2019 IEEE 7th International Conference on Bioinformatics and Computational Biology ( ICBCB)最新文献_第2页

Predicting RNA Molecular Specific Hybridization via Random Forest 随机森林预测RNA分子特异性杂交

2019 IEEE 7th International Conference on Bioinformatics and Computational Biology ( ICBCB) Pub Date : 2019-03-01 DOI: 10.1109/ICBCB.2019.8854665

Weijun Zhu, Xiaokai Liu, Zhenfei Wang, Yongwen Fan, Jianwei Wang

引用次数: 1

Gene Regulatory Network Construction and Key Gene Recognition of Diabetic Nephropathy 糖尿病肾病基因调控网络构建及关键基因识别

2019 IEEE 7th International Conference on Bioinformatics and Computational Biology ( ICBCB) Pub Date : 2019-03-01 DOI: 10.1109/ICBCB.2019.8854648

R. Zheng, Yun Wang, Zhaoying Lyu, A. Armaou

{"title":"Gene Regulatory Network Construction and Key Gene Recognition of Diabetic Nephropathy","authors":"R. Zheng, Yun Wang, Zhaoying Lyu, A. Armaou","doi":"10.1109/ICBCB.2019.8854648","DOIUrl":"https://doi.org/10.1109/ICBCB.2019.8854648","url":null,"abstract":"Diabetic nephropathy (DN) is a diabetic complication that seriously endangers human health. Its pathogenesis involves a variety of factors. The purpose of this paper is to determine key genes in the disease progression that will be potential therapeutic targets of DN. Based on gene expression profiles and the databases of interactions of proteins-proteins, transcription factors-genes, transcription factors-miRNAs and miRNAs-genes, the differentially expressed genes of DN were screened. The regulatory network of DN differential genes was established and key genes of DN were identified using the entity grammar system. According to the regulatory interaction between genes, key genes were defined as the ones that could regulate the state of other genes from abnormal towards normal expression. Identified key genes include BMP2 (bone morphogenetic protein 2), VEGFA (vascular endothelial growth factor A), F3 (coagulation factor III/tissue factor), EGR2 (early growth response protein 2), CDS1 (CDP- diacylglycerol synthase 1) and PLCE1 (phospholipase C epsilon 1). These findings provide clues for the successful drug development of DN.","PeriodicalId":136995,"journal":{"name":"2019 IEEE 7th International Conference on Bioinformatics and Computational Biology ( ICBCB)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130437241","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

Whole-Genome Sequencing to Determine Origin of Diarrhea in Suckling Piglets in Southern China 全基因组测序确定中国南方哺乳仔猪腹泻的起源

2019 IEEE 7th International Conference on Bioinformatics and Computational Biology ( ICBCB) Pub Date : 2019-03-01 DOI: 10.1109/ICBCB.2019.8854647

Jie Li, Jiating Qian, Xuanxuan Mao, C. Xue, Yongchang Cao

引用次数: 0

Proceedings of 2019 IEEE 7th International Conference on Bioinformatics and Computational Biology ICBCB 2019 2019年IEEE第七届生物信息学与计算生物学国际会议论文集

2019 IEEE 7th International Conference on Bioinformatics and Computational Biology ( ICBCB) Pub Date : 2019-03-01 DOI: 10.1109/icbcb.2019.8854640

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引用次数: 0

A Head Pose Estimation Method Based on Multi-feature Fusion 基于多特征融合的头部姿态估计方法

2019 IEEE 7th International Conference on Bioinformatics and Computational Biology ( ICBCB) Pub Date : 2019-03-01 DOI: 10.1109/ICBCB.2019.8854672

Zhiqiang Zhao, Qiaoli Zheng, Yan Zhang, Xin Shi

引用次数: 1

A Novel RNN-Based Blood Glucose Prediction Approach Using Population and Individual Characteristics 一种基于rnn的基于人群和个体特征的血糖预测新方法

