2021 IEEE 9th International Conference on Bioinformatics and Computational Biology (ICBCB)最新文献_第2页

Investigating Oscillatory Activity in Cerebral Cortex during Affective Picture Processing 情感图像处理过程中大脑皮层振荡活动的研究

2021 IEEE 9th International Conference on Bioinformatics and Computational Biology (ICBCB) Pub Date : 2021-05-25 DOI: 10.1109/ICBCB52223.2021.9459213

Zhu Ning, Kai Yang, Bin Yan, Li Tong, Jun Shu, Ying Zeng

{"title":"Investigating Oscillatory Activity in Cerebral Cortex during Affective Picture Processing","authors":"Zhu Ning, Kai Yang, Bin Yan, Li Tong, Jun Shu, Ying Zeng","doi":"10.1109/ICBCB52223.2021.9459213","DOIUrl":"https://doi.org/10.1109/ICBCB52223.2021.9459213","url":null,"abstract":"Emotion plays an important role in people's life. Previous studies have revealed that the characteristics of high frequency bands of Electroencephalogram (EEG) have shown good performance in emotion recognition. However, there is a lack of clear and unified conclusions about which brain regions to select for feature extraction. In this study, pleasant, neutral, unpleasant and scrambled pictures selected from International Affective Picture System (IAPS) were presented to subjects. In order to improve the spatial resolution, source estimation algorithm was used to reconstruct the cortical response in the processing of affective pictures. Oscillation activities of different frequency bands in the key brain regions were studied in cerebral cortex. The results showed that the activation of the brain was the weakest under scrambled condition. Referring to neutral condition, the energy of Alpha, Beta and Gamma bands under pleasant condition increased significantly in the bilateral middle temporal gyrus, middle frontal gyrus and prefrontal gyrus, while the energy of Alpha and Beta bands under unpleasant condition decreased significantly in the left middle occipital gyrus and bilateral middle temporal gyrus. These results provide a scientific basis for the selection of electrodes and frequency bands in emotion recognition based on EEG signals.","PeriodicalId":178168,"journal":{"name":"2021 IEEE 9th International Conference on Bioinformatics and Computational Biology (ICBCB)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125181147","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

Identification of Potentially Therapeutic Target Genes in Ovarian Cancer via Bioinformatic Approach 利用生物信息学方法鉴定卵巢癌潜在治疗靶基因

2021 IEEE 9th International Conference on Bioinformatics and Computational Biology (ICBCB) Pub Date : 2021-05-25 DOI: 10.1109/ICBCB52223.2021.9459203

Liao Chengzhang, Xu Jiucheng

{"title":"Identification of Potentially Therapeutic Target Genes in Ovarian Cancer via Bioinformatic Approach","authors":"Liao Chengzhang, Xu Jiucheng","doi":"10.1109/ICBCB52223.2021.9459203","DOIUrl":"https://doi.org/10.1109/ICBCB52223.2021.9459203","url":null,"abstract":"Objective: To identify potentially therapeutic target genes involved in the pathogenesis of ovarian cancer using bioinformatic approach. Methods: The GEO2R online tool was employed to analyze the gene expression profiles of ovarian cancer. GO and KEGG enrichment analysis was utilized to annotate differentially expressed genes (DEGs). STRING database was employed to construct a protein-protein interaction (PPI) network with the DEGs. The PPI network interaction information was then visualized using Cytoscape software and ovarian cancer hub genes were identified based on Maximal Clique Centrality (MCC) algorithm. The identified hub genes were then analyzed with Kaplan Meier plotter to check their role on survival time of ovarian cancer patients. Results: Differentially expressed analysis resulted in 332 DEGs, of which 340 were down-regulated and 92 were up-regulated. Gene Ontology (GO) enrichment analysis indicated that the DEGs were significantly enriched in some tumor-associated biological processes, molecular functions, and cellular components. Kyoto Encyclopedia Genes and Genomes (KEGG) pathway enrichment analysis resulted in 5 cancer related pathways. A total of 10 hub genes were identified based on the topological analysis of PPI network. Survival analysis showed 7 of the hub genes were associated with significantly decreased survival time of the ovarian cancer patients (P<0.05). Conclusion: Our study resulted in identification of 7 hub genes contributing to the development of ovarian cancer. These hub genes may be potentially therapeutic target genes for treatment of ovarian cancer.","PeriodicalId":178168,"journal":{"name":"2021 IEEE 9th International Conference on Bioinformatics and Computational Biology (ICBCB)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130430177","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: 1

A Comparative Study About Coronary CTA for Patients with Arrhythmia under Different Time Phase One-Beat Scanning Mode 不同时相单拍扫描方式对心律失常患者冠脉CTA的比较研究

