arXiv: Quantitative Methods最新文献_第3页

Pulsing corals: A story of scale and mixing 脉动珊瑚:规模和混合的故事

arXiv: Quantitative Methods Pub Date : 2017-09-14 DOI: 10.11145/j.biomath.2017.12.169

J. Samson, Nicholas A. Battista, S. Khatri, L. Miller

引用次数: 7

Dynamic Analysis of a Predator and Prey Model with some Computational Simulations 捕食者与猎物模型的动力学分析及一些计算仿真

arXiv: Quantitative Methods Pub Date : 2017-08-28 DOI: 10.4172/2329-9533.1000137

S. Khoshnaw

引用次数: 1

arXiv: Quantitative Methods Pub Date : 2017-08-22 DOI: 10.3390/CONDMAT2030029

M. D. Gioacchino, G. Campi, N. Poccia, A. Bianconi

{"title":"Correlated Disorder in Myelinated Axons Orientational Geometry and Structure","authors":"M. D. Gioacchino, G. Campi, N. Poccia, A. Bianconi","doi":"10.3390/CONDMAT2030029","DOIUrl":"https://doi.org/10.3390/CONDMAT2030029","url":null,"abstract":"While the ultrastructure of myelin is considered a quasi-crystalline stable system, nowadays its multiscale complex dynamics appear to play a key role in its functionality, degeneration and repair processes following neurological diseases and trauma. In this work, we investigated the fluctuation of the myelin supramolecular assembly by measuring the spatial distribution of orientation fluctuations of axons in a Xenopus Laevis sciatic nerve associated with nerve functionality. To this end, we used scanning micro X-ray diffraction (SμXRD), a non-invasive technique that has already been applied to other heterogeneous systems presenting complex geometries from microscale to nanoscale. We found that the orientation of the spatial fluctuations of fresh axons show a Levy flight distribution, which is a clear indication of correlated disorder. We found that the Levy flight distribution was missing in the aged nerve prepared in an unfresh state. This result shows that the spatial distribution of axon orientation fluctuations in unfresh nerve state loses the correlated disorder and assumes a random disorder behavior. This work provides a deeper understanding of the ultrastructure-function nerve relation and paves the way for the study of other materials and biomaterials using the SμXRD technique to detect fluctuations in their supramolecular structure.","PeriodicalId":119149,"journal":{"name":"arXiv: Quantitative Methods","volume":"131 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123233283","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

A Computational Resolution of the Inverse Problem of Kinetic Capillary Electrophoresis (KCE) 动态毛细管电泳反问题的一种计算方法

arXiv: Quantitative Methods Pub Date : 2017-07-25 DOI: 10.1007/978-3-319-99719-3_28

J. Vass, S. Krylov

引用次数: 1

Pharmacokinetic and Molecular Docking Studies of Plant-Derived Natural Compounds to Exploring Potential Anti-Alzheimer Activity 植物源性天然化合物的药代动力学和分子对接研究探索潜在的抗阿尔茨海默病活性

arXiv: Quantitative Methods Pub Date : 2017-07-19 DOI: 10.1007/978-981-13-0347-0_13

A. Alam, Naaila Tamkeen, N. Imam, Anam Farooqui, Mohd Murshad Ahmed, Shahnawaz Ali, M. Malik, R. Ishrat

引用次数: 16

Bayesian multi--dipole localization and uncertainty quantification from simultaneous EEG and MEG recordings 贝叶斯多偶极子定位和脑磁图同步记录的不确定度量化

arXiv: Quantitative Methods Pub Date : 2017-06-11 DOI: 10.1007/978-981-10-5122-7_211