2019 IEEE 7th International Conference on Bioinformatics and Computational Biology ( ICBCB) Pub Date : 2019-03-01 DOI: 10.1109/ICBCB.2019.8854657

Yuhan Dong, Rui Wen, Kai Zhang, Lin Zhang

{"title":"A Novel RNN-Based Blood Glucose Prediction Approach Using Population and Individual Characteristics","authors":"Yuhan Dong, Rui Wen, Kai Zhang, Lin Zhang","doi":"10.1109/ICBCB.2019.8854657","DOIUrl":"https://doi.org/10.1109/ICBCB.2019.8854657","url":null,"abstract":"As a common endocrine disease, diabetes has been plagued the lives of patients. An accurate blood glucose (BG) prediction approach can not only be used in daily BG management to reduce the occurrence of hypoglycemia or hyperglycemia, but also regulate the amount and time of insulin injection combined with insulin pump. Data driven methods have become an effective way for predicting BG. While time series analysis methods only deal with one patient at a time and most machine learning approaches simply use multiple patients' data to capture the population characteristics of BG but ignore the individual characteristics. To overcome these shortcomings, we propose a novel neural network approach based on GRU in which both population and individual characteristics of BG fluctuation are well integrated by pre-training and fine-tune processes. The proposed approach not only overcomes the problem of insufficient data for individual patient, but also makes full use of the population and individual differences of BG fluctuation. Compared with other machine learning or neural network approaches, the numerical results suggest that the proposed approach gains significant improvements on prediction accuracy.","PeriodicalId":136995,"journal":{"name":"2019 IEEE 7th International Conference on Bioinformatics and Computational Biology ( ICBCB)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131071550","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: 5

Adaptive Deep Brain Stimulation System Based on ADS1292 基于ADS1292的自适应深部脑刺激系统

2019 IEEE 7th International Conference on Bioinformatics and Computational Biology ( ICBCB) Pub Date : 2019-03-01 DOI: 10.1109/ICBCB.2019.8854629

Dechun Zhao, Li Wang, Shanshan Cheng

{"title":"Adaptive Deep Brain Stimulation System Based on ADS1292","authors":"Dechun Zhao, Li Wang, Shanshan Cheng","doi":"10.1109/ICBCB.2019.8854629","DOIUrl":"https://doi.org/10.1109/ICBCB.2019.8854629","url":null,"abstract":"In order to monitor the development of Parkinson's disease for a long time and to study the mechanism of deep brain stimulation for Parkinson's disease, an adaptive deep brain stimulation system based on ADS1292 was designed for Parkinson's rats. The system consists of a main control unit, an acquisition module, a stimulation module and a wireless communication module, the system uses high-performance, low-power MSP430 as the main control chip. The high resolution, low noise analog to digital conversion chip ADS1292 acquires local field potential (LFP) signals. The stimulus module uses the DAC8532 to output a square wave with adjustable amplitude, frequency, and pulse width. At the same time, the wireless communication module uses the Bluetooth to transmit the LFP signal to the upper computer for processing and receive the control command from the upper computer for achieving adaptive adjustment of the stimulus parameters. Through verification, the system completes the generation of stimulation signals and the acquisition of weak bioelectric signals. The system is light in weight, small in size and low in power consumption, and is very suitable for small animal experiments such as rats.","PeriodicalId":136995,"journal":{"name":"2019 IEEE 7th International Conference on Bioinformatics and Computational Biology ( ICBCB)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114487457","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

Decoding Attention Position Based on Shifted Receptive Field in Visual Cortex 基于视觉皮层感受野移位的注意位置解码

2019 IEEE 7th International Conference on Bioinformatics and Computational Biology ( ICBCB) Pub Date : 2019-03-01 DOI: 10.1109/ICBCB.2019.8854642