2021 IEEE 9th International Conference on Bioinformatics and Computational Biology (ICBCB) Pub Date : 2021-05-25 DOI: 10.1109/ICBCB52223.2021.9459212

Dewu Yang, Wang Junying, Yin Hongxia, Yan Zixu

{"title":"A Comparative Study About Coronary CTA for Patients with Arrhythmia under Different Time Phase One-Beat Scanning Mode","authors":"Dewu Yang, Wang Junying, Yin Hongxia, Yan Zixu","doi":"10.1109/ICBCB52223.2021.9459212","DOIUrl":"https://doi.org/10.1109/ICBCB52223.2021.9459212","url":null,"abstract":"Objectives: The results of coronary CTA for patients with arrhythmia were compared under different phase One-Beat scanning mode. Methods: 100 patients with arrhythmia were selected and randomly divided into control group and observation group. The relative phase-scanning mode and absolute phase-scanning mode were used for examination. Subjective and objective evaluation methods were used for image quality analysis, while variance analysis and Spearman correlation analysis were used for statistical analysis. Results: The subjective scores of all 13 segments in the observation group were higher than those in the control group, and the differences in 6 segments were statistically significant (P<0.05). CNR values in 3 segments in the observation group were higher than those in the control group, with statistically significant differences (P< 0.05). In the observation group, the correlation between the evaluation data and heart rate was weak (0<r<0.3), while the correlation in the control group was significantly negative (- 0.8<r<-0.3). Conclusions: The image quality in the absolute time-phase scanning mode is better than that in the relative time-phase and is not affected by the heart rate. Therefore, the absolute time-phase scanning mode has a good application value in the CCTA for patients with arrhythmia.","PeriodicalId":178168,"journal":{"name":"2021 IEEE 9th International Conference on Bioinformatics and Computational Biology (ICBCB)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133174463","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: 1

Chaotic Harmony Search based Multi-objective Feature Selection for Classification of Gene Expression Profiles 基于混沌和谐搜索的基因表达谱多目标特征选择

2021 IEEE 9th International Conference on Bioinformatics and Computational Biology (ICBCB) Pub Date : 2021-05-25 DOI: 10.1109/ICBCB52223.2021.9459222

Aiguo Wang, Huancheng Liu, Guilin Chen

{"title":"Chaotic Harmony Search based Multi-objective Feature Selection for Classification of Gene Expression Profiles","authors":"Aiguo Wang, Huancheng Liu, Guilin Chen","doi":"10.1109/ICBCB52223.2021.9459222","DOIUrl":"https://doi.org/10.1109/ICBCB52223.2021.9459222","url":null,"abstract":"How to effectively select a subset of discriminant features from the high-dimensional low- sample-size microarray gene expression profiles remains crucial and meaningful for the bioinformatics analysis tasks such as locating disease genes and building classifiers for cancer diagnosis. Though meta-heuristic harmony search algorithm has been used for feature selection, it suffers from entrapment in local optima and low convergence speed. To this end, we propose a hybrid chaotic harmony search based multi-objective feature selection method, which uses the chaotic map to replace the parameter of harmony search during the optimization process. Specifically, the minimum redundancy maximum relevancy feature selector is first used to pre-select a subset of relevant features. Then, the chaotic harmony search is employed on the reduced feature set to find an optimal feature subset, where the fitness of a candidate solution is evaluated by a multi-objective formulation. Finally, extensive comparative experiments against its competitors, including six filter and four wrapper feature selection methods, are conducted on six public microarray datasets. Results show that the proposed method obtains higher classification accuracy. Besides, the convergence analysis indicates its efficiency.","PeriodicalId":178168,"journal":{"name":"2021 IEEE 9th International Conference on Bioinformatics and Computational Biology (ICBCB)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124631322","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: 4

Modeling Human Travel and Social Contact with Multi-layer Networks for Epidemic Prediction 基于多层网络的流行病预测人类出行和社会联系建模

2021 IEEE 9th International Conference on Bioinformatics and Computational Biology (ICBCB) Pub Date : 2021-05-25 DOI: 10.1109/ICBCB52223.2021.9459225

