Quantitative Biology
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Perspective on the q‐bio Summer School and Conference: 2007 – 2014 and beyond
Quantitative Biology - Tập 2 Số 1 - Trang 54-58 - 2014
Generic properties of random gene regulatory networks
Quantitative Biology - Tập 1 - Trang 253-260 - 2014
Modeling gene regulatory networks (GRNs) is an important topic in systems biology. Although there has been much work focusing on various specific systems, the generic behavior of GRNs with continuous variables is still elusive. In particular, it is not clear typically how attractors partition among the three types of orbits: steady state, periodic and chaotic, and how the dynamical properties chan......
International Workshop on Applications of Probability and Statistics to Biology, July 11–13, 2019
Quantitative Biology - Tập 8 - Trang 177-186 - 2019
System identification and parameter estimation in mathematical medicine: examples demonstrated for prostate cancer
Quantitative Biology - - 2016
We review our studies on how to identify the most appropriate models of diseases, and how to determine their parameters in a quantitative manner given a short time series of biomarkers, using intermittent androgen deprivation therapy of prostate cancer as an example. Recently, it has become possible to estimate the specific parameters of individual patients within a reasonable time by employing th......
Synthetic biology: a new approach to study biological pattern formation
Quantitative Biology - Tập 1 - Trang 246-252 - 2014
The principles and molecular mechanisms underlying biological pattern formation are difficult to elucidate in most cases due to the overwhelming physiologic complexity associated with the natural context. The understanding of a particular mechanism, not to speak of underlying universal principles, is difficult due to the diversity and uncertainty of the biological systems. Although current genetic......
Strategic planning for national biomedical big data infrastructure in China
Quantitative Biology - Tập 5 - Trang 272-275 - 2017
The promise that big data will revolutionize scientific discovery and technology innovation is now being widely recognized. With the explosive growth of biomedical data, life science is being transformed into a digital science in which novel insights are gained from in-depth data analysis and modeling. Extensive and innovative utilization of biomedical big data is a key to the success of precision......
On the possibility of identifying human subjects using behavioural complexity analysesBackground Identification of human subjects using a geometric approach to complexity analysis of behavioural data is designed to provide a basis for a more precise diagnosis leading towards personalised medicine. Methods The approach is based on capturing behavioural time‐series that can be chara...
Quantitative Biology - Tập 4 Số 4 - Trang 261-269 - 2016
MRHCA: a nonparametric statistics based method for hub and co-expression module identification in large gene co-expression network
Quantitative Biology - Tập 6 - Trang 40-55 - 2018
Gene co-expression and differential co-expression analysis has been increasingly used to study cofunctional and co-regulatory biological mechanisms from large scale transcriptomics data sets. In this study, we develop a nonparametric approach to identify hub genes and modules in a large coexpression network with low computational and memory cost, namely MRHCA. We have applied the method to simulat......
Comprehensive simulation of metagenomic sequencing data with non‐uniform sampling distributionBackground Metagenomic sequencing is a complex sampling procedure from unknown mixtures of many genomes. Having metagenome data with known genome compositions is essential for both benchmarking bioinformatics software and for investigating influences of various factors on the data. Compared to data from real microbiome samples or from defined microbial moc...
Quantitative Biology - Tập 6 Số 2 - Trang 175-185 - 2018
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