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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 Q4 MATHEMATICAL & COMPUTATIONAL BIOLOGY Pub Date : 2019-08-02 DOI: 10.1007/s40484-019-0173-x
Yang Yang, Qi Li, Zhaoyang Liu, Fang Ye, Ke Deng
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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 Q4 MATHEMATICAL & COMPUTATIONAL 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 Q4 MATHEMATICAL & COMPUTATIONAL BIOLOGY Pub Date : 2019-06-04 DOI: 10.1007/s40484-019-0171-z
Chuang Han, Yu Wu
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引用次数: 0
Progress in molecular docking 分子对接研究进展
IF 3.1 4区 生物学 Q4 MATHEMATICAL & COMPUTATIONAL BIOLOGY Pub Date : 2019-06-01 DOI: 10.1007/s40484-019-0172-y
Jiyu Fan, Ailing Fu, Le Zhang
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引用次数: 174
Predicting microRNA-disease association based on microRNA structural and functional similarity network 基于microRNA结构和功能相似性网络预测microRNA与疾病的关联
IF 3.1 4区 生物学 Q4 MATHEMATICAL & COMPUTATIONAL BIOLOGY Pub Date : 2019-05-30 DOI: 10.1007/s40484-019-0170-0
Tao Ding, Jie Gao, Shanshan Zhu, Junhua Xu, Min Wu
{"title":"Predicting microRNA-disease association based on microRNA structural and functional similarity network","authors":"Tao Ding, Jie Gao, Shanshan Zhu, Junhua Xu, Min Wu","doi":"10.1007/s40484-019-0170-0","DOIUrl":"https://doi.org/10.1007/s40484-019-0170-0","url":null,"abstract":"","PeriodicalId":45660,"journal":{"name":"Quantitative Biology","volume":"7 1","pages":"138-146"},"PeriodicalIF":3.1,"publicationDate":"2019-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1007/s40484-019-0170-0","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44596978","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
Current challenges and solutions of de novo assembly 从头组装的当前挑战和解决方案
IF 3.1 4区 生物学 Q4 MATHEMATICAL & COMPUTATIONAL BIOLOGY Pub Date : 2019-05-30 DOI: 10.1007/s40484-019-0166-9
Xingyu Liao, Min Li, You Zou, Fang-Xiang Wu, Yi Pan, Jianxin Wang
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引用次数: 36
Computational methods and applications for quantitative systems pharmacology 定量系统药理学的计算方法和应用
IF 3.1 4区 生物学 Q4 MATHEMATICAL & COMPUTATIONAL BIOLOGY Pub Date : 2019-03-22 DOI: 10.1007/s40484-018-0161-6
F. Xie, Jiangyong Gu
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引用次数: 5
Pharmacodynamics simulation of HOEC by a computational model of arachidonic acid metabolic network 花生四烯酸代谢网络计算模型对HOEC的药效学模拟
IF 3.1 4区 生物学 Q4 MATHEMATICAL & COMPUTATIONAL BIOLOGY Pub Date : 2019-03-22 DOI: 10.1007/s40484-018-0163-4
Wen Yang, Xia Wang, Kenan Li, Yuanru Liu, Y. Liu, Rui Wang, Honglin Li
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引用次数: 1
High-throughput quantification of microbial birth and death dynamics using fluorescence microscopy. 使用荧光显微镜对微生物出生和死亡动态进行高通量量化。
IF 3.1 4区 生物学 Q4 MATHEMATICAL & COMPUTATIONAL BIOLOGY Pub Date : 2019-03-01 Epub Date: 2019-01-04 DOI: 10.1007/s40484-018-0160-7
Samuel F M Hart, David Skelding, Adam J Waite, Justin C Burton, Wenying Shou

Background: Microbes live in dynamic environments where nutrient concentrations fluctuate. Quantifying fitness in terms of birth rate and death rate in a wide range of environments is critical for understanding microbial evolution and ecology.

Methods: Here, using high-throughput time-lapse microscopy, we have quantified how Saccharomyces cerevisiae mutants incapable of synthesizing an essential metabolite (auxotrophs) grow or die in various concentrations of the required metabolite. We establish that cells normally expressing fluorescent proteins lose fluorescence upon death and that the total fluorescence in an imaging frame is proportional to the number of live cells even when cells form multiple layers. We validate our microscopy approach of measuring birth and death rates using flow cytometry, cell counting, and chemostat culturing.

Results: For lysine-requiring cells, very low concentrations of lysine are not detectably consumed and do not support cell birth, but delay the onset of death phase and reduce the death rate compared to no lysine. In contrast, in low hypoxanthine, hypoxanthine-requiring cells can produce new cells, yet also die faster than in the absence of hypoxanthine. For both strains, birth rates under various metabolite concentrations are better described by the sigmoidal-shaped Moser model than the well-known Monod model, while death rates can vary with metabolite concentration and time.

Conclusions: Our work reveals how time-lapse microscopy can be used to discover non-intuitive microbial birth and death dynamics and to quantify growth rates in many environments.

背景:微生物生活在营养物质浓度波动的动态环境中。量化各种环境中出生率和死亡率的适应度对于理解微生物进化和生态学至关重要。方法:在这里,使用高通量延时显微镜,我们量化了无法合成必需代谢产物(营养缺陷型)的酿酒酵母突变体在不同浓度的必需代谢产物中是如何生长或死亡的。我们确定,正常表达荧光蛋白的细胞在死亡时会失去荧光,并且即使细胞形成多层,成像框中的总荧光也与活细胞的数量成比例。我们使用流式细胞术、细胞计数和恒化器培养验证了我们测量出生率和死亡率的显微镜方法。结果:对于需要赖氨酸的细胞,与没有赖氨酸相比,非常低浓度的赖氨酸不能被检测到消耗,也不支持细胞的出生,但可以延迟死亡期的开始并降低死亡率。相反,在次黄嘌呤含量低的情况下,需要次黄嘌呤的细胞可以产生新细胞,但也比没有次黄嘌呤时死亡更快。对于这两种菌株,S形Moser模型比众所周知的Monod模型更好地描述了不同代谢物浓度下的出生率,而死亡率可能随代谢物浓度和时间而变化。结论:我们的工作揭示了延时显微镜如何用于发现非直观的微生物出生和死亡动态,并量化许多环境中的生长率。
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引用次数: 16
A survey of web resources and tools for the study of TCM network pharmacology 中医网络药理学研究的网络资源和工具综述
IF 3.1 4区 生物学 Q4 MATHEMATICAL & COMPUTATIONAL BIOLOGY Pub Date : 2019-03-01 DOI: 10.1007/s40484-019-0167-8
Jing Zhao, Jian Yang, Saisai Tian, Weidong Zhang
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引用次数: 25
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