Xiaohan Duan, Ziya Yu, Li Tong, Linyuan Wang

{"title":"Decoding Attention Position Based on Shifted Receptive Field in Visual Cortex","authors":"Xiaohan Duan, Ziya Yu, Li Tong, Linyuan Wang","doi":"10.1109/ICBCB.2019.8854642","DOIUrl":"https://doi.org/10.1109/ICBCB.2019.8854642","url":null,"abstract":"Visual attention is an important issue in the field of neuroscience and computer vision. According to recent research of visual cognitive computation, receptive fields are thought to be shifted with the influence of spatial attention. In the traditional method, researchers decoded various positions of attention based on constant population receptive field (pRF) parameters. Comparing with previous attention decoding researches, recent discovery may help improve the decoding accuracy. In this research, to get a better accuracy, a new decoding method is proposed with introducing the shift of pRF parameters. Firstly, we adopted two-dimensional Gaussian receptive field model to characterize the population receptive field(pRF) of each voxel in seven visual areas [V1-V4, inferior occipital gyrus (IOG), posterior fusiform gyrus (pFus), and mid-fusiform gyrus (mFus)]. Then, we introduced a parameter to measure the shift of pRF. With the shifted pRF parameters, the attention position could be decoded by maximum likelihood estimation. With published fMRI dataset, a better decoding accuracy could be obtained in most regions, especially in higher regions. The result also indicated that with the modulation of spatial attention, pRF parameters of voxels in high regions were shifted much more than those in early regions.","PeriodicalId":136995,"journal":{"name":"2019 IEEE 7th International Conference on Bioinformatics and Computational Biology ( ICBCB)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130504765","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

Synchronous Optimal Design of Genetic Oscillator Networks Using a Novel VonPSO Algorithm 基于新型VonPSO算法的遗传振荡网络同步优化设计

2019 IEEE 7th International Conference on Bioinformatics and Computational Biology ( ICBCB) Pub Date : 2019-03-01 DOI: 10.1109/ICBCB.2019.8854651

Wei Zhang, Qinqin Yao, Jianming Zhang, Guangye Li

{"title":"Synchronous Optimal Design of Genetic Oscillator Networks Using a Novel VonPSO Algorithm","authors":"Wei Zhang, Qinqin Yao, Jianming Zhang, Guangye Li","doi":"10.1109/ICBCB.2019.8854651","DOIUrl":"https://doi.org/10.1109/ICBCB.2019.8854651","url":null,"abstract":"As a common phenomenon in biological systems, synchronization plays a vital role in construction of genetic oscillator networks with specific cellular functions. Considering the complexity of connections, optimal synchronous design of oscillator networks become feasible with optimization approaches. In order to improve the efficiency of optimal synchronous design, a novel VonPSO algorithm that applies Von-Neumann topology is proposed to solve the combinational optimization problem involved in optimizing directed interactions within coupled oscillator networks. This VonPSO algorithm applies mutation and crossover operations to generate new candidates that represent the network adjacent matrices. Using order parameter to evaluate the degree of synchronization, this paper applies a twostages optimization framework that adjusts network topologies and coupling parameters at two independent stages. Simulation outcomes indicate that the proposed framework is effective to improve the synchronous indexes between coupled genetic oscillators using the VonPSO algorithm. Experimental outcomes indicate that synchronization of coupled oscillator networks can be significantly enhanced by the two-stages optimization using VonPSO algorithm.","PeriodicalId":136995,"journal":{"name":"2019 IEEE 7th International Conference on Bioinformatics and Computational Biology ( ICBCB)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114370017","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

Characterization of Cell Microcapsules and Preparation via Digital Coaxial Injection 细胞微胶囊的表征及数字同轴注射制备

2019 IEEE 7th International Conference on Bioinformatics and Computational Biology ( ICBCB) Pub Date : 2019-03-01 DOI: 10.1109/ICBCB.2019.8854652

Qing Li, Rongshuai Liu, Weipeng Zhang, Yuxi Feng

引用次数: 0