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Quantitative Biology 2019: Dynamic Signaling in Cells and Embryos 定量生物学2019:细胞和胚胎的动态信号传导
IF 3.1 4区 生物学
Quantitative Biology Pub Date : 2019-12-01 DOI: 10.1007/s40484-019-0190-9
Feng Liu, Yihan Lin, Chunmei Li, Miaomiao Tian
{"title":"Quantitative Biology 2019: Dynamic Signaling in Cells and Embryos","authors":"Feng Liu, Yihan Lin, Chunmei Li, Miaomiao Tian","doi":"10.1007/s40484-019-0190-9","DOIUrl":"https://doi.org/10.1007/s40484-019-0190-9","url":null,"abstract":"","PeriodicalId":45660,"journal":{"name":"Quantitative Biology","volume":"7 1","pages":"335 - 337"},"PeriodicalIF":3.1,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s40484-019-0190-9","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42775401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Computational prediction and functional analysis of arsenic-binding proteins in human cells 人体细胞中砷结合蛋白的计算预测和功能分析
IF 3.1 4区 生物学
Quantitative Biology Pub Date : 2019-10-14 DOI: 10.1007/s40484-019-0169-6
Shichao Pang, Junchen Yang, Yilei Zhao, Yixue Li, Jingfang Wang
{"title":"Computational prediction and functional analysis of arsenic-binding proteins in human cells","authors":"Shichao Pang, Junchen Yang, Yilei Zhao, Yixue Li, Jingfang Wang","doi":"10.1007/s40484-019-0169-6","DOIUrl":"https://doi.org/10.1007/s40484-019-0169-6","url":null,"abstract":"","PeriodicalId":45660,"journal":{"name":"Quantitative Biology","volume":"1 1","pages":"1-8"},"PeriodicalIF":3.1,"publicationDate":"2019-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s40484-019-0169-6","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49479693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
EpiFIT: functional interpretation of transcription factors based on combination of sequence and epigenetic information EpiFIT：基于序列和表观遗传信息的转录因子功能解释
IF 3.1 4区 生物学
Quantitative Biology Pub Date : 2019-10-14 DOI: 10.1007/s40484-019-0175-8
Shaoming Song, Hongfei Cui, Shengquan Chen, Qiao Liu, R. Jiang
{"title":"EpiFIT: functional interpretation of transcription factors based on combination of sequence and epigenetic information","authors":"Shaoming Song, Hongfei Cui, Shengquan Chen, Qiao Liu, R. Jiang","doi":"10.1007/s40484-019-0175-8","DOIUrl":"https://doi.org/10.1007/s40484-019-0175-8","url":null,"abstract":"","PeriodicalId":45660,"journal":{"name":"Quantitative Biology","volume":"7 1","pages":"233 - 243"},"PeriodicalIF":3.1,"publicationDate":"2019-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s40484-019-0175-8","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47687422","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 2
2019 China Symposium on Single-Cell Genomics 2019中国单细胞基因组学学术研讨会
IF 3.1 4区 生物学
Quantitative Biology Pub Date : 2019-09-01 DOI: 10.1007/s40484-019-0178-5
Yinqing Li, Miaomiao Tian
{"title":"2019 China Symposium on Single-Cell Genomics","authors":"Yinqing Li, Miaomiao Tian","doi":"10.1007/s40484-019-0178-5","DOIUrl":"https://doi.org/10.1007/s40484-019-0178-5","url":null,"abstract":"","PeriodicalId":45660,"journal":{"name":"Quantitative Biology","volume":"7 1","pages":"244-246"},"PeriodicalIF":3.1,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s40484-019-0178-5","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49654838","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Applications of single-cell technology on bacterial analysis 单细胞技术在细菌分析中的应用
IF 3.1 4区 生物学
Quantitative Biology Pub Date : 2019-09-01 DOI: 10.1007/s40484-019-0177-6
Zhixin Ma, Pan Chu, Yingtong Su, Yue Yu, Hui Wen, Xiongfei Fu, Shuqiang Huang
{"title":"Applications of single-cell technology on bacterial analysis","authors":"Zhixin Ma, Pan Chu, Yingtong Su, Yue Yu, Hui Wen, Xiongfei Fu, Shuqiang Huang","doi":"10.1007/s40484-019-0177-6","DOIUrl":"https://doi.org/10.1007/s40484-019-0177-6","url":null,"abstract":"","PeriodicalId":45660,"journal":{"name":"Quantitative Biology","volume":"7 1","pages":"171 - 181"},"PeriodicalIF":3.1,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s40484-019-0177-6","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46041837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Identifying MiRNA-disease association based on integrating miRNA topological similarity and functional similarity 基于MiRNA拓扑相似性和功能相似性的MiRNA疾病关联性鉴定
IF 3.1 4区 生物学
Quantitative Biology Pub Date : 2019-08-28 DOI: 10.1007/s40484-019-0176-7
Qingfeng Chen, Zhao Zhe, Wei Lan, Ruchang Zhang, Zhiqiang Wang, Cheng Luo, Y. Chen
{"title":"Identifying MiRNA-disease association based on integrating miRNA topological similarity and functional similarity","authors":"Qingfeng Chen, Zhao Zhe, Wei Lan, Ruchang Zhang, Zhiqiang Wang, Cheng Luo, Y. Chen","doi":"10.1007/s40484-019-0176-7","DOIUrl":"https://doi.org/10.1007/s40484-019-0176-7","url":null,"abstract":"","PeriodicalId":45660,"journal":{"name":"Quantitative Biology","volume":"7 1","pages":"202 - 209"},"PeriodicalIF":3.1,"publicationDate":"2019-08-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s40484-019-0176-7","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46484802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