Wei Duan, Tao Wang, Peng Wang, Rusheng Ju, Xiao Wang, Tian Yang

{"title":"Modeling Human Travel and Social Contact with Multi-layer Networks for Epidemic Prediction","authors":"Wei Duan, Tao Wang, Peng Wang, Rusheng Ju, Xiao Wang, Tian Yang","doi":"10.1109/ICBCB52223.2021.9459225","DOIUrl":"https://doi.org/10.1109/ICBCB52223.2021.9459225","url":null,"abstract":"It is a key issue to reasonably represent human travel and social contact in epidemic models. Various measures were applied to develop the models of human mobility and contact in a long range or a short range, such as Brown movement, random walks, spatial networks, gravity models, contact networks. We proposed a method of representing human daily movement and social contact by using multi-layer networks with temporal edge weights. We combined bipartite networks with social networks to describe human daily trip and social contact, respectively. Temporal edge weights of multi-layer networks were employed to denote the propensity of individual movement and contact. We also verified our models and parameters by incorporating human daily travel and contact regularities, as well as comparing experimental results with human behavior statistical laws. At last, we applied a Chinese university campus as a case study to investigate students' daily travel and social contact, and studied the transmission and control strategies of COVID-19 virus. We found stricter control strategies are needed to mitigate the transmission of COVID-19 virus in a university. Once a patient case emerges in a university, it is better to close the campus and quarantine all students. Partial control strategies such as quarantining a part of students and buildings cannot achieve a great effect of mitigating the transmission of COVID-19 virus. Our works are beneficial for the practitioners in the field of computational epidemiology.","PeriodicalId":178168,"journal":{"name":"2021 IEEE 9th International Conference on Bioinformatics and Computational Biology (ICBCB)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123659852","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

Analyzing Genomic Features with Predictive Chromatin Interaction Models: A Comprehensive Evaluation 用预测染色质相互作用模型分析基因组特征:一个综合评价

2021 IEEE 9th International Conference on Bioinformatics and Computational Biology (ICBCB) Pub Date : 2021-05-25 DOI: 10.1109/ICBCB52223.2021.9459215

Yi Kou, Daniel Zhao

{"title":"Analyzing Genomic Features with Predictive Chromatin Interaction Models: A Comprehensive Evaluation","authors":"Yi Kou, Daniel Zhao","doi":"10.1109/ICBCB52223.2021.9459215","DOIUrl":"https://doi.org/10.1109/ICBCB52223.2021.9459215","url":null,"abstract":"Enhancer-Promoter (EP) interactions reflected by Hi-C technology are crucial to understanding genomic functions. Particularly, identifying ‘unique’ genomic features that are characteristically important in a specific cell line can further our current understanding of the mechanisms that drive cell differentiation, tissue development, and disease progression. However, classic prediction models such as TargetFinder provide little valuable insight towards the large disparity between important genomic features across different cell lines. To comprehensively approach this question, herein we first evaluated seven classifiers to predict EP interactions using high-resolution Hi-C maps of genome loci across six classic cell lines, surpassing TargetFinder in all benchmark metrics. We then evaluated the model's predictive performance with features provided by seven feature selection methods from the embedded, wrapper and filter categories. Moreover, groups of features were aggregated from the results of two or more feature methods and analyzed based on the model's performance. Finally, we examined the distinguishing features across six cell lines. Our study suggests the existence of ‘unique’ genomic features that are especially predictive of EP interactions only in specific cell lines.","PeriodicalId":178168,"journal":{"name":"2021 IEEE 9th International Conference on Bioinformatics and Computational Biology (ICBCB)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129156691","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

Phenotype Anomaly Detection in Early C. elegans Embryos by Variational Auto-Encoder 用变分自编码器检测秀丽隐杆线虫早期胚胎的表型异常

2021 IEEE 9th International Conference on Bioinformatics and Computational Biology (ICBCB) Pub Date : 2021-05-25 DOI: 10.1109/ICBCB52223.2021.9459228

Takumi Oibayashi, Takaya Ueda, Yukiyo Kimura, Y. Tohsato, I. Nishikawa

{"title":"Phenotype Anomaly Detection in Early C. elegans Embryos by Variational Auto-Encoder","authors":"Takumi Oibayashi, Takaya Ueda, Yukiyo Kimura, Y. Tohsato, I. Nishikawa","doi":"10.1109/ICBCB52223.2021.9459228","DOIUrl":"https://doi.org/10.1109/ICBCB52223.2021.9459228","url":null,"abstract":"Variational auto encoder (VAE) is used to detect and quantify the phenotype anomaly in the nuclear division of the early embryo of C. elegans. The latent space of VAE, on which the normal data distribution is obtained through the training, is used to characterize not only the morphological anomaly, but also the temporal anomaly of the time series data, based on the position in the latent space. The proposed method is applied to the time series of three dimensional DIC data of nuclear division process during two-cell stage of C. elegans. Wild type data is used as the normal data for the training, and then an anomaly is evaluated on an embryo, for which one of the lethal genes is silenced by RNAi. First, Morphological anomaly is quantified by the reconstruction error. Then, for the well-reconstructed data, the trajectory in the latent space corresponding to the input time series is used to characterize the time development of the division process. Anomaly score is defined based on the normal time distribution in the latent space, and the proposed method successfully obtains a list of lethal genes, which cause the temporal anomaly by the knocking down.","PeriodicalId":178168,"journal":{"name":"2021 IEEE 9th International Conference on Bioinformatics and Computational Biology (ICBCB)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129867611","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