Filippo Rossi, Gianvittorio Luria, Sara Sommariva, A. Sorrentino

引用次数: 2

Computational approaches for disease gene identification 疾病基因鉴定的计算方法

arXiv: Quantitative Methods Pub Date : 2017-04-11 DOI: 10.32657/10356/59238

Peng Yang

{"title":"Computational approaches for disease gene identification","authors":"Peng Yang","doi":"10.32657/10356/59238","DOIUrl":"https://doi.org/10.32657/10356/59238","url":null,"abstract":"Identifying disease genes from human genome is an important and fundamental problem in biomedical research. Despite many publications of machine learning methods applied to discover new disease genes, it still remains a challenge because of the pleiotropy of genes, the limited number of confirmed disease genes among whole genome and the genetic heterogeneity of diseases. Recent approaches have applied the concept of 'guilty by association' to investigate the association between a disease phenotype and its causative genes, which means that candidate genes with similar characteristics as known disease genes are more likely to be associated with diseases. However, due to the imbalance issues (few genes are experimentally confirmed as disease related genes within human genome) in disease gene identification, semi-supervised approaches, like label propagation approaches and positive-unlabeled learning, are used to identify candidate disease genes via making use of unknown genes for training - typically in the scenario of a small amount of confirmed disease genes (labeled data) with a large amount of unknown genome (unlabeled data). The performance of Disease gene prediction models are limited by potential bias of single learning models and incompleteness and noise of single biological data sources, therefore ensemble learning models are applied via combining multiple diverse biological sources and learning models to obtain better predictive performance. In this thesis, we propose three computational models for identifying candidate disease genes.","PeriodicalId":119149,"journal":{"name":"arXiv: Quantitative Methods","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116309645","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

Advances in Microfluidics and Lab-on-a-Chip Technologies 微流体与芯片实验室技术进展

arXiv: Quantitative Methods Pub Date : 2017-03-24 DOI: 10.1016/B978-0-12-802971-8.00011-0

H. Jayamohan, Valentin Romanov, Huizhong Li, Jiyoung Son, R. Samuel, J. Nelson, B. Gale

引用次数: 17

Quantitative Prediction of Linear B-Cell Epitopes 线性b细胞表位的定量预测

arXiv: Quantitative Methods Pub Date : 2017-01-22 DOI: 10.11648/j.bsi.20170201.11

R. Isea

引用次数: 7

Bridging the time scales of single-cell and population dynamics 弥合单细胞和种群动态的时间尺度

arXiv: Quantitative Methods Pub Date : 2016-11-16 DOI: 10.1103/PhysRevX.8.021007

Srividya Iyer-Biswas, Herman Gudjonson, Charles S. Wright, Jedidiah Riebling, Emma R. Dawson, Klevin Lo, Aretha Fiebig, S. Crosson, A. Dinner

{"title":"Bridging the time scales of single-cell and population dynamics","authors":"Srividya Iyer-Biswas, Herman Gudjonson, Charles S. Wright, Jedidiah Riebling, Emma R. Dawson, Klevin Lo, Aretha Fiebig, S. Crosson, A. Dinner","doi":"10.1103/PhysRevX.8.021007","DOIUrl":"https://doi.org/10.1103/PhysRevX.8.021007","url":null,"abstract":"How are granular details of stochastic growth and division of individual cells reflected in smooth deterministic growth of population numbers? We provide an integrated, multiscale perspective of microbial growth dynamics by formulating a data-validated theoretical framework that accounts for observables at both single-cell and population scales. We derive exact analytical complete time-dependent solutions to cell-age distributions and population growth rates as functionals of the underlying interdivision time distributions, for symmetric and asymmetric cell division. These results provide insights into the surprising implications of stochastic single-cell dynamics for population growth. Using our results for asymmetric division, we deduce the time to transition from the reproductively quiescent (swarmer) to replication-competent (stalked) stage of the {em Caulobacter crescentus} lifecycle. Remarkably, population numbers can spontaneously oscillate with time. We elucidate the physics leading to these population oscillations. For {em C. crescentus} cells, we show that a simple measurement of the population growth rate, for a given growth condition, is sufficient to characterize the condition-specific cellular unit of time, and thus yields the mean (single-cell) growth and division timescales, fluctuations in cell division times, the cell age distribution, and the quiescence timescale.","PeriodicalId":119149,"journal":{"name":"arXiv: Quantitative Methods","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127798125","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: 19