分类

Proceedings of the 2022 6th International Conference on Computational Biology and Bioinformatics Pub Date : 2022-12-26 DOI: 10.1145/3589437.3589443

Niken Prasasti Martono, Toru Nishiguchi, H. Ohwada

引用次数: 0

High-Resolution Ultrasonic System for Measuring Temperature in Soft Tissue-Mimicking Phantoms Using a FPGA Platform 基于FPGA平台的高分辨率超声软组织温度测量系统

Proceedings of the 2022 6th International Conference on Computational Biology and Bioinformatics Pub Date : 2022-12-26 DOI: 10.1145/3589437.3589447

D. Garcia Nocetti, P. A. Acevedo Contla, Martin Fuentes Cruz, Adalberto Joel Duran Ortega, Hugo Rolon Acevedo

{"title":"High-Resolution Ultrasonic System for Measuring Temperature in Soft Tissue-Mimicking Phantoms Using a FPGA Platform","authors":"D. Garcia Nocetti, P. A. Acevedo Contla, Martin Fuentes Cruz, Adalberto Joel Duran Ortega, Hugo Rolon Acevedo","doi":"10.1145/3589437.3589447","DOIUrl":"https://doi.org/10.1145/3589437.3589447","url":null,"abstract":"This article describes the design and development of a high-resolution ultrasonic system for measuring temperature in soft tissue-mimicking phantoms using a FPGA module. The system uses a DE0-Nano FPGA development platform, a 2x16 LCD display, an optical encoder, two PVDF ultrasonic transducers, and an External Circuit module. In the experimental implementation, a distance was set between the transducers and an operating temperature range of 35 ºC to 40 ºC with a resolution of 0.1 ºC was selected, considering the initial value of the range as the reference temperature. The difference between flight times with respect to the initial temperature flight time, produces a narrow pulse that is converted into a DC voltage, This DC voltage is proportional to the change in temperature. The system is based on a reconfigurable architecture; this allows the transmission burst and the reception control pulses to be programmable, allowing its adjustment for different operation ranges. The experimentation was carried out in an experimental tank filled with distilled and degassed water with a controlled temperature, one piece of soft tissue-mimicking phantom (2.5x2.5x3.0 cm) and a support structure to assemble the PVDF transducers separated 3.0 cm from each other. The system acquires 100 samples per second, calculates the average temperature with a polynomial fit curve and displays the result with a refresh rate of one second. Due to its design characteristics it is feasible to extend its application to measure temperature in biological soft tissue.","PeriodicalId":119590,"journal":{"name":"Proceedings of the 2022 6th International Conference on Computational Biology and Bioinformatics","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125676896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0