Genetic Epidemiology of Porcine Transmissible Gastroenteritis Virus Based on Whole Genome and S Gene Sequences 基于猪传染性胃肠炎病毒全基因组和S基因序列的遗传流行病学研究

2021 IEEE 9th International Conference on Bioinformatics and Computational Biology (ICBCB) Pub Date : 2021-05-25 DOI: 10.1109/ICBCB52223.2021.9459208

Jiating Qian, Mengjiao Li, Yifan Feng, Wenjuan Li, Jie Li

引用次数: 0

The Supervised CNN Image Edge Detection Algorithm in Scotopic Vision Environment 暗域视觉环境下有监督CNN图像边缘检测算法

2021 IEEE 9th International Conference on Bioinformatics and Computational Biology (ICBCB) Pub Date : 2021-05-25 DOI: 10.1109/ICBCB52223.2021.9459230

Qin Zhang, Xiangling Zhou, Xiaowen Xu, Xinhong Xie, Mengyuan Zhang, Yuxiang Tao, Ke Li, Zhiqiang Zhao

{"title":"The Supervised CNN Image Edge Detection Algorithm in Scotopic Vision Environment","authors":"Qin Zhang, Xiangling Zhou, Xiaowen Xu, Xinhong Xie, Mengyuan Zhang, Yuxiang Tao, Ke Li, Zhiqiang Zhao","doi":"10.1109/ICBCB52223.2021.9459230","DOIUrl":"https://doi.org/10.1109/ICBCB52223.2021.9459230","url":null,"abstract":"Scotopic vision environment images are characterized by low contrast and some details hidden in the image background, that causes human eyes are hard to detect and brings difficulties to the subsequent application of computer vision tasks. In order to solve the problem that many false edges are generated when DexiNed (Dense Extreme Inception Network for Edge Detection) model detects scotopic vision images, an improved DexiNed edge detection model was proposed in this paper. The improved edge detection model retained the backbone network of the DexiNed model. By adding the convolution layers and residual units in the appropriate position of the DexiNed model, the model can eliminate most of the false edges generated by the DexiNed model in the scotopic vision images better. In order to further improve the edge detection accuracy of scotopic vision image by the improved DexiNed model, this paper builds scotopic vision image training set based on edge annotation data set BIPED (Barcelona Images for Perceptual Edge Detection) from RGB and YUV color space respectively. And scotopic vision image test dataset results showed that the effect of scotopic vision image based on RGB color space to have better performance, because edge continuity was better and the edge detection model of MSE (mean square error) index dropped, PSNR (peak signal to noise ratio) and SSIM (structural similarity) index raised.","PeriodicalId":178168,"journal":{"name":"2021 IEEE 9th International Conference on Bioinformatics and Computational Biology (ICBCB)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124646221","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: 2

The Application of Pearson and Mutual Information Correlation Network Structure Analysis in Mining Pathogenic Mechanism 皮尔逊与互信息关联网络结构分析在采矿致病机理中的应用

2021 IEEE 9th International Conference on Bioinformatics and Computational Biology (ICBCB) Pub Date : 2021-05-25 DOI: 10.1109/ICBCB52223.2021.9459210

Wang Yanhui, Lin ChenXin, Dazhi Meng

{"title":"The Application of Pearson and Mutual Information Correlation Network Structure Analysis in Mining Pathogenic Mechanism","authors":"Wang Yanhui, Lin ChenXin, Dazhi Meng","doi":"10.1109/ICBCB52223.2021.9459210","DOIUrl":"https://doi.org/10.1109/ICBCB52223.2021.9459210","url":null,"abstract":"The structural parameters of Pearson correlation (PC) and mutual information correlation (MUC) network of gens are used to study the pathogenic mechanism and the difference between the two correlations in the study of biological function. As an example, the PC and MUC networks of bipolar disorder (BD) are constructed, and the top 30 genes (namely, SKGs) with large difference in the average degree of the networks are analyzed. It is found that BD is significantly correlated with nervous system, and is related to immune system, genetic regulation, cell growth/apoptosis and angiogenesis. In addition, PC has universality in revealing biological functions, but the effect of MUC is obviously greater than that of PC. This suggests that the influence of non-linear components on biological function attributes is greater than that of linear components. Therefore, research methods based on linear correlation PC are not enough to reveal the comprehensive information of biological mechanism, and research methods only using MUC also omit linear components.","PeriodicalId":178168,"journal":{"name":"2021 IEEE 9th International Conference on Bioinformatics and Computational Biology (ICBCB)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128393817","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