Understanding traditional Chinese medicine via statistical learning of expert-specific Electronic Medical Records 通过专家电子病历的统计学习了解中医
IF 3.1 4区 生物学
Quantitative Biology Pub Date : 2019-08-02 DOI: 10.1007/s40484-019-0173-x
Yang Yang, Qi Li, Zhaoyang Liu, Fang Ye, Ke Deng
{"title":"Understanding traditional Chinese medicine via statistical learning of expert-specific Electronic Medical Records","authors":"Yang Yang, Qi Li, Zhaoyang Liu, Fang Ye, Ke Deng","doi":"10.1007/s40484-019-0173-x","DOIUrl":"https://doi.org/10.1007/s40484-019-0173-x","url":null,"abstract":"","PeriodicalId":45660,"journal":{"name":"Quantitative Biology","volume":"7 1","pages":"210 - 232"},"PeriodicalIF":3.1,"publicationDate":"2019-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s40484-019-0173-x","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45973738","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
Identification of candidate disease genes in patients with common variable immunodeficiency 常见变异性免疫缺陷患者候选疾病基因的鉴定
IF 3.1 4区 生物学
Quantitative Biology Pub Date : 2019-07-09 DOI: 10.1007/s40484-019-0174-9
Guojun Liu, M. Bolkov, I. Tuzankina, I. Danilova
{"title":"Identification of candidate disease genes in patients with common variable immunodeficiency","authors":"Guojun Liu, M. Bolkov, I. Tuzankina, I. Danilova","doi":"10.1007/s40484-019-0174-9","DOIUrl":"https://doi.org/10.1007/s40484-019-0174-9","url":null,"abstract":"","PeriodicalId":45660,"journal":{"name":"Quantitative Biology","volume":"7 1","pages":"190 - 201"},"PeriodicalIF":3.1,"publicationDate":"2019-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s40484-019-0174-9","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46230614","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 1
A model of NSCLC microenvironment predicts optimal receptor targets 非小细胞肺癌微环境模型预测最佳受体靶点
IF 3.1 4区 生物学
Quantitative Biology Pub Date : 2019-06-04 DOI: 10.1007/s40484-019-0171-z
Chuang Han, Yu Wu
{"title":"A model of NSCLC microenvironment predicts optimal receptor targets","authors":"Chuang Han, Yu Wu","doi":"10.1007/s40484-019-0171-z","DOIUrl":"https://doi.org/10.1007/s40484-019-0171-z","url":null,"abstract":"","PeriodicalId":45660,"journal":{"name":"Quantitative Biology","volume":"7 1","pages":"147-161"},"PeriodicalIF":3.1,"publicationDate":"2019-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s40484-019-0171-z","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47100373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Predicting enhancer-promoter interaction from genomic sequence with deep neural networks. 基于深度神经网络的基因组序列增强子-启动子相互作用预测。
IF 3.1 4区 生物学
Quantitative Biology Pub Date : 2019-06-01 DOI: 10.1007/s40484-019-0154-0
Shashank Singh, Yang Yang, Barnabás Póczos, Jian Ma
{"title":"Predicting enhancer-promoter interaction from genomic sequence with deep neural networks.","authors":"Shashank Singh,&nbsp;Yang Yang,&nbsp;Barnabás Póczos,&nbsp;Jian Ma","doi":"10.1007/s40484-019-0154-0","DOIUrl":"https://doi.org/10.1007/s40484-019-0154-0","url":null,"abstract":"<p><strong>Background: </strong>In the human genome, distal enhancers are involved in regulating target genes through proximal promoters by forming enhancer-promoter interactions. Although recently developed high-throughput experimental approaches have allowed us to recognize potential enhancer-promoter interactions genome-wide, it is still largely unclear to what extent the sequence-level information encoded in our genome help guide such interactions.</p><p><strong>Methods: </strong>Here we report a new computational method (named \"SPEID\") using deep learning models to predict enhancer-promoter interactions based on sequence-based features only, when the locations of putative enhancers and promoters in a particular cell type are given.</p><p><strong>Results: </strong>Our results across six different cell types demonstrate that SPEID is effective in predicting enhancer-promoter interactions as compared to state-of-the-art methods that only use information from a single cell type. As a proof-of-principle, we also applied SPEID to identify somatic non-coding mutations in melanoma samples that may have reduced enhancer-promoter interactions in tumor genomes.</p><p><strong>Conclusions: </strong>This work demonstrates that deep learning models can help reveal that sequence-based features alone are sufficient to reliably predict enhancer-promoter interactions genome-wide.</p>","PeriodicalId":45660,"journal":{"name":"Quantitative Biology","volume":"7 2","pages":"122-137"},"PeriodicalIF":3.1,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s40484-019-0154-0","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39082600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 